+ 
+ 
+ 
+ 
Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including [Opik](https://www.comet.com/docs/opik/integrations/dify), [Langfuse](https://docs.langfuse.com), and [Arize Phoenix](https://docs.arize.com/phoenix)) and more, letting you quickly go from prototype to production. Here's a list of the core features:
diff --git a/api/.env.example b/api/.env.example
index 40e1c2dfdfc..c6541731e64 100644
--- a/api/.env.example
+++ b/api/.env.example
@@ -127,7 +127,8 @@ ALIYUN_OSS_AUTH_VERSION=v1
ALIYUN_OSS_REGION=your-region
# Don't start with '/'. OSS doesn't support leading slash in object names.
ALIYUN_OSS_PATH=your-path
-ALIYUN_CLOUDBOX_ID=your-cloudbox-id
+# Optional CloudBox ID for Aliyun OSS, DO NOT enable it if you are not using CloudBox.
+#ALIYUN_CLOUDBOX_ID=your-cloudbox-id
# Google Storage configuration
GOOGLE_STORAGE_BUCKET_NAME=your-bucket-name
@@ -353,6 +354,9 @@ BAIDU_VECTOR_DB_SHARD=1
BAIDU_VECTOR_DB_REPLICAS=3
BAIDU_VECTOR_DB_INVERTED_INDEX_ANALYZER=DEFAULT_ANALYZER
BAIDU_VECTOR_DB_INVERTED_INDEX_PARSER_MODE=COARSE_MODE
+BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT=500
+BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT_RATIO=0.05
+BAIDU_VECTOR_DB_REBUILD_INDEX_TIMEOUT_IN_SECONDS=300
# Upstash configuration
UPSTASH_VECTOR_URL=your-server-url
diff --git a/api/.importlinter b/api/.importlinter
index a836d090887..5e06947d941 100644
--- a/api/.importlinter
+++ b/api/.importlinter
@@ -1,202 +1,14 @@
[importlinter]
root_packages =
core
- dify_graph
+ constants
+ context
configs
controllers
extensions
+ factories
+ libs
models
tasks
services
include_external_packages = True
-
-[importlinter:contract:workflow]
-name = Workflow
-type=layers
-layers =
- graph_engine
- graph_events
- graph
- nodes
- node_events
- runtime
- entities
-containers =
- dify_graph
-ignore_imports =
- dify_graph.nodes.base.node -> dify_graph.graph_events
- dify_graph.nodes.iteration.iteration_node -> dify_graph.graph_events
- dify_graph.nodes.loop.loop_node -> dify_graph.graph_events
-
- dify_graph.nodes.iteration.iteration_node -> dify_graph.graph_engine
- dify_graph.nodes.loop.loop_node -> dify_graph.graph_engine
- # TODO(QuantumGhost): fix the import violation later
- dify_graph.entities.pause_reason -> dify_graph.nodes.human_input.entities
-
-[importlinter:contract:workflow-infrastructure-dependencies]
-name = Workflow Infrastructure Dependencies
-type = forbidden
-source_modules =
- dify_graph
-forbidden_modules =
- extensions.ext_database
- extensions.ext_redis
-allow_indirect_imports = True
-ignore_imports =
- dify_graph.nodes.llm.node -> extensions.ext_database
- dify_graph.model_runtime.model_providers.__base.ai_model -> extensions.ext_redis
- dify_graph.model_runtime.model_providers.model_provider_factory -> extensions.ext_redis
-
-[importlinter:contract:workflow-external-imports]
-name = Workflow External Imports
-type = forbidden
-source_modules =
- dify_graph
-forbidden_modules =
- configs
- controllers
- extensions
- models
- services
- tasks
- core.agent
- core.app
- core.base
- core.callback_handler
- core.datasource
- core.db
- core.entities
- core.errors
- core.extension
- core.external_data_tool
- core.file
- core.helper
- core.hosting_configuration
- core.indexing_runner
- core.llm_generator
- core.logging
- core.mcp
- core.memory
- core.moderation
- core.ops
- core.plugin
- core.prompt
- core.provider_manager
- core.rag
- core.repositories
- core.schemas
- core.tools
- core.trigger
- core.variables
-ignore_imports =
- dify_graph.nodes.llm.llm_utils -> core.model_manager
- dify_graph.nodes.llm.protocols -> core.model_manager
- dify_graph.nodes.llm.llm_utils -> dify_graph.model_runtime.model_providers.__base.large_language_model
- dify_graph.nodes.llm.node -> core.tools.signature
- dify_graph.nodes.tool.tool_node -> core.callback_handler.workflow_tool_callback_handler
- dify_graph.nodes.tool.tool_node -> core.tools.tool_engine
- dify_graph.nodes.tool.tool_node -> core.tools.tool_manager
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.advanced_prompt_transform
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.simple_prompt_transform
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> dify_graph.model_runtime.model_providers.__base.large_language_model
- dify_graph.nodes.question_classifier.question_classifier_node -> core.prompt.simple_prompt_transform
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.model_manager
- dify_graph.nodes.question_classifier.question_classifier_node -> core.model_manager
- dify_graph.nodes.tool.tool_node -> core.tools.utils.message_transformer
- dify_graph.nodes.llm.node -> core.llm_generator.output_parser.errors
- dify_graph.nodes.llm.node -> core.llm_generator.output_parser.structured_output
- dify_graph.nodes.llm.node -> core.model_manager
- dify_graph.nodes.llm.entities -> core.prompt.entities.advanced_prompt_entities
- dify_graph.nodes.llm.node -> core.prompt.entities.advanced_prompt_entities
- dify_graph.nodes.llm.node -> core.prompt.utils.prompt_message_util
- dify_graph.nodes.parameter_extractor.entities -> core.prompt.entities.advanced_prompt_entities
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.entities.advanced_prompt_entities
- dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.utils.prompt_message_util
- dify_graph.nodes.question_classifier.entities -> core.prompt.entities.advanced_prompt_entities
- dify_graph.nodes.question_classifier.question_classifier_node -> core.prompt.utils.prompt_message_util
- dify_graph.nodes.llm.node -> models.dataset
- dify_graph.nodes.llm.file_saver -> core.tools.signature
- dify_graph.nodes.llm.file_saver -> core.tools.tool_file_manager
- dify_graph.nodes.tool.tool_node -> core.tools.errors
- dify_graph.nodes.llm.node -> extensions.ext_database
- dify_graph.nodes.llm.node -> models.model
- dify_graph.nodes.tool.tool_node -> services
- dify_graph.model_runtime.model_providers.__base.ai_model -> configs
- dify_graph.model_runtime.model_providers.__base.ai_model -> extensions.ext_redis
- dify_graph.model_runtime.model_providers.__base.large_language_model -> configs
- dify_graph.model_runtime.model_providers.__base.text_embedding_model -> core.entities.embedding_type
- dify_graph.model_runtime.model_providers.model_provider_factory -> configs
- dify_graph.model_runtime.model_providers.model_provider_factory -> extensions.ext_redis
- dify_graph.model_runtime.model_providers.model_provider_factory -> models.provider_ids
-
-[importlinter:contract:rsc]
-name = RSC
-type = layers
-layers =
- graph_engine
- response_coordinator
-containers =
- dify_graph.graph_engine
-
-[importlinter:contract:worker]
-name = Worker
-type = layers
-layers =
- graph_engine
- worker
-containers =
- dify_graph.graph_engine
-
-[importlinter:contract:graph-engine-architecture]
-name = Graph Engine Architecture
-type = layers
-layers =
- graph_engine
- orchestration
- command_processing
- event_management
- error_handler
- graph_traversal
- graph_state_manager
- worker_management
- domain
-containers =
- dify_graph.graph_engine
-
-[importlinter:contract:domain-isolation]
-name = Domain Model Isolation
-type = forbidden
-source_modules =
- dify_graph.graph_engine.domain
-forbidden_modules =
- dify_graph.graph_engine.worker_management
- dify_graph.graph_engine.command_channels
- dify_graph.graph_engine.layers
- dify_graph.graph_engine.protocols
-
-[importlinter:contract:worker-management]
-name = Worker Management
-type = forbidden
-source_modules =
- dify_graph.graph_engine.worker_management
-forbidden_modules =
- dify_graph.graph_engine.orchestration
- dify_graph.graph_engine.command_processing
- dify_graph.graph_engine.event_management
-
-
-[importlinter:contract:graph-traversal-components]
-name = Graph Traversal Components
-type = layers
-layers =
- edge_processor
- skip_propagator
-containers =
- dify_graph.graph_engine.graph_traversal
-
-[importlinter:contract:command-channels]
-name = Command Channels Independence
-type = independence
-modules =
- dify_graph.graph_engine.command_channels.in_memory_channel
- dify_graph.graph_engine.command_channels.redis_channel
diff --git a/api/.ruff.toml b/api/.ruff.toml
index b0947eb6190..4b1252a8613 100644
--- a/api/.ruff.toml
+++ b/api/.ruff.toml
@@ -100,7 +100,7 @@ ignore = [
"configs/*" = [
"N802", # invalid-function-name
]
-"dify_graph/model_runtime/callbacks/base_callback.py" = ["T201"]
+"graphon/model_runtime/callbacks/base_callback.py" = ["T201"]
"core/workflow/callbacks/workflow_logging_callback.py" = ["T201"]
"libs/gmpy2_pkcs10aep_cipher.py" = [
"N803", # invalid-argument-name
diff --git a/api/README.md b/api/README.md
index b6473670469..00562f3f78c 100644
--- a/api/README.md
+++ b/api/README.md
@@ -40,6 +40,8 @@ The scripts resolve paths relative to their location, so you can run them from a
./dev/start-web
```
+ `./dev/setup` and `./dev/start-web` install JavaScript dependencies through the repository root workspace, so you do not need a separate `cd web && pnpm install` step.
+
1. Set up your application by visiting `http://localhost:3000`.
1. Start the worker service (async and scheduler tasks, runs from `api`).
diff --git a/api/app_factory.py b/api/app_factory.py
index 066eb2ae2c8..76838f9925d 100644
--- a/api/app_factory.py
+++ b/api/app_factory.py
@@ -143,6 +143,7 @@ def initialize_extensions(app: DifyApp):
ext_commands,
ext_compress,
ext_database,
+ ext_enterprise_telemetry,
ext_fastopenapi,
ext_forward_refs,
ext_hosting_provider,
@@ -193,6 +194,7 @@ def initialize_extensions(app: DifyApp):
ext_commands,
ext_fastopenapi,
ext_otel,
+ ext_enterprise_telemetry,
ext_request_logging,
ext_session_factory,
]
diff --git a/api/commands/vector.py b/api/commands/vector.py
index 4cf11c9ad1a..cb7eb7c4522 100644
--- a/api/commands/vector.py
+++ b/api/commands/vector.py
@@ -10,6 +10,7 @@ from configs import dify_config
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.datasource.vdb.vector_type import VectorType
from core.rag.index_processor.constant.built_in_field import BuiltInField
+from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from core.rag.models.document import ChildDocument, Document
from extensions.ext_database import db
from models.dataset import Dataset, DatasetCollectionBinding, DatasetMetadata, DatasetMetadataBinding, DocumentSegment
@@ -85,7 +86,7 @@ def migrate_annotation_vector_database():
dataset = Dataset(
id=app.id,
tenant_id=app.tenant_id,
- indexing_technique="high_quality",
+ indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider=dataset_collection_binding.provider_name,
embedding_model=dataset_collection_binding.model_name,
collection_binding_id=dataset_collection_binding.id,
@@ -177,7 +178,9 @@ def migrate_knowledge_vector_database():
while True:
try:
stmt = (
- select(Dataset).where(Dataset.indexing_technique == "high_quality").order_by(Dataset.created_at.desc())
+ select(Dataset)
+ .where(Dataset.indexing_technique == IndexTechniqueType.HIGH_QUALITY)
+ .order_by(Dataset.created_at.desc())
)
datasets = db.paginate(select=stmt, page=page, per_page=50, max_per_page=50, error_out=False)
@@ -269,7 +272,7 @@ def migrate_knowledge_vector_database():
"dataset_id": segment.dataset_id,
},
)
- if dataset_document.doc_form == "hierarchical_model":
+ if dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX:
child_chunks = segment.get_child_chunks()
if child_chunks:
child_documents = []
diff --git a/api/configs/app_config.py b/api/configs/app_config.py
index d3b1cf9d5b9..831f0a49e01 100644
--- a/api/configs/app_config.py
+++ b/api/configs/app_config.py
@@ -8,7 +8,7 @@ from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, Settings
from libs.file_utils import search_file_upwards
from .deploy import DeploymentConfig
-from .enterprise import EnterpriseFeatureConfig
+from .enterprise import EnterpriseFeatureConfig, EnterpriseTelemetryConfig
from .extra import ExtraServiceConfig
from .feature import FeatureConfig
from .middleware import MiddlewareConfig
@@ -73,6 +73,8 @@ class DifyConfig(
# Enterprise feature configs
# **Before using, please contact business@dify.ai by email to inquire about licensing matters.**
EnterpriseFeatureConfig,
+ # Enterprise telemetry configs
+ EnterpriseTelemetryConfig,
):
model_config = SettingsConfigDict(
# read from dotenv format config file
diff --git a/api/configs/enterprise/__init__.py b/api/configs/enterprise/__init__.py
index f8447c6979a..8a6a921a4ea 100644
--- a/api/configs/enterprise/__init__.py
+++ b/api/configs/enterprise/__init__.py
@@ -22,3 +22,52 @@ class EnterpriseFeatureConfig(BaseSettings):
ENTERPRISE_REQUEST_TIMEOUT: int = Field(
ge=1, description="Maximum timeout in seconds for enterprise requests", default=5
)
+
+
+class EnterpriseTelemetryConfig(BaseSettings):
+ """
+ Configuration for enterprise telemetry.
+ """
+
+ ENTERPRISE_TELEMETRY_ENABLED: bool = Field(
+ description="Enable enterprise telemetry collection (also requires ENTERPRISE_ENABLED=true).",
+ default=False,
+ )
+
+ ENTERPRISE_OTLP_ENDPOINT: str = Field(
+ description="Enterprise OTEL collector endpoint.",
+ default="",
+ )
+
+ ENTERPRISE_OTLP_HEADERS: str = Field(
+ description="Auth headers for OTLP export (key=value,key2=value2).",
+ default="",
+ )
+
+ ENTERPRISE_OTLP_PROTOCOL: str = Field(
+ description="OTLP protocol: 'http' or 'grpc' (default: http).",
+ default="http",
+ )
+
+ ENTERPRISE_OTLP_API_KEY: str = Field(
+ description="Bearer token for enterprise OTLP export authentication.",
+ default="",
+ )
+
+ ENTERPRISE_INCLUDE_CONTENT: bool = Field(
+ description="Include input/output content in traces (privacy toggle).",
+ # Setting the default value to False to avoid accidentally log PII data in traces.
+ default=False,
+ )
+
+ ENTERPRISE_SERVICE_NAME: str = Field(
+ description="Service name for OTEL resource.",
+ default="dify",
+ )
+
+ ENTERPRISE_OTEL_SAMPLING_RATE: float = Field(
+ description="Sampling rate for enterprise traces (0.0 to 1.0, default 1.0 = 100%).",
+ default=1.0,
+ ge=0.0,
+ le=1.0,
+ )
diff --git a/api/configs/middleware/vdb/baidu_vector_config.py b/api/configs/middleware/vdb/baidu_vector_config.py
index 8f956745b1e..c8e4f7309f7 100644
--- a/api/configs/middleware/vdb/baidu_vector_config.py
+++ b/api/configs/middleware/vdb/baidu_vector_config.py
@@ -51,3 +51,18 @@ class BaiduVectorDBConfig(BaseSettings):
description="Parser mode for inverted index in Baidu Vector Database (default is COARSE_MODE)",
default="COARSE_MODE",
)
+
+ BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT: int = Field(
+ description="Auto build row count increment threshold (default is 500)",
+ default=500,
+ )
+
+ BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT_RATIO: float = Field(
+ description="Auto build row count increment ratio threshold (default is 0.05)",
+ default=0.05,
+ )
+
+ BAIDU_VECTOR_DB_REBUILD_INDEX_TIMEOUT_IN_SECONDS: int = Field(
+ description="Timeout in seconds for rebuilding the index in Baidu Vector Database (default is 3600 seconds)",
+ default=300,
+ )
diff --git a/api/context/__init__.py b/api/context/__init__.py
index 969e5f583d5..8df37138e8b 100644
--- a/api/context/__init__.py
+++ b/api/context/__init__.py
@@ -1,74 +1,36 @@
"""
-Core Context - Framework-agnostic context management.
+Application-layer context adapters.
-This module provides context management that is independent of any specific
-web framework. Framework-specific implementations register their context
-capture functions at application initialization time.
-
-This ensures the workflow layer remains completely decoupled from Flask
-or any other web framework.
+Concrete execution-context implementations live here so `graphon` only
+depends on injected context managers rather than framework state capture.
"""
-import contextvars
-from collections.abc import Callable
-
-from dify_graph.context.execution_context import (
+from context.execution_context import (
+ AppContext,
+ ContextProviderNotFoundError,
ExecutionContext,
+ ExecutionContextBuilder,
IExecutionContext,
NullAppContext,
+ capture_current_context,
+ read_context,
+ register_context,
+ register_context_capturer,
+ reset_context_provider,
)
-
-# Global capturer function - set by framework-specific modules
-_capturer: Callable[[], IExecutionContext] | None = None
-
-
-def register_context_capturer(capturer: Callable[[], IExecutionContext]) -> None:
- """
- Register a context capture function.
-
- This should be called by framework-specific modules (e.g., Flask)
- during application initialization.
-
- Args:
- capturer: Function that captures current context and returns IExecutionContext
- """
- global _capturer
- _capturer = capturer
-
-
-def capture_current_context() -> IExecutionContext:
- """
- Capture current execution context.
-
- This function uses the registered context capturer. If no capturer
- is registered, it returns a minimal context with only contextvars
- (suitable for non-framework environments like tests or standalone scripts).
-
- Returns:
- IExecutionContext with captured context
- """
- if _capturer is None:
- # No framework registered - return minimal context
- return ExecutionContext(
- app_context=NullAppContext(),
- context_vars=contextvars.copy_context(),
- )
-
- return _capturer()
-
-
-def reset_context_provider() -> None:
- """
- Reset the context capturer.
-
- This is primarily useful for testing to ensure a clean state.
- """
- global _capturer
- _capturer = None
-
+from context.models import SandboxContext
__all__ = [
+ "AppContext",
+ "ContextProviderNotFoundError",
+ "ExecutionContext",
+ "ExecutionContextBuilder",
+ "IExecutionContext",
+ "NullAppContext",
+ "SandboxContext",
"capture_current_context",
+ "read_context",
+ "register_context",
"register_context_capturer",
"reset_context_provider",
]
diff --git a/api/dify_graph/context/execution_context.py b/api/context/execution_context.py
similarity index 60%
rename from api/dify_graph/context/execution_context.py
rename to api/context/execution_context.py
index e3007530f08..ba9a24d4f33 100644
--- a/api/dify_graph/context/execution_context.py
+++ b/api/context/execution_context.py
@@ -1,5 +1,8 @@
"""
-Execution Context - Abstracted context management for workflow execution.
+Application-layer execution context adapters.
+
+Concrete context capture lives outside `graphon` so the graph package only
+consumes injected context managers when it needs to preserve thread-local state.
"""
import contextvars
@@ -16,33 +19,33 @@ class AppContext(ABC):
"""
Abstract application context interface.
- This abstraction allows workflow execution to work with or without Flask
- by providing a common interface for application context management.
+ Application adapters can implement this to restore framework-specific state
+ such as Flask app context around worker execution.
"""
@abstractmethod
def get_config(self, key: str, default: Any = None) -> Any:
"""Get configuration value by key."""
- pass
+ raise NotImplementedError
@abstractmethod
def get_extension(self, name: str) -> Any:
- """Get Flask extension by name (e.g., 'db', 'cache')."""
- pass
+ """Get application extension by name."""
+ raise NotImplementedError
@abstractmethod
def enter(self) -> AbstractContextManager[None]:
"""Enter the application context."""
- pass
+ raise NotImplementedError
@runtime_checkable
class IExecutionContext(Protocol):
"""
- Protocol for execution context.
+ Protocol for enterable execution context objects.
- This protocol defines the interface that all execution contexts must implement,
- allowing both ExecutionContext and FlaskExecutionContext to be used interchangeably.
+ Concrete implementations may carry extra framework state, but callers only
+ depend on standard context-manager behavior plus optional user metadata.
"""
def __enter__(self) -> "IExecutionContext":
@@ -62,14 +65,10 @@ class IExecutionContext(Protocol):
@final
class ExecutionContext:
"""
- Execution context for workflow execution in worker threads.
+ Generic execution context used by application-layer adapters.
- This class encapsulates all context needed for workflow execution:
- - Application context (Flask app or standalone)
- - Context variables for Python contextvars
- - User information (optional)
-
- It is designed to be serializable and passable to worker threads.
+ It restores captured `contextvars` and optionally enters an application
+ context before the worker executes graph logic.
"""
def __init__(
@@ -78,14 +77,6 @@ class ExecutionContext:
context_vars: contextvars.Context | None = None,
user: Any = None,
) -> None:
- """
- Initialize execution context.
-
- Args:
- app_context: Application context (Flask or standalone)
- context_vars: Python contextvars to preserve
- user: User object (optional)
- """
self._app_context = app_context
self._context_vars = context_vars
self._user = user
@@ -98,27 +89,21 @@ class ExecutionContext:
@property
def context_vars(self) -> contextvars.Context | None:
- """Get context variables."""
+ """Get captured context variables."""
return self._context_vars
@property
def user(self) -> Any:
- """Get user object."""
+ """Get captured user object."""
return self._user
@contextmanager
def enter(self) -> Generator[None, None, None]:
- """
- Enter this execution context.
-
- This is a convenience method that creates a context manager.
- """
- # Restore context variables if provided
+ """Enter this execution context."""
if self._context_vars:
for var, val in self._context_vars.items():
var.set(val)
- # Enter app context if available
if self._app_context is not None:
with self._app_context.enter():
yield
@@ -141,18 +126,10 @@ class ExecutionContext:
class NullAppContext(AppContext):
"""
- Null implementation of AppContext for non-Flask environments.
-
- This is used when running without Flask (e.g., in tests or standalone mode).
+ Null application context for non-framework environments.
"""
def __init__(self, config: dict[str, Any] | None = None) -> None:
- """
- Initialize null app context.
-
- Args:
- config: Optional configuration dictionary
- """
self._config = config or {}
self._extensions: dict[str, Any] = {}
@@ -165,7 +142,7 @@ class NullAppContext(AppContext):
return self._extensions.get(name)
def set_extension(self, name: str, extension: Any) -> None:
- """Set extension by name."""
+ """Register an extension for tests or standalone execution."""
self._extensions[name] = extension
@contextmanager
@@ -176,9 +153,7 @@ class NullAppContext(AppContext):
class ExecutionContextBuilder:
"""
- Builder for creating ExecutionContext instances.
-
- This provides a fluent API for building execution contexts.
+ Builder for creating `ExecutionContext` instances.
"""
def __init__(self) -> None:
@@ -211,63 +186,42 @@ class ExecutionContextBuilder:
_capturer: Callable[[], IExecutionContext] | None = None
-
-# Tenant-scoped providers using tuple keys for clarity and constant-time lookup.
-# Key mapping:
-# (name, tenant_id) -> provider
-# - name: namespaced identifier (recommend prefixing, e.g. "workflow.sandbox")
-# - tenant_id: tenant identifier string
-# Value:
-# provider: Callable[[], BaseModel] returning the typed context value
-# Type-safety note:
-# - This registry cannot enforce that all providers for a given name return the same BaseModel type.
-# - Implementors SHOULD provide typed wrappers around register/read (like Go's context best practice),
-# e.g. def register_sandbox_ctx(tenant_id: str, p: Callable[[], SandboxContext]) and
-# def read_sandbox_ctx(tenant_id: str) -> SandboxContext.
_tenant_context_providers: dict[tuple[str, str], Callable[[], BaseModel]] = {}
T = TypeVar("T", bound=BaseModel)
class ContextProviderNotFoundError(KeyError):
- """Raised when a tenant-scoped context provider is missing for a given (name, tenant_id)."""
+ """Raised when a tenant-scoped context provider is missing."""
pass
def register_context_capturer(capturer: Callable[[], IExecutionContext]) -> None:
- """Register a single enterable execution context capturer (e.g., Flask)."""
+ """Register an enterable execution context capturer."""
global _capturer
_capturer = capturer
def register_context(name: str, tenant_id: str, provider: Callable[[], BaseModel]) -> None:
- """Register a tenant-specific provider for a named context.
-
- Tip: use a namespaced "name" (e.g., "workflow.sandbox") to avoid key collisions.
- Consider adding a typed wrapper for this registration in your feature module.
- """
+ """Register a tenant-specific provider for a named context."""
_tenant_context_providers[(name, tenant_id)] = provider
def read_context(name: str, *, tenant_id: str) -> BaseModel:
- """
- Read a context value for a specific tenant.
-
- Raises KeyError if the provider for (name, tenant_id) is not registered.
- """
- prov = _tenant_context_providers.get((name, tenant_id))
- if prov is None:
+ """Read a context value for a specific tenant."""
+ provider = _tenant_context_providers.get((name, tenant_id))
+ if provider is None:
raise ContextProviderNotFoundError(f"Context provider '{name}' not registered for tenant '{tenant_id}'")
- return prov()
+ return provider()
def capture_current_context() -> IExecutionContext:
"""
Capture current execution context from the calling environment.
- If a capturer is registered (e.g., Flask), use it. Otherwise, return a minimal
- context with NullAppContext + copy of current contextvars.
+ If no framework adapter is registered, return a minimal context that only
+ restores `contextvars`.
"""
if _capturer is None:
return ExecutionContext(
@@ -278,7 +232,22 @@ def capture_current_context() -> IExecutionContext:
def reset_context_provider() -> None:
- """Reset the capturer and all tenant-scoped context providers (primarily for tests)."""
+ """Reset the capturer and tenant-scoped providers."""
global _capturer
_capturer = None
_tenant_context_providers.clear()
+
+
+__all__ = [
+ "AppContext",
+ "ContextProviderNotFoundError",
+ "ExecutionContext",
+ "ExecutionContextBuilder",
+ "IExecutionContext",
+ "NullAppContext",
+ "capture_current_context",
+ "read_context",
+ "register_context",
+ "register_context_capturer",
+ "reset_context_provider",
+]
diff --git a/api/context/flask_app_context.py b/api/context/flask_app_context.py
index 324a9ee8b44..eddd6448d83 100644
--- a/api/context/flask_app_context.py
+++ b/api/context/flask_app_context.py
@@ -10,11 +10,7 @@ from typing import Any, final
from flask import Flask, current_app, g
-from dify_graph.context import register_context_capturer
-from dify_graph.context.execution_context import (
- AppContext,
- IExecutionContext,
-)
+from context.execution_context import AppContext, IExecutionContext, register_context_capturer
@final
diff --git a/api/dify_graph/context/models.py b/api/context/models.py
similarity index 100%
rename from api/dify_graph/context/models.py
rename to api/context/models.py
diff --git a/api/contexts/__init__.py b/api/contexts/__init__.py
index c52dcf8a574..764f9f8ee27 100644
--- a/api/contexts/__init__.py
+++ b/api/contexts/__init__.py
@@ -6,7 +6,6 @@ from contexts.wrapper import RecyclableContextVar
if TYPE_CHECKING:
from core.datasource.__base.datasource_provider import DatasourcePluginProviderController
- from core.plugin.entities.plugin_daemon import PluginModelProviderEntity
from core.tools.plugin_tool.provider import PluginToolProviderController
from core.trigger.provider import PluginTriggerProviderController
@@ -20,14 +19,6 @@ plugin_tool_providers: RecyclableContextVar[dict[str, "PluginToolProviderControl
plugin_tool_providers_lock: RecyclableContextVar[Lock] = RecyclableContextVar(ContextVar("plugin_tool_providers_lock"))
-plugin_model_providers: RecyclableContextVar[list["PluginModelProviderEntity"] | None] = RecyclableContextVar(
- ContextVar("plugin_model_providers")
-)
-
-plugin_model_providers_lock: RecyclableContextVar[Lock] = RecyclableContextVar(
- ContextVar("plugin_model_providers_lock")
-)
-
datasource_plugin_providers: RecyclableContextVar[dict[str, "DatasourcePluginProviderController"]] = (
RecyclableContextVar(ContextVar("datasource_plugin_providers"))
)
diff --git a/api/controllers/common/fields.py b/api/controllers/common/fields.py
index ff5326dade6..7348ef62aad 100644
--- a/api/controllers/common/fields.py
+++ b/api/controllers/common/fields.py
@@ -2,9 +2,9 @@ from __future__ import annotations
from typing import Any, TypeAlias
+from graphon.file import helpers as file_helpers
from pydantic import BaseModel, ConfigDict, computed_field
-from dify_graph.file import helpers as file_helpers
from models.model import IconType
JSONValue: TypeAlias = str | int | float | bool | None | dict[str, Any] | list[Any]
diff --git a/api/controllers/console/apikey.py b/api/controllers/console/apikey.py
index b6d1df319e5..783cb5c444b 100644
--- a/api/controllers/console/apikey.py
+++ b/api/controllers/console/apikey.py
@@ -1,7 +1,7 @@
import flask_restx
from flask_restx import Resource, fields, marshal_with
from flask_restx._http import HTTPStatus
-from sqlalchemy import select
+from sqlalchemy import delete, func, select
from sqlalchemy.orm import Session
from werkzeug.exceptions import Forbidden
@@ -9,6 +9,7 @@ from extensions.ext_database import db
from libs.helper import TimestampField
from libs.login import current_account_with_tenant, login_required
from models.dataset import Dataset
+from models.enums import ApiTokenType
from models.model import ApiToken, App
from services.api_token_service import ApiTokenCache
@@ -33,16 +34,10 @@ api_key_list_model = console_ns.model(
def _get_resource(resource_id, tenant_id, resource_model):
- if resource_model == App:
- with Session(db.engine) as session:
- resource = session.execute(
- select(resource_model).filter_by(id=resource_id, tenant_id=tenant_id)
- ).scalar_one_or_none()
- else:
- with Session(db.engine) as session:
- resource = session.execute(
- select(resource_model).filter_by(id=resource_id, tenant_id=tenant_id)
- ).scalar_one_or_none()
+ with Session(db.engine) as session:
+ resource = session.execute(
+ select(resource_model).filter_by(id=resource_id, tenant_id=tenant_id)
+ ).scalar_one_or_none()
if resource is None:
flask_restx.abort(HTTPStatus.NOT_FOUND, message=f"{resource_model.__name__} not found.")
@@ -53,7 +48,7 @@ def _get_resource(resource_id, tenant_id, resource_model):
class BaseApiKeyListResource(Resource):
method_decorators = [account_initialization_required, login_required, setup_required]
- resource_type: str | None = None
+ resource_type: ApiTokenType | None = None
resource_model: type | None = None
resource_id_field: str | None = None
token_prefix: str | None = None
@@ -80,10 +75,13 @@ class BaseApiKeyListResource(Resource):
resource_id = str(resource_id)
_, current_tenant_id = current_account_with_tenant()
_get_resource(resource_id, current_tenant_id, self.resource_model)
- current_key_count = (
- db.session.query(ApiToken)
- .where(ApiToken.type == self.resource_type, getattr(ApiToken, self.resource_id_field) == resource_id)
- .count()
+ current_key_count: int = (
+ db.session.scalar(
+ select(func.count(ApiToken.id)).where(
+ ApiToken.type == self.resource_type, getattr(ApiToken, self.resource_id_field) == resource_id
+ )
+ )
+ or 0
)
if current_key_count >= self.max_keys:
@@ -94,6 +92,7 @@ class BaseApiKeyListResource(Resource):
)
key = ApiToken.generate_api_key(self.token_prefix or "", 24)
+ assert self.resource_type is not None, "resource_type must be set"
api_token = ApiToken()
setattr(api_token, self.resource_id_field, resource_id)
api_token.tenant_id = current_tenant_id
@@ -107,7 +106,7 @@ class BaseApiKeyListResource(Resource):
class BaseApiKeyResource(Resource):
method_decorators = [account_initialization_required, login_required, setup_required]
- resource_type: str | None = None
+ resource_type: ApiTokenType | None = None
resource_model: type | None = None
resource_id_field: str | None = None
@@ -119,14 +118,14 @@ class BaseApiKeyResource(Resource):
if not current_user.is_admin_or_owner:
raise Forbidden()
- key = (
- db.session.query(ApiToken)
+ key = db.session.scalar(
+ select(ApiToken)
.where(
getattr(ApiToken, self.resource_id_field) == resource_id,
ApiToken.type == self.resource_type,
ApiToken.id == api_key_id,
)
- .first()
+ .limit(1)
)
if key is None:
@@ -137,7 +136,7 @@ class BaseApiKeyResource(Resource):
assert key is not None # nosec - for type checker only
ApiTokenCache.delete(key.token, key.type)
- db.session.query(ApiToken).where(ApiToken.id == api_key_id).delete()
+ db.session.execute(delete(ApiToken).where(ApiToken.id == api_key_id))
db.session.commit()
return {"result": "success"}, 204
@@ -162,7 +161,7 @@ class AppApiKeyListResource(BaseApiKeyListResource):
"""Create a new API key for an app"""
return super().post(resource_id)
- resource_type = "app"
+ resource_type = ApiTokenType.APP
resource_model = App
resource_id_field = "app_id"
token_prefix = "app-"
@@ -178,7 +177,7 @@ class AppApiKeyResource(BaseApiKeyResource):
"""Delete an API key for an app"""
return super().delete(resource_id, api_key_id)
- resource_type = "app"
+ resource_type = ApiTokenType.APP
resource_model = App
resource_id_field = "app_id"
@@ -202,7 +201,7 @@ class DatasetApiKeyListResource(BaseApiKeyListResource):
"""Create a new API key for a dataset"""
return super().post(resource_id)
- resource_type = "dataset"
+ resource_type = ApiTokenType.DATASET
resource_model = Dataset
resource_id_field = "dataset_id"
token_prefix = "ds-"
@@ -218,6 +217,6 @@ class DatasetApiKeyResource(BaseApiKeyResource):
"""Delete an API key for a dataset"""
return super().delete(resource_id, api_key_id)
- resource_type = "dataset"
+ resource_type = ApiTokenType.DATASET
resource_model = Dataset
resource_id_field = "dataset_id"
diff --git a/api/controllers/console/app/app.py b/api/controllers/console/app/app.py
index 5ac0e342e6e..738e77b3715 100644
--- a/api/controllers/console/app/app.py
+++ b/api/controllers/console/app/app.py
@@ -5,6 +5,8 @@ from typing import Any, Literal, TypeAlias
from flask import request
from flask_restx import Resource
+from graphon.enums import WorkflowExecutionStatus
+from graphon.file import helpers as file_helpers
from pydantic import AliasChoices, BaseModel, ConfigDict, Field, computed_field, field_validator
from sqlalchemy import select
from sqlalchemy.orm import Session
@@ -26,8 +28,6 @@ from controllers.console.wraps import (
from core.ops.ops_trace_manager import OpsTraceManager
from core.rag.retrieval.retrieval_methods import RetrievalMethod
from core.trigger.constants import TRIGGER_NODE_TYPES
-from dify_graph.enums import WorkflowExecutionStatus
-from dify_graph.file import helpers as file_helpers
from extensions.ext_database import db
from libs.login import current_account_with_tenant, login_required
from models import App, DatasetPermissionEnum, Workflow
@@ -95,7 +95,7 @@ class CreateAppPayload(BaseModel):
name: str = Field(..., min_length=1, description="App name")
description: str | None = Field(default=None, description="App description (max 400 chars)", max_length=400)
mode: Literal["chat", "agent-chat", "advanced-chat", "workflow", "completion"] = Field(..., description="App mode")
- icon_type: str | None = Field(default=None, description="Icon type")
+ icon_type: IconType | None = Field(default=None, description="Icon type")
icon: str | None = Field(default=None, description="Icon")
icon_background: str | None = Field(default=None, description="Icon background color")
@@ -103,7 +103,7 @@ class CreateAppPayload(BaseModel):
class UpdateAppPayload(BaseModel):
name: str = Field(..., min_length=1, description="App name")
description: str | None = Field(default=None, description="App description (max 400 chars)", max_length=400)
- icon_type: str | None = Field(default=None, description="Icon type")
+ icon_type: IconType | None = Field(default=None, description="Icon type")
icon: str | None = Field(default=None, description="Icon")
icon_background: str | None = Field(default=None, description="Icon background color")
use_icon_as_answer_icon: bool | None = Field(default=None, description="Use icon as answer icon")
@@ -113,7 +113,7 @@ class UpdateAppPayload(BaseModel):
class CopyAppPayload(BaseModel):
name: str | None = Field(default=None, description="Name for the copied app")
description: str | None = Field(default=None, description="Description for the copied app", max_length=400)
- icon_type: str | None = Field(default=None, description="Icon type")
+ icon_type: IconType | None = Field(default=None, description="Icon type")
icon: str | None = Field(default=None, description="Icon")
icon_background: str | None = Field(default=None, description="Icon background color")
@@ -594,7 +594,7 @@ class AppApi(Resource):
args_dict: AppService.ArgsDict = {
"name": args.name,
"description": args.description or "",
- "icon_type": args.icon_type or "",
+ "icon_type": args.icon_type,
"icon": args.icon or "",
"icon_background": args.icon_background or "",
"use_icon_as_answer_icon": args.use_icon_as_answer_icon or False,
diff --git a/api/controllers/console/app/audio.py b/api/controllers/console/app/audio.py
index 2c5e8d29ee9..78ddb904e14 100644
--- a/api/controllers/console/app/audio.py
+++ b/api/controllers/console/app/audio.py
@@ -2,6 +2,7 @@ import logging
from flask import request
from flask_restx import Resource, fields
+from graphon.model_runtime.errors.invoke import InvokeError
from pydantic import BaseModel, Field
from werkzeug.exceptions import InternalServerError
@@ -22,7 +23,6 @@ from controllers.console.app.error import (
from controllers.console.app.wraps import get_app_model
from controllers.console.wraps import account_initialization_required, setup_required
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
-from dify_graph.model_runtime.errors.invoke import InvokeError
from libs.login import login_required
from models import App, AppMode
from services.audio_service import AudioService
diff --git a/api/controllers/console/app/completion.py b/api/controllers/console/app/completion.py
index 4d7ddfea139..d83925d173a 100644
--- a/api/controllers/console/app/completion.py
+++ b/api/controllers/console/app/completion.py
@@ -3,6 +3,7 @@ from typing import Any, Literal
from flask import request
from flask_restx import Resource
+from graphon.model_runtime.errors.invoke import InvokeError
from pydantic import BaseModel, Field, field_validator
from werkzeug.exceptions import InternalServerError, NotFound
@@ -26,7 +27,6 @@ from core.errors.error import (
QuotaExceededError,
)
from core.helper.trace_id_helper import get_external_trace_id
-from dify_graph.model_runtime.errors.invoke import InvokeError
from libs import helper
from libs.helper import uuid_value
from libs.login import current_user, login_required
diff --git a/api/controllers/console/app/conversation.py b/api/controllers/console/app/conversation.py
index 5eb61493c38..d329d22309d 100644
--- a/api/controllers/console/app/conversation.py
+++ b/api/controllers/console/app/conversation.py
@@ -5,7 +5,7 @@ from flask import abort, request
from flask_restx import Resource, fields, marshal_with
from pydantic import BaseModel, Field, field_validator
from sqlalchemy import func, or_
-from sqlalchemy.orm import joinedload
+from sqlalchemy.orm import selectinload
from werkzeug.exceptions import NotFound
from controllers.console import console_ns
@@ -376,8 +376,12 @@ class CompletionConversationApi(Resource):
# FIXME, the type ignore in this file
if args.annotation_status == "annotated":
- query = query.options(joinedload(Conversation.message_annotations)).join( # type: ignore
- MessageAnnotation, MessageAnnotation.conversation_id == Conversation.id
+ query = (
+ query.options(selectinload(Conversation.message_annotations)) # type: ignore[arg-type]
+ .join( # type: ignore
+ MessageAnnotation, MessageAnnotation.conversation_id == Conversation.id
+ )
+ .distinct()
)
elif args.annotation_status == "not_annotated":
query = (
@@ -454,9 +458,7 @@ class ChatConversationApi(Resource):
args = ChatConversationQuery.model_validate(request.args.to_dict(flat=True)) # type: ignore
subquery = (
- db.session.query(
- Conversation.id.label("conversation_id"), EndUser.session_id.label("from_end_user_session_id")
- )
+ sa.select(Conversation.id.label("conversation_id"), EndUser.session_id.label("from_end_user_session_id"))
.outerjoin(EndUser, Conversation.from_end_user_id == EndUser.id)
.subquery()
)
@@ -511,8 +513,12 @@ class ChatConversationApi(Resource):
match args.annotation_status:
case "annotated":
- query = query.options(joinedload(Conversation.message_annotations)).join( # type: ignore
- MessageAnnotation, MessageAnnotation.conversation_id == Conversation.id
+ query = (
+ query.options(selectinload(Conversation.message_annotations)) # type: ignore[arg-type]
+ .join( # type: ignore
+ MessageAnnotation, MessageAnnotation.conversation_id == Conversation.id
+ )
+ .distinct()
)
case "not_annotated":
query = (
@@ -587,10 +593,8 @@ class ChatConversationDetailApi(Resource):
def _get_conversation(app_model, conversation_id):
current_user, _ = current_account_with_tenant()
- conversation = (
- db.session.query(Conversation)
- .where(Conversation.id == conversation_id, Conversation.app_id == app_model.id)
- .first()
+ conversation = db.session.scalar(
+ sa.select(Conversation).where(Conversation.id == conversation_id, Conversation.app_id == app_model.id).limit(1)
)
if not conversation:
diff --git a/api/controllers/console/app/generator.py b/api/controllers/console/app/generator.py
index af4ac450bbc..7101d5df7b4 100644
--- a/api/controllers/console/app/generator.py
+++ b/api/controllers/console/app/generator.py
@@ -1,6 +1,7 @@
from collections.abc import Sequence
from flask_restx import Resource
+from graphon.model_runtime.errors.invoke import InvokeError
from pydantic import BaseModel, Field
from controllers.console import console_ns
@@ -18,7 +19,6 @@ from core.helper.code_executor.javascript.javascript_code_provider import Javasc
from core.helper.code_executor.python3.python3_code_provider import Python3CodeProvider
from core.llm_generator.entities import RuleCodeGeneratePayload, RuleGeneratePayload, RuleStructuredOutputPayload
from core.llm_generator.llm_generator import LLMGenerator
-from dify_graph.model_runtime.errors.invoke import InvokeError
from extensions.ext_database import db
from libs.login import current_account_with_tenant, login_required
from models import App
@@ -168,7 +168,7 @@ class InstructionGenerateApi(Resource):
try:
# Generate from nothing for a workflow node
if (args.current in (code_template, "")) and args.node_id != "":
- app = db.session.query(App).where(App.id == args.flow_id).first()
+ app = db.session.get(App, args.flow_id)
if not app:
return {"error": f"app {args.flow_id} not found"}, 400
workflow = WorkflowService().get_draft_workflow(app_model=app)
diff --git a/api/controllers/console/app/mcp_server.py b/api/controllers/console/app/mcp_server.py
index 4b20418b534..412fc8795a4 100644
--- a/api/controllers/console/app/mcp_server.py
+++ b/api/controllers/console/app/mcp_server.py
@@ -2,6 +2,7 @@ import json
from flask_restx import Resource, marshal_with
from pydantic import BaseModel, Field
+from sqlalchemy import select
from werkzeug.exceptions import NotFound
from controllers.console import console_ns
@@ -47,7 +48,7 @@ class AppMCPServerController(Resource):
@get_app_model
@marshal_with(app_server_model)
def get(self, app_model):
- server = db.session.query(AppMCPServer).where(AppMCPServer.app_id == app_model.id).first()
+ server = db.session.scalar(select(AppMCPServer).where(AppMCPServer.app_id == app_model.id).limit(1))
return server
@console_ns.doc("create_app_mcp_server")
@@ -98,7 +99,7 @@ class AppMCPServerController(Resource):
@edit_permission_required
def put(self, app_model):
payload = MCPServerUpdatePayload.model_validate(console_ns.payload or {})
- server = db.session.query(AppMCPServer).where(AppMCPServer.id == payload.id).first()
+ server = db.session.get(AppMCPServer, payload.id)
if not server:
raise NotFound()
@@ -135,11 +136,10 @@ class AppMCPServerRefreshController(Resource):
@edit_permission_required
def get(self, server_id):
_, current_tenant_id = current_account_with_tenant()
- server = (
- db.session.query(AppMCPServer)
- .where(AppMCPServer.id == server_id)
- .where(AppMCPServer.tenant_id == current_tenant_id)
- .first()
+ server = db.session.scalar(
+ select(AppMCPServer)
+ .where(AppMCPServer.id == server_id, AppMCPServer.tenant_id == current_tenant_id)
+ .limit(1)
)
if not server:
raise NotFound()
diff --git a/api/controllers/console/app/message.py b/api/controllers/console/app/message.py
index 4fb73f61f37..2afe2767427 100644
--- a/api/controllers/console/app/message.py
+++ b/api/controllers/console/app/message.py
@@ -3,8 +3,9 @@ from typing import Literal
from flask import request
from flask_restx import Resource, fields, marshal_with
+from graphon.model_runtime.errors.invoke import InvokeError
from pydantic import BaseModel, Field, field_validator
-from sqlalchemy import exists, select
+from sqlalchemy import exists, func, select
from werkzeug.exceptions import InternalServerError, NotFound
from controllers.common.schema import register_schema_models
@@ -24,7 +25,6 @@ from controllers.console.wraps import (
)
from core.app.entities.app_invoke_entities import InvokeFrom
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
-from dify_graph.model_runtime.errors.invoke import InvokeError
from extensions.ext_database import db
from fields.raws import FilesContainedField
from libs.helper import TimestampField, uuid_value
@@ -244,27 +244,25 @@ class ChatMessageListApi(Resource):
def get(self, app_model):
args = ChatMessagesQuery.model_validate(request.args.to_dict())
- conversation = (
- db.session.query(Conversation)
+ conversation = db.session.scalar(
+ select(Conversation)
.where(Conversation.id == args.conversation_id, Conversation.app_id == app_model.id)
- .first()
+ .limit(1)
)
if not conversation:
raise NotFound("Conversation Not Exists.")
if args.first_id:
- first_message = (
- db.session.query(Message)
- .where(Message.conversation_id == conversation.id, Message.id == args.first_id)
- .first()
+ first_message = db.session.scalar(
+ select(Message).where(Message.conversation_id == conversation.id, Message.id == args.first_id).limit(1)
)
if not first_message:
raise NotFound("First message not found")
- history_messages = (
- db.session.query(Message)
+ history_messages = db.session.scalars(
+ select(Message)
.where(
Message.conversation_id == conversation.id,
Message.created_at < first_message.created_at,
@@ -272,16 +270,14 @@ class ChatMessageListApi(Resource):
)
.order_by(Message.created_at.desc())
.limit(args.limit)
- .all()
- )
+ ).all()
else:
- history_messages = (
- db.session.query(Message)
+ history_messages = db.session.scalars(
+ select(Message)
.where(Message.conversation_id == conversation.id)
.order_by(Message.created_at.desc())
.limit(args.limit)
- .all()
- )
+ ).all()
# Initialize has_more based on whether we have a full page
if len(history_messages) == args.limit:
@@ -326,7 +322,9 @@ class MessageFeedbackApi(Resource):
message_id = str(args.message_id)
- message = db.session.query(Message).where(Message.id == message_id, Message.app_id == app_model.id).first()
+ message = db.session.scalar(
+ select(Message).where(Message.id == message_id, Message.app_id == app_model.id).limit(1)
+ )
if not message:
raise NotFound("Message Not Exists.")
@@ -375,7 +373,9 @@ class MessageAnnotationCountApi(Resource):
@login_required
@account_initialization_required
def get(self, app_model):
- count = db.session.query(MessageAnnotation).where(MessageAnnotation.app_id == app_model.id).count()
+ count = db.session.scalar(
+ select(func.count(MessageAnnotation.id)).where(MessageAnnotation.app_id == app_model.id)
+ )
return {"count": count}
@@ -479,7 +479,9 @@ class MessageApi(Resource):
def get(self, app_model, message_id: str):
message_id = str(message_id)
- message = db.session.query(Message).where(Message.id == message_id, Message.app_id == app_model.id).first()
+ message = db.session.scalar(
+ select(Message).where(Message.id == message_id, Message.app_id == app_model.id).limit(1)
+ )
if not message:
raise NotFound("Message Not Exists.")
diff --git a/api/controllers/console/app/model_config.py b/api/controllers/console/app/model_config.py
index a85e54fb512..8bb5aa2c1b1 100644
--- a/api/controllers/console/app/model_config.py
+++ b/api/controllers/console/app/model_config.py
@@ -69,9 +69,7 @@ class ModelConfigResource(Resource):
if app_model.mode == AppMode.AGENT_CHAT or app_model.is_agent:
# get original app model config
- original_app_model_config = (
- db.session.query(AppModelConfig).where(AppModelConfig.id == app_model.app_model_config_id).first()
- )
+ original_app_model_config = db.session.get(AppModelConfig, app_model.app_model_config_id)
if original_app_model_config is None:
raise ValueError("Original app model config not found")
agent_mode = original_app_model_config.agent_mode_dict
@@ -90,6 +88,7 @@ class ModelConfigResource(Resource):
tenant_id=current_tenant_id,
app_id=app_model.id,
agent_tool=agent_tool_entity,
+ user_id=current_user.id,
)
manager = ToolParameterConfigurationManager(
tenant_id=current_tenant_id,
@@ -129,6 +128,7 @@ class ModelConfigResource(Resource):
tenant_id=current_tenant_id,
app_id=app_model.id,
agent_tool=agent_tool_entity,
+ user_id=current_user.id,
)
except Exception:
continue
diff --git a/api/controllers/console/app/site.py b/api/controllers/console/app/site.py
index db218d8b813..7f44a99ff13 100644
--- a/api/controllers/console/app/site.py
+++ b/api/controllers/console/app/site.py
@@ -2,6 +2,7 @@ from typing import Literal
from flask_restx import Resource, marshal_with
from pydantic import BaseModel, Field, field_validator
+from sqlalchemy import select
from werkzeug.exceptions import NotFound
from constants.languages import supported_language
@@ -75,7 +76,7 @@ class AppSite(Resource):
def post(self, app_model):
args = AppSiteUpdatePayload.model_validate(console_ns.payload or {})
current_user, _ = current_account_with_tenant()
- site = db.session.query(Site).where(Site.app_id == app_model.id).first()
+ site = db.session.scalar(select(Site).where(Site.app_id == app_model.id).limit(1))
if not site:
raise NotFound
@@ -124,7 +125,7 @@ class AppSiteAccessTokenReset(Resource):
@marshal_with(app_site_model)
def post(self, app_model):
current_user, _ = current_account_with_tenant()
- site = db.session.query(Site).where(Site.app_id == app_model.id).first()
+ site = db.session.scalar(select(Site).where(Site.app_id == app_model.id).limit(1))
if not site:
raise NotFound
diff --git a/api/controllers/console/app/workflow.py b/api/controllers/console/app/workflow.py
index 837245ecb11..1f5a84c0b2b 100644
--- a/api/controllers/console/app/workflow.py
+++ b/api/controllers/console/app/workflow.py
@@ -5,9 +5,13 @@ from typing import Any
from flask import abort, request
from flask_restx import Resource, fields, marshal_with
+from graphon.enums import NodeType
+from graphon.file import File
+from graphon.graph_engine.manager import GraphEngineManager
+from graphon.model_runtime.utils.encoders import jsonable_encoder
from pydantic import BaseModel, Field, field_validator
from sqlalchemy.orm import Session
-from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
+from werkzeug.exceptions import BadRequest, Forbidden, InternalServerError, NotFound
import services
from controllers.console import console_ns
@@ -20,6 +24,7 @@ from core.app.app_config.features.file_upload.manager import FileUploadConfigMan
from core.app.apps.base_app_queue_manager import AppQueueManager
from core.app.apps.workflow.app_generator import SKIP_PREPARE_USER_INPUTS_KEY
from core.app.entities.app_invoke_entities import InvokeFrom
+from core.app.file_access import DatabaseFileAccessController
from core.helper.trace_id_helper import get_external_trace_id
from core.plugin.impl.exc import PluginInvokeError
from core.trigger.constants import TRIGGER_SCHEDULE_NODE_TYPE
@@ -29,10 +34,6 @@ from core.trigger.debug.event_selectors import (
create_event_poller,
select_trigger_debug_events,
)
-from dify_graph.enums import NodeType
-from dify_graph.file.models import File
-from dify_graph.graph_engine.manager import GraphEngineManager
-from dify_graph.model_runtime.utils.encoders import jsonable_encoder
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from factories import file_factory, variable_factory
@@ -46,13 +47,15 @@ from models import App
from models.model import AppMode
from models.workflow import Workflow
from services.app_generate_service import AppGenerateService
-from services.errors.app import WorkflowHashNotEqualError
+from services.errors.app import IsDraftWorkflowError, WorkflowHashNotEqualError, WorkflowNotFoundError
from services.errors.llm import InvokeRateLimitError
from services.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError, WorkflowService
logger = logging.getLogger(__name__)
+_file_access_controller = DatabaseFileAccessController()
LISTENING_RETRY_IN = 2000
DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+RESTORE_SOURCE_WORKFLOW_MUST_BE_PUBLISHED_MESSAGE = "source workflow must be published"
# Register models for flask_restx to avoid dict type issues in Swagger
# Register in dependency order: base models first, then dependent models
@@ -203,6 +206,7 @@ def _parse_file(workflow: Workflow, files: list[dict] | None = None) -> Sequence
mappings=files,
tenant_id=workflow.tenant_id,
config=file_extra_config,
+ access_controller=_file_access_controller,
)
return file_objs
@@ -284,7 +288,9 @@ class DraftWorkflowApi(Resource):
workflow_service = WorkflowService()
try:
- environment_variables_list = args.get("environment_variables") or []
+ environment_variables_list = Workflow.normalize_environment_variable_mappings(
+ args.get("environment_variables") or [],
+ )
environment_variables = [
variable_factory.build_environment_variable_from_mapping(obj) for obj in environment_variables_list
]
@@ -994,6 +1000,43 @@ class PublishedAllWorkflowApi(Resource):
}
+@console_ns.route("/apps/") for cell in item.rows[0].cells] - markdown_table = f"| {' | '.join(cell_texts)} |\n" - markdown_table += f"| {' | '.join(['---'] * len(item.rows[0].cells))} |\n" - - for row in item.rows[1:]: - # Replace newlines with
in each cell - row_cells = [cell.text.replace("\n", "
") for cell in row.cells] - markdown_table += "| " + " | ".join(row_cells) + " |\n" - - text.append(markdown_table) - except Exception as e: - logger.warning("Failed to extract table from DOC: %s", e) - continue - - return "\n".join(text) - - except Exception as e: - raise TextExtractionError(f"Failed to extract text from DOCX: {str(e)}") from e - - -def _download_file_content(http_client: HttpClientProtocol, file: File) -> bytes: - """Download the content of a file based on its transfer method.""" - try: - if file.transfer_method == FileTransferMethod.REMOTE_URL: - if file.remote_url is None: - raise FileDownloadError("Missing URL for remote file") - response = http_client.get(file.remote_url) - response.raise_for_status() - return response.content - else: - return file_manager.download(file) - except Exception as e: - raise FileDownloadError(f"Error downloading file: {str(e)}") from e - - -def _extract_text_from_file( - http_client: HttpClientProtocol, file: File, *, unstructured_api_config: UnstructuredApiConfig -) -> str: - file_content = _download_file_content(http_client, file) - if file.extension: - extracted_text = _extract_text_by_file_extension( - file_content=file_content, - file_extension=file.extension, - unstructured_api_config=unstructured_api_config, - ) - elif file.mime_type: - extracted_text = _extract_text_by_mime_type( - file_content=file_content, - mime_type=file.mime_type, - unstructured_api_config=unstructured_api_config, - ) - else: - raise UnsupportedFileTypeError("Unable to determine file type: MIME type or file extension is missing") - return extracted_text - - -def _extract_text_from_csv(file_content: bytes) -> str: - try: - # Detect encoding using charset_normalizer - result = charset_normalizer.from_bytes(file_content).best() - if result: - encoding = result.encoding - else: - encoding = "utf-8" - - # Fallback to utf-8 if detection fails - if not encoding: - encoding = "utf-8" - - try: - csv_file = io.StringIO(file_content.decode(encoding, errors="ignore")) - except (UnicodeDecodeError, LookupError): - # If decoding fails, try with utf-8 as last resort - csv_file = io.StringIO(file_content.decode("utf-8", errors="ignore")) - - csv_reader = csv.reader(csv_file) - rows = list(csv_reader) - - if not rows: - return "" - - # Combine multi-line text in the header row - header_row = [cell.replace("\n", " ").replace("\r", "") for cell in rows[0]] - - # Create Markdown table - markdown_table = "| " + " | ".join(header_row) + " |\n" - markdown_table += "| " + " | ".join(["-" * len(col) for col in rows[0]]) + " |\n" - - # Process each data row and combine multi-line text in each cell - for row in rows[1:]: - processed_row = [cell.replace("\n", " ").replace("\r", "") for cell in row] - markdown_table += "| " + " | ".join(processed_row) + " |\n" - - return markdown_table - except Exception as e: - raise TextExtractionError(f"Failed to extract text from CSV: {str(e)}") from e - - -def _extract_text_from_excel(file_content: bytes) -> str: - """Extract text from an Excel file using pandas.""" - - def _construct_markdown_table(df: pd.DataFrame) -> str: - """Manually construct a Markdown table from a DataFrame.""" - # Construct the header row - header_row = "| " + " | ".join(df.columns) + " |" - - # Construct the separator row - separator_row = "| " + " | ".join(["-" * len(col) for col in df.columns]) + " |" - - # Construct the data rows - data_rows = [] - for _, row in df.iterrows(): - data_row = "| " + " | ".join(map(str, row)) + " |" - data_rows.append(data_row) - - # Combine all rows into a single string - markdown_table = "\n".join([header_row, separator_row] + data_rows) - return markdown_table - - try: - excel_file = pd.ExcelFile(io.BytesIO(file_content)) - markdown_table = "" - for sheet_name in excel_file.sheet_names: - try: - df = excel_file.parse(sheet_name=sheet_name) - df.dropna(how="all", inplace=True) - - # Combine multi-line text in each cell into a single line - df = df.map(lambda x: " ".join(str(x).splitlines()) if isinstance(x, str) else x) - - # Combine multi-line text in column names into a single line - df.columns = pd.Index([" ".join(str(col).splitlines()) for col in df.columns]) - - # Manually construct the Markdown table - markdown_table += _construct_markdown_table(df) + "\n\n" - except Exception: - continue - return markdown_table - except Exception as e: - raise TextExtractionError(f"Failed to extract text from Excel file: {str(e)}") from e - - -def _extract_text_from_ppt(file_content: bytes, *, unstructured_api_config: UnstructuredApiConfig) -> str: - from unstructured.partition.api import partition_via_api - from unstructured.partition.ppt import partition_ppt - - api_key = unstructured_api_config.api_key or "" - - try: - if unstructured_api_config.api_url: - with tempfile.NamedTemporaryFile(suffix=".ppt", delete=False) as temp_file: - temp_file.write(file_content) - temp_file.flush() - with open(temp_file.name, "rb") as file: - elements = partition_via_api( - file=file, - metadata_filename=temp_file.name, - api_url=unstructured_api_config.api_url, - api_key=api_key, - ) - os.unlink(temp_file.name) - else: - with io.BytesIO(file_content) as file: - elements = partition_ppt(file=file) - return "\n".join([getattr(element, "text", "") for element in elements]) - - except Exception as e: - raise TextExtractionError(f"Failed to extract text from PPTX: {str(e)}") from e - - -def _extract_text_from_pptx(file_content: bytes, *, unstructured_api_config: UnstructuredApiConfig) -> str: - from unstructured.partition.api import partition_via_api - from unstructured.partition.pptx import partition_pptx - - api_key = unstructured_api_config.api_key or "" - - try: - if unstructured_api_config.api_url: - with tempfile.NamedTemporaryFile(suffix=".pptx", delete=False) as temp_file: - temp_file.write(file_content) - temp_file.flush() - with open(temp_file.name, "rb") as file: - elements = partition_via_api( - file=file, - metadata_filename=temp_file.name, - api_url=unstructured_api_config.api_url, - api_key=api_key, - ) - os.unlink(temp_file.name) - else: - with io.BytesIO(file_content) as file: - elements = partition_pptx(file=file) - return "\n".join([getattr(element, "text", "") for element in elements]) - except Exception as e: - raise TextExtractionError(f"Failed to extract text from PPTX: {str(e)}") from e - - -def _extract_text_from_epub(file_content: bytes, *, unstructured_api_config: UnstructuredApiConfig) -> str: - from unstructured.partition.api import partition_via_api - from unstructured.partition.epub import partition_epub - - api_key = unstructured_api_config.api_key or "" - - try: - if unstructured_api_config.api_url: - with tempfile.NamedTemporaryFile(suffix=".epub", delete=False) as temp_file: - temp_file.write(file_content) - temp_file.flush() - with open(temp_file.name, "rb") as file: - elements = partition_via_api( - file=file, - metadata_filename=temp_file.name, - api_url=unstructured_api_config.api_url, - api_key=api_key, - ) - os.unlink(temp_file.name) - else: - pypandoc.download_pandoc() - with io.BytesIO(file_content) as file: - elements = partition_epub(file=file) - return "\n".join([str(element) for element in elements]) - except Exception as e: - raise TextExtractionError(f"Failed to extract text from EPUB: {str(e)}") from e - - -def _extract_text_from_eml(file_content: bytes) -> str: - from unstructured.partition.email import partition_email - - try: - with io.BytesIO(file_content) as file: - elements = partition_email(file=file) - return "\n".join([str(element) for element in elements]) - except Exception as e: - raise TextExtractionError(f"Failed to extract text from EML: {str(e)}") from e - - -def _extract_text_from_msg(file_content: bytes) -> str: - from unstructured.partition.msg import partition_msg - - try: - with io.BytesIO(file_content) as file: - elements = partition_msg(file=file) - return "\n".join([str(element) for element in elements]) - except Exception as e: - raise TextExtractionError(f"Failed to extract text from MSG: {str(e)}") from e - - -def _extract_text_from_vtt(vtt_bytes: bytes) -> str: - text = _extract_text_from_plain_text(vtt_bytes) - - # remove bom - text = text.lstrip("\ufeff") - - raw_results = [] - for caption in webvtt.from_string(text): - raw_results.append((caption.voice, caption.text)) - - # Merge consecutive utterances by the same speaker - merged_results = [] - if raw_results: - current_speaker, current_text = raw_results[0] - - for i in range(1, len(raw_results)): - spk, txt = raw_results[i] - if spk is None: - merged_results.append((None, current_text)) - continue - - if spk == current_speaker: - # If it is the same speaker, merge the utterances (joined by space) - current_text += " " + txt - else: - # If the speaker changes, register the utterance so far and move on - merged_results.append((current_speaker, current_text)) - current_speaker, current_text = spk, txt - - # Add the last element - merged_results.append((current_speaker, current_text)) - else: - merged_results = raw_results - - # Return the result in the specified format: Speaker "text" style - formatted = [f'{spk or ""} "{txt}"' for spk, txt in merged_results] - return "\n".join(formatted) - - -def _extract_text_from_properties(file_content: bytes) -> str: - try: - text = _extract_text_from_plain_text(file_content) - lines = text.splitlines() - result = [] - for line in lines: - line = line.strip() - # Preserve comments and empty lines - if not line or line.startswith("#") or line.startswith("!"): - result.append(line) - continue - - if "=" in line: - key, value = line.split("=", 1) - elif ":" in line: - key, value = line.split(":", 1) - else: - key, value = line, "" - - result.append(f"{key.strip()}: {value.strip()}") - - return "\n".join(result) - except Exception as e: - raise TextExtractionError(f"Failed to extract text from properties file: {str(e)}") from e diff --git a/api/dify_graph/nodes/end/end_node.py b/api/dify_graph/nodes/end/end_node.py deleted file mode 100644 index 1f5cfab22bc..00000000000 --- a/api/dify_graph/nodes/end/end_node.py +++ /dev/null @@ -1,47 +0,0 @@ -from dify_graph.enums import BuiltinNodeTypes, NodeExecutionType, WorkflowNodeExecutionStatus -from dify_graph.node_events import NodeRunResult -from dify_graph.nodes.base.node import Node -from dify_graph.nodes.base.template import Template -from dify_graph.nodes.end.entities import EndNodeData - - -class EndNode(Node[EndNodeData]): - node_type = BuiltinNodeTypes.END - execution_type = NodeExecutionType.RESPONSE - - @classmethod - def version(cls) -> str: - return "1" - - def _run(self) -> NodeRunResult: - """ - Run node - collect all outputs at once. - - This method runs after streaming is complete (if streaming was enabled). - It collects all output variables and returns them. - """ - output_variables = self.node_data.outputs - - outputs = {} - for variable_selector in output_variables: - variable = self.graph_runtime_state.variable_pool.get(variable_selector.value_selector) - value = variable.to_object() if variable is not None else None - outputs[variable_selector.variable] = value - - return NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, - inputs=outputs, - outputs=outputs, - ) - - def get_streaming_template(self) -> Template: - """ - Get the template for streaming. - - Returns: - Template instance for this End node - """ - outputs_config = [ - {"variable": output.variable, "value_selector": output.value_selector} for output in self.node_data.outputs - ] - return Template.from_end_outputs(outputs_config) diff --git a/api/dify_graph/nodes/end/entities.py b/api/dify_graph/nodes/end/entities.py deleted file mode 100644 index be7f0c8de8a..00000000000 --- a/api/dify_graph/nodes/end/entities.py +++ /dev/null @@ -1,27 +0,0 @@ -from pydantic import BaseModel, Field - -from dify_graph.entities.base_node_data import BaseNodeData -from dify_graph.enums import BuiltinNodeTypes, NodeType -from dify_graph.nodes.base.entities import OutputVariableEntity - - -class EndNodeData(BaseNodeData): - """ - END Node Data. - """ - - type: NodeType = BuiltinNodeTypes.END - outputs: list[OutputVariableEntity] - - -class EndStreamParam(BaseModel): - """ - EndStreamParam entity - """ - - end_dependencies: dict[str, list[str]] = Field( - ..., description="end dependencies (end node id -> dependent node ids)" - ) - end_stream_variable_selector_mapping: dict[str, list[list[str]]] = Field( - ..., description="end stream variable selector mapping (end node id -> stream variable selectors)" - ) diff --git a/api/dify_graph/nodes/http_request/__init__.py b/api/dify_graph/nodes/http_request/__init__.py deleted file mode 100644 index b29099db230..00000000000 --- a/api/dify_graph/nodes/http_request/__init__.py +++ /dev/null @@ -1,22 +0,0 @@ -from .config import build_http_request_config, resolve_http_request_config -from .entities import ( - HTTP_REQUEST_CONFIG_FILTER_KEY, - BodyData, - HttpRequestNodeAuthorization, - HttpRequestNodeBody, - HttpRequestNodeConfig, - HttpRequestNodeData, -) -from .node import HttpRequestNode - -__all__ = [ - "HTTP_REQUEST_CONFIG_FILTER_KEY", - "BodyData", - "HttpRequestNode", - "HttpRequestNodeAuthorization", - "HttpRequestNodeBody", - "HttpRequestNodeConfig", - "HttpRequestNodeData", - "build_http_request_config", - "resolve_http_request_config", -] diff --git a/api/dify_graph/nodes/http_request/config.py b/api/dify_graph/nodes/http_request/config.py deleted file mode 100644 index 53bf6c7ae4c..00000000000 --- a/api/dify_graph/nodes/http_request/config.py +++ /dev/null @@ -1,33 +0,0 @@ -from collections.abc import Mapping - -from .entities import HTTP_REQUEST_CONFIG_FILTER_KEY, HttpRequestNodeConfig - - -def build_http_request_config( - *, - max_connect_timeout: int = 10, - max_read_timeout: int = 600, - max_write_timeout: int = 600, - max_binary_size: int = 10 * 1024 * 1024, - max_text_size: int = 1 * 1024 * 1024, - ssl_verify: bool = True, - ssrf_default_max_retries: int = 3, -) -> HttpRequestNodeConfig: - return HttpRequestNodeConfig( - max_connect_timeout=max_connect_timeout, - max_read_timeout=max_read_timeout, - max_write_timeout=max_write_timeout, - max_binary_size=max_binary_size, - max_text_size=max_text_size, - ssl_verify=ssl_verify, - ssrf_default_max_retries=ssrf_default_max_retries, - ) - - -def resolve_http_request_config(filters: Mapping[str, object] | None) -> HttpRequestNodeConfig: - if not filters: - raise ValueError("http_request_config is required to build HTTP request default config") - config = filters.get(HTTP_REQUEST_CONFIG_FILTER_KEY) - if not isinstance(config, HttpRequestNodeConfig): - raise ValueError("http_request_config must be an HttpRequestNodeConfig instance") - return config diff --git a/api/dify_graph/nodes/http_request/entities.py b/api/dify_graph/nodes/http_request/entities.py deleted file mode 100644 index f594d58ae64..00000000000 --- a/api/dify_graph/nodes/http_request/entities.py +++ /dev/null @@ -1,241 +0,0 @@ -import mimetypes -from collections.abc import Sequence -from dataclasses import dataclass -from email.message import Message -from typing import Any, Literal - -import charset_normalizer -import httpx -from pydantic import BaseModel, Field, ValidationInfo, field_validator - -from dify_graph.entities.base_node_data import BaseNodeData -from dify_graph.enums import BuiltinNodeTypes, NodeType - -HTTP_REQUEST_CONFIG_FILTER_KEY = "http_request_config" - - -class HttpRequestNodeAuthorizationConfig(BaseModel): - type: Literal["basic", "bearer", "custom"] - api_key: str - header: str = "" - - -class HttpRequestNodeAuthorization(BaseModel): - type: Literal["no-auth", "api-key"] - config: HttpRequestNodeAuthorizationConfig | None = None - - @field_validator("config", mode="before") - @classmethod - def check_config(cls, v: HttpRequestNodeAuthorizationConfig, values: ValidationInfo): - """ - Check config, if type is no-auth, config should be None, otherwise it should be a dict. - """ - if values.data["type"] == "no-auth": - return None - else: - if not v or not isinstance(v, dict): - raise ValueError("config should be a dict") - - return v - - -class BodyData(BaseModel): - key: str = "" - type: Literal["file", "text"] - value: str = "" - file: Sequence[str] = Field(default_factory=list) - - -class HttpRequestNodeBody(BaseModel): - type: Literal["none", "form-data", "x-www-form-urlencoded", "raw-text", "json", "binary"] - data: Sequence[BodyData] = Field(default_factory=list) - - @field_validator("data", mode="before") - @classmethod - def check_data(cls, v: Any): - """For compatibility, if body is not set, return empty list.""" - if not v: - return [] - if isinstance(v, str): - return [BodyData(key="", type="text", value=v)] - return v - - -class HttpRequestNodeTimeout(BaseModel): - connect: int | None = None - read: int | None = None - write: int | None = None - - -@dataclass(frozen=True, slots=True) -class HttpRequestNodeConfig: - max_connect_timeout: int - max_read_timeout: int - max_write_timeout: int - max_binary_size: int - max_text_size: int - ssl_verify: bool - ssrf_default_max_retries: int - - def default_timeout(self) -> "HttpRequestNodeTimeout": - return HttpRequestNodeTimeout( - connect=self.max_connect_timeout, - read=self.max_read_timeout, - write=self.max_write_timeout, - ) - - -class HttpRequestNodeData(BaseNodeData): - """ - Code Node Data. - """ - - type: NodeType = BuiltinNodeTypes.HTTP_REQUEST - method: Literal[ - "get", - "post", - "put", - "patch", - "delete", - "head", - "options", - "GET", - "POST", - "PUT", - "PATCH", - "DELETE", - "HEAD", - "OPTIONS", - ] - url: str - authorization: HttpRequestNodeAuthorization - headers: str - params: str - body: HttpRequestNodeBody | None = None - timeout: HttpRequestNodeTimeout | None = None - ssl_verify: bool | None = None - - -class Response: - headers: dict[str, str] - response: httpx.Response - _cached_text: str | None - - def __init__(self, response: httpx.Response): - self.response = response - self.headers = dict(response.headers) - self._cached_text = None - - @property - def is_file(self): - """ - Determine if the response contains a file by checking: - 1. Content-Disposition header (RFC 6266) - 2. Content characteristics - 3. MIME type analysis - """ - content_type = self.content_type.split(";")[0].strip().lower() - parsed_content_disposition = self.parsed_content_disposition - - # Check if it's explicitly marked as an attachment - if parsed_content_disposition: - disp_type = parsed_content_disposition.get_content_disposition() # Returns 'attachment', 'inline', or None - filename = parsed_content_disposition.get_filename() # Returns filename if present, None otherwise - if disp_type == "attachment" or filename is not None: - return True - - # For 'text/' types, only 'csv' should be downloaded as file - if content_type.startswith("text/") and "csv" not in content_type: - return False - - # For application types, try to detect if it's a text-based format - if content_type.startswith("application/"): - # Common text-based application types - if any( - text_type in content_type - for text_type in ("json", "xml", "javascript", "x-www-form-urlencoded", "yaml", "graphql") - ): - return False - - # Try to detect if content is text-based by sampling first few bytes - try: - # Sample first 1024 bytes for text detection - content_sample = self.response.content[:1024] - content_sample.decode("utf-8") - # If we can decode as UTF-8 and find common text patterns, likely not a file - text_markers = (b"{", b"[", b"<", b"function", b"var ", b"const ", b"let ") - if any(marker in content_sample for marker in text_markers): - return False - except UnicodeDecodeError: - # If we can't decode as UTF-8, likely a binary file - return True - - # For other types, use MIME type analysis - main_type, _ = mimetypes.guess_type("dummy" + (mimetypes.guess_extension(content_type) or "")) - if main_type: - return main_type.split("/")[0] in ("application", "image", "audio", "video") - - # For unknown types, check if it's a media type - return any(media_type in content_type for media_type in ("image/", "audio/", "video/")) - - @property - def content_type(self) -> str: - return self.headers.get("content-type", "") - - @property - def text(self) -> str: - """ - Get response text with robust encoding detection. - - Uses charset_normalizer for better encoding detection than httpx's default, - which helps handle Chinese and other non-ASCII characters properly. - """ - # Check cache first - if hasattr(self, "_cached_text") and self._cached_text is not None: - return self._cached_text - - # Try charset_normalizer for robust encoding detection first - detected_encoding = charset_normalizer.from_bytes(self.response.content).best() - if detected_encoding and detected_encoding.encoding: - try: - text = self.response.content.decode(detected_encoding.encoding) - self._cached_text = text - return text - except (UnicodeDecodeError, TypeError, LookupError): - # Fallback to httpx's encoding detection if charset_normalizer fails - pass - - # Fallback to httpx's built-in encoding detection - text = self.response.text - self._cached_text = text - return text - - @property - def content(self) -> bytes: - return self.response.content - - @property - def status_code(self) -> int: - return self.response.status_code - - @property - def size(self) -> int: - return len(self.content) - - @property - def readable_size(self) -> str: - if self.size < 1024: - return f"{self.size} bytes" - elif self.size < 1024 * 1024: - return f"{(self.size / 1024):.2f} KB" - else: - return f"{(self.size / 1024 / 1024):.2f} MB" - - @property - def parsed_content_disposition(self) -> Message | None: - content_disposition = self.headers.get("content-disposition", "") - if content_disposition: - msg = Message() - msg["content-disposition"] = content_disposition - return msg - return None diff --git a/api/dify_graph/nodes/http_request/exc.py b/api/dify_graph/nodes/http_request/exc.py deleted file mode 100644 index 46613c9e861..00000000000 --- a/api/dify_graph/nodes/http_request/exc.py +++ /dev/null @@ -1,26 +0,0 @@ -class HttpRequestNodeError(ValueError): - """Custom error for HTTP request node.""" - - -class AuthorizationConfigError(HttpRequestNodeError): - """Raised when authorization config is missing or invalid.""" - - -class FileFetchError(HttpRequestNodeError): - """Raised when a file cannot be fetched.""" - - -class InvalidHttpMethodError(HttpRequestNodeError): - """Raised when an invalid HTTP method is used.""" - - -class ResponseSizeError(HttpRequestNodeError): - """Raised when the response size exceeds the allowed threshold.""" - - -class RequestBodyError(HttpRequestNodeError): - """Raised when the request body is invalid.""" - - -class InvalidURLError(HttpRequestNodeError): - """Raised when the URL is invalid.""" diff --git a/api/dify_graph/nodes/http_request/executor.py b/api/dify_graph/nodes/http_request/executor.py deleted file mode 100644 index 892b0fc688a..00000000000 --- a/api/dify_graph/nodes/http_request/executor.py +++ /dev/null @@ -1,488 +0,0 @@ -import base64 -import json -import secrets -import string -from collections.abc import Callable, Mapping -from copy import deepcopy -from typing import Any, Literal -from urllib.parse import urlencode, urlparse - -import httpx -from json_repair import repair_json - -from dify_graph.file.enums import FileTransferMethod -from dify_graph.runtime import VariablePool -from dify_graph.variables.segments import ArrayFileSegment, FileSegment - -from ..protocols import FileManagerProtocol, HttpClientProtocol -from .entities import ( - HttpRequestNodeAuthorization, - HttpRequestNodeConfig, - HttpRequestNodeData, - HttpRequestNodeTimeout, - Response, -) -from .exc import ( - AuthorizationConfigError, - FileFetchError, - HttpRequestNodeError, - InvalidHttpMethodError, - InvalidURLError, - RequestBodyError, - ResponseSizeError, -) - -BODY_TYPE_TO_CONTENT_TYPE = { - "json": "application/json", - "x-www-form-urlencoded": "application/x-www-form-urlencoded", - "form-data": "multipart/form-data", - "raw-text": "text/plain", -} - - -class Executor: - method: Literal[ - "get", - "head", - "post", - "put", - "delete", - "patch", - "options", - "GET", - "POST", - "PUT", - "PATCH", - "DELETE", - "HEAD", - "OPTIONS", - ] - url: str - params: list[tuple[str, str]] | None - content: str | bytes | None - data: Mapping[str, Any] | None - files: list[tuple[str, tuple[str | None, bytes, str]]] | None - json: Any - headers: dict[str, str] - auth: HttpRequestNodeAuthorization - timeout: HttpRequestNodeTimeout - max_retries: int - - boundary: str - - def __init__( - self, - *, - node_data: HttpRequestNodeData, - timeout: HttpRequestNodeTimeout, - variable_pool: VariablePool, - http_request_config: HttpRequestNodeConfig, - max_retries: int | None = None, - ssl_verify: bool | None = None, - http_client: HttpClientProtocol, - file_manager: FileManagerProtocol, - ): - self._http_request_config = http_request_config - # If authorization API key is present, convert the API key using the variable pool - if node_data.authorization.type == "api-key": - if node_data.authorization.config is None: - raise AuthorizationConfigError("authorization config is required") - node_data.authorization.config.api_key = variable_pool.convert_template( - node_data.authorization.config.api_key - ).text - # Validate that API key is not empty after template conversion - if not node_data.authorization.config.api_key or not node_data.authorization.config.api_key.strip(): - raise AuthorizationConfigError( - "API key is required for authorization but was empty. Please provide a valid API key." - ) - - self.url = node_data.url - self.method = node_data.method - self.auth = node_data.authorization - self.timeout = timeout - self.ssl_verify = ssl_verify if ssl_verify is not None else node_data.ssl_verify - if self.ssl_verify is None: - self.ssl_verify = self._http_request_config.ssl_verify - if not isinstance(self.ssl_verify, bool): - raise ValueError("ssl_verify must be a boolean") - self.params = None - self.headers = {} - self.content = None - self.files = None - self.data = None - self.json = None - self.max_retries = ( - max_retries if max_retries is not None else self._http_request_config.ssrf_default_max_retries - ) - self._http_client = http_client - self._file_manager = file_manager - - # init template - self.variable_pool = variable_pool - self.node_data = node_data - self._initialize() - - def _initialize(self): - self._init_url() - self._init_params() - self._init_headers() - self._init_body() - - def _init_url(self): - self.url = self.variable_pool.convert_template(self.node_data.url).text - - # check if url is a valid URL - if not self.url: - raise InvalidURLError("url is required") - if not self.url.startswith(("http://", "https://")): - raise InvalidURLError("url should start with http:// or https://") - - def _init_params(self): - """ - Almost same as _init_headers(), difference: - 1. response a list tuple to support same key, like 'aa=1&aa=2' - 2. param value may have '\n', we need to splitlines then extract the variable value. - """ - result = [] - for line in self.node_data.params.splitlines(): - if not (line := line.strip()): - continue - - key, *value = line.split(":", 1) - if not (key := key.strip()): - continue - - value_str = value[0].strip() if value else "" - result.append( - (self.variable_pool.convert_template(key).text, self.variable_pool.convert_template(value_str).text) - ) - - if result: - self.params = result - - def _init_headers(self): - """ - Convert the header string of frontend to a dictionary. - - Each line in the header string represents a key-value pair. - Keys and values are separated by ':'. - Empty values are allowed. - - Examples: - 'aa:bb\n cc:dd' -> {'aa': 'bb', 'cc': 'dd'} - 'aa:\n cc:dd\n' -> {'aa': '', 'cc': 'dd'} - 'aa\n cc : dd' -> {'aa': '', 'cc': 'dd'} - - """ - headers = self.variable_pool.convert_template(self.node_data.headers).text - self.headers = { - key.strip(): (value[0].strip() if value else "") - for line in headers.splitlines() - if line.strip() - for key, *value in [line.split(":", 1)] - } - - def _init_body(self): - body = self.node_data.body - if body is not None: - data = body.data - match body.type: - case "none": - self.content = "" - case "raw-text": - if len(data) != 1: - raise RequestBodyError("raw-text body type should have exactly one item") - self.content = self.variable_pool.convert_template(data[0].value).text - case "json": - if len(data) != 1: - raise RequestBodyError("json body type should have exactly one item") - json_string = self.variable_pool.convert_template(data[0].value).text - try: - repaired = repair_json(json_string) - json_object = json.loads(repaired, strict=False) - except json.JSONDecodeError as e: - raise RequestBodyError(f"Failed to parse JSON: {json_string}") from e - self.json = json_object - # self.json = self._parse_object_contains_variables(json_object) - case "binary": - if len(data) != 1: - raise RequestBodyError("binary body type should have exactly one item") - file_selector = data[0].file - file_variable = self.variable_pool.get_file(file_selector) - if file_variable is None: - raise FileFetchError(f"cannot fetch file with selector {file_selector}") - file = file_variable.value - self.content = self._file_manager.download(file) - case "x-www-form-urlencoded": - form_data = { - self.variable_pool.convert_template(item.key).text: self.variable_pool.convert_template( - item.value - ).text - for item in data - } - self.data = form_data - case "form-data": - form_data = { - self.variable_pool.convert_template(item.key).text: self.variable_pool.convert_template( - item.value - ).text - for item in filter(lambda item: item.type == "text", data) - } - file_selectors = { - self.variable_pool.convert_template(item.key).text: item.file - for item in filter(lambda item: item.type == "file", data) - } - - # get files from file_selectors, add support for array file variables - files_list = [] - for key, selector in file_selectors.items(): - segment = self.variable_pool.get(selector) - if isinstance(segment, FileSegment): - files_list.append((key, [segment.value])) - elif isinstance(segment, ArrayFileSegment): - files_list.append((key, list(segment.value))) - - # get files from file_manager - files: dict[str, list[tuple[str | None, bytes, str]]] = {} - for key, files_in_segment in files_list: - for file in files_in_segment: - if file.related_id is not None or ( - file.transfer_method == FileTransferMethod.REMOTE_URL and file.remote_url is not None - ): - file_tuple = ( - file.filename, - self._file_manager.download(file), - file.mime_type or "application/octet-stream", - ) - if key not in files: - files[key] = [] - files[key].append(file_tuple) - - # convert files to list for httpx request - # If there are no actual files, we still need to force httpx to use `multipart/form-data`. - # This is achieved by inserting a harmless placeholder file that will be ignored by the server. - if not files: - self.files = [("__multipart_placeholder__", ("", b"", "application/octet-stream"))] - if files: - self.files = [] - for key, file_tuples in files.items(): - for file_tuple in file_tuples: - self.files.append((key, file_tuple)) - - self.data = form_data - - def _assembling_headers(self) -> dict[str, Any]: - authorization = deepcopy(self.auth) - headers = deepcopy(self.headers) or {} - if self.auth.type == "api-key": - if self.auth.config is None: - raise AuthorizationConfigError("self.authorization config is required") - if authorization.config is None: - raise AuthorizationConfigError("authorization config is required") - - if not authorization.config.header: - authorization.config.header = "Authorization" - - if self.auth.config.type == "bearer" and authorization.config.api_key: - headers[authorization.config.header] = f"Bearer {authorization.config.api_key}" - elif self.auth.config.type == "basic" and authorization.config.api_key: - credentials = authorization.config.api_key - if ":" in credentials: - encoded_credentials = base64.b64encode(credentials.encode("utf-8")).decode("utf-8") - else: - encoded_credentials = credentials - headers[authorization.config.header] = f"Basic {encoded_credentials}" - elif self.auth.config.type == "custom": - if authorization.config.header and authorization.config.api_key: - headers[authorization.config.header] = authorization.config.api_key - - # Handle Content-Type for multipart/form-data requests - # Fix for issue #23829: Missing boundary when using multipart/form-data - body = self.node_data.body - if body and body.type == "form-data": - # For multipart/form-data with files (including placeholder files), - # remove any manually set Content-Type header to let httpx handle - # For multipart/form-data, if any files are present (including placeholder files), - # we must remove any manually set Content-Type header. This is because httpx needs to - # automatically set the Content-Type and boundary for multipart encoding whenever files - # are included, even if they are placeholders, to avoid boundary issues and ensure correct - # file upload behaviour. Manually setting Content-Type can cause httpx to fail to set the - # boundary, resulting in invalid requests. - if self.files: - # Remove Content-Type if it was manually set to avoid boundary issues - headers = {k: v for k, v in headers.items() if k.lower() != "content-type"} - else: - # No files at all, set Content-Type manually - if "content-type" not in (k.lower() for k in headers): - headers["Content-Type"] = "multipart/form-data" - elif body and body.type in BODY_TYPE_TO_CONTENT_TYPE: - # Set Content-Type for other body types - if "content-type" not in (k.lower() for k in headers): - headers["Content-Type"] = BODY_TYPE_TO_CONTENT_TYPE[body.type] - - return headers - - def _validate_and_parse_response(self, response: httpx.Response) -> Response: - executor_response = Response(response) - - threshold_size = ( - self._http_request_config.max_binary_size - if executor_response.is_file - else self._http_request_config.max_text_size - ) - if executor_response.size > threshold_size: - raise ResponseSizeError( - f"{'File' if executor_response.is_file else 'Text'} size is too large," - f" max size is {threshold_size / 1024 / 1024:.2f} MB," - f" but current size is {executor_response.readable_size}." - ) - - return executor_response - - def _do_http_request(self, headers: dict[str, Any]) -> httpx.Response: - """ - do http request depending on api bundle - """ - _METHOD_MAP: dict[str, Callable[..., httpx.Response]] = { - "get": self._http_client.get, - "head": self._http_client.head, - "post": self._http_client.post, - "put": self._http_client.put, - "delete": self._http_client.delete, - "patch": self._http_client.patch, - } - method_lc = self.method.lower() - if method_lc not in _METHOD_MAP: - raise InvalidHttpMethodError(f"Invalid http method {self.method}") - - request_args: dict[str, Any] = { - "data": self.data, - "files": self.files, - "json": self.json, - "content": self.content, - "headers": headers, - "params": self.params, - "timeout": (self.timeout.connect, self.timeout.read, self.timeout.write), - "ssl_verify": self.ssl_verify, - "follow_redirects": True, - } - # request_args = {k: v for k, v in request_args.items() if v is not None} - try: - response = _METHOD_MAP[method_lc]( - url=self.url, - **request_args, - max_retries=self.max_retries, - ) - except self._http_client.max_retries_exceeded_error as e: - raise HttpRequestNodeError(f"Reached maximum retries for URL {self.url}") from e - except self._http_client.request_error as e: - raise HttpRequestNodeError(str(e)) from e - return response - - def invoke(self) -> Response: - # assemble headers - headers = self._assembling_headers() - # do http request - response = self._do_http_request(headers) - # validate response - return self._validate_and_parse_response(response) - - def to_log(self): - url_parts = urlparse(self.url) - path = url_parts.path or "/" - - # Add query parameters - if self.params: - query_string = urlencode(self.params) - path += f"?{query_string}" - elif url_parts.query: - path += f"?{url_parts.query}" - - raw = f"{self.method.upper()} {path} HTTP/1.1\r\n" - raw += f"Host: {url_parts.netloc}\r\n" - - headers = self._assembling_headers() - body = self.node_data.body - boundary = f"----WebKitFormBoundary{_generate_random_string(16)}" - if body: - if "content-type" not in (k.lower() for k in self.headers) and body.type in BODY_TYPE_TO_CONTENT_TYPE: - headers["Content-Type"] = BODY_TYPE_TO_CONTENT_TYPE[body.type] - if body.type == "form-data": - headers["Content-Type"] = f"multipart/form-data; boundary={boundary}" - for k, v in headers.items(): - if self.auth.type == "api-key": - authorization_header = "Authorization" - if self.auth.config and self.auth.config.header: - authorization_header = self.auth.config.header - if k.lower() == authorization_header.lower(): - raw += f"{k}: {'*' * len(v)}\r\n" - continue - raw += f"{k}: {v}\r\n" - - body_string = "" - # Only log actual files if present. - # '__multipart_placeholder__' is inserted to force multipart encoding but is not a real file. - # This prevents logging meaningless placeholder entries. - if self.files and not all(f[0] == "__multipart_placeholder__" for f in self.files): - for file_entry in self.files: - # file_entry should be (key, (filename, content, mime_type)), but handle edge cases - if len(file_entry) != 2 or len(file_entry[1]) < 2: - continue # skip malformed entries - key = file_entry[0] - content = file_entry[1][1] - body_string += f"--{boundary}\r\n" - body_string += f'Content-Disposition: form-data; name="{key}"\r\n\r\n' - # decode content safely - # Do not decode binary content; use a placeholder with file metadata instead. - # Includes filename, size, and MIME type for better logging context. - body_string += ( - f"
hello
", - expiration_time=datetime.utcnow(), + expiration_time=naive_utc_now(), ).model_dump_json() @@ -421,22 +423,22 @@ class TestHumanInputFormRepositoryImplPublicMethods: ) session = _FakeSession(scalars_results=[form, [recipient]]) _patch_repo_session_factory(monkeypatch, session) - repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id") + repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id", workflow_execution_id=form.workflow_run_id) - entity = repo.get_form(form.workflow_run_id, form.node_id) + entity = repo.get_form(form.node_id) assert entity is not None assert entity.id == form.id - assert entity.web_app_token == "token-123" + assert entity.submission_token == "token-123" assert len(entity.recipients) == 1 assert entity.recipients[0].token == "token-123" def test_get_form_returns_none_when_missing(self, monkeypatch: pytest.MonkeyPatch): session = _FakeSession(scalars_results=[None]) _patch_repo_session_factory(monkeypatch, session) - repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id") + repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id", workflow_execution_id="run-1") - assert repo.get_form("run-1", "node-1") is None + assert repo.get_form("node-1") is None def test_get_form_returns_unsubmitted_state(self, monkeypatch: pytest.MonkeyPatch): form = _DummyForm( @@ -451,9 +453,9 @@ class TestHumanInputFormRepositoryImplPublicMethods: ) session = _FakeSession(scalars_results=[form, []]) _patch_repo_session_factory(monkeypatch, session) - repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id") + repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id", workflow_execution_id=form.workflow_run_id) - entity = repo.get_form(form.workflow_run_id, form.node_id) + entity = repo.get_form(form.node_id) assert entity is not None assert entity.submitted is False @@ -476,9 +478,9 @@ class TestHumanInputFormRepositoryImplPublicMethods: ) session = _FakeSession(scalars_results=[form, []]) _patch_repo_session_factory(monkeypatch, session) - repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id") + repo = HumanInputFormRepositoryImpl(tenant_id="tenant-id", workflow_execution_id=form.workflow_run_id) - entity = repo.get_form(form.workflow_run_id, form.node_id) + entity = repo.get_form(form.node_id) assert entity is not None assert entity.submitted is True diff --git a/api/tests/unit_tests/core/repositories/test_human_input_repository.py b/api/tests/unit_tests/core/repositories/test_human_input_repository.py new file mode 100644 index 00000000000..8ff0e405874 --- /dev/null +++ b/api/tests/unit_tests/core/repositories/test_human_input_repository.py @@ -0,0 +1,679 @@ +from __future__ import annotations + +import dataclasses +import json +from collections.abc import Sequence +from datetime import datetime, timedelta +from types import SimpleNamespace +from typing import Any +from unittest.mock import MagicMock + +import pytest +from graphon.nodes.human_input.entities import HumanInputNodeData, UserAction +from graphon.nodes.human_input.enums import HumanInputFormKind, HumanInputFormStatus + +from core.repositories.human_input_repository import ( + FormCreateParams, + FormNotFoundError, + HumanInputFormRecord, + HumanInputFormRepositoryImpl, + HumanInputFormSubmissionRepository, + _HumanInputFormEntityImpl, + _HumanInputFormRecipientEntityImpl, + _InvalidTimeoutStatusError, + _WorkspaceMemberInfo, +) +from core.workflow.human_input_compat import ( + EmailDeliveryConfig, + EmailDeliveryMethod, + EmailRecipients, + ExternalRecipient, + MemberRecipient, + WebAppDeliveryMethod, +) +from libs.datetime_utils import naive_utc_now +from models.human_input import HumanInputFormRecipient, RecipientType + + +@pytest.fixture(autouse=True) +def _stub_select(monkeypatch: pytest.MonkeyPatch) -> None: + class _FakeSelect: + def join(self, *_args: Any, **_kwargs: Any) -> _FakeSelect: + return self + + def where(self, *_args: Any, **_kwargs: Any) -> _FakeSelect: + return self + + def options(self, *_args: Any, **_kwargs: Any) -> _FakeSelect: + return self + + monkeypatch.setattr("core.repositories.human_input_repository.select", lambda *_args, **_kwargs: _FakeSelect()) + monkeypatch.setattr("core.repositories.human_input_repository.selectinload", lambda *_args, **_kwargs: "_loader") + + +def _make_form_definition_json(*, include_expiration_time: bool) -> str: + payload: dict[str, Any] = { + "form_content": "hi", + "inputs": [], + "user_actions": [{"id": "submit", "title": "Submit"}], + "rendered_content": "hi
", + } + if include_expiration_time: + payload["expiration_time"] = naive_utc_now() + return json.dumps(payload, default=str) + + +@dataclasses.dataclass +class _DummyForm: + id: str + workflow_run_id: str | None + node_id: str + tenant_id: str + app_id: str + form_definition: str + rendered_content: str + expiration_time: datetime + form_kind: HumanInputFormKind = HumanInputFormKind.RUNTIME + created_at: datetime = dataclasses.field(default_factory=naive_utc_now) + selected_action_id: str | None = None + submitted_data: str | None = None + submitted_at: datetime | None = None + submission_user_id: str | None = None + submission_end_user_id: str | None = None + completed_by_recipient_id: str | None = None + status: HumanInputFormStatus = HumanInputFormStatus.WAITING + + +@dataclasses.dataclass +class _DummyRecipient: + id: str + form_id: str + recipient_type: RecipientType + access_token: str | None + + +class _FakeScalarResult: + def __init__(self, obj: Any): + self._obj = obj + + def first(self) -> Any: + if isinstance(self._obj, list): + return self._obj[0] if self._obj else None + return self._obj + + def all(self) -> list[Any]: + if self._obj is None: + return [] + if isinstance(self._obj, list): + return list(self._obj) + return [self._obj] + + +class _FakeExecuteResult: + def __init__(self, rows: Sequence[tuple[Any, ...]]): + self._rows = list(rows) + + def all(self) -> list[tuple[Any, ...]]: + return list(self._rows) + + +class _FakeSession: + def __init__( + self, + *, + scalars_result: Any = None, + scalars_results: list[Any] | None = None, + forms: dict[str, _DummyForm] | None = None, + recipients: dict[str, _DummyRecipient] | None = None, + execute_rows: Sequence[tuple[Any, ...]] = (), + ): + if scalars_results is not None: + self._scalars_queue = list(scalars_results) + else: + self._scalars_queue = [scalars_result] + self._forms = forms or {} + self._recipients = recipients or {} + self._execute_rows = list(execute_rows) + self.added: list[Any] = [] + + def scalars(self, _query: Any) -> _FakeScalarResult: + if self._scalars_queue: + value = self._scalars_queue.pop(0) + else: + value = None + return _FakeScalarResult(value) + + def execute(self, _stmt: Any) -> _FakeExecuteResult: + return _FakeExecuteResult(self._execute_rows) + + def get(self, model_cls: Any, obj_id: str) -> Any: + name = getattr(model_cls, "__name__", "") + if name == "HumanInputForm": + return self._forms.get(obj_id) + if name == "HumanInputFormRecipient": + return self._recipients.get(obj_id) + return None + + def add(self, obj: Any) -> None: + self.added.append(obj) + + def add_all(self, objs: Sequence[Any]) -> None: + self.added.extend(list(objs)) + + def flush(self) -> None: + # Simulate DB default population for attributes referenced in entity wrappers. + for obj in self.added: + if hasattr(obj, "id") and obj.id in (None, ""): + obj.id = f"gen-{len(str(self.added))}" + if isinstance(obj, HumanInputFormRecipient) and obj.access_token is None: + if obj.recipient_type == RecipientType.CONSOLE: + obj.access_token = "token-console" + elif obj.recipient_type == RecipientType.BACKSTAGE: + obj.access_token = "token-backstage" + else: + obj.access_token = "token-webapp" + + def refresh(self, _obj: Any) -> None: + return None + + def begin(self) -> _FakeSession: + return self + + def __enter__(self) -> _FakeSession: + return self + + def __exit__(self, exc_type, exc, tb) -> None: + return None + + +class _SessionFactoryStub: + def __init__(self, session: _FakeSession): + self._session = session + + def create_session(self) -> _FakeSession: + return self._session + + +def _patch_session_factory(monkeypatch: pytest.MonkeyPatch, session: _FakeSession) -> None: + monkeypatch.setattr("core.repositories.human_input_repository.session_factory", _SessionFactoryStub(session)) + + +def test_recipient_entity_token_raises_when_missing() -> None: + recipient = SimpleNamespace(id="r1", access_token=None) + entity = _HumanInputFormRecipientEntityImpl(recipient) # type: ignore[arg-type] + with pytest.raises(AssertionError, match="access_token should not be None"): + _ = entity.token + + +def test_recipient_entity_id_and_token_success() -> None: + recipient = SimpleNamespace(id="r1", access_token="tok") + entity = _HumanInputFormRecipientEntityImpl(recipient) # type: ignore[arg-type] + assert entity.id == "r1" + assert entity.token == "tok" + + +def test_form_entity_submission_token_prefers_console_then_webapp_then_none() -> None: + form = _DummyForm( + id="f1", + workflow_run_id="run", + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + ) + console = _DummyRecipient(id="c1", form_id=form.id, recipient_type=RecipientType.CONSOLE, access_token="ctok") + webapp = _DummyRecipient( + id="w1", form_id=form.id, recipient_type=RecipientType.STANDALONE_WEB_APP, access_token="wtok" + ) + + entity = _HumanInputFormEntityImpl(form_model=form, recipient_models=[webapp, console]) # type: ignore[arg-type] + assert entity.submission_token == "ctok" + + entity = _HumanInputFormEntityImpl(form_model=form, recipient_models=[webapp]) # type: ignore[arg-type] + assert entity.submission_token == "wtok" + + entity = _HumanInputFormEntityImpl(form_model=form, recipient_models=[]) # type: ignore[arg-type] + assert entity.submission_token is None + + +def test_form_entity_submitted_data_parsed() -> None: + form = _DummyForm( + id="f1", + workflow_run_id="run", + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + submitted_data='{"a": 1}', + submitted_at=naive_utc_now(), + ) + entity = _HumanInputFormEntityImpl(form_model=form, recipient_models=[]) # type: ignore[arg-type] + assert entity.submitted is True + assert entity.submitted_data == {"a": 1} + assert entity.rendered_content == "x
" + assert entity.selected_action_id is None + assert entity.status == HumanInputFormStatus.WAITING + + +def test_form_record_from_models_injects_expiration_time_when_missing() -> None: + expiration = naive_utc_now() + form = _DummyForm( + id="f1", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=False), + rendered_content="x
", + expiration_time=expiration, + submitted_data='{"k": "v"}', + ) + record = HumanInputFormRecord.from_models(form, None) # type: ignore[arg-type] + assert record.definition.expiration_time == expiration + assert record.submitted_data == {"k": "v"} + assert record.submitted is False + + +def test_create_email_recipients_from_resolved_dedupes_and_skips_blank(monkeypatch: pytest.MonkeyPatch) -> None: + created: list[SimpleNamespace] = [] + + def fake_new(cls, form_id: str, delivery_id: str, payload: Any): # type: ignore[no-untyped-def] + recipient = SimpleNamespace( + id=f"{payload.TYPE}-{len(created)}", + form_id=form_id, + delivery_id=delivery_id, + recipient_type=payload.TYPE, + recipient_payload=payload.model_dump_json(), + access_token="tok", + ) + created.append(recipient) + return recipient + + monkeypatch.setattr("core.repositories.human_input_repository.HumanInputFormRecipient.new", classmethod(fake_new)) + + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + recipients = repo._create_email_recipients_from_resolved( # type: ignore[attr-defined] + form_id="f", + delivery_id="d", + members=[ + _WorkspaceMemberInfo(user_id="u1", email=""), + _WorkspaceMemberInfo(user_id="u2", email="a@example.com"), + _WorkspaceMemberInfo(user_id="u3", email="a@example.com"), + ], + external_emails=["", "a@example.com", "b@example.com", "b@example.com"], + ) + assert [r.recipient_type for r in recipients] == [RecipientType.EMAIL_MEMBER, RecipientType.EMAIL_EXTERNAL] + + +def test_query_workspace_members_by_ids_empty_returns_empty() -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + assert repo._query_workspace_members_by_ids(session=MagicMock(), restrict_to_user_ids=["", ""]) == [] + + +def test_query_workspace_members_by_ids_maps_rows() -> None: + session = _FakeSession(execute_rows=[("u1", "a@example.com"), ("u2", "b@example.com")]) + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + rows = repo._query_workspace_members_by_ids(session=session, restrict_to_user_ids=["u1", "u2"]) + assert rows == [ + _WorkspaceMemberInfo(user_id="u1", email="a@example.com"), + _WorkspaceMemberInfo(user_id="u2", email="b@example.com"), + ] + + +def test_query_all_workspace_members_maps_rows() -> None: + session = _FakeSession(execute_rows=[("u1", "a@example.com")]) + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + rows = repo._query_all_workspace_members(session=session) + assert rows == [_WorkspaceMemberInfo(user_id="u1", email="a@example.com")] + + +def test_repository_init_sets_tenant_id() -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + assert repo._tenant_id == "tenant" + + +def test_delivery_method_to_model_webapp_creates_delivery_and_recipient(monkeypatch: pytest.MonkeyPatch) -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + monkeypatch.setattr("core.repositories.human_input_repository.uuidv7", lambda: "del-1") + result = repo._delivery_method_to_model( + session=MagicMock(), form_id="form-1", delivery_method=WebAppDeliveryMethod() + ) + assert result.delivery.id == "del-1" + assert result.delivery.form_id == "form-1" + assert len(result.recipients) == 1 + assert result.recipients[0].recipient_type == RecipientType.STANDALONE_WEB_APP + + +def test_delivery_method_to_model_email_uses_build_email_recipients(monkeypatch: pytest.MonkeyPatch) -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + monkeypatch.setattr("core.repositories.human_input_repository.uuidv7", lambda: "del-1") + called: dict[str, Any] = {} + + def fake_build(*, session: Any, form_id: str, delivery_id: str, recipients_config: Any) -> list[Any]: + called.update( + {"session": session, "form_id": form_id, "delivery_id": delivery_id, "recipients_config": recipients_config} + ) + return ["r"] + + monkeypatch.setattr(repo, "_build_email_recipients", fake_build) + + method = EmailDeliveryMethod( + config=EmailDeliveryConfig( + recipients=EmailRecipients( + include_bound_group=False, + items=[MemberRecipient(reference_id="u1"), ExternalRecipient(email="e@example.com")], + ), + subject="s", + body="b", + ) + ) + result = repo._delivery_method_to_model(session="sess", form_id="form-1", delivery_method=method) + assert result.recipients == ["r"] + assert called["delivery_id"] == "del-1" + + +def test_build_email_recipients_uses_all_members_when_whole_workspace(monkeypatch: pytest.MonkeyPatch) -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + monkeypatch.setattr( + repo, + "_query_all_workspace_members", + lambda *, session: [_WorkspaceMemberInfo(user_id="u", email="a@example.com")], + ) + monkeypatch.setattr(repo, "_create_email_recipients_from_resolved", lambda **_: ["ok"]) + recipients = repo._build_email_recipients( + session=MagicMock(), + form_id="f", + delivery_id="d", + recipients_config=EmailRecipients(include_bound_group=True, items=[ExternalRecipient(email="e@example.com")]), + ) + assert recipients == ["ok"] + + +def test_build_email_recipients_uses_selected_members_when_not_whole_workspace(monkeypatch: pytest.MonkeyPatch) -> None: + repo = HumanInputFormRepositoryImpl(tenant_id="tenant") + + def fake_query(*, session: Any, restrict_to_user_ids: Sequence[str]) -> list[_WorkspaceMemberInfo]: + assert restrict_to_user_ids == ["u1"] + return [_WorkspaceMemberInfo(user_id="u1", email="a@example.com")] + + monkeypatch.setattr(repo, "_query_workspace_members_by_ids", fake_query) + monkeypatch.setattr(repo, "_create_email_recipients_from_resolved", lambda **_: ["ok"]) + recipients = repo._build_email_recipients( + session=MagicMock(), + form_id="f", + delivery_id="d", + recipients_config=EmailRecipients( + include_bound_group=False, + items=[MemberRecipient(reference_id="u1"), ExternalRecipient(email="e@example.com")], + ), + ) + assert recipients == ["ok"] + + +def test_get_form_returns_entity_and_none_when_missing(monkeypatch: pytest.MonkeyPatch) -> None: + _patch_session_factory(monkeypatch, _FakeSession(scalars_results=[None])) + repo = HumanInputFormRepositoryImpl(tenant_id="tenant", workflow_execution_id="run") + assert repo.get_form("node") is None + + form = _DummyForm( + id="f1", + workflow_run_id="run", + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + ) + recipient = _DummyRecipient( + id="r1", + form_id=form.id, + recipient_type=RecipientType.STANDALONE_WEB_APP, + access_token="tok", + ) + session = _FakeSession(scalars_results=[form, [recipient]]) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormRepositoryImpl(tenant_id="tenant", workflow_execution_id="run") + entity = repo.get_form("node") + assert entity is not None + assert entity.id == "f1" + assert entity.recipients[0].id == "r1" + assert entity.recipients[0].token == "tok" + + +def test_create_form_adds_console_and_backstage_recipients(monkeypatch: pytest.MonkeyPatch) -> None: + fixed_now = datetime(2024, 1, 1, 0, 0, 0) + monkeypatch.setattr("core.repositories.human_input_repository.naive_utc_now", lambda: fixed_now) + + ids = iter(["form-id", "del-web", "del-console", "del-backstage"]) + monkeypatch.setattr("core.repositories.human_input_repository.uuidv7", lambda: next(ids)) + + session = _FakeSession() + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormRepositoryImpl( + tenant_id="tenant", + app_id="app", + workflow_execution_id="run", + invoke_source="debugger", + submission_actor_id="acc-1", + ) + + form_config = HumanInputNodeData( + title="Title", + delivery_methods=[], + form_content="hello", + inputs=[], + user_actions=[UserAction(id="submit", title="Submit")], + ) + params = FormCreateParams( + workflow_execution_id=None, + node_id="node", + form_config=form_config, + rendered_content="hello
", + delivery_methods=[WebAppDeliveryMethod()], + display_in_ui=True, + resolved_default_values={}, + form_kind=HumanInputFormKind.RUNTIME, + ) + + entity = repo.create_form(params) + assert entity.id == "form-id" + assert entity.expiration_time == fixed_now + timedelta(hours=form_config.timeout) + # Console token should take precedence when console recipient is present. + assert entity.submission_token == "token-console" + assert len(entity.recipients) == 3 + + +def test_submission_get_by_token_returns_none_when_missing_or_form_missing(monkeypatch: pytest.MonkeyPatch) -> None: + _patch_session_factory(monkeypatch, _FakeSession(scalars_result=None)) + repo = HumanInputFormSubmissionRepository() + assert repo.get_by_token("tok") is None + + recipient = SimpleNamespace(form=None) + _patch_session_factory(monkeypatch, _FakeSession(scalars_result=recipient)) + repo = HumanInputFormSubmissionRepository() + assert repo.get_by_token("tok") is None + + +def test_submission_repository_init_no_args() -> None: + repo = HumanInputFormSubmissionRepository() + assert isinstance(repo, HumanInputFormSubmissionRepository) + + +def test_submission_get_by_token_and_get_by_form_id_success_paths(monkeypatch: pytest.MonkeyPatch) -> None: + form = _DummyForm( + id="f1", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + ) + recipient = SimpleNamespace( + id="r1", + form_id=form.id, + recipient_type=RecipientType.STANDALONE_WEB_APP, + access_token="tok", + form=form, + ) + + _patch_session_factory(monkeypatch, _FakeSession(scalars_result=recipient)) + repo = HumanInputFormSubmissionRepository() + record = repo.get_by_token("tok") + assert record is not None + assert record.access_token == "tok" + + _patch_session_factory(monkeypatch, _FakeSession(scalars_result=recipient)) + repo = HumanInputFormSubmissionRepository() + record = repo.get_by_form_id_and_recipient_type(form_id=form.id, recipient_type=RecipientType.STANDALONE_WEB_APP) + assert record is not None + assert record.recipient_id == "r1" + + +def test_submission_get_by_form_id_returns_none_on_missing(monkeypatch: pytest.MonkeyPatch) -> None: + _patch_session_factory(monkeypatch, _FakeSession(scalars_result=None)) + repo = HumanInputFormSubmissionRepository() + assert repo.get_by_form_id_and_recipient_type(form_id="f", recipient_type=RecipientType.CONSOLE) is None + + +def test_mark_submitted_updates_and_raises_when_missing(monkeypatch: pytest.MonkeyPatch) -> None: + fixed_now = datetime(2024, 1, 1, 0, 0, 0) + monkeypatch.setattr("core.repositories.human_input_repository.naive_utc_now", lambda: fixed_now) + + missing_session = _FakeSession(forms={}) + _patch_session_factory(monkeypatch, missing_session) + repo = HumanInputFormSubmissionRepository() + with pytest.raises(FormNotFoundError, match="form not found"): + repo.mark_submitted( + form_id="missing", + recipient_id=None, + selected_action_id="a", + form_data={}, + submission_user_id=None, + submission_end_user_id=None, + ) + + form = _DummyForm( + id="f", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=fixed_now, + ) + recipient = _DummyRecipient(id="r", form_id=form.id, recipient_type=RecipientType.CONSOLE, access_token="tok") + session = _FakeSession(forms={form.id: form}, recipients={recipient.id: recipient}) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormSubmissionRepository() + record = repo.mark_submitted( + form_id=form.id, + recipient_id=recipient.id, + selected_action_id="approve", + form_data={"k": "v"}, + submission_user_id="u", + submission_end_user_id="eu", + ) + assert form.status == HumanInputFormStatus.SUBMITTED + assert form.submitted_at == fixed_now + assert record.submitted_data == {"k": "v"} + + +def test_mark_timeout_invalid_status_raises(monkeypatch: pytest.MonkeyPatch) -> None: + form = _DummyForm( + id="f", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + ) + session = _FakeSession(forms={form.id: form}) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormSubmissionRepository() + with pytest.raises(_InvalidTimeoutStatusError, match="invalid timeout status"): + repo.mark_timeout(form_id=form.id, timeout_status=HumanInputFormStatus.SUBMITTED) # type: ignore[arg-type] + + +def test_mark_timeout_already_timed_out_returns_record(monkeypatch: pytest.MonkeyPatch) -> None: + form = _DummyForm( + id="f", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + status=HumanInputFormStatus.TIMEOUT, + ) + session = _FakeSession(forms={form.id: form}) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormSubmissionRepository() + record = repo.mark_timeout(form_id=form.id, timeout_status=HumanInputFormStatus.TIMEOUT, reason="r") + assert record.status == HumanInputFormStatus.TIMEOUT + + +def test_mark_timeout_submitted_raises_form_not_found(monkeypatch: pytest.MonkeyPatch) -> None: + form = _DummyForm( + id="f", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + status=HumanInputFormStatus.SUBMITTED, + ) + session = _FakeSession(forms={form.id: form}) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormSubmissionRepository() + with pytest.raises(FormNotFoundError, match="form already submitted"): + repo.mark_timeout(form_id=form.id, timeout_status=HumanInputFormStatus.EXPIRED) + + +def test_mark_timeout_updates_fields(monkeypatch: pytest.MonkeyPatch) -> None: + form = _DummyForm( + id="f", + workflow_run_id=None, + node_id="node", + tenant_id="tenant", + app_id="app", + form_definition=_make_form_definition_json(include_expiration_time=True), + rendered_content="x
", + expiration_time=naive_utc_now(), + selected_action_id="a", + submitted_data="{}", + submission_user_id="u", + submission_end_user_id="eu", + completed_by_recipient_id="r", + status=HumanInputFormStatus.WAITING, + ) + session = _FakeSession(forms={form.id: form}) + _patch_session_factory(monkeypatch, session) + repo = HumanInputFormSubmissionRepository() + record = repo.mark_timeout(form_id=form.id, timeout_status=HumanInputFormStatus.EXPIRED) + assert form.status == HumanInputFormStatus.EXPIRED + assert form.selected_action_id is None + assert form.submitted_data is None + assert form.submission_user_id is None + assert form.submission_end_user_id is None + assert form.completed_by_recipient_id is None + assert record.status == HumanInputFormStatus.EXPIRED + + +def test_mark_timeout_raises_when_form_missing(monkeypatch: pytest.MonkeyPatch) -> None: + _patch_session_factory(monkeypatch, _FakeSession(forms={})) + repo = HumanInputFormSubmissionRepository() + with pytest.raises(FormNotFoundError, match="form not found"): + repo.mark_timeout(form_id="missing", timeout_status=HumanInputFormStatus.TIMEOUT) diff --git a/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_execution_repository.py b/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_execution_repository.py index c66e50437ab..e5c3e854875 100644 --- a/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_execution_repository.py +++ b/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_execution_repository.py @@ -1,84 +1,292 @@ -from datetime import datetime +from datetime import UTC, datetime from unittest.mock import MagicMock from uuid import uuid4 -from sqlalchemy import create_engine +import pytest +from graphon.entities import WorkflowExecution +from graphon.enums import WorkflowExecutionStatus, WorkflowType +from sqlalchemy.engine import Engine from sqlalchemy.orm import sessionmaker from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository -from dify_graph.entities.workflow_execution import WorkflowExecution, WorkflowType -from models import Account, WorkflowRun +from models import Account, CreatorUserRole, EndUser, WorkflowRun from models.enums import WorkflowRunTriggeredFrom -def _build_repository_with_mocked_session(session: MagicMock) -> SQLAlchemyWorkflowExecutionRepository: - engine = create_engine("sqlite:///:memory:") - real_session_factory = sessionmaker(bind=engine, expire_on_commit=False) - - user = MagicMock(spec=Account) - user.id = str(uuid4()) - user.current_tenant_id = str(uuid4()) - - repository = SQLAlchemyWorkflowExecutionRepository( - session_factory=real_session_factory, - user=user, - app_id="app-id", - triggered_from=WorkflowRunTriggeredFrom.APP_RUN, - ) - - session_context = MagicMock() - session_context.__enter__.return_value = session - session_context.__exit__.return_value = False - repository._session_factory = MagicMock(return_value=session_context) - return repository - - -def _build_execution(*, execution_id: str, started_at: datetime) -> WorkflowExecution: - return WorkflowExecution.new( - id_=execution_id, - workflow_id="workflow-id", - workflow_type=WorkflowType.WORKFLOW, - workflow_version="1.0.0", - graph={"nodes": [], "edges": []}, - inputs={"query": "hello"}, - started_at=started_at, - ) - - -def test_save_uses_execution_started_at_when_record_does_not_exist(): +@pytest.fixture +def mock_session_factory(): + """Mock SQLAlchemy session factory.""" + session_factory = MagicMock(spec=sessionmaker) session = MagicMock() session.get.return_value = None - repository = _build_repository_with_mocked_session(session) - - started_at = datetime(2026, 1, 1, 12, 0, 0) - execution = _build_execution(execution_id=str(uuid4()), started_at=started_at) - - repository.save(execution) - - saved_model = session.merge.call_args.args[0] - assert saved_model.created_at == started_at - session.commit.assert_called_once() + session_factory.return_value.__enter__.return_value = session + return session_factory -def test_save_preserves_existing_created_at_when_record_already_exists(): - session = MagicMock() - repository = _build_repository_with_mocked_session(session) +@pytest.fixture +def mock_engine(): + """Mock SQLAlchemy Engine.""" + return MagicMock(spec=Engine) - execution_id = str(uuid4()) - existing_created_at = datetime(2026, 1, 1, 12, 0, 0) - existing_run = WorkflowRun() - existing_run.id = execution_id - existing_run.tenant_id = repository._tenant_id - existing_run.created_at = existing_created_at - session.get.return_value = existing_run - execution = _build_execution( - execution_id=execution_id, - started_at=datetime(2026, 1, 1, 12, 30, 0), +@pytest.fixture +def mock_account(): + """Mock Account user.""" + account = MagicMock(spec=Account) + account.id = str(uuid4()) + account.current_tenant_id = str(uuid4()) + return account + + +@pytest.fixture +def mock_end_user(): + """Mock EndUser.""" + user = MagicMock(spec=EndUser) + user.id = str(uuid4()) + user.tenant_id = str(uuid4()) + return user + + +@pytest.fixture +def sample_workflow_execution(): + """Sample WorkflowExecution for testing.""" + return WorkflowExecution( + id_=str(uuid4()), + workflow_id=str(uuid4()), + workflow_type=WorkflowType.WORKFLOW, + workflow_version="1.0", + graph={"nodes": [], "edges": []}, + inputs={"input1": "value1"}, + outputs={"output1": "result1"}, + status=WorkflowExecutionStatus.SUCCEEDED, + error_message="", + total_tokens=100, + total_steps=5, + exceptions_count=0, + started_at=datetime.now(UTC), + finished_at=datetime.now(UTC), ) - repository.save(execution) - saved_model = session.merge.call_args.args[0] - assert saved_model.created_at == existing_created_at - session.commit.assert_called_once() +class TestSQLAlchemyWorkflowExecutionRepository: + def test_init_with_sessionmaker(self, mock_session_factory, mock_account): + app_id = "test_app_id" + triggered_from = WorkflowRunTriggeredFrom.APP_RUN + + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, user=mock_account, app_id=app_id, triggered_from=triggered_from + ) + + assert repo._session_factory == mock_session_factory + assert repo._tenant_id == mock_account.current_tenant_id + assert repo._app_id == app_id + assert repo._triggered_from == triggered_from + assert repo._creator_user_id == mock_account.id + assert repo._creator_user_role == CreatorUserRole.ACCOUNT + + def test_init_with_engine(self, mock_engine, mock_account): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_engine, + user=mock_account, + app_id="test_app_id", + triggered_from=WorkflowRunTriggeredFrom.APP_RUN, + ) + + assert isinstance(repo._session_factory, sessionmaker) + assert repo._session_factory.kw["bind"] == mock_engine + + def test_init_invalid_session_factory(self, mock_account): + with pytest.raises(ValueError, match="Invalid session_factory type"): + SQLAlchemyWorkflowExecutionRepository( + session_factory="invalid", user=mock_account, app_id=None, triggered_from=None + ) + + def test_init_no_tenant_id(self, mock_session_factory): + user = MagicMock(spec=Account) + user.current_tenant_id = None + + with pytest.raises(ValueError, match="User must have a tenant_id"): + SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, user=user, app_id=None, triggered_from=None + ) + + def test_init_with_end_user(self, mock_session_factory, mock_end_user): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, user=mock_end_user, app_id=None, triggered_from=None + ) + assert repo._tenant_id == mock_end_user.tenant_id + assert repo._creator_user_role == CreatorUserRole.END_USER + + def test_to_domain_model(self, mock_session_factory, mock_account): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, user=mock_account, app_id=None, triggered_from=None + ) + + db_model = MagicMock(spec=WorkflowRun) + db_model.id = str(uuid4()) + db_model.workflow_id = str(uuid4()) + db_model.type = "workflow" + db_model.version = "1.0" + db_model.inputs_dict = {"in": "val"} + db_model.outputs_dict = {"out": "val"} + db_model.graph_dict = {"nodes": []} + db_model.status = "succeeded" + db_model.error = "some error" + db_model.total_tokens = 50 + db_model.total_steps = 3 + db_model.exceptions_count = 1 + db_model.created_at = datetime.now(UTC) + db_model.finished_at = datetime.now(UTC) + + domain_model = repo._to_domain_model(db_model) + + assert domain_model.id_ == db_model.id + assert domain_model.workflow_id == db_model.workflow_id + assert domain_model.status == WorkflowExecutionStatus.SUCCEEDED + assert domain_model.inputs == db_model.inputs_dict + assert domain_model.error_message == "some error" + + def test_to_db_model(self, mock_session_factory, mock_account, sample_workflow_execution): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id="test_app", + triggered_from=WorkflowRunTriggeredFrom.DEBUGGING, + ) + + # Make elapsed time deterministic to avoid flaky tests + sample_workflow_execution.started_at = datetime(2023, 1, 1, 0, 0, 0, tzinfo=UTC) + sample_workflow_execution.finished_at = datetime(2023, 1, 1, 0, 0, 10, tzinfo=UTC) + + db_model = repo._to_db_model(sample_workflow_execution) + + assert db_model.id == sample_workflow_execution.id_ + assert db_model.tenant_id == repo._tenant_id + assert db_model.app_id == "test_app" + assert db_model.triggered_from == WorkflowRunTriggeredFrom.DEBUGGING + assert db_model.status == sample_workflow_execution.status.value + assert db_model.total_tokens == sample_workflow_execution.total_tokens + assert db_model.elapsed_time == 10.0 + + def test_to_db_model_edge_cases(self, mock_session_factory, mock_account, sample_workflow_execution): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id="test_app", + triggered_from=WorkflowRunTriggeredFrom.DEBUGGING, + ) + # Test with empty/None fields + sample_workflow_execution.graph = None + sample_workflow_execution.inputs = None + sample_workflow_execution.outputs = None + sample_workflow_execution.error_message = None + sample_workflow_execution.finished_at = None + + db_model = repo._to_db_model(sample_workflow_execution) + + assert db_model.graph is None + assert db_model.inputs is None + assert db_model.outputs is None + assert db_model.error is None + assert db_model.elapsed_time == 0 + + def test_to_db_model_app_id_none(self, mock_session_factory, mock_account, sample_workflow_execution): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id=None, + triggered_from=WorkflowRunTriggeredFrom.APP_RUN, + ) + + db_model = repo._to_db_model(sample_workflow_execution) + assert not hasattr(db_model, "app_id") or db_model.app_id is None + assert db_model.tenant_id == repo._tenant_id + + def test_to_db_model_missing_context(self, mock_session_factory, mock_account, sample_workflow_execution): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, user=mock_account, app_id=None, triggered_from=None + ) + + # Test triggered_from missing + with pytest.raises(ValueError, match="triggered_from is required"): + repo._to_db_model(sample_workflow_execution) + + repo._triggered_from = WorkflowRunTriggeredFrom.APP_RUN + repo._creator_user_id = None + with pytest.raises(ValueError, match="created_by is required"): + repo._to_db_model(sample_workflow_execution) + + repo._creator_user_id = "some_id" + repo._creator_user_role = None + with pytest.raises(ValueError, match="created_by_role is required"): + repo._to_db_model(sample_workflow_execution) + + def test_save(self, mock_session_factory, mock_account, sample_workflow_execution): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id="test_app", + triggered_from=WorkflowRunTriggeredFrom.APP_RUN, + ) + + repo.save(sample_workflow_execution) + + session = mock_session_factory.return_value.__enter__.return_value + session.merge.assert_called_once() + session.commit.assert_called_once() + + # Check cache + assert sample_workflow_execution.id_ in repo._execution_cache + cached_model = repo._execution_cache[sample_workflow_execution.id_] + assert cached_model.id == sample_workflow_execution.id_ + + def test_save_uses_execution_started_at_when_record_does_not_exist( + self, mock_session_factory, mock_account, sample_workflow_execution + ): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id="test_app", + triggered_from=WorkflowRunTriggeredFrom.APP_RUN, + ) + + started_at = datetime(2026, 1, 1, 12, 0, 0, tzinfo=UTC) + sample_workflow_execution.started_at = started_at + + session = mock_session_factory.return_value.__enter__.return_value + session.get.return_value = None + + repo.save(sample_workflow_execution) + + saved_model = session.merge.call_args.args[0] + assert saved_model.created_at == started_at + session.commit.assert_called_once() + + def test_save_preserves_existing_created_at_when_record_already_exists( + self, mock_session_factory, mock_account, sample_workflow_execution + ): + repo = SQLAlchemyWorkflowExecutionRepository( + session_factory=mock_session_factory, + user=mock_account, + app_id="test_app", + triggered_from=WorkflowRunTriggeredFrom.APP_RUN, + ) + + execution_id = sample_workflow_execution.id_ + existing_created_at = datetime(2026, 1, 1, 12, 0, 0, tzinfo=UTC) + + existing_run = WorkflowRun() + existing_run.id = execution_id + existing_run.tenant_id = repo._tenant_id + existing_run.created_at = existing_created_at + + session = mock_session_factory.return_value.__enter__.return_value + session.get.return_value = existing_run + + sample_workflow_execution.started_at = datetime(2026, 1, 1, 12, 30, 0, tzinfo=UTC) + + repo.save(sample_workflow_execution) + + saved_model = session.merge.call_args.args[0] + assert saved_model.created_at == existing_created_at + session.commit.assert_called_once() diff --git a/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_node_execution_repository.py b/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_node_execution_repository.py new file mode 100644 index 00000000000..5b4d26b7808 --- /dev/null +++ b/api/tests/unit_tests/core/repositories/test_sqlalchemy_workflow_node_execution_repository.py @@ -0,0 +1,772 @@ +from __future__ import annotations + +import json +import logging +from collections.abc import Mapping +from datetime import UTC, datetime +from types import SimpleNamespace +from typing import Any +from unittest.mock import MagicMock, Mock + +import psycopg2.errors +import pytest +from graphon.entities import WorkflowNodeExecution +from graphon.enums import ( + BuiltinNodeTypes, + WorkflowNodeExecutionMetadataKey, + WorkflowNodeExecutionStatus, +) +from sqlalchemy import Engine, create_engine +from sqlalchemy.exc import IntegrityError +from sqlalchemy.orm import sessionmaker + +from configs import dify_config +from core.repositories.factory import OrderConfig +from core.repositories.sqlalchemy_workflow_node_execution_repository import ( + SQLAlchemyWorkflowNodeExecutionRepository, + _deterministic_json_dump, + _filter_by_offload_type, + _find_first, + _replace_or_append_offload, +) +from models import Account, EndUser +from models.enums import ExecutionOffLoadType +from models.workflow import WorkflowNodeExecutionModel, WorkflowNodeExecutionOffload, WorkflowNodeExecutionTriggeredFrom + + +def _mock_account(*, tenant_id: str = "tenant", user_id: str = "user") -> Account: + user = Mock(spec=Account) + user.id = user_id + user.current_tenant_id = tenant_id + return user + + +def _mock_end_user(*, tenant_id: str = "tenant", user_id: str = "user") -> EndUser: + user = Mock(spec=EndUser) + user.id = user_id + user.tenant_id = tenant_id + return user + + +def _execution( + *, + execution_id: str = "exec-id", + node_execution_id: str = "node-exec-id", + workflow_run_id: str = "run-id", + status: WorkflowNodeExecutionStatus = WorkflowNodeExecutionStatus.SUCCEEDED, + inputs: Mapping[str, Any] | None = None, + outputs: Mapping[str, Any] | None = None, + process_data: Mapping[str, Any] | None = None, + metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = None, +) -> WorkflowNodeExecution: + return WorkflowNodeExecution( + id=execution_id, + node_execution_id=node_execution_id, + workflow_id="workflow-id", + workflow_execution_id=workflow_run_id, + index=1, + predecessor_node_id=None, + node_id="node-id", + node_type=BuiltinNodeTypes.LLM, + title="Title", + inputs=inputs, + outputs=outputs, + process_data=process_data, + status=status, + error=None, + elapsed_time=1.0, + metadata=metadata, + created_at=datetime.now(UTC), + finished_at=None, + ) + + +class _SessionCtx: + def __init__(self, session: Any): + self._session = session + + def __enter__(self) -> Any: + return self._session + + def __exit__(self, exc_type, exc, tb) -> None: + return None + + +def _session_factory(session: Any) -> sessionmaker: + factory = Mock(spec=sessionmaker) + factory.return_value = _SessionCtx(session) + return factory + + +def test_init_accepts_engine_and_sessionmaker_and_sets_role(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + + engine: Engine = create_engine("sqlite:///:memory:") + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=engine, + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + assert isinstance(repo._session_factory, sessionmaker) + + sm = Mock(spec=sessionmaker) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=sm, + user=_mock_end_user(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP, + ) + assert repo._creator_user_role.value == "end_user" + + +def test_init_rejects_invalid_session_factory_type(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + with pytest.raises(ValueError, match="Invalid session_factory type"): + SQLAlchemyWorkflowNodeExecutionRepository( # type: ignore[arg-type] + session_factory=object(), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + +def test_init_requires_tenant_id(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + user = _mock_account() + user.current_tenant_id = None + with pytest.raises(ValueError, match="User must have a tenant_id"): + SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=user, + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + +def test_create_truncator_uses_config(monkeypatch: pytest.MonkeyPatch) -> None: + created: dict[str, Any] = {} + + class FakeTruncator: + def __init__(self, *, max_size_bytes: int, array_element_limit: int, string_length_limit: int): + created.update( + { + "max_size_bytes": max_size_bytes, + "array_element_limit": array_element_limit, + "string_length_limit": string_length_limit, + } + ) + + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.VariableTruncator", + FakeTruncator, + ) + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + _ = repo._create_truncator() + assert created["max_size_bytes"] == dify_config.WORKFLOW_VARIABLE_TRUNCATION_MAX_SIZE + + +def test_helpers_find_first_and_replace_or_append_and_filter() -> None: + assert _deterministic_json_dump({"b": 1, "a": 2}) == '{"a": 2, "b": 1}' + assert _find_first([], lambda _: True) is None + assert _find_first([1, 2, 3], lambda x: x > 1) == 2 + + off1 = WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.INPUTS) + off2 = WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.OUTPUTS) + assert _find_first([off1, off2], _filter_by_offload_type(ExecutionOffLoadType.OUTPUTS)) is off2 + + replaced = _replace_or_append_offload([off1, off2], WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.INPUTS)) + assert len(replaced) == 2 + assert [o.type_ for o in replaced] == [ExecutionOffLoadType.OUTPUTS, ExecutionOffLoadType.INPUTS] + + +def test_to_db_model_requires_constructor_context(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + execution = _execution(inputs={"b": 1, "a": 2}, metadata={WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: 1}) + + # Happy path: deterministic json dump should be sorted + db_model = repo._to_db_model(execution) + assert json.loads(db_model.inputs or "{}") == {"a": 2, "b": 1} + assert json.loads(db_model.execution_metadata or "{}")["total_tokens"] == 1 + + repo._triggered_from = None + with pytest.raises(ValueError, match="triggered_from is required"): + repo._to_db_model(execution) + + +def test_to_db_model_requires_creator_user_id_and_role(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + execution = _execution() + db_model = repo._to_db_model(execution) + assert db_model.app_id == "app" + + repo._creator_user_id = None + with pytest.raises(ValueError, match="created_by is required"): + repo._to_db_model(execution) + + repo._creator_user_id = "user" + repo._creator_user_role = None + with pytest.raises(ValueError, match="created_by_role is required"): + repo._to_db_model(execution) + + +def test_is_duplicate_key_error_and_regenerate_id( + monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture +) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + unique = Mock(spec=psycopg2.errors.UniqueViolation) + duplicate_error = IntegrityError("dup", params=None, orig=unique) + assert repo._is_duplicate_key_error(duplicate_error) is True + assert repo._is_duplicate_key_error(IntegrityError("other", params=None, orig=None)) is False + + execution = _execution(execution_id="old-id") + db_model = WorkflowNodeExecutionModel() + db_model.id = "old-id" + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.uuidv7", lambda: "new-id") + caplog.set_level(logging.WARNING) + repo._regenerate_id_on_duplicate(execution, db_model) + assert execution.id == "new-id" + assert db_model.id == "new-id" + assert any("Duplicate key conflict" in r.message for r in caplog.records) + + +def test_persist_to_database_updates_existing_and_inserts_new(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + session = MagicMock() + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + db_model = WorkflowNodeExecutionModel() + db_model.id = "id1" + db_model.node_execution_id = "node1" + db_model.foo = "bar" # type: ignore[attr-defined] + db_model.__dict__["_private"] = "x" + + existing = SimpleNamespace() + session.get.return_value = existing + repo._persist_to_database(db_model) + assert existing.foo == "bar" + session.add.assert_not_called() + assert repo._node_execution_cache["node1"] is db_model + + session.reset_mock() + session.get.return_value = None + repo._node_execution_cache.clear() + repo._persist_to_database(db_model) + session.add.assert_called_once_with(db_model) + assert repo._node_execution_cache["node1"] is db_model + + +def test_truncate_and_upload_returns_none_when_no_values_or_not_truncated(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + assert repo._truncate_and_upload(None, "e", ExecutionOffLoadType.INPUTS) is None + + class FakeTruncator: + def truncate_variable_mapping(self, value: Any): # type: ignore[no-untyped-def] + return value, False + + monkeypatch.setattr(repo, "_create_truncator", lambda: FakeTruncator()) + assert repo._truncate_and_upload({"a": 1}, "e", ExecutionOffLoadType.INPUTS) is None + + +def test_truncate_and_upload_uploads_and_builds_offload(monkeypatch: pytest.MonkeyPatch) -> None: + uploaded: dict[str, Any] = {} + + class FakeFileService: + def upload_file(self, *, filename: str, content: bytes, mimetype: str, user: Any): # type: ignore[no-untyped-def] + uploaded.update({"filename": filename, "content": content, "mimetype": mimetype, "user": user}) + return SimpleNamespace(id="file-id", key="file-key") + + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", lambda *_: FakeFileService() + ) + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.uuidv7", lambda: "offload-id") + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + class FakeTruncator: + def truncate_variable_mapping(self, value: Any): # type: ignore[no-untyped-def] + return {"truncated": True}, True + + monkeypatch.setattr(repo, "_create_truncator", lambda: FakeTruncator()) + + result = repo._truncate_and_upload({"a": 1}, "exec", ExecutionOffLoadType.INPUTS) + assert result is not None + assert result.truncated_value == {"truncated": True} + assert uploaded["filename"].startswith("node_execution_exec_inputs.json") + assert result.offload.file_id == "file-id" + assert result.offload.type_ == ExecutionOffLoadType.INPUTS + + +def test_to_domain_model_loads_offloaded_files(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + db_model = WorkflowNodeExecutionModel() + db_model.id = "id" + db_model.node_execution_id = "node-exec" + db_model.workflow_id = "wf" + db_model.workflow_run_id = "run" + db_model.index = 1 + db_model.predecessor_node_id = None + db_model.node_id = "node" + db_model.node_type = BuiltinNodeTypes.LLM + db_model.title = "t" + db_model.inputs = json.dumps({"trunc": "i"}) + db_model.process_data = json.dumps({"trunc": "p"}) + db_model.outputs = json.dumps({"trunc": "o"}) + db_model.status = WorkflowNodeExecutionStatus.SUCCEEDED + db_model.error = None + db_model.elapsed_time = 0.1 + db_model.execution_metadata = json.dumps({"total_tokens": 3}) + db_model.created_at = datetime.now(UTC) + db_model.finished_at = None + + off_in = WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.INPUTS) + off_out = WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.OUTPUTS) + off_proc = WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.PROCESS_DATA) + off_in.file = SimpleNamespace(key="k-in") + off_out.file = SimpleNamespace(key="k-out") + off_proc.file = SimpleNamespace(key="k-proc") + db_model.offload_data = [off_out, off_in, off_proc] + + def fake_load(key: str) -> bytes: + return json.dumps({"full": key}).encode() + + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.storage.load", fake_load) + + domain = repo._to_domain_model(db_model) + assert domain.inputs == {"full": "k-in"} + assert domain.outputs == {"full": "k-out"} + assert domain.process_data == {"full": "k-proc"} + assert domain.get_truncated_inputs() == {"trunc": "i"} + assert domain.get_truncated_outputs() == {"trunc": "o"} + assert domain.get_truncated_process_data() == {"trunc": "p"} + + +def test_to_domain_model_returns_early_when_no_offload_data(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + db_model = WorkflowNodeExecutionModel() + db_model.id = "id" + db_model.node_execution_id = "node-exec" + db_model.workflow_id = "wf" + db_model.workflow_run_id = "run" + db_model.index = 1 + db_model.predecessor_node_id = None + db_model.node_id = "node" + db_model.node_type = BuiltinNodeTypes.LLM + db_model.title = "t" + db_model.inputs = json.dumps({"i": 1}) + db_model.process_data = json.dumps({"p": 2}) + db_model.outputs = json.dumps({"o": 3}) + db_model.status = WorkflowNodeExecutionStatus.SUCCEEDED + db_model.error = None + db_model.elapsed_time = 0.1 + db_model.execution_metadata = "{}" + db_model.created_at = datetime.now(UTC) + db_model.finished_at = None + db_model.offload_data = [] + + domain = repo._to_domain_model(db_model) + assert domain.inputs == {"i": 1} + assert domain.outputs == {"o": 3} + + +def test_json_encode_uses_runtime_converter(monkeypatch: pytest.MonkeyPatch) -> None: + class FakeConverter: + def to_json_encodable(self, values: Mapping[str, Any]) -> Mapping[str, Any]: + return {"wrapped": values["a"]} + + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.WorkflowRuntimeTypeConverter", + FakeConverter, + ) + assert SQLAlchemyWorkflowNodeExecutionRepository._json_encode({"a": 1}) == '{"wrapped": 1}' + + +def test_save_execution_data_handles_existing_db_model_and_truncation(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + session = MagicMock() + session.execute.return_value.scalars.return_value.first.return_value = SimpleNamespace( + id="id", + offload_data=[WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.INPUTS)], + inputs=None, + outputs=None, + process_data=None, + ) + session.merge = Mock() + session.flush = Mock() + session.begin.return_value.__enter__ = Mock(return_value=session) + session.begin.return_value.__exit__ = Mock(return_value=None) + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + execution = _execution(inputs={"a": 1}, outputs={"b": 2}, process_data={"c": 3}) + + trunc_result = SimpleNamespace( + truncated_value={"trunc": True}, + offload=WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.INPUTS, file_id="f1"), + ) + monkeypatch.setattr( + repo, "_truncate_and_upload", lambda values, *_args, **_kwargs: trunc_result if values == {"a": 1} else None + ) + monkeypatch.setattr(repo, "_json_encode", lambda values: json.dumps(values, sort_keys=True)) + + repo.save_execution_data(execution) + # Inputs should be truncated, outputs/process_data encoded directly + db_model = session.merge.call_args.args[0] + assert json.loads(db_model.inputs) == {"trunc": True} + assert json.loads(db_model.outputs) == {"b": 2} + assert json.loads(db_model.process_data) == {"c": 3} + assert any(off.type_ == ExecutionOffLoadType.INPUTS for off in db_model.offload_data) + assert execution.get_truncated_inputs() == {"trunc": True} + + +def test_save_execution_data_truncates_outputs_and_process_data(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + existing = SimpleNamespace( + id="id", + offload_data=[], + inputs=None, + outputs=None, + process_data=None, + ) + session = MagicMock() + session.execute.return_value.scalars.return_value.first.return_value = existing + session.merge = Mock() + session.flush = Mock() + session.begin.return_value.__enter__ = Mock(return_value=session) + session.begin.return_value.__exit__ = Mock(return_value=None) + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + execution = _execution(inputs={"a": 1}, outputs={"b": 2}, process_data={"c": 3}) + + def trunc(values: Mapping[str, Any], *_args: Any, **_kwargs: Any) -> Any: + if values == {"b": 2}: + return SimpleNamespace( + truncated_value={"b": "trunc"}, + offload=WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.OUTPUTS, file_id="f2"), + ) + if values == {"c": 3}: + return SimpleNamespace( + truncated_value={"c": "trunc"}, + offload=WorkflowNodeExecutionOffload(type_=ExecutionOffLoadType.PROCESS_DATA, file_id="f3"), + ) + return None + + monkeypatch.setattr(repo, "_truncate_and_upload", trunc) + monkeypatch.setattr(repo, "_json_encode", lambda values: json.dumps(values, sort_keys=True)) + + repo.save_execution_data(execution) + db_model = session.merge.call_args.args[0] + assert json.loads(db_model.outputs) == {"b": "trunc"} + assert json.loads(db_model.process_data) == {"c": "trunc"} + assert execution.get_truncated_outputs() == {"b": "trunc"} + assert execution.get_truncated_process_data() == {"c": "trunc"} + + +def test_save_execution_data_handles_missing_db_model(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + session = MagicMock() + session.execute.return_value.scalars.return_value.first.return_value = None + session.merge = Mock() + session.flush = Mock() + session.begin.return_value.__enter__ = Mock(return_value=session) + session.begin.return_value.__exit__ = Mock(return_value=None) + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + execution = _execution(inputs={"a": 1}) + fake_db_model = SimpleNamespace(id=execution.id, offload_data=[], inputs=None, outputs=None, process_data=None) + monkeypatch.setattr(repo, "_to_db_model", lambda *_: fake_db_model) + monkeypatch.setattr(repo, "_truncate_and_upload", lambda *_args, **_kwargs: None) + monkeypatch.setattr(repo, "_json_encode", lambda values: json.dumps(values)) + + repo.save_execution_data(execution) + merged = session.merge.call_args.args[0] + assert merged.inputs == '{"a": 1}' + + +def test_save_retries_duplicate_and_logs_non_duplicate( + monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture +) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + execution = _execution(execution_id="id") + unique = Mock(spec=psycopg2.errors.UniqueViolation) + duplicate_error = IntegrityError("dup", params=None, orig=unique) + other_error = IntegrityError("other", params=None, orig=None) + + calls = {"n": 0} + + def persist(_db_model: Any) -> None: + calls["n"] += 1 + if calls["n"] == 1: + raise duplicate_error + + monkeypatch.setattr(repo, "_persist_to_database", persist) + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.uuidv7", lambda: "new-id") + repo.save(execution) + assert execution.id == "new-id" + assert repo._node_execution_cache[execution.node_execution_id] is not None + + caplog.set_level(logging.ERROR) + monkeypatch.setattr(repo, "_persist_to_database", lambda _db: (_ for _ in ()).throw(other_error)) + with pytest.raises(IntegrityError): + repo.save(_execution(execution_id="id2", node_execution_id="node2")) + assert any("Non-duplicate key integrity error" in r.message for r in caplog.records) + + +def test_save_logs_and_reraises_on_unexpected_error( + monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture +) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + caplog.set_level(logging.ERROR) + monkeypatch.setattr(repo, "_persist_to_database", lambda _db: (_ for _ in ()).throw(RuntimeError("boom"))) + with pytest.raises(RuntimeError, match="boom"): + repo.save(_execution(execution_id="id3", node_execution_id="node3")) + assert any("Failed to save workflow node execution" in r.message for r in caplog.records) + + +def test_get_db_models_by_workflow_run_orders_and_caches(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + + class FakeStmt: + def __init__(self) -> None: + self.where_calls = 0 + self.order_by_args: tuple[Any, ...] | None = None + + def where(self, *_args: Any) -> FakeStmt: + self.where_calls += 1 + return self + + def order_by(self, *args: Any) -> FakeStmt: + self.order_by_args = args + return self + + stmt = FakeStmt() + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.WorkflowNodeExecutionModel.preload_offload_data_and_files", + lambda _q: stmt, + ) + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.select", lambda *_: "select") + + model1 = SimpleNamespace(node_execution_id="n1") + model2 = SimpleNamespace(node_execution_id=None) + session = MagicMock() + session.scalars.return_value.all.return_value = [model1, model2] + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id="app", + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + order = OrderConfig(order_by=["index", "missing"], order_direction="desc") + db_models = repo.get_db_models_by_workflow_run("run", order) + assert db_models == [model1, model2] + assert repo._node_execution_cache["n1"] is model1 + assert stmt.order_by_args is not None + + +def test_get_db_models_by_workflow_run_uses_asc_order(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + + class FakeStmt: + def where(self, *_args: Any) -> FakeStmt: + return self + + def order_by(self, *args: Any) -> FakeStmt: + self.args = args # type: ignore[attr-defined] + return self + + stmt = FakeStmt() + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.WorkflowNodeExecutionModel.preload_offload_data_and_files", + lambda _q: stmt, + ) + monkeypatch.setattr("core.repositories.sqlalchemy_workflow_node_execution_repository.select", lambda *_: "select") + + session = MagicMock() + session.scalars.return_value.all.return_value = [] + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=_session_factory(session), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + repo.get_db_models_by_workflow_run("run", OrderConfig(order_by=["index"], order_direction="asc")) + + +def test_get_by_workflow_run_maps_to_domain(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.FileService", + lambda *_: SimpleNamespace(upload_file=Mock()), + ) + + repo = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=Mock(spec=sessionmaker), + user=_mock_account(), + app_id=None, + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + + db_models = [SimpleNamespace(id="db1"), SimpleNamespace(id="db2")] + monkeypatch.setattr(repo, "get_db_models_by_workflow_run", lambda *_args, **_kwargs: db_models) + monkeypatch.setattr(repo, "_to_domain_model", lambda m: f"domain:{m.id}") + + class FakeExecutor: + def __enter__(self) -> FakeExecutor: + return self + + def __exit__(self, exc_type, exc, tb) -> None: + return None + + def map(self, func, items, timeout: int): # type: ignore[no-untyped-def] + assert timeout == 30 + return list(map(func, items)) + + monkeypatch.setattr( + "core.repositories.sqlalchemy_workflow_node_execution_repository.ThreadPoolExecutor", + lambda max_workers: FakeExecutor(), + ) + + result = repo.get_by_workflow_execution("run", order_config=None) + assert result == ["domain:db1", "domain:db2"] diff --git a/api/tests/unit_tests/core/repositories/test_workflow_node_execution_conflict_handling.py b/api/tests/unit_tests/core/repositories/test_workflow_node_execution_conflict_handling.py index 456c3dde12c..84fe522388e 100644 --- a/api/tests/unit_tests/core/repositories/test_workflow_node_execution_conflict_handling.py +++ b/api/tests/unit_tests/core/repositories/test_workflow_node_execution_conflict_handling.py @@ -4,17 +4,17 @@ from unittest.mock import MagicMock, Mock import psycopg2.errors import pytest +from graphon.entities.workflow_node_execution import ( + WorkflowNodeExecution, + WorkflowNodeExecutionStatus, +) +from graphon.enums import BuiltinNodeTypes from sqlalchemy.exc import IntegrityError from sqlalchemy.orm import sessionmaker from core.repositories.sqlalchemy_workflow_node_execution_repository import ( SQLAlchemyWorkflowNodeExecutionRepository, ) -from dify_graph.entities.workflow_node_execution import ( - WorkflowNodeExecution, - WorkflowNodeExecutionStatus, -) -from dify_graph.enums import BuiltinNodeTypes from libs.datetime_utils import naive_utc_now from models import Account, WorkflowNodeExecutionTriggeredFrom diff --git a/api/tests/unit_tests/core/repositories/test_workflow_node_execution_truncation.py b/api/tests/unit_tests/core/repositories/test_workflow_node_execution_truncation.py index eeab81a1789..27729e7f06b 100644 --- a/api/tests/unit_tests/core/repositories/test_workflow_node_execution_truncation.py +++ b/api/tests/unit_tests/core/repositories/test_workflow_node_execution_truncation.py @@ -11,17 +11,17 @@ from datetime import UTC, datetime from typing import Any from unittest.mock import MagicMock +from graphon.entities.workflow_node_execution import ( + WorkflowNodeExecution, + WorkflowNodeExecutionStatus, +) +from graphon.enums import BuiltinNodeTypes from sqlalchemy import Engine from configs import dify_config from core.repositories.sqlalchemy_workflow_node_execution_repository import ( SQLAlchemyWorkflowNodeExecutionRepository, ) -from dify_graph.entities.workflow_node_execution import ( - WorkflowNodeExecution, - WorkflowNodeExecutionStatus, -) -from dify_graph.enums import BuiltinNodeTypes from models import Account, WorkflowNodeExecutionTriggeredFrom from models.enums import ExecutionOffLoadType from models.workflow import WorkflowNodeExecutionModel, WorkflowNodeExecutionOffload diff --git a/api/tests/unit_tests/core/schemas/test_registry.py b/api/tests/unit_tests/core/schemas/test_registry.py new file mode 100644 index 00000000000..5749e72eb03 --- /dev/null +++ b/api/tests/unit_tests/core/schemas/test_registry.py @@ -0,0 +1,137 @@ +import json +from unittest.mock import patch + +from core.schemas.registry import SchemaRegistry + + +class TestSchemaRegistry: + def test_initialization(self, tmp_path): + base_dir = tmp_path / "schemas" + base_dir.mkdir() + registry = SchemaRegistry(str(base_dir)) + assert registry.base_dir == base_dir + assert registry.versions == {} + assert registry.metadata == {} + + def test_default_registry_singleton(self): + registry1 = SchemaRegistry.default_registry() + registry2 = SchemaRegistry.default_registry() + assert registry1 is registry2 + assert isinstance(registry1, SchemaRegistry) + + def test_load_all_versions_non_existent_dir(self, tmp_path): + base_dir = tmp_path / "non_existent" + registry = SchemaRegistry(str(base_dir)) + registry.load_all_versions() + assert registry.versions == {} + + def test_load_all_versions_filtering(self, tmp_path): + base_dir = tmp_path / "schemas" + base_dir.mkdir() + (base_dir / "not_a_version_dir").mkdir() + (base_dir / "v1").mkdir() + (base_dir / "some_file.txt").write_text("content") + + registry = SchemaRegistry(str(base_dir)) + with patch.object(registry, "_load_version_dir") as mock_load: + registry.load_all_versions() + mock_load.assert_called_once() + assert mock_load.call_args[0][0] == "v1" + + def test_load_version_dir_filtering(self, tmp_path): + version_dir = tmp_path / "v1" + version_dir.mkdir() + (version_dir / "schema1.json").write_text("{}") + (version_dir / "not_a_schema.txt").write_text("content") + + registry = SchemaRegistry(str(tmp_path)) + with patch.object(registry, "_load_schema") as mock_load: + registry._load_version_dir("v1", version_dir) + mock_load.assert_called_once() + assert mock_load.call_args[0][1] == "schema1" + + def test_load_version_dir_non_existent(self, tmp_path): + version_dir = tmp_path / "non_existent" + registry = SchemaRegistry(str(tmp_path)) + registry._load_version_dir("v1", version_dir) + assert "v1" not in registry.versions + + def test_load_schema_success(self, tmp_path): + schema_path = tmp_path / "test.json" + schema_content = {"title": "Test Schema", "description": "A test schema"} + schema_path.write_text(json.dumps(schema_content)) + + registry = SchemaRegistry(str(tmp_path)) + registry.versions["v1"] = {} + registry._load_schema("v1", "test", schema_path) + + assert registry.versions["v1"]["test"] == schema_content + uri = "https://dify.ai/schemas/v1/test.json" + assert registry.metadata[uri]["title"] == "Test Schema" + assert registry.metadata[uri]["version"] == "v1" + + def test_load_schema_invalid_json(self, tmp_path, caplog): + schema_path = tmp_path / "invalid.json" + schema_path.write_text("invalid json") + + registry = SchemaRegistry(str(tmp_path)) + registry.versions["v1"] = {} + registry._load_schema("v1", "invalid", schema_path) + + assert "Failed to load schema v1/invalid" in caplog.text + + def test_load_schema_os_error(self, tmp_path, caplog): + schema_path = tmp_path / "error.json" + schema_path.write_text("{}") + + registry = SchemaRegistry(str(tmp_path)) + registry.versions["v1"] = {} + + with patch("builtins.open", side_effect=OSError("Read error")): + registry._load_schema("v1", "error", schema_path) + + assert "Failed to load schema v1/error" in caplog.text + + def test_get_schema(self): + registry = SchemaRegistry("/tmp") + registry.versions = {"v1": {"test": {"type": "object"}}} + + # Valid URI + assert registry.get_schema("https://dify.ai/schemas/v1/test.json") == {"type": "object"} + + # Invalid URI + assert registry.get_schema("invalid-uri") is None + + # Missing version + assert registry.get_schema("https://dify.ai/schemas/v2/test.json") is None + + def test_list_versions(self): + registry = SchemaRegistry("/tmp") + registry.versions = {"v2": {}, "v1": {}} + assert registry.list_versions() == ["v1", "v2"] + + def test_list_schemas(self): + registry = SchemaRegistry("/tmp") + registry.versions = {"v1": {"b": {}, "a": {}}} + + assert registry.list_schemas("v1") == ["a", "b"] + assert registry.list_schemas("v2") == [] + + def test_get_all_schemas_for_version(self): + registry = SchemaRegistry("/tmp") + registry.versions = {"v1": {"test": {"title": "Test Label"}}} + + results = registry.get_all_schemas_for_version("v1") + assert len(results) == 1 + assert results[0]["name"] == "test" + assert results[0]["label"] == "Test Label" + assert results[0]["schema"] == {"title": "Test Label"} + + # Default label if title missing + registry.versions["v1"]["no_title"] = {} + results = registry.get_all_schemas_for_version("v1") + item = next(r for r in results if r["name"] == "no_title") + assert item["label"] == "no_title" + + # Empty if version missing + assert registry.get_all_schemas_for_version("v2") == [] diff --git a/api/tests/unit_tests/core/schemas/test_schema_manager.py b/api/tests/unit_tests/core/schemas/test_schema_manager.py new file mode 100644 index 00000000000..cb07340c6d2 --- /dev/null +++ b/api/tests/unit_tests/core/schemas/test_schema_manager.py @@ -0,0 +1,80 @@ +from unittest.mock import MagicMock, patch + +from core.schemas.registry import SchemaRegistry +from core.schemas.schema_manager import SchemaManager + + +def test_init_with_provided_registry(): + mock_registry = MagicMock(spec=SchemaRegistry) + manager = SchemaManager(registry=mock_registry) + assert manager.registry == mock_registry + + +@patch("core.schemas.schema_manager.SchemaRegistry.default_registry") +def test_init_with_default_registry(mock_default_registry): + mock_registry = MagicMock(spec=SchemaRegistry) + mock_default_registry.return_value = mock_registry + + manager = SchemaManager() + + mock_default_registry.assert_called_once() + assert manager.registry == mock_registry + + +def test_get_all_schema_definitions(): + mock_registry = MagicMock(spec=SchemaRegistry) + expected_definitions = [{"name": "schema1", "schema": {}}, {"name": "schema2", "schema": {}}] + mock_registry.get_all_schemas_for_version.return_value = expected_definitions + + manager = SchemaManager(registry=mock_registry) + result = manager.get_all_schema_definitions(version="v2") + + mock_registry.get_all_schemas_for_version.assert_called_once_with("v2") + assert result == expected_definitions + + +def test_get_schema_by_name_success(): + mock_registry = MagicMock(spec=SchemaRegistry) + mock_schema = {"type": "object"} + mock_registry.get_schema.return_value = mock_schema + + manager = SchemaManager(registry=mock_registry) + result = manager.get_schema_by_name("my_schema", version="v1") + + expected_uri = "https://dify.ai/schemas/v1/my_schema.json" + mock_registry.get_schema.assert_called_once_with(expected_uri) + assert result == {"name": "my_schema", "schema": mock_schema} + + +def test_get_schema_by_name_not_found(): + mock_registry = MagicMock(spec=SchemaRegistry) + mock_registry.get_schema.return_value = None + + manager = SchemaManager(registry=mock_registry) + result = manager.get_schema_by_name("non_existent", version="v1") + + assert result is None + + +def test_list_available_schemas(): + mock_registry = MagicMock(spec=SchemaRegistry) + expected_schemas = ["schema1", "schema2"] + mock_registry.list_schemas.return_value = expected_schemas + + manager = SchemaManager(registry=mock_registry) + result = manager.list_available_schemas(version="v1") + + mock_registry.list_schemas.assert_called_once_with("v1") + assert result == expected_schemas + + +def test_list_available_versions(): + mock_registry = MagicMock(spec=SchemaRegistry) + expected_versions = ["v1", "v2"] + mock_registry.list_versions.return_value = expected_versions + + manager = SchemaManager(registry=mock_registry) + result = manager.list_available_versions() + + mock_registry.list_versions.assert_called_once() + assert result == expected_versions diff --git a/api/tests/unit_tests/core/telemetry/test_facade.py b/api/tests/unit_tests/core/telemetry/test_facade.py new file mode 100644 index 00000000000..36e8e1bbb13 --- /dev/null +++ b/api/tests/unit_tests/core/telemetry/test_facade.py @@ -0,0 +1,181 @@ +"""Unit tests for core.telemetry.emit() routing and enterprise-only filtering.""" + +from __future__ import annotations + +import queue +import sys +import types +from unittest.mock import MagicMock, patch + +import pytest + +from core.ops.entities.trace_entity import TraceTaskName +from core.telemetry.events import TelemetryContext, TelemetryEvent + + +@pytest.fixture +def telemetry_test_setup(monkeypatch): + module_name = "core.ops.ops_trace_manager" + ops_stub = types.ModuleType(module_name) + + class StubTraceTask: + def __init__(self, trace_type, **kwargs): + self.trace_type = trace_type + self.app_id = None + self.kwargs = kwargs + + class StubTraceQueueManager: + def __init__(self, app_id=None, user_id=None): + self.app_id = app_id + self.user_id = user_id + self.trace_instance = StubOpsTraceManager.get_ops_trace_instance(app_id) + + def add_trace_task(self, trace_task): + trace_task.app_id = self.app_id + from core.ops.ops_trace_manager import trace_manager_queue + + trace_manager_queue.put(trace_task) + + class StubOpsTraceManager: + @staticmethod + def get_ops_trace_instance(app_id): + return None + + ops_stub.TraceQueueManager = StubTraceQueueManager + ops_stub.TraceTask = StubTraceTask + ops_stub.OpsTraceManager = StubOpsTraceManager + ops_stub.trace_manager_queue = MagicMock(spec=queue.Queue) + monkeypatch.setitem(sys.modules, module_name, ops_stub) + + from core.telemetry import emit + + return emit, ops_stub.trace_manager_queue + + +class TestTelemetryEmit: + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_emit_enterprise_trace_creates_trace_task(self, mock_ee, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + event = TelemetryEvent( + name=TraceTaskName.DRAFT_NODE_EXECUTION_TRACE, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={"key": "value"}, + ) + + emit_fn(event) + + mock_queue.put.assert_called_once() + called_task = mock_queue.put.call_args[0][0] + assert called_task.trace_type == TraceTaskName.DRAFT_NODE_EXECUTION_TRACE + + def test_emit_community_trace_enqueued(self, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + event = TelemetryEvent( + name=TraceTaskName.WORKFLOW_TRACE, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={}, + ) + + emit_fn(event) + + mock_queue.put.assert_called_once() + + def test_emit_enterprise_only_trace_dropped_when_ee_disabled(self, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + event = TelemetryEvent( + name=TraceTaskName.DRAFT_NODE_EXECUTION_TRACE, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={}, + ) + + emit_fn(event) + + mock_queue.put.assert_not_called() + + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_emit_all_enterprise_only_traces_allowed_when_ee_enabled(self, mock_ee, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + enterprise_only_traces = [ + TraceTaskName.DRAFT_NODE_EXECUTION_TRACE, + TraceTaskName.NODE_EXECUTION_TRACE, + TraceTaskName.PROMPT_GENERATION_TRACE, + ] + + for trace_name in enterprise_only_traces: + mock_queue.reset_mock() + + event = TelemetryEvent( + name=trace_name, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={}, + ) + + emit_fn(event) + + mock_queue.put.assert_called_once() + called_task = mock_queue.put.call_args[0][0] + assert called_task.trace_type == trace_name + + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_emit_passes_name_directly_to_trace_task(self, mock_ee, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + event = TelemetryEvent( + name=TraceTaskName.DRAFT_NODE_EXECUTION_TRACE, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={"extra": "data"}, + ) + + emit_fn(event) + + mock_queue.put.assert_called_once() + called_task = mock_queue.put.call_args[0][0] + assert called_task.trace_type == TraceTaskName.DRAFT_NODE_EXECUTION_TRACE + assert isinstance(called_task.trace_type, TraceTaskName) + + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_emit_with_provided_trace_manager(self, mock_ee, telemetry_test_setup): + emit_fn, mock_queue = telemetry_test_setup + + mock_trace_manager = MagicMock() + mock_trace_manager.add_trace_task = MagicMock() + + event = TelemetryEvent( + name=TraceTaskName.NODE_EXECUTION_TRACE, + context=TelemetryContext( + tenant_id="test-tenant", + user_id="test-user", + app_id="test-app", + ), + payload={}, + ) + + emit_fn(event, trace_manager=mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + called_task = mock_trace_manager.add_trace_task.call_args[0][0] + assert called_task.trace_type == TraceTaskName.NODE_EXECUTION_TRACE diff --git a/api/tests/unit_tests/core/telemetry/test_gateway_integration.py b/api/tests/unit_tests/core/telemetry/test_gateway_integration.py new file mode 100644 index 00000000000..a68fce5e7fa --- /dev/null +++ b/api/tests/unit_tests/core/telemetry/test_gateway_integration.py @@ -0,0 +1,225 @@ +from __future__ import annotations + +import sys +from unittest.mock import MagicMock, patch + +import pytest + +from core.telemetry.gateway import emit, is_enterprise_telemetry_enabled +from enterprise.telemetry.contracts import TelemetryCase + + +class TestTelemetryCoreExports: + def test_is_enterprise_telemetry_enabled_exported(self) -> None: + from core.telemetry.gateway import is_enterprise_telemetry_enabled as exported_func + + assert callable(exported_func) + + +@pytest.fixture +def mock_ops_trace_manager(): + mock_module = MagicMock() + mock_trace_task_class = MagicMock() + mock_trace_task_class.return_value = MagicMock() + mock_module.TraceTask = mock_trace_task_class + mock_module.TraceQueueManager = MagicMock() + + mock_trace_entity = MagicMock() + mock_trace_task_name = MagicMock() + mock_trace_task_name.return_value = "workflow" + mock_trace_entity.TraceTaskName = mock_trace_task_name + + with ( + patch.dict(sys.modules, {"core.ops.ops_trace_manager": mock_module}), + patch.dict(sys.modules, {"core.ops.entities.trace_entity": mock_trace_entity}), + ): + yield mock_module, mock_trace_entity + + +class TestGatewayIntegrationTraceRouting: + @pytest.fixture + def mock_trace_manager(self) -> MagicMock: + return MagicMock() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_ce_eligible_trace_routed_to_trace_manager( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True): + context = {"app_id": "app-123", "user_id": "user-456", "tenant_id": "tenant-789"} + payload = {"workflow_run_id": "run-abc"} + + emit(TelemetryCase.WORKFLOW_RUN, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_ce_eligible_trace_routed_when_ee_disabled( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"workflow_run_id": "run-abc"} + + emit(TelemetryCase.WORKFLOW_RUN, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_enterprise_only_trace_dropped_when_ee_disabled( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"node_id": "node-abc"} + + emit(TelemetryCase.NODE_EXECUTION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_not_called() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_enterprise_only_trace_routed_when_ee_enabled( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"node_id": "node-abc"} + + emit(TelemetryCase.NODE_EXECUTION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + +class TestGatewayIntegrationMetricRouting: + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_metric_case_routes_to_celery_task( + self, + mock_ee_enabled: MagicMock, + ) -> None: + from enterprise.telemetry.contracts import TelemetryEnvelope + + with patch("tasks.enterprise_telemetry_task.process_enterprise_telemetry.delay") as mock_delay: + context = {"tenant_id": "tenant-123"} + payload = {"app_id": "app-abc", "name": "My App"} + + emit(TelemetryCase.APP_CREATED, context, payload) + + mock_delay.assert_called_once() + envelope_json = mock_delay.call_args[0][0] + envelope = TelemetryEnvelope.model_validate_json(envelope_json) + assert envelope.case == TelemetryCase.APP_CREATED + assert envelope.tenant_id == "tenant-123" + assert envelope.payload["app_id"] == "app-abc" + + @pytest.mark.usefixtures("mock_ops_trace_manager") + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_tool_execution_trace_routed( + self, + mock_ee_enabled: MagicMock, + ) -> None: + mock_trace_manager = MagicMock() + context = {"tenant_id": "tenant-123", "app_id": "app-123"} + payload = {"tool_name": "test_tool", "tool_inputs": {}, "tool_outputs": "result"} + + emit(TelemetryCase.TOOL_EXECUTION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + @patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=True) + def test_moderation_check_trace_routed( + self, + mock_ee_enabled: MagicMock, + ) -> None: + mock_trace_manager = MagicMock() + context = {"tenant_id": "tenant-123", "app_id": "app-123"} + payload = {"message_id": "msg-123", "moderation_result": {"flagged": False}} + + emit(TelemetryCase.MODERATION_CHECK, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + +class TestGatewayIntegrationCEEligibility: + @pytest.fixture + def mock_trace_manager(self) -> MagicMock: + return MagicMock() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_workflow_run_is_ce_eligible( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"workflow_run_id": "run-abc"} + + emit(TelemetryCase.WORKFLOW_RUN, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_message_run_is_ce_eligible( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"message_id": "msg-abc", "conversation_id": "conv-123"} + + emit(TelemetryCase.MESSAGE_RUN, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_called_once() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_node_execution_not_ce_eligible( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"node_id": "node-abc"} + + emit(TelemetryCase.NODE_EXECUTION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_not_called() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_draft_node_execution_not_ce_eligible( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456"} + payload = {"node_execution_data": {}} + + emit(TelemetryCase.DRAFT_NODE_EXECUTION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_not_called() + + @pytest.mark.usefixtures("mock_ops_trace_manager") + def test_prompt_generation_not_ce_eligible( + self, + mock_trace_manager: MagicMock, + ) -> None: + with patch("core.telemetry.gateway.is_enterprise_telemetry_enabled", return_value=False): + context = {"app_id": "app-123", "user_id": "user-456", "tenant_id": "tenant-789"} + payload = {"operation_type": "generate", "instruction": "test"} + + emit(TelemetryCase.PROMPT_GENERATION, context, payload, mock_trace_manager) + + mock_trace_manager.add_trace_task.assert_not_called() + + +class TestIsEnterpriseTelemetryEnabled: + def test_returns_false_when_exporter_import_fails(self) -> None: + with patch.dict(sys.modules, {"enterprise.telemetry.exporter": None}): + result = is_enterprise_telemetry_enabled() + assert result is False + + def test_function_is_callable(self) -> None: + assert callable(is_enterprise_telemetry_enabled) diff --git a/api/tests/unit_tests/core/test_file.py b/api/tests/unit_tests/core/test_file.py index 251d6fd25ea..ac65d0c02bc 100644 --- a/api/tests/unit_tests/core/test_file.py +++ b/api/tests/unit_tests/core/test_file.py @@ -1,6 +1,7 @@ import json -from dify_graph.file import File, FileTransferMethod, FileType, FileUploadConfig +from graphon.file import File, FileTransferMethod, FileType, FileUploadConfig + from models.workflow import Workflow diff --git a/api/tests/unit_tests/core/test_model_manager.py b/api/tests/unit_tests/core/test_model_manager.py index 92e4b584736..f5efb78b614 100644 --- a/api/tests/unit_tests/core/test_model_manager.py +++ b/api/tests/unit_tests/core/test_model_manager.py @@ -2,11 +2,11 @@ from unittest.mock import MagicMock, patch import pytest import redis +from graphon.model_runtime.entities.model_entities import ModelType from pytest_mock import MockerFixture from core.entities.provider_entities import ModelLoadBalancingConfiguration from core.model_manager import LBModelManager -from dify_graph.model_runtime.entities.model_entities import ModelType from extensions.ext_redis import redis_client diff --git a/api/tests/unit_tests/core/test_provider_configuration.py b/api/tests/unit_tests/core/test_provider_configuration.py index 90ed1647aac..331166fe63c 100644 --- a/api/tests/unit_tests/core/test_provider_configuration.py +++ b/api/tests/unit_tests/core/test_provider_configuration.py @@ -1,6 +1,15 @@ from unittest.mock import Mock, patch import pytest +from graphon.model_runtime.entities.common_entities import I18nObject +from graphon.model_runtime.entities.model_entities import ModelType +from graphon.model_runtime.entities.provider_entities import ( + ConfigurateMethod, + CredentialFormSchema, + FormOption, + FormType, + ProviderEntity, +) from core.entities.provider_configuration import ProviderConfiguration, SystemConfigurationStatus from core.entities.provider_entities import ( @@ -12,15 +21,6 @@ from core.entities.provider_entities import ( RestrictModel, SystemConfiguration, ) -from dify_graph.model_runtime.entities.common_entities import I18nObject -from dify_graph.model_runtime.entities.model_entities import ModelType -from dify_graph.model_runtime.entities.provider_entities import ( - ConfigurateMethod, - CredentialFormSchema, - FormOption, - FormType, - ProviderEntity, -) from models.provider import Provider, ProviderType diff --git a/api/tests/unit_tests/core/test_provider_manager.py b/api/tests/unit_tests/core/test_provider_manager.py index 69567c54eb8..259cb5fdd07 100644 --- a/api/tests/unit_tests/core/test_provider_manager.py +++ b/api/tests/unit_tests/core/test_provider_manager.py @@ -1,12 +1,26 @@ -from unittest.mock import Mock, PropertyMock, patch +from types import SimpleNamespace +from unittest.mock import MagicMock, Mock, PropertyMock, patch import pytest +from graphon.model_runtime.entities.common_entities import I18nObject +from graphon.model_runtime.entities.model_entities import ModelType +from pytest_mock import MockerFixture from core.entities.provider_entities import ModelSettings from core.provider_manager import ProviderManager -from dify_graph.model_runtime.entities.common_entities import I18nObject -from dify_graph.model_runtime.entities.model_entities import ModelType -from models.provider import LoadBalancingModelConfig, ProviderModelSetting +from models.provider import LoadBalancingModelConfig, ProviderModelSetting, TenantDefaultModel +from models.provider_ids import ModelProviderID + + +def _build_provider_manager(mocker: MockerFixture) -> ProviderManager: + return ProviderManager(model_runtime=mocker.Mock()) + + +def _build_session_context(session: Mock) -> MagicMock: + session_cm = MagicMock() + session_cm.__enter__.return_value = session + session_cm.__exit__.return_value = False + return session_cm @pytest.fixture @@ -28,7 +42,7 @@ def mock_provider_entity(): return mock_entity -def test__to_model_settings(mock_provider_entity): +def test__to_model_settings(mocker: MockerFixture, mock_provider_entity): # Mocking the inputs ps = ProviderModelSetting( tenant_id="tenant_id", @@ -69,7 +83,7 @@ def test__to_model_settings(mock_provider_entity): "core.helper.model_provider_cache.ProviderCredentialsCache.get", return_value={"openai_api_key": "fake_key"}, ): - provider_manager = ProviderManager() + provider_manager = _build_provider_manager(mocker) # Running the method result = provider_manager._to_model_settings( @@ -89,7 +103,7 @@ def test__to_model_settings(mock_provider_entity): assert result[0].load_balancing_configs[1].name == "first" -def test__to_model_settings_only_one_lb(mock_provider_entity): +def test__to_model_settings_only_one_lb(mocker: MockerFixture, mock_provider_entity): # Mocking the inputs ps = ProviderModelSetting( @@ -119,7 +133,7 @@ def test__to_model_settings_only_one_lb(mock_provider_entity): "core.helper.model_provider_cache.ProviderCredentialsCache.get", return_value={"openai_api_key": "fake_key"}, ): - provider_manager = ProviderManager() + provider_manager = _build_provider_manager(mocker) # Running the method result = provider_manager._to_model_settings( @@ -137,7 +151,7 @@ def test__to_model_settings_only_one_lb(mock_provider_entity): assert len(result[0].load_balancing_configs) == 0 -def test__to_model_settings_lb_disabled(mock_provider_entity): +def test__to_model_settings_lb_disabled(mocker: MockerFixture, mock_provider_entity): # Mocking the inputs ps = ProviderModelSetting( tenant_id="tenant_id", @@ -176,7 +190,7 @@ def test__to_model_settings_lb_disabled(mock_provider_entity): "core.helper.model_provider_cache.ProviderCredentialsCache.get", return_value={"openai_api_key": "fake_key"}, ): - provider_manager = ProviderManager() + provider_manager = _build_provider_manager(mocker) # Running the method result = provider_manager._to_model_settings( @@ -194,7 +208,7 @@ def test__to_model_settings_lb_disabled(mock_provider_entity): assert len(result[0].load_balancing_configs) == 0 -def test_get_default_model_uses_first_available_active_model(): +def test_get_default_model_uses_first_available_active_model(mocker: MockerFixture): mock_session = Mock() mock_session.scalar.return_value = None @@ -204,7 +218,7 @@ def test_get_default_model_uses_first_available_active_model(): Mock(model="gpt-4", provider=Mock(provider="openai")), ] - manager = ProviderManager() + manager = _build_provider_manager(mocker) with ( patch("core.provider_manager.db.session", mock_session), patch.object(manager, "get_configurations", return_value=provider_configurations), @@ -228,3 +242,345 @@ def test_get_default_model_uses_first_available_active_model(): assert saved_default_model.model_name == "gpt-3.5-turbo" assert saved_default_model.provider_name == "openai" mock_session.commit.assert_called_once() + + +def test_get_default_model_returns_none_when_no_default_or_active_models(mocker: MockerFixture): + mock_session = Mock() + mock_session.scalar.return_value = None + provider_configurations = Mock() + provider_configurations.get_models.return_value = [] + manager = _build_provider_manager(mocker) + + with ( + patch("core.provider_manager.db.session", mock_session), + patch.object(manager, "get_configurations", return_value=provider_configurations), + patch("core.provider_manager.ModelProviderFactory") as mock_factory_cls, + ): + result = manager.get_default_model("tenant-id", ModelType.LLM) + + assert result is None + provider_configurations.get_models.assert_called_once_with(model_type=ModelType.LLM, only_active=True) + mock_factory_cls.assert_not_called() + mock_session.add.assert_not_called() + mock_session.commit.assert_not_called() + + +def test_get_default_model_uses_injected_runtime_for_existing_default_record(mocker: MockerFixture): + existing_default_model = TenantDefaultModel( + tenant_id="tenant-id", + provider_name="openai", + model_name="gpt-4", + model_type=ModelType.LLM.to_origin_model_type(), + ) + mock_session = Mock() + mock_session.scalar.return_value = existing_default_model + manager = _build_provider_manager(mocker) + + with ( + patch("core.provider_manager.db.session", mock_session), + patch("core.provider_manager.ModelProviderFactory") as mock_factory_cls, + ): + mock_factory_cls.return_value.get_provider_schema.return_value = Mock( + provider="openai", + label=I18nObject(en_US="OpenAI", zh_Hans="OpenAI"), + icon_small=I18nObject(en_US="icon_small.png", zh_Hans="icon_small.png"), + supported_model_types=[ModelType.LLM], + ) + + result = manager.get_default_model("tenant-id", ModelType.LLM) + + mock_factory_cls.assert_called_once_with(model_runtime=manager._model_runtime) + assert result is not None + assert result.model == "gpt-4" + assert result.provider.provider == "openai" + + +def test_get_configurations_uses_injected_runtime_and_adds_provider_aliases(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_records = {"openai": [SimpleNamespace(provider_name="openai")]} + provider_model_records = {"openai": [SimpleNamespace(provider_name="openai")]} + preferred_provider_records = {"openai": SimpleNamespace(preferred_provider_type="system")} + + with ( + patch.object(manager, "_get_all_providers", return_value=provider_records), + patch.object(manager, "_init_trial_provider_records", return_value=provider_records), + patch.object(manager, "_get_all_provider_models", return_value=provider_model_records), + patch.object(manager, "_get_all_preferred_model_providers", return_value=preferred_provider_records), + patch.object(manager, "_get_all_provider_model_settings", return_value={}), + patch.object(manager, "_get_all_provider_load_balancing_configs", return_value={}), + patch.object(manager, "_get_all_provider_model_credentials", return_value={}), + patch("core.provider_manager.ModelProviderFactory") as mock_factory_cls, + ): + mock_factory_cls.return_value.get_providers.return_value = [] + + result = manager.get_configurations("tenant-id") + + expected_alias = str(ModelProviderID("openai")) + mock_factory_cls.assert_called_once_with(model_runtime=manager._model_runtime) + assert result.tenant_id == "tenant-id" + assert expected_alias in provider_records + assert expected_alias in provider_model_records + assert expected_alias in preferred_provider_records + + +@pytest.mark.parametrize( + ("provider_name", "expected_provider_names"), + [ + ("openai", ["openai", "langgenius/openai/openai"]), + ("langgenius/openai/openai", ["langgenius/openai/openai", "openai"]), + ("langgenius/gemini/google", ["langgenius/gemini/google", "google"]), + ], +) +def test_get_provider_names_returns_short_and_full_aliases(provider_name: str, expected_provider_names: list[str]): + assert ProviderManager._get_provider_names(provider_name) == expected_provider_names + + +def test_get_provider_model_bundle_raises_for_unknown_provider(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + + with patch.object(manager, "get_configurations", return_value={}): + with pytest.raises(ValueError, match="Provider openai does not exist."): + manager.get_provider_model_bundle("tenant-id", "openai", ModelType.LLM) + + +def test_get_configurations_binds_manager_runtime_to_provider_configuration( + mocker: MockerFixture, mock_provider_entity +): + manager = _build_provider_manager(mocker) + provider_configuration = Mock() + provider_factory = Mock() + provider_factory.get_providers.return_value = [mock_provider_entity] + custom_configuration = SimpleNamespace(provider=None, models=[]) + system_configuration = SimpleNamespace(enabled=False, quota_configurations=[], current_quota_type=None) + + with ( + patch.object(manager, "_get_all_providers", return_value={"openai": []}), + patch.object(manager, "_init_trial_provider_records", return_value={"openai": []}), + patch.object(manager, "_get_all_provider_models", return_value={"openai": []}), + patch.object(manager, "_get_all_preferred_model_providers", return_value={}), + patch.object(manager, "_get_all_provider_model_settings", return_value={}), + patch.object(manager, "_get_all_provider_load_balancing_configs", return_value={}), + patch.object(manager, "_get_all_provider_model_credentials", return_value={}), + patch.object(manager, "_to_custom_configuration", return_value=custom_configuration), + patch.object(manager, "_to_system_configuration", return_value=system_configuration), + patch.object(manager, "_to_model_settings", return_value=[]), + patch("core.provider_manager.ModelProviderFactory", return_value=provider_factory), + patch("core.provider_manager.ProviderConfiguration", return_value=provider_configuration), + ): + manager.get_configurations("tenant-id") + + provider_configuration.bind_model_runtime.assert_called_once_with(manager._model_runtime) + + +def test_get_provider_model_bundle_returns_selected_model_type_instance(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configuration = Mock() + model_type_instance = Mock() + provider_configuration.get_model_type_instance.return_value = model_type_instance + expected_bundle = Mock() + + with ( + patch.object(manager, "get_configurations", return_value={"openai": provider_configuration}), + patch("core.provider_manager.ProviderModelBundle", return_value=expected_bundle) as mock_bundle, + ): + result = manager.get_provider_model_bundle("tenant-id", "openai", ModelType.LLM) + + provider_configuration.get_model_type_instance.assert_called_once_with(ModelType.LLM) + mock_bundle.assert_called_once_with( + configuration=provider_configuration, + model_type_instance=model_type_instance, + ) + assert result is expected_bundle + + +def test_get_first_provider_first_model_returns_none_when_no_models(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configurations = Mock() + provider_configurations.get_models.return_value = [] + + with patch.object(manager, "get_configurations", return_value=provider_configurations): + result = manager.get_first_provider_first_model("tenant-id", ModelType.LLM) + + assert result == (None, None) + provider_configurations.get_models.assert_called_once_with(model_type=ModelType.LLM, only_active=False) + + +def test_get_first_provider_first_model_returns_first_model_and_provider(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configurations = Mock() + provider_configurations.get_models.return_value = [ + Mock(model="gpt-4", provider=Mock(provider="openai")), + Mock(model="gpt-4o", provider=Mock(provider="openai")), + ] + + with patch.object(manager, "get_configurations", return_value=provider_configurations): + result = manager.get_first_provider_first_model("tenant-id", ModelType.LLM) + + assert result == ("openai", "gpt-4") + + +def test_update_default_model_record_raises_for_unknown_provider(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + + with patch.object(manager, "get_configurations", return_value={}): + with pytest.raises(ValueError, match="Provider openai does not exist."): + manager.update_default_model_record("tenant-id", ModelType.LLM, "openai", "gpt-4") + + +def test_update_default_model_record_raises_for_unknown_model(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configurations = MagicMock() + provider_configurations.__contains__.return_value = True + provider_configurations.get_models.return_value = [Mock(model="gpt-4")] + + with patch.object(manager, "get_configurations", return_value=provider_configurations): + with pytest.raises(ValueError, match="Model gpt-3.5-turbo does not exist."): + manager.update_default_model_record("tenant-id", ModelType.LLM, "openai", "gpt-3.5-turbo") + + provider_configurations.get_models.assert_called_once_with(model_type=ModelType.LLM, only_active=True) + + +def test_update_default_model_record_updates_existing_record(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configurations = MagicMock() + provider_configurations.__contains__.return_value = True + provider_configurations.get_models.return_value = [Mock(model="gpt-3.5-turbo")] + existing_default_model = TenantDefaultModel( + tenant_id="tenant-id", + provider_name="anthropic", + model_name="claude-3-sonnet", + model_type=ModelType.LLM.to_origin_model_type(), + ) + mock_session = Mock() + mock_session.scalar.return_value = existing_default_model + + with ( + patch.object(manager, "get_configurations", return_value=provider_configurations), + patch("core.provider_manager.db.session", mock_session), + ): + result = manager.update_default_model_record("tenant-id", ModelType.LLM, "openai", "gpt-3.5-turbo") + + assert result is existing_default_model + assert existing_default_model.provider_name == "openai" + assert existing_default_model.model_name == "gpt-3.5-turbo" + mock_session.commit.assert_called_once() + mock_session.add.assert_not_called() + + +def test_update_default_model_record_creates_record_with_origin_model_type(mocker: MockerFixture): + manager = _build_provider_manager(mocker) + provider_configurations = MagicMock() + provider_configurations.__contains__.return_value = True + provider_configurations.get_models.return_value = [Mock(model="gpt-4")] + mock_session = Mock() + mock_session.scalar.return_value = None + + with ( + patch.object(manager, "get_configurations", return_value=provider_configurations), + patch("core.provider_manager.db.session", mock_session), + ): + result = manager.update_default_model_record("tenant-id", ModelType.LLM, "openai", "gpt-4") + + mock_session.add.assert_called_once() + created_default_model = mock_session.add.call_args.args[0] + assert result is created_default_model + assert created_default_model.tenant_id == "tenant-id" + assert created_default_model.provider_name == "openai" + assert created_default_model.model_name == "gpt-4" + assert created_default_model.model_type == ModelType.LLM.to_origin_model_type() + mock_session.commit.assert_called_once() + + +def test_get_all_providers_normalizes_provider_names_with_model_provider_id() -> None: + session = Mock() + openai_provider = SimpleNamespace(provider_name="openai") + gemini_provider = SimpleNamespace(provider_name="langgenius/gemini/google") + session.scalars.return_value = [openai_provider, gemini_provider] + + with ( + patch("core.provider_manager.db", SimpleNamespace(engine=object())), + patch("core.provider_manager.Session", return_value=_build_session_context(session)), + ): + result = ProviderManager._get_all_providers("tenant-id") + + assert list(result[str(ModelProviderID("openai"))]) == [openai_provider] + assert list(result[str(ModelProviderID("langgenius/gemini/google"))]) == [gemini_provider] + + +@pytest.mark.parametrize( + "method_name", + [ + "_get_all_provider_models", + "_get_all_provider_model_settings", + "_get_all_provider_model_credentials", + ], +) +def test_provider_grouping_helpers_group_records_by_provider_name(method_name: str) -> None: + session = Mock() + openai_primary = SimpleNamespace(provider_name="openai") + openai_secondary = SimpleNamespace(provider_name="openai") + anthropic_record = SimpleNamespace(provider_name="anthropic") + session.scalars.return_value = [openai_primary, openai_secondary, anthropic_record] + + with ( + patch("core.provider_manager.db", SimpleNamespace(engine=object())), + patch("core.provider_manager.Session", return_value=_build_session_context(session)), + ): + result = getattr(ProviderManager, method_name)("tenant-id") + + assert list(result["openai"]) == [openai_primary, openai_secondary] + assert list(result["anthropic"]) == [anthropic_record] + + +def test_get_all_preferred_model_providers_returns_mapping_by_provider_name() -> None: + session = Mock() + openai_preference = SimpleNamespace(provider_name="openai") + anthropic_preference = SimpleNamespace(provider_name="anthropic") + session.scalars.return_value = [openai_preference, anthropic_preference] + + with ( + patch("core.provider_manager.db", SimpleNamespace(engine=object())), + patch("core.provider_manager.Session", return_value=_build_session_context(session)), + ): + result = ProviderManager._get_all_preferred_model_providers("tenant-id") + + assert result == { + "openai": openai_preference, + "anthropic": anthropic_preference, + } + + +def test_get_all_provider_load_balancing_configs_returns_empty_when_cached_flag_is_disabled() -> None: + with ( + patch("core.provider_manager.redis_client.get", return_value=b"False"), + patch("core.provider_manager.FeatureService.get_features") as mock_get_features, + patch("core.provider_manager.Session") as mock_session_cls, + ): + result = ProviderManager._get_all_provider_load_balancing_configs("tenant-id") + + assert result == {} + mock_get_features.assert_not_called() + mock_session_cls.assert_not_called() + + +def test_get_all_provider_load_balancing_configs_populates_cache_and_groups_configs() -> None: + session = Mock() + openai_config = SimpleNamespace(provider_name="openai") + anthropic_config = SimpleNamespace(provider_name="anthropic") + session.scalars.return_value = [openai_config, anthropic_config] + + with ( + patch("core.provider_manager.db", SimpleNamespace(engine=object())), + patch("core.provider_manager.redis_client.get", return_value=None), + patch("core.provider_manager.redis_client.setex") as mock_setex, + patch( + "core.provider_manager.FeatureService.get_features", + return_value=SimpleNamespace(model_load_balancing_enabled=True), + ), + patch("core.provider_manager.Session", return_value=_build_session_context(session)), + ): + result = ProviderManager._get_all_provider_load_balancing_configs("tenant-id") + + mock_setex.assert_called_once_with("tenant:tenant-id:model_load_balancing_enabled", 120, "True") + assert list(result["openai"]) == [openai_config] + assert list(result["anthropic"]) == [anthropic_config] diff --git a/api/tests/unit_tests/core/tools/test_builtin_tool_base.py b/api/tests/unit_tests/core/tools/test_builtin_tool_base.py index f123f60a34a..5d744f88c9b 100644 --- a/api/tests/unit_tests/core/tools/test_builtin_tool_base.py +++ b/api/tests/unit_tests/core/tools/test_builtin_tool_base.py @@ -6,13 +6,13 @@ from typing import Any from unittest.mock import patch import pytest +from graphon.model_runtime.entities.message_entities import UserPromptMessage from core.app.entities.app_invoke_entities import InvokeFrom from core.tools.__base.tool_runtime import ToolRuntime from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ToolEntity, ToolIdentity, ToolInvokeMessage, ToolProviderType -from dify_graph.model_runtime.entities.message_entities import UserPromptMessage class _BuiltinDummyTool(BuiltinTool): @@ -27,12 +27,12 @@ class _BuiltinDummyTool(BuiltinTool): yield self.create_text_message("ok") -def _build_tool() -> _BuiltinDummyTool: +def _build_tool(user_id: str | None = None) -> _BuiltinDummyTool: entity = ToolEntity( identity=ToolIdentity(author="author", name="tool-a", label=I18nObject(en_US="tool-a"), provider="provider-a"), parameters=[], ) - runtime = ToolRuntime(tenant_id="tenant-1", invoke_from=InvokeFrom.DEBUGGER) + runtime = ToolRuntime(tenant_id="tenant-1", user_id=user_id, invoke_from=InvokeFrom.DEBUGGER) return _BuiltinDummyTool(provider="provider-a", entity=entity, runtime=runtime) @@ -45,7 +45,7 @@ def test_builtin_tool_fork_and_provider_type(): def test_invoke_model_calls_model_invocation_utils_invoke(): - tool = _build_tool() + tool = _build_tool(user_id="runtime-user") with patch("core.tools.builtin_tool.tool.ModelInvocationUtils.invoke", return_value="result") as mock_invoke: assert ( tool.invoke_model( @@ -55,19 +55,47 @@ def test_invoke_model_calls_model_invocation_utils_invoke(): ) == "result" ) - mock_invoke.assert_called_once() + mock_invoke.assert_called_once_with( + user_id="u1", + tenant_id="tenant-1", + tool_type=ToolProviderType.BUILT_IN, + tool_name="tool-a", + prompt_messages=[UserPromptMessage(content="hello")], + caller_user_id="runtime-user", + ) def test_get_max_tokens_returns_value(): - tool = _build_tool() - with patch("core.tools.builtin_tool.tool.ModelInvocationUtils.get_max_llm_context_tokens", return_value=4096): + tool = _build_tool(user_id="runtime-user") + with patch( + "core.tools.builtin_tool.tool.ModelInvocationUtils.get_max_llm_context_tokens", return_value=4096 + ) as mock_get: assert tool.get_max_tokens() == 4096 + mock_get.assert_called_once_with(tenant_id="tenant-1", user_id="runtime-user") def test_get_prompt_tokens_returns_value(): - tool = _build_tool() - with patch("core.tools.builtin_tool.tool.ModelInvocationUtils.calculate_tokens", return_value=7): + tool = _build_tool(user_id="runtime-user") + with patch("core.tools.builtin_tool.tool.ModelInvocationUtils.calculate_tokens", return_value=7) as mock_calculate: assert tool.get_prompt_tokens([UserPromptMessage(content="hello")]) == 7 + mock_calculate.assert_called_once_with( + tenant_id="tenant-1", + prompt_messages=[UserPromptMessage(content="hello")], + user_id="runtime-user", + ) + + +def test_get_prompt_tokens_falls_back_to_tenant_scope_when_runtime_user_id_missing(): + tool = _build_tool() + + with patch("core.tools.builtin_tool.tool.ModelInvocationUtils.calculate_tokens", return_value=7) as mock_calculate: + assert tool.get_prompt_tokens([UserPromptMessage(content="hello")]) == 7 + + mock_calculate.assert_called_once_with( + tenant_id="tenant-1", + prompt_messages=[UserPromptMessage(content="hello")], + user_id=None, + ) def test_runtime_none_raises(): diff --git a/api/tests/unit_tests/core/tools/test_builtin_tools_extra.py b/api/tests/unit_tests/core/tools/test_builtin_tools_extra.py index 62cfb6ce5bf..ee0ce51eec9 100644 --- a/api/tests/unit_tests/core/tools/test_builtin_tools_extra.py +++ b/api/tests/unit_tests/core/tools/test_builtin_tools_extra.py @@ -1,9 +1,13 @@ from __future__ import annotations +import calendar import math +from datetime import date from types import SimpleNamespace import pytest +from graphon.file import FileType +from graphon.model_runtime.entities.model_entities import ModelPropertyKey from core.app.entities.app_invoke_entities import InvokeFrom from core.tools.__base.tool_runtime import ToolRuntime @@ -25,8 +29,6 @@ from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ToolEntity, ToolIdentity, ToolInvokeMessage from core.tools.errors import ToolInvokeError -from dify_graph.file.enums import FileType -from dify_graph.model_runtime.entities.model_entities import ModelPropertyKey def _build_builtin_tool(tool_cls: type[BuiltinTool]) -> BuiltinTool: @@ -98,7 +100,13 @@ def test_timezone_conversion_tool(): def test_weekday_tool(): weekday_tool = _build_builtin_tool(WeekdayTool) valid = list(weekday_tool.invoke(user_id="u", tool_parameters={"year": 2024, "month": 1, "day": 1}))[0].message.text - assert "January 1, 2024" in valid + expected_date = date(2024, 1, 1) + expected_message = ( + f"{calendar.month_name[expected_date.month]} " + f"{expected_date.day}, {expected_date.year} " + f"is {calendar.day_name[expected_date.weekday()]}." + ) + assert valid == expected_message invalid = list(weekday_tool.invoke(user_id="u", tool_parameters={"year": 2024, "month": 2, "day": 31}))[ 0 ].message.text @@ -186,13 +194,19 @@ def test_asr_invalid_file(): def test_asr_valid_file_invocation(monkeypatch): asr = _build_builtin_tool(ASRTool) - model_instance = type("M", (), {"invoke_speech2text": lambda self, file, user: "transcript"})() + model_instance = type("M", (), {"invoke_speech2text": lambda self, file: "transcript"})() model_manager = type("Mgr", (), {"get_model_instance": lambda *a, **k: model_instance})() monkeypatch.setattr("core.tools.builtin_tool.providers.audio.tools.asr.download", lambda file: b"audio-bytes") - monkeypatch.setattr("core.tools.builtin_tool.providers.audio.tools.asr.ModelManager", lambda: model_manager) + captured_manager_kwargs = {} + + monkeypatch.setattr( + "core.tools.builtin_tool.providers.audio.tools.asr.ModelManager.for_tenant", + lambda **kwargs: captured_manager_kwargs.update(kwargs) or model_manager, + ) audio_file = SimpleNamespace(type=FileType.AUDIO) ok = list(asr.invoke(user_id="u", tool_parameters={"audio_file": audio_file, "model": "p#m"}))[0].message.text assert ok == "transcript" + assert captured_manager_kwargs == {"tenant_id": "tenant-1", "user_id": "u"} def test_asr_available_models_and_runtime_parameters(monkeypatch): @@ -208,6 +222,7 @@ def test_asr_available_models_and_runtime_parameters(monkeypatch): def test_tts_invoke_returns_messages(monkeypatch): tts = _build_builtin_tool(TTSTool) + captured_manager_kwargs = {} voices_model_instance = type( "TTSM", (), @@ -217,11 +232,15 @@ def test_tts_invoke_returns_messages(monkeypatch): }, )() monkeypatch.setattr( - "core.tools.builtin_tool.providers.audio.tools.tts.ModelManager", - lambda: type("M", (), {"get_model_instance": lambda *a, **k: voices_model_instance})(), + "core.tools.builtin_tool.providers.audio.tools.tts.ModelManager.for_tenant", + lambda **kwargs: ( + captured_manager_kwargs.update(kwargs) + or type("M", (), {"get_model_instance": lambda *a, **k: voices_model_instance})() + ), ) messages = list(tts.invoke(user_id="u", tool_parameters={"model": "p#m", "text": "hello"})) assert [m.type for m in messages] == [ToolInvokeMessage.MessageType.TEXT, ToolInvokeMessage.MessageType.BLOB] + assert captured_manager_kwargs == {"tenant_id": "tenant-1", "user_id": "u"} def test_tts_get_available_models_requires_runtime(): @@ -254,8 +273,8 @@ def test_tts_tool_raises_when_voice_unavailable(monkeypatch, voices): }, )() monkeypatch.setattr( - "core.tools.builtin_tool.providers.audio.tools.tts.ModelManager", - lambda: type("Manager", (), {"get_model_instance": lambda *args, **kwargs: model_without_voice})(), + "core.tools.builtin_tool.providers.audio.tools.tts.ModelManager.for_tenant", + lambda **_: type("Manager", (), {"get_model_instance": lambda *args, **kwargs: model_without_voice})(), ) with pytest.raises(ValueError, match="no voice available"): list(tts.invoke(user_id="u", tool_parameters={"model": "p#m", "text": "hello"})) diff --git a/api/tests/unit_tests/core/tools/test_signature.py b/api/tests/unit_tests/core/tools/test_signature.py index a5242a78c50..353988d7a64 100644 --- a/api/tests/unit_tests/core/tools/test_signature.py +++ b/api/tests/unit_tests/core/tools/test_signature.py @@ -6,7 +6,13 @@ from urllib.parse import parse_qs, urlparse import pytest -from core.tools.signature import sign_tool_file, sign_upload_file, verify_tool_file_signature +from core.tools.signature import ( + get_signed_file_url_for_plugin, + sign_tool_file, + sign_upload_file, + verify_plugin_file_signature, + verify_tool_file_signature, +) def test_sign_tool_file_and_verify_roundtrip(monkeypatch: pytest.MonkeyPatch) -> None: @@ -117,3 +123,82 @@ def test_sign_upload_file_uses_files_url_fallback(monkeypatch: pytest.MonkeyPatc assert query["timestamp"][0] assert query["nonce"][0] assert query["sign"][0] + + +def test_get_signed_file_url_for_plugin_and_verify_roundtrip(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr("core.tools.signature.time.time", lambda: 1700000000) + monkeypatch.setattr("core.tools.signature.os.urandom", lambda _: b"\x06" * 16) + monkeypatch.setattr("core.tools.signature.dify_config.SECRET_KEY", "unit-secret") + monkeypatch.setattr("core.tools.signature.dify_config.FILES_URL", "https://files.example.com") + monkeypatch.setattr("core.tools.signature.dify_config.INTERNAL_FILES_URL", "https://internal.example.com") + monkeypatch.setattr("core.tools.signature.dify_config.FILES_ACCESS_TIMEOUT", 60) + + url = get_signed_file_url_for_plugin( + filename="report.pdf", + mimetype="application/pdf", + tenant_id="tenant-id", + user_id="user-id", + ) + parsed = urlparse(url) + query = parse_qs(parsed.query) + + assert parsed.netloc == "internal.example.com" + assert parsed.path == "/files/upload/for-plugin" + assert query["tenant_id"] == ["tenant-id"] + assert query["user_id"] == ["user-id"] + assert ( + verify_plugin_file_signature( + filename="report.pdf", + mimetype="application/pdf", + tenant_id="tenant-id", + user_id="user-id", + timestamp=query["timestamp"][0], + nonce=query["nonce"][0], + sign=query["sign"][0], + ) + is True + ) + + +def test_verify_plugin_file_signature_rejects_invalid_signatures(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr("core.tools.signature.time.time", lambda: 1700000000) + monkeypatch.setattr("core.tools.signature.os.urandom", lambda _: b"\x07" * 16) + monkeypatch.setattr("core.tools.signature.dify_config.SECRET_KEY", "unit-secret") + monkeypatch.setattr("core.tools.signature.dify_config.FILES_URL", "https://files.example.com") + monkeypatch.setattr("core.tools.signature.dify_config.INTERNAL_FILES_URL", "") + monkeypatch.setattr("core.tools.signature.dify_config.FILES_ACCESS_TIMEOUT", 30) + + url = get_signed_file_url_for_plugin( + filename="report.pdf", + mimetype="application/pdf", + tenant_id="tenant-id", + user_id="user-id", + ) + query = parse_qs(urlparse(url).query) + + assert ( + verify_plugin_file_signature( + filename="report.pdf", + mimetype="application/pdf", + tenant_id="tenant-id", + user_id="user-id", + timestamp=query["timestamp"][0], + nonce=query["nonce"][0], + sign="bad-signature", + ) + is False + ) + + monkeypatch.setattr("core.tools.signature.time.time", lambda: 1700000100) + assert ( + verify_plugin_file_signature( + filename="report.pdf", + mimetype="application/pdf", + tenant_id="tenant-id", + user_id="user-id", + timestamp=query["timestamp"][0], + nonce=query["nonce"][0], + sign=query["sign"][0], + ) + is False + ) diff --git a/api/tests/unit_tests/core/tools/test_tool_file_manager.py b/api/tests/unit_tests/core/tools/test_tool_file_manager.py index cca8254dd69..7fcebde3c55 100644 --- a/api/tests/unit_tests/core/tools/test_tool_file_manager.py +++ b/api/tests/unit_tests/core/tools/test_tool_file_manager.py @@ -12,6 +12,7 @@ from unittest.mock import MagicMock, Mock, patch import httpx import pytest +from graphon.file import FileTransferMethod from core.tools.tool_file_manager import ToolFileManager @@ -232,7 +233,14 @@ def test_get_file_generator_returns_none_when_toolfile_missing() -> None: def test_get_file_generator_returns_stream_when_found() -> None: # Arrange manager = ToolFileManager() - tool_file = SimpleNamespace(file_key="k2", mimetype="image/png") + tool_file = SimpleNamespace( + id="tool123", + file_key="k2", + mimetype="image/png", + original_url=None, + name="image.png", + size=12, + ) session = Mock() session.query.return_value.where.return_value.first.return_value = tool_file @@ -240,10 +248,10 @@ def test_get_file_generator_returns_stream_when_found() -> None: with patch("core.tools.tool_file_manager.storage") as storage: stream = iter([b"a", b"b"]) storage.load_stream.return_value = stream - with ( - _patch_session_factory(session), - patch("core.tools.tool_file_manager.ToolFilePydanticModel.model_validate", return_value="validated-file"), - ): + with _patch_session_factory(session): result_stream, result_file = manager.get_file_generator_by_tool_file_id("tool123") assert list(result_stream) == [b"a", b"b"] - assert result_file == "validated-file" + assert result_file is not None + assert result_file.related_id == "tool123" + assert result_file.mime_type == "image/png" + assert result_file.transfer_method == FileTransferMethod.TOOL_FILE diff --git a/api/tests/unit_tests/core/tools/test_tool_label_manager.py b/api/tests/unit_tests/core/tools/test_tool_label_manager.py index 857f4aa1780..8c0e7e9419e 100644 --- a/api/tests/unit_tests/core/tools/test_tool_label_manager.py +++ b/api/tests/unit_tests/core/tools/test_tool_label_manager.py @@ -38,11 +38,9 @@ def test_tool_label_manager_filter_tool_labels(): def test_tool_label_manager_update_tool_labels_db(): controller = _api_controller("api-1") with patch("core.tools.tool_label_manager.db") as mock_db: - delete_query = mock_db.session.query.return_value.where.return_value - delete_query.delete.return_value = None ToolLabelManager.update_tool_labels(controller, ["search", "search", "invalid"]) - delete_query.delete.assert_called_once() + mock_db.session.execute.assert_called_once() # only one valid unique label should be inserted. assert mock_db.session.add.call_count == 1 mock_db.session.commit.assert_called_once() diff --git a/api/tests/unit_tests/core/tools/test_tool_manager.py b/api/tests/unit_tests/core/tools/test_tool_manager.py index 0f73e226547..31b68f0b3f3 100644 --- a/api/tests/unit_tests/core/tools/test_tool_manager.py +++ b/api/tests/unit_tests/core/tools/test_tool_manager.py @@ -15,6 +15,7 @@ from core.plugin.entities.plugin_daemon import CredentialType from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.tool_entities import ( ApiProviderAuthType, + ToolInvokeFrom, ToolParameter, ToolProviderType, ) @@ -219,9 +220,7 @@ def test_get_tool_runtime_builtin_with_credentials_decrypts_and_forks(): with patch.object(ToolManager, "get_builtin_provider", return_value=controller): with patch("core.helper.credential_utils.check_credential_policy_compliance"): with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value.where.return_value.order_by.return_value.first.return_value = ( - builtin_provider - ) + mock_db.session.scalar.return_value = builtin_provider encrypter = Mock() encrypter.decrypt.return_value = {"api_key": "secret"} cache = Mock() @@ -273,7 +272,7 @@ def test_get_tool_runtime_builtin_refreshes_expired_oauth_credentials( ) refreshed = SimpleNamespace(credentials={"token": "new"}, expires_at=123456) - mock_db.session.query.return_value.where.return_value.order_by.return_value.first.return_value = builtin_provider + mock_db.session.scalar.return_value = builtin_provider encrypter = Mock() encrypter.decrypt.return_value = {"token": "old"} encrypter.encrypt.return_value = {"token": "encrypted"} @@ -421,7 +420,7 @@ def test_get_agent_runtime_apply_runtime_parameters(): tool_runtime = SimpleNamespace(runtime=ToolRuntime(tenant_id="tenant-1", runtime_parameters={})) tool_runtime.get_merged_runtime_parameters = Mock(return_value=[parameter]) - with patch.object(ToolManager, "get_tool_runtime", return_value=tool_runtime): + with patch.object(ToolManager, "get_tool_runtime", return_value=tool_runtime) as mock_get_tool_runtime: with patch.object(ToolManager, "_convert_tool_parameters_type", return_value={"query": "hello"}): manager = Mock() manager.decrypt_tool_parameters.return_value = {"query": "decrypted"} @@ -437,12 +436,23 @@ def test_get_agent_runtime_apply_runtime_parameters(): tenant_id="tenant-1", app_id="app-1", agent_tool=agent_tool, + user_id="user-1", invoke_from=InvokeFrom.DEBUGGER, variable_pool=None, ) assert result is tool_runtime assert tool_runtime.runtime.runtime_parameters["query"] == "decrypted" + mock_get_tool_runtime.assert_called_once_with( + provider_type=ToolProviderType.API, + provider_id="api-1", + tool_name="search", + tenant_id="tenant-1", + user_id="user-1", + invoke_from=InvokeFrom.DEBUGGER, + tool_invoke_from=ToolInvokeFrom.AGENT, + credential_id=None, + ) def test_get_workflow_runtime_apply_runtime_parameters(): @@ -463,7 +473,7 @@ def test_get_workflow_runtime_apply_runtime_parameters(): ) tool_runtime2 = SimpleNamespace(runtime=ToolRuntime(tenant_id="tenant-1", runtime_parameters={})) tool_runtime2.get_merged_runtime_parameters = Mock(return_value=[parameter]) - with patch.object(ToolManager, "get_tool_runtime", return_value=tool_runtime2): + with patch.object(ToolManager, "get_tool_runtime", return_value=tool_runtime2) as mock_get_tool_runtime: with patch.object(ToolManager, "_convert_tool_parameters_type", return_value={"query": "workflow"}): manager = Mock() manager.decrypt_tool_parameters.return_value = {"query": "workflow-dec"} @@ -473,12 +483,23 @@ def test_get_workflow_runtime_apply_runtime_parameters(): app_id="app-1", node_id="node-1", workflow_tool=workflow_tool, + user_id="user-1", invoke_from=InvokeFrom.DEBUGGER, variable_pool=None, ) assert workflow_result is tool_runtime2 assert tool_runtime2.runtime.runtime_parameters["query"] == "workflow-dec" + mock_get_tool_runtime.assert_called_once_with( + provider_type=ToolProviderType.API, + provider_id="api-1", + tool_name="search", + tenant_id="tenant-1", + user_id="user-1", + invoke_from=InvokeFrom.DEBUGGER, + tool_invoke_from=ToolInvokeFrom.WORKFLOW, + credential_id=None, + ) def test_get_agent_runtime_raises_when_runtime_missing(): @@ -520,17 +541,28 @@ def test_get_tool_runtime_from_plugin_only_uses_form_parameters(): tool_entity = SimpleNamespace(runtime=ToolRuntime(tenant_id="tenant-1", runtime_parameters={})) tool_entity.get_merged_runtime_parameters = Mock(return_value=[form_param, llm_param]) - with patch.object(ToolManager, "get_tool_runtime", return_value=tool_entity): + with patch.object(ToolManager, "get_tool_runtime", return_value=tool_entity) as mock_get_tool_runtime: result = ToolManager.get_tool_runtime_from_plugin( tool_type=ToolProviderType.API, tenant_id="tenant-1", provider="api-1", tool_name="search", tool_parameters={"q": "hello", "llm": "ignore"}, + user_id="user-1", ) assert result is tool_entity assert tool_entity.runtime.runtime_parameters == {"q": "hello"} + mock_get_tool_runtime.assert_called_once_with( + provider_type=ToolProviderType.API, + provider_id="api-1", + tool_name="search", + tenant_id="tenant-1", + user_id="user-1", + invoke_from=InvokeFrom.SERVICE_API, + tool_invoke_from=ToolInvokeFrom.PLUGIN, + credential_id=None, + ) def test_hardcoded_provider_icon_success(): @@ -664,12 +696,10 @@ def test_get_api_provider_controller_returns_controller_and_credentials(): privacy_policy="privacy", custom_disclaimer="disclaimer", ) - db_query = Mock() - db_query.where.return_value.first.return_value = provider controller = Mock() with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value = db_query + mock_db.session.scalar.return_value = provider with patch( "core.tools.tool_manager.ApiToolProviderController.from_db", return_value=controller ) as mock_from_db: @@ -696,12 +726,10 @@ def test_user_get_api_provider_masks_credentials_and_adds_labels(): privacy_policy="privacy", custom_disclaimer="disclaimer", ) - db_query = Mock() - db_query.where.return_value.first.return_value = provider controller = Mock() with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value = db_query + mock_db.session.scalar.return_value = provider with patch("core.tools.tool_manager.ApiToolProviderController.from_db", return_value=controller): encrypter = Mock() encrypter.decrypt.return_value = {"api_key_value": "secret"} @@ -716,7 +744,7 @@ def test_user_get_api_provider_masks_credentials_and_adds_labels(): def test_get_api_provider_controller_not_found_raises(): with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value.where.return_value.first.return_value = None + mock_db.session.scalar.return_value = None with pytest.raises(ToolProviderNotFoundError, match="api provider missing not found"): ToolManager.get_api_provider_controller("tenant-1", "missing") @@ -775,14 +803,14 @@ def test_generate_tool_icon_urls_for_workflow_and_api(): workflow_provider = SimpleNamespace(icon='{"background": "#222", "content": "W"}') api_provider = SimpleNamespace(icon='{"background": "#333", "content": "A"}') with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value.where.return_value.first.side_effect = [workflow_provider, api_provider] + mock_db.session.scalar.side_effect = [workflow_provider, api_provider] assert ToolManager.generate_workflow_tool_icon_url("tenant-1", "wf-1") == {"background": "#222", "content": "W"} assert ToolManager.generate_api_tool_icon_url("tenant-1", "api-1") == {"background": "#333", "content": "A"} def test_generate_tool_icon_urls_missing_workflow_and_api_use_default(): with patch("core.tools.tool_manager.db") as mock_db: - mock_db.session.query.return_value.where.return_value.first.return_value = None + mock_db.session.scalar.return_value = None assert ToolManager.generate_workflow_tool_icon_url("tenant-1", "missing")["background"] == "#252525" assert ToolManager.generate_api_tool_icon_url("tenant-1", "missing")["background"] == "#252525" diff --git a/api/tests/unit_tests/core/tools/utils/test_configuration.py b/api/tests/unit_tests/core/tools/utils/test_configuration.py index 5ceaa08893b..ae5638784c4 100644 --- a/api/tests/unit_tests/core/tools/utils/test_configuration.py +++ b/api/tests/unit_tests/core/tools/utils/test_configuration.py @@ -110,7 +110,7 @@ def test_encrypt_tool_parameters(): assert encrypted["plain"] == "x" -def test_decrypt_tool_parameters_cache_hit_and_miss(): +def test_decrypt_tool_parameters_cache_hit_and_miss(monkeypatch): manager = _build_manager() with ( @@ -139,7 +139,7 @@ def test_delete_tool_parameters_cache(): mock_delete.assert_called_once() -def test_configuration_manager_decrypt_suppresses_errors(): +def test_configuration_manager_decrypt_suppresses_errors(monkeypatch): manager = _build_manager() with ( patch.object(ToolParameterCache, "get", return_value=None), diff --git a/api/tests/unit_tests/core/tools/utils/test_message_transformer.py b/api/tests/unit_tests/core/tools/utils/test_message_transformer.py index af3cdddd5f8..6454a5bcd1f 100644 --- a/api/tests/unit_tests/core/tools/utils/test_message_transformer.py +++ b/api/tests/unit_tests/core/tools/utils/test_message_transformer.py @@ -84,3 +84,24 @@ def test_transform_tool_invoke_messages_mimetype_key_present_but_none(): # meta is preserved (still contains mime_type: None) assert "mime_type" in (o.meta or {}) assert o.meta["mime_type"] is None + assert o.meta["tool_file_id"] == "fake-tool-file-id" + + +def test_transform_tool_invoke_messages_parses_existing_tool_file_link_meta(): + msg = ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.IMAGE_LINK, + message=ToolInvokeMessage.TextMessage(text="/files/tools/existing-tool-file.png"), + meta={}, + ) + + out = list( + mt.ToolFileMessageTransformer.transform_tool_invoke_messages( + messages=_gen([msg]), + user_id="u1", + tenant_id="t1", + conversation_id="c1", + ) + ) + + assert len(out) == 1 + assert out[0].meta["tool_file_id"] == "existing-tool-file" diff --git a/api/tests/unit_tests/core/tools/utils/test_misc_utils_extra.py b/api/tests/unit_tests/core/tools/utils/test_misc_utils_extra.py index 4ce73272bf0..a93624123e2 100644 --- a/api/tests/unit_tests/core/tools/utils/test_misc_utils_extra.py +++ b/api/tests/unit_tests/core/tools/utils/test_misc_utils_extra.py @@ -263,7 +263,7 @@ def test_single_dataset_retriever_non_economy_run_sorts_context_and_resources(): ) db_session = Mock() db_session.scalar.side_effect = [dataset, lookup_doc_low, lookup_doc_high] - db_session.query.return_value.filter_by.return_value.first.return_value = dataset + db_session.get.return_value = dataset tool = SingleDatasetRetrieverTool( tenant_id="tenant-1", @@ -444,7 +444,7 @@ def test_multi_dataset_retriever_run_orders_segments_and_returns_resources(): ) db_session = Mock() db_session.scalars.return_value.all.return_value = [segment_for_node_2, segment_for_node_1] - db_session.query.return_value.filter_by.return_value.first.side_effect = [ + db_session.get.side_effect = [ SimpleNamespace(id="dataset-2", name="Dataset Two"), SimpleNamespace(id="dataset-1", name="Dataset One"), ] diff --git a/api/tests/unit_tests/core/tools/utils/test_model_invocation_utils.py b/api/tests/unit_tests/core/tools/utils/test_model_invocation_utils.py index 2acae889b24..52f262e1cf1 100644 --- a/api/tests/unit_tests/core/tools/utils/test_model_invocation_utils.py +++ b/api/tests/unit_tests/core/tools/utils/test_model_invocation_utils.py @@ -13,10 +13,8 @@ from types import SimpleNamespace from unittest.mock import Mock, patch import pytest - -from core.tools.utils.model_invocation_utils import InvokeModelError, ModelInvocationUtils -from dify_graph.model_runtime.entities.model_entities import ModelPropertyKey -from dify_graph.model_runtime.errors.invoke import ( +from graphon.model_runtime.entities.model_entities import ModelPropertyKey +from graphon.model_runtime.errors.invoke import ( InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError, @@ -24,6 +22,8 @@ from dify_graph.model_runtime.errors.invoke import ( InvokeServerUnavailableError, ) +from core.tools.utils.model_invocation_utils import InvokeModelError, ModelInvocationUtils + def _mock_model_instance(*, schema: dict | None = None) -> SimpleNamespace: model_type_instance = Mock() @@ -60,20 +60,23 @@ def test_get_max_llm_context_tokens_branches(model_instance, expected, error_mat manager = Mock() manager.get_default_model_instance.return_value = model_instance - with patch("core.tools.utils.model_invocation_utils.ModelManager", return_value=manager): + with patch("core.tools.utils.model_invocation_utils.ModelManager.for_tenant", return_value=manager) as mock_factory: if error_match: with pytest.raises(InvokeModelError, match=error_match): - ModelInvocationUtils.get_max_llm_context_tokens("tenant") + ModelInvocationUtils.get_max_llm_context_tokens("tenant", user_id="user-1") else: - assert ModelInvocationUtils.get_max_llm_context_tokens("tenant") == expected + assert ModelInvocationUtils.get_max_llm_context_tokens("tenant", user_id="user-1") == expected + + mock_factory.assert_called_once_with(tenant_id="tenant", user_id="user-1") def test_calculate_tokens_handles_missing_model(): manager = Mock() manager.get_default_model_instance.return_value = None - with patch("core.tools.utils.model_invocation_utils.ModelManager", return_value=manager): + with patch("core.tools.utils.model_invocation_utils.ModelManager.for_tenant", return_value=manager) as mock_factory: with pytest.raises(InvokeModelError, match="Model not found"): ModelInvocationUtils.calculate_tokens("tenant", []) + mock_factory.assert_called_once_with(tenant_id="tenant", user_id=None) def test_invoke_success_and_error_mappings(): @@ -98,7 +101,7 @@ def test_invoke_success_and_error_mappings(): db_mock = SimpleNamespace(session=Mock()) - with patch("core.tools.utils.model_invocation_utils.ModelManager", return_value=manager): + with patch("core.tools.utils.model_invocation_utils.ModelManager.for_tenant", return_value=manager) as mock_factory: with patch("core.tools.utils.model_invocation_utils.ToolModelInvoke", _ToolModelInvoke): with patch("core.tools.utils.model_invocation_utils.db", db_mock): response = ModelInvocationUtils.invoke( @@ -107,11 +110,13 @@ def test_invoke_success_and_error_mappings(): tool_type="builtin", tool_name="tool-a", prompt_messages=[], + caller_user_id="caller-1", ) assert response.message.content == "ok" assert db_mock.session.add.call_count == 1 assert db_mock.session.commit.call_count == 2 + mock_factory.assert_called_once_with(tenant_id="tenant", user_id="caller-1") @pytest.mark.parametrize( @@ -145,7 +150,7 @@ def test_invoke_error_mappings(exc, expected): db_mock = SimpleNamespace(session=Mock()) - with patch("core.tools.utils.model_invocation_utils.ModelManager", return_value=manager): + with patch("core.tools.utils.model_invocation_utils.ModelManager.for_tenant", return_value=manager) as mock_factory: with patch("core.tools.utils.model_invocation_utils.ToolModelInvoke", _ToolModelInvoke): with patch("core.tools.utils.model_invocation_utils.db", db_mock): with pytest.raises(InvokeModelError, match=expected): @@ -156,3 +161,4 @@ def test_invoke_error_mappings(exc, expected): tool_name="tool-a", prompt_messages=[], ) + mock_factory.assert_called_once_with(tenant_id="tenant", user_id="u1") diff --git a/api/tests/unit_tests/core/tools/utils/test_workflow_configuration_sync.py b/api/tests/unit_tests/core/tools/utils/test_workflow_configuration_sync.py index dd79b797186..0e3a7e623a8 100644 --- a/api/tests/unit_tests/core/tools/utils/test_workflow_configuration_sync.py +++ b/api/tests/unit_tests/core/tools/utils/test_workflow_configuration_sync.py @@ -1,9 +1,9 @@ import pytest +from graphon.variables.input_entities import VariableEntity, VariableEntityType from core.tools.entities.tool_entities import ToolParameter, WorkflowToolParameterConfiguration from core.tools.errors import WorkflowToolHumanInputNotSupportedError from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils -from dify_graph.variables.input_entities import VariableEntity, VariableEntityType def test_ensure_no_human_input_nodes_passes_for_non_human_input(): diff --git a/api/tests/unit_tests/core/tools/workflow_as_tool/test_provider.py b/api/tests/unit_tests/core/tools/workflow_as_tool/test_provider.py index dd140cbb276..2607861b59d 100644 --- a/api/tests/unit_tests/core/tools/workflow_as_tool/test_provider.py +++ b/api/tests/unit_tests/core/tools/workflow_as_tool/test_provider.py @@ -4,6 +4,7 @@ from types import SimpleNamespace from unittest.mock import MagicMock, Mock, patch import pytest +from graphon.variables.input_entities import VariableEntity, VariableEntityType from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ( @@ -13,7 +14,6 @@ from core.tools.entities.tool_entities import ( ToolProviderType, ) from core.tools.workflow_as_tool.provider import WorkflowToolProviderController -from dify_graph.variables.input_entities import VariableEntity, VariableEntityType def _controller() -> WorkflowToolProviderController: diff --git a/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py b/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py index cc00f796980..c20edd74004 100644 --- a/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py +++ b/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py @@ -11,6 +11,7 @@ from typing import Any from unittest.mock import MagicMock, Mock, patch import pytest +from graphon.file import FILE_MODEL_IDENTITY, FileTransferMethod, FileType from core.app.entities.app_invoke_entities import InvokeFrom from core.tools.__base.tool_runtime import ToolRuntime @@ -24,7 +25,6 @@ from core.tools.entities.tool_entities import ( ) from core.tools.errors import ToolInvokeError from core.tools.workflow_as_tool.tool import WorkflowTool -from dify_graph.file import FILE_MODEL_IDENTITY class StubScalars: @@ -439,6 +439,32 @@ def _setup_transform_args_tool(monkeypatch: pytest.MonkeyPatch) -> WorkflowTool: def test_transform_args_valid_files(monkeypatch: pytest.MonkeyPatch): """Transform args into parameters and files payloads.""" tool = _setup_transform_args_tool(monkeypatch) + build_file_from_stored_mapping = MagicMock( + side_effect=[ + SimpleNamespace( + transfer_method=FileTransferMethod.TOOL_FILE, + type=FileType.IMAGE, + reference="tool-1", + generate_url=lambda: None, + ), + SimpleNamespace( + transfer_method=FileTransferMethod.LOCAL_FILE, + type=FileType.DOCUMENT, + reference="upload-1", + generate_url=lambda: None, + ), + SimpleNamespace( + transfer_method=FileTransferMethod.REMOTE_URL, + type=FileType.DOCUMENT, + reference=None, + generate_url=lambda: "https://example.com/a.pdf", + ), + ] + ) + monkeypatch.setattr( + "core.tools.workflow_as_tool.tool.build_file_from_stored_mapping", + build_file_from_stored_mapping, + ) params, files = tool._transform_args( { @@ -470,6 +496,8 @@ def test_transform_args_valid_files(monkeypatch: pytest.MonkeyPatch): assert any(file_item.get("tool_file_id") == "tool-1" for file_item in files) assert any(file_item.get("upload_file_id") == "upload-1" for file_item in files) assert any(file_item.get("url") == "https://example.com/a.pdf" for file_item in files) + assert build_file_from_stored_mapping.call_count == 3 + assert all(call.kwargs["tenant_id"] == "test_tool" for call in build_file_from_stored_mapping.call_args_list) def test_transform_args_invalid_files(monkeypatch: pytest.MonkeyPatch): diff --git a/api/tests/unit_tests/core/trigger/debug/test_debug_event_selectors.py b/api/tests/unit_tests/core/trigger/debug/test_debug_event_selectors.py index bcb1d745e3a..78622b78b6b 100644 --- a/api/tests/unit_tests/core/trigger/debug/test_debug_event_selectors.py +++ b/api/tests/unit_tests/core/trigger/debug/test_debug_event_selectors.py @@ -11,6 +11,7 @@ from datetime import datetime from unittest.mock import MagicMock, patch import pytest +from graphon.enums import BuiltinNodeTypes, NodeType from core.plugin.entities.request import TriggerInvokeEventResponse from core.trigger.constants import ( @@ -26,7 +27,6 @@ from core.trigger.debug.event_selectors import ( select_trigger_debug_events, ) from core.trigger.debug.events import PluginTriggerDebugEvent, WebhookDebugEvent -from dify_graph.enums import BuiltinNodeTypes, NodeType from tests.unit_tests.core.trigger.conftest import VALID_PROVIDER_ID diff --git a/api/tests/unit_tests/core/variables/test_segment.py b/api/tests/unit_tests/core/variables/test_segment.py index 91259c9a454..7406b88270b 100644 --- a/api/tests/unit_tests/core/variables/test_segment.py +++ b/api/tests/unit_tests/core/variables/test_segment.py @@ -2,14 +2,10 @@ import dataclasses import orjson import pytest -from pydantic import BaseModel - -from core.helper import encrypter -from dify_graph.file import File, FileTransferMethod, FileType -from dify_graph.runtime import VariablePool -from dify_graph.system_variable import SystemVariable -from dify_graph.variables.segment_group import SegmentGroup -from dify_graph.variables.segments import ( +from graphon.file import File, FileTransferMethod, FileType +from graphon.runtime import VariablePool +from graphon.variables.segment_group import SegmentGroup +from graphon.variables.segments import ( ArrayAnySegment, ArrayFileSegment, ArrayNumberSegment, @@ -25,13 +21,13 @@ from dify_graph.variables.segments import ( StringSegment, get_segment_discriminator, ) -from dify_graph.variables.types import SegmentType -from dify_graph.variables.utils import ( +from graphon.variables.types import SegmentType +from graphon.variables.utils import ( dumps_with_segments, segment_orjson_default, to_selector, ) -from dify_graph.variables.variables import ( +from graphon.variables.variables import ( ArrayAnyVariable, ArrayFileVariable, ArrayNumberVariable, @@ -46,16 +42,35 @@ from dify_graph.variables.variables import ( StringVariable, Variable, ) +from pydantic import BaseModel + +from core.helper import encrypter +from core.workflow.system_variables import build_bootstrap_variables, build_system_variables +from core.workflow.variable_pool_initializer import add_variables_to_pool + + +def _build_variable_pool( + *, + system_variables: list[Variable] | None = None, + environment_variables: list[Variable] | None = None, +) -> VariablePool: + variable_pool = VariablePool() + add_variables_to_pool( + variable_pool, + build_bootstrap_variables( + system_variables=system_variables or [], + environment_variables=environment_variables or [], + ), + ) + return variable_pool def test_segment_group_to_text(): - variable_pool = VariablePool( - system_variables=SystemVariable(user_id="fake-user-id"), - user_inputs={}, + variable_pool = _build_variable_pool( + system_variables=build_system_variables(user_id="fake-user-id"), environment_variables=[ SecretVariable(name="secret_key", value="fake-secret-key"), ], - conversation_variables=[], ) variable_pool.add(("node_id", "custom_query"), "fake-user-query") template = ( @@ -71,11 +86,8 @@ def test_segment_group_to_text(): def test_convert_constant_to_segment_group(): - variable_pool = VariablePool( - system_variables=SystemVariable(user_id="1", app_id="1", workflow_id="1"), - user_inputs={}, - environment_variables=[], - conversation_variables=[], + variable_pool = _build_variable_pool( + system_variables=build_system_variables(user_id="1", app_id="1", workflow_id="1"), ) template = "Hello, world!" segments_group = variable_pool.convert_template(template) @@ -84,12 +96,7 @@ def test_convert_constant_to_segment_group(): def test_convert_variable_to_segment_group(): - variable_pool = VariablePool( - system_variables=SystemVariable(user_id="fake-user-id"), - user_inputs={}, - environment_variables=[], - conversation_variables=[], - ) + variable_pool = _build_variable_pool(system_variables=build_system_variables(user_id="fake-user-id")) template = "{{#sys.user_id#}}" segments_group = variable_pool.convert_template(template) assert segments_group.text == "fake-user-id" @@ -116,7 +123,6 @@ def create_test_file( ) -> File: """Factory function to create File objects for testing""" return File( - tenant_id="test-tenant", type=file_type, transfer_method=transfer_method, filename=filename, @@ -190,7 +196,6 @@ class TestSegmentDumpAndLoad: loaded_file = loaded_segment.value assert isinstance(orig_file, File) assert isinstance(loaded_file, File) - assert loaded_file.tenant_id == orig_file.tenant_id assert loaded_file.type == orig_file.type assert loaded_file.filename == orig_file.filename else: @@ -234,7 +239,6 @@ class TestSegmentDumpAndLoad: loaded_file = loaded_variable.value assert isinstance(orig_file, File) assert isinstance(loaded_file, File) - assert loaded_file.tenant_id == orig_file.tenant_id assert loaded_file.type == orig_file.type assert loaded_file.filename == orig_file.filename else: diff --git a/api/tests/unit_tests/core/variables/test_segment_type.py b/api/tests/unit_tests/core/variables/test_segment_type.py index bb234d9bbd4..37ecd2890bb 100644 --- a/api/tests/unit_tests/core/variables/test_segment_type.py +++ b/api/tests/unit_tests/core/variables/test_segment_type.py @@ -1,8 +1,7 @@ import pytest - -from dify_graph.variables.segment_group import SegmentGroup -from dify_graph.variables.segments import StringSegment -from dify_graph.variables.types import ArrayValidation, SegmentType +from graphon.variables.segment_group import SegmentGroup +from graphon.variables.segments import StringSegment +from graphon.variables.types import ArrayValidation, SegmentType class TestSegmentTypeIsArrayType: diff --git a/api/tests/unit_tests/core/variables/test_segment_type_validation.py b/api/tests/unit_tests/core/variables/test_segment_type_validation.py index 41ce4834476..09254e17a30 100644 --- a/api/tests/unit_tests/core/variables/test_segment_type_validation.py +++ b/api/tests/unit_tests/core/variables/test_segment_type_validation.py @@ -9,11 +9,9 @@ from dataclasses import dataclass from typing import Any import pytest - -from dify_graph.file.enums import FileTransferMethod, FileType -from dify_graph.file.models import File -from dify_graph.variables.segment_group import SegmentGroup -from dify_graph.variables.segments import ( +from graphon.file import File, FileTransferMethod, FileType +from graphon.variables.segment_group import SegmentGroup +from graphon.variables.segments import ( ArrayFileSegment, BooleanSegment, FileSegment, @@ -22,7 +20,7 @@ from dify_graph.variables.segments import ( ObjectSegment, StringSegment, ) -from dify_graph.variables.types import ArrayValidation, SegmentType +from graphon.variables.types import ArrayValidation, SegmentType def create_test_file( diff --git a/api/tests/unit_tests/core/variables/test_variables.py b/api/tests/unit_tests/core/variables/test_variables.py index dd0fe2e65a7..75b01bf42e9 100644 --- a/api/tests/unit_tests/core/variables/test_variables.py +++ b/api/tests/unit_tests/core/variables/test_variables.py @@ -1,7 +1,5 @@ import pytest -from pydantic import ValidationError - -from dify_graph.variables import ( +from graphon.variables import ( ArrayFileVariable, ArrayVariable, FloatVariable, @@ -11,7 +9,8 @@ from dify_graph.variables import ( SegmentType, StringVariable, ) -from dify_graph.variables.variables import VariableBase +from graphon.variables.variables import VariableBase +from pydantic import ValidationError def test_frozen_variables(): diff --git a/api/tests/unit_tests/core/workflow/context/test_execution_context.py b/api/tests/unit_tests/core/workflow/context/test_execution_context.py index d09b8397c3b..3ce4bb753b9 100644 --- a/api/tests/unit_tests/core/workflow/context/test_execution_context.py +++ b/api/tests/unit_tests/core/workflow/context/test_execution_context.py @@ -9,7 +9,7 @@ from unittest.mock import MagicMock import pytest from pydantic import BaseModel -from dify_graph.context.execution_context import ( +from context.execution_context import ( AppContext, ExecutionContext, ExecutionContextBuilder, @@ -286,7 +286,7 @@ class TestCaptureCurrentContext: def test_capture_current_context_returns_context(self): """Test that capture_current_context returns a valid context.""" - from dify_graph.context.execution_context import capture_current_context + from context.execution_context import capture_current_context result = capture_current_context() @@ -303,7 +303,7 @@ class TestCaptureCurrentContext: test_var = contextvars.ContextVar("capture_test_var") test_var.set("test_value_123") - from dify_graph.context.execution_context import capture_current_context + from context.execution_context import capture_current_context result = capture_current_context() @@ -313,12 +313,12 @@ class TestCaptureCurrentContext: class TestTenantScopedContextRegistry: def setup_method(self): - from dify_graph.context import reset_context_provider + from context import reset_context_provider reset_context_provider() def teardown_method(self): - from dify_graph.context import reset_context_provider + from context import reset_context_provider reset_context_provider() @@ -333,7 +333,7 @@ class TestTenantScopedContextRegistry: assert read_context("workflow.sandbox", tenant_id="t2").base_url == "http://t2" def test_missing_provider_raises_keyerror(self): - from dify_graph.context import ContextProviderNotFoundError + from context import ContextProviderNotFoundError with pytest.raises(ContextProviderNotFoundError): read_context("missing", tenant_id="unknown") diff --git a/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py b/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py deleted file mode 100644 index 22792eb5b3a..00000000000 --- a/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py +++ /dev/null @@ -1,296 +0,0 @@ -import json -from time import time -from unittest.mock import MagicMock, patch - -import pytest - -from dify_graph.constants import CONVERSATION_VARIABLE_NODE_ID -from dify_graph.model_runtime.entities.llm_entities import LLMUsage -from dify_graph.runtime import GraphRuntimeState, ReadOnlyGraphRuntimeStateWrapper, VariablePool -from dify_graph.variables.variables import StringVariable - - -class StubCoordinator: - def __init__(self) -> None: - self.state = "initial" - - def dumps(self) -> str: - return json.dumps({"state": self.state}) - - def loads(self, data: str) -> None: - payload = json.loads(data) - self.state = payload["state"] - - -class TestGraphRuntimeState: - def test_property_getters_and_setters(self): - # FIXME(-LAN-): Mock VariablePool if needed - variable_pool = VariablePool() - start_time = time() - - state = GraphRuntimeState(variable_pool=variable_pool, start_at=start_time) - - # Test variable_pool property (read-only) - assert state.variable_pool == variable_pool - - # Test start_at property - assert state.start_at == start_time - new_time = time() + 100 - state.start_at = new_time - assert state.start_at == new_time - - # Test total_tokens property - assert state.total_tokens == 0 - state.total_tokens = 100 - assert state.total_tokens == 100 - - # Test node_run_steps property - assert state.node_run_steps == 0 - state.node_run_steps = 5 - assert state.node_run_steps == 5 - - def test_outputs_immutability(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - # Test that getting outputs returns a copy - outputs1 = state.outputs - outputs2 = state.outputs - assert outputs1 == outputs2 - assert outputs1 is not outputs2 # Different objects - - # Test that modifying retrieved outputs doesn't affect internal state - outputs = state.outputs - outputs["test"] = "value" - assert "test" not in state.outputs - - # Test set_output method - state.set_output("key1", "value1") - assert state.get_output("key1") == "value1" - - # Test update_outputs method - state.update_outputs({"key2": "value2", "key3": "value3"}) - assert state.get_output("key2") == "value2" - assert state.get_output("key3") == "value3" - - def test_llm_usage_immutability(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - # Test that getting llm_usage returns a copy - usage1 = state.llm_usage - usage2 = state.llm_usage - assert usage1 is not usage2 # Different objects - - def test_type_validation(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - # Test total_tokens validation - with pytest.raises(ValueError): - state.total_tokens = -1 - - # Test node_run_steps validation - with pytest.raises(ValueError): - state.node_run_steps = -1 - - def test_helper_methods(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - # Test increment_node_run_steps - initial_steps = state.node_run_steps - state.increment_node_run_steps() - assert state.node_run_steps == initial_steps + 1 - - # Test add_tokens - initial_tokens = state.total_tokens - state.add_tokens(50) - assert state.total_tokens == initial_tokens + 50 - - # Test add_tokens validation - with pytest.raises(ValueError): - state.add_tokens(-1) - - def test_ready_queue_default_instantiation(self): - state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time()) - - queue = state.ready_queue - - from dify_graph.graph_engine.ready_queue import InMemoryReadyQueue - - assert isinstance(queue, InMemoryReadyQueue) - - def test_graph_execution_lazy_instantiation(self): - state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time()) - - execution = state.graph_execution - - from dify_graph.graph_engine.domain.graph_execution import GraphExecution - - assert isinstance(execution, GraphExecution) - assert execution.workflow_id == "" - assert state.graph_execution is execution - - def test_response_coordinator_configuration(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - with pytest.raises(ValueError): - _ = state.response_coordinator - - mock_graph = MagicMock() - with patch( - "dify_graph.graph_engine.response_coordinator.ResponseStreamCoordinator", autospec=True - ) as coordinator_cls: - coordinator_instance = coordinator_cls.return_value - state.configure(graph=mock_graph) - - assert state.response_coordinator is coordinator_instance - coordinator_cls.assert_called_once_with(variable_pool=variable_pool, graph=mock_graph) - - # Configure again with same graph should be idempotent - state.configure(graph=mock_graph) - - other_graph = MagicMock() - with pytest.raises(ValueError): - state.attach_graph(other_graph) - - def test_read_only_wrapper_exposes_additional_state(self): - state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time()) - state.configure() - - wrapper = ReadOnlyGraphRuntimeStateWrapper(state) - - assert wrapper.ready_queue_size == 0 - assert wrapper.exceptions_count == 0 - - def test_read_only_wrapper_serializes_runtime_state(self): - state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time()) - state.total_tokens = 5 - state.set_output("result", {"success": True}) - state.ready_queue.put("node-1") - - wrapper = ReadOnlyGraphRuntimeStateWrapper(state) - - wrapper_snapshot = json.loads(wrapper.dumps()) - state_snapshot = json.loads(state.dumps()) - - assert wrapper_snapshot == state_snapshot - - def test_dumps_and_loads_roundtrip_with_response_coordinator(self): - variable_pool = VariablePool() - variable_pool.add(("node1", "value"), "payload") - - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - state.total_tokens = 10 - state.node_run_steps = 3 - state.set_output("final", {"result": True}) - usage = LLMUsage.from_metadata( - { - "prompt_tokens": 2, - "completion_tokens": 3, - "total_tokens": 5, - "total_price": "1.23", - "currency": "USD", - "latency": 0.5, - } - ) - state.llm_usage = usage - state.ready_queue.put("node-A") - - graph_execution = state.graph_execution - graph_execution.workflow_id = "wf-123" - graph_execution.exceptions_count = 4 - graph_execution.started = True - - mock_graph = MagicMock() - stub = StubCoordinator() - with patch.object(GraphRuntimeState, "_build_response_coordinator", return_value=stub, autospec=True): - state.attach_graph(mock_graph) - - stub.state = "configured" - - snapshot = state.dumps() - - restored = GraphRuntimeState.from_snapshot(snapshot) - - assert restored.total_tokens == 10 - assert restored.node_run_steps == 3 - assert restored.get_output("final") == {"result": True} - assert restored.llm_usage.total_tokens == usage.total_tokens - assert restored.ready_queue.qsize() == 1 - assert restored.ready_queue.get(timeout=0.01) == "node-A" - - restored_segment = restored.variable_pool.get(("node1", "value")) - assert restored_segment is not None - assert restored_segment.value == "payload" - - restored_execution = restored.graph_execution - assert restored_execution.workflow_id == "wf-123" - assert restored_execution.exceptions_count == 4 - assert restored_execution.started is True - - new_stub = StubCoordinator() - with patch.object(GraphRuntimeState, "_build_response_coordinator", return_value=new_stub, autospec=True): - restored.attach_graph(mock_graph) - - assert new_stub.state == "configured" - - def test_loads_rehydrates_existing_instance(self): - variable_pool = VariablePool() - variable_pool.add(("node", "key"), "value") - - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - state.total_tokens = 7 - state.node_run_steps = 2 - state.set_output("foo", "bar") - state.ready_queue.put("node-1") - - execution = state.graph_execution - execution.workflow_id = "wf-456" - execution.started = True - - mock_graph = MagicMock() - original_stub = StubCoordinator() - with patch.object(GraphRuntimeState, "_build_response_coordinator", return_value=original_stub, autospec=True): - state.attach_graph(mock_graph) - - original_stub.state = "configured" - snapshot = state.dumps() - - new_stub = StubCoordinator() - with patch.object(GraphRuntimeState, "_build_response_coordinator", return_value=new_stub, autospec=True): - restored = GraphRuntimeState(variable_pool=VariablePool(), start_at=0.0) - restored.attach_graph(mock_graph) - restored.loads(snapshot) - - assert restored.total_tokens == 7 - assert restored.node_run_steps == 2 - assert restored.get_output("foo") == "bar" - assert restored.ready_queue.qsize() == 1 - assert restored.ready_queue.get(timeout=0.01) == "node-1" - - restored_segment = restored.variable_pool.get(("node", "key")) - assert restored_segment is not None - assert restored_segment.value == "value" - - restored_execution = restored.graph_execution - assert restored_execution.workflow_id == "wf-456" - assert restored_execution.started is True - - assert new_stub.state == "configured" - - def test_snapshot_restore_preserves_updated_conversation_variable(self): - variable_pool = VariablePool( - conversation_variables=[StringVariable(name="session_name", value="before")], - ) - variable_pool.add((CONVERSATION_VARIABLE_NODE_ID, "session_name"), "after") - - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - snapshot = state.dumps() - restored = GraphRuntimeState.from_snapshot(snapshot) - - restored_value = restored.variable_pool.get((CONVERSATION_VARIABLE_NODE_ID, "session_name")) - assert restored_value is not None - assert restored_value.value == "after" diff --git a/api/tests/unit_tests/core/workflow/entities/test_pause_reason.py b/api/tests/unit_tests/core/workflow/entities/test_pause_reason.py deleted file mode 100644 index 158f7018b51..00000000000 --- a/api/tests/unit_tests/core/workflow/entities/test_pause_reason.py +++ /dev/null @@ -1,88 +0,0 @@ -""" -Tests for PauseReason discriminated union serialization/deserialization. -""" - -import pytest -from pydantic import BaseModel, ValidationError - -from dify_graph.entities.pause_reason import ( - HumanInputRequired, - PauseReason, - SchedulingPause, -) - - -class _Holder(BaseModel): - """Helper model that embeds PauseReason for union tests.""" - - reason: PauseReason - - -class TestPauseReasonDiscriminator: - """Test suite for PauseReason union discriminator.""" - - @pytest.mark.parametrize( - ("dict_value", "expected"), - [ - pytest.param( - { - "reason": { - "TYPE": "human_input_required", - "form_id": "form_id", - "form_content": "form_content", - "node_id": "node_id", - "node_title": "node_title", - }, - }, - HumanInputRequired( - form_id="form_id", - form_content="form_content", - node_id="node_id", - node_title="node_title", - ), - id="HumanInputRequired", - ), - pytest.param( - { - "reason": { - "TYPE": "scheduled_pause", - "message": "Hold on", - } - }, - SchedulingPause(message="Hold on"), - id="SchedulingPause", - ), - ], - ) - def test_model_validate(self, dict_value, expected): - """Ensure scheduled pause payloads with lowercase TYPE deserialize.""" - holder = _Holder.model_validate(dict_value) - - assert type(holder.reason) == type(expected) - assert holder.reason == expected - - @pytest.mark.parametrize( - "reason", - [ - HumanInputRequired( - form_id="form_id", - form_content="form_content", - node_id="node_id", - node_title="node_title", - ), - SchedulingPause(message="Hold on"), - ], - ids=lambda x: type(x).__name__, - ) - def test_model_construct(self, reason): - holder = _Holder(reason=reason) - assert holder.reason == reason - - def test_model_construct_with_invalid_type(self): - with pytest.raises(ValidationError): - holder = _Holder(reason=object()) # type: ignore - - def test_unknown_type_fails_validation(self): - """Unknown TYPE values should raise a validation error.""" - with pytest.raises(ValidationError): - _Holder.model_validate({"reason": {"TYPE": "UNKNOWN"}}) diff --git a/api/tests/unit_tests/core/workflow/entities/test_template.py b/api/tests/unit_tests/core/workflow/entities/test_template.py deleted file mode 100644 index 2d4c7f7b77e..00000000000 --- a/api/tests/unit_tests/core/workflow/entities/test_template.py +++ /dev/null @@ -1,87 +0,0 @@ -"""Tests for template module.""" - -from dify_graph.nodes.base.template import Template, TextSegment, VariableSegment - - -class TestTemplate: - """Test Template class functionality.""" - - def test_from_answer_template_simple(self): - """Test parsing a simple answer template.""" - template_str = "Hello, {{#node1.name#}}!" - template = Template.from_answer_template(template_str) - - assert len(template.segments) == 3 - assert isinstance(template.segments[0], TextSegment) - assert template.segments[0].text == "Hello, " - assert isinstance(template.segments[1], VariableSegment) - assert template.segments[1].selector == ["node1", "name"] - assert isinstance(template.segments[2], TextSegment) - assert template.segments[2].text == "!" - - def test_from_answer_template_multiple_vars(self): - """Test parsing an answer template with multiple variables.""" - template_str = "Hello {{#node1.name#}}, your age is {{#node2.age#}}." - template = Template.from_answer_template(template_str) - - assert len(template.segments) == 5 - assert isinstance(template.segments[0], TextSegment) - assert template.segments[0].text == "Hello " - assert isinstance(template.segments[1], VariableSegment) - assert template.segments[1].selector == ["node1", "name"] - assert isinstance(template.segments[2], TextSegment) - assert template.segments[2].text == ", your age is " - assert isinstance(template.segments[3], VariableSegment) - assert template.segments[3].selector == ["node2", "age"] - assert isinstance(template.segments[4], TextSegment) - assert template.segments[4].text == "." - - def test_from_answer_template_no_vars(self): - """Test parsing an answer template with no variables.""" - template_str = "Hello, world!" - template = Template.from_answer_template(template_str) - - assert len(template.segments) == 1 - assert isinstance(template.segments[0], TextSegment) - assert template.segments[0].text == "Hello, world!" - - def test_from_end_outputs_single(self): - """Test creating template from End node outputs with single variable.""" - outputs_config = [{"variable": "text", "value_selector": ["node1", "text"]}] - template = Template.from_end_outputs(outputs_config) - - assert len(template.segments) == 1 - assert isinstance(template.segments[0], VariableSegment) - assert template.segments[0].selector == ["node1", "text"] - - def test_from_end_outputs_multiple(self): - """Test creating template from End node outputs with multiple variables.""" - outputs_config = [ - {"variable": "text", "value_selector": ["node1", "text"]}, - {"variable": "result", "value_selector": ["node2", "result"]}, - ] - template = Template.from_end_outputs(outputs_config) - - assert len(template.segments) == 3 - assert isinstance(template.segments[0], VariableSegment) - assert template.segments[0].selector == ["node1", "text"] - assert template.segments[0].variable_name == "text" - assert isinstance(template.segments[1], TextSegment) - assert template.segments[1].text == "\n" - assert isinstance(template.segments[2], VariableSegment) - assert template.segments[2].selector == ["node2", "result"] - assert template.segments[2].variable_name == "result" - - def test_from_end_outputs_empty(self): - """Test creating template from empty End node outputs.""" - outputs_config = [] - template = Template.from_end_outputs(outputs_config) - - assert len(template.segments) == 0 - - def test_template_str_representation(self): - """Test string representation of template.""" - template_str = "Hello, {{#node1.name#}}!" - template = Template.from_answer_template(template_str) - - assert str(template) == template_str diff --git a/api/tests/unit_tests/core/workflow/entities/test_variable_pool.py b/api/tests/unit_tests/core/workflow/entities/test_variable_pool.py deleted file mode 100644 index 6100ebede51..00000000000 --- a/api/tests/unit_tests/core/workflow/entities/test_variable_pool.py +++ /dev/null @@ -1,136 +0,0 @@ -from dify_graph.runtime import VariablePool -from dify_graph.variables.segments import ( - BooleanSegment, - IntegerSegment, - NoneSegment, - StringSegment, -) - - -class TestVariablePoolGetAndNestedAttribute: - # - # _get_nested_attribute tests - # - def test__get_nested_attribute_existing_key(self): - pool = VariablePool.empty() - obj = {"a": 123} - segment = pool._get_nested_attribute(obj, "a") - assert segment is not None - assert segment.value == 123 - - def test__get_nested_attribute_missing_key(self): - pool = VariablePool.empty() - obj = {"a": 123} - segment = pool._get_nested_attribute(obj, "b") - assert segment is None - - def test__get_nested_attribute_non_dict(self): - pool = VariablePool.empty() - obj = ["not", "a", "dict"] - segment = pool._get_nested_attribute(obj, "a") - assert segment is None - - def test__get_nested_attribute_with_none_value(self): - pool = VariablePool.empty() - obj = {"a": None} - segment = pool._get_nested_attribute(obj, "a") - assert segment is not None - assert isinstance(segment, NoneSegment) - - def test__get_nested_attribute_with_empty_string(self): - pool = VariablePool.empty() - obj = {"a": ""} - segment = pool._get_nested_attribute(obj, "a") - assert segment is not None - assert isinstance(segment, StringSegment) - assert segment.value == "" - - # - # get tests - # - def test_get_simple_variable(self): - pool = VariablePool.empty() - pool.add(("node1", "var1"), "value1") - segment = pool.get(("node1", "var1")) - assert segment is not None - assert segment.value == "value1" - - def test_get_missing_variable(self): - pool = VariablePool.empty() - result = pool.get(("node1", "unknown")) - assert result is None - - def test_get_with_too_short_selector(self): - pool = VariablePool.empty() - result = pool.get(("only_node",)) - assert result is None - - def test_get_nested_object_attribute(self): - pool = VariablePool.empty() - obj_value = {"inner": "hello"} - pool.add(("node1", "obj"), obj_value) - - # simulate selector with nested attr - segment = pool.get(("node1", "obj", "inner")) - assert segment is not None - assert segment.value == "hello" - - def test_get_nested_object_missing_attribute(self): - pool = VariablePool.empty() - obj_value = {"inner": "hello"} - pool.add(("node1", "obj"), obj_value) - - result = pool.get(("node1", "obj", "not_exist")) - assert result is None - - def test_get_nested_object_attribute_with_falsy_values(self): - pool = VariablePool.empty() - obj_value = { - "inner_none": None, - "inner_empty": "", - "inner_zero": 0, - "inner_false": False, - } - pool.add(("node1", "obj"), obj_value) - - segment_none = pool.get(("node1", "obj", "inner_none")) - assert segment_none is not None - assert isinstance(segment_none, NoneSegment) - - segment_empty = pool.get(("node1", "obj", "inner_empty")) - assert segment_empty is not None - assert isinstance(segment_empty, StringSegment) - assert segment_empty.value == "" - - segment_zero = pool.get(("node1", "obj", "inner_zero")) - assert segment_zero is not None - assert isinstance(segment_zero, IntegerSegment) - assert segment_zero.value == 0 - - segment_false = pool.get(("node1", "obj", "inner_false")) - assert segment_false is not None - assert isinstance(segment_false, BooleanSegment) - assert segment_false.value is False - - -class TestVariablePoolGetNotModifyVariableDictionary: - _NODE_ID = "start" - _VAR_NAME = "name" - - def test_convert_to_template_should_not_introduce_extra_keys(self): - pool = VariablePool.empty() - pool.add([self._NODE_ID, self._VAR_NAME], 0) - pool.convert_template("The start.name is {{#start.name#}}") - assert "The start" not in pool.variable_dictionary - - def test_get_should_not_modify_variable_dictionary(self): - pool = VariablePool.empty() - pool.get([self._NODE_ID, self._VAR_NAME]) - assert len(pool.variable_dictionary) == 1 # only contains `sys` node id - assert "start" not in pool.variable_dictionary - - pool = VariablePool.empty() - pool.add([self._NODE_ID, self._VAR_NAME], "Joe") - pool.get([self._NODE_ID, "count"]) - start_subdict = pool.variable_dictionary[self._NODE_ID] - assert "count" not in start_subdict diff --git a/api/tests/unit_tests/core/workflow/entities/test_workflow_node_execution.py b/api/tests/unit_tests/core/workflow/entities/test_workflow_node_execution.py deleted file mode 100644 index 216e64db8d9..00000000000 --- a/api/tests/unit_tests/core/workflow/entities/test_workflow_node_execution.py +++ /dev/null @@ -1,225 +0,0 @@ -""" -Unit tests for WorkflowNodeExecution domain model, focusing on process_data truncation functionality. -""" - -from dataclasses import dataclass -from datetime import datetime -from typing import Any - -import pytest - -from dify_graph.entities.workflow_node_execution import WorkflowNodeExecution -from dify_graph.enums import BuiltinNodeTypes - - -class TestWorkflowNodeExecutionProcessDataTruncation: - """Test process_data truncation functionality in WorkflowNodeExecution domain model.""" - - def create_workflow_node_execution( - self, - process_data: dict[str, Any] | None = None, - ) -> WorkflowNodeExecution: - """Create a WorkflowNodeExecution instance for testing.""" - return WorkflowNodeExecution( - id="test-execution-id", - workflow_id="test-workflow-id", - index=1, - node_id="test-node-id", - node_type=BuiltinNodeTypes.LLM, - title="Test Node", - process_data=process_data, - created_at=datetime.now(), - ) - - def test_initial_process_data_truncated_state(self): - """Test that process_data_truncated returns False initially.""" - execution = self.create_workflow_node_execution() - - assert execution.process_data_truncated is False - assert execution.get_truncated_process_data() is None - - def test_set_and_get_truncated_process_data(self): - """Test setting and getting truncated process_data.""" - execution = self.create_workflow_node_execution() - test_truncated_data = {"truncated": True, "key": "value"} - - execution.set_truncated_process_data(test_truncated_data) - - assert execution.process_data_truncated is True - assert execution.get_truncated_process_data() == test_truncated_data - - def test_set_truncated_process_data_to_none(self): - """Test setting truncated process_data to None.""" - execution = self.create_workflow_node_execution() - - # First set some data - execution.set_truncated_process_data({"key": "value"}) - assert execution.process_data_truncated is True - - # Then set to None - execution.set_truncated_process_data(None) - assert execution.process_data_truncated is False - assert execution.get_truncated_process_data() is None - - def test_get_response_process_data_with_no_truncation(self): - """Test get_response_process_data when no truncation is set.""" - original_data = {"original": True, "data": "value"} - execution = self.create_workflow_node_execution(process_data=original_data) - - response_data = execution.get_response_process_data() - - assert response_data == original_data - assert execution.process_data_truncated is False - - def test_get_response_process_data_with_truncation(self): - """Test get_response_process_data when truncation is set.""" - original_data = {"original": True, "large_data": "x" * 10000} - truncated_data = {"original": True, "large_data": "[TRUNCATED]"} - - execution = self.create_workflow_node_execution(process_data=original_data) - execution.set_truncated_process_data(truncated_data) - - response_data = execution.get_response_process_data() - - # Should return truncated data, not original - assert response_data == truncated_data - assert response_data != original_data - assert execution.process_data_truncated is True - - def test_get_response_process_data_with_none_process_data(self): - """Test get_response_process_data when process_data is None.""" - execution = self.create_workflow_node_execution(process_data=None) - - response_data = execution.get_response_process_data() - - assert response_data is None - assert execution.process_data_truncated is False - - def test_consistency_with_inputs_outputs_pattern(self): - """Test that process_data truncation follows the same pattern as inputs/outputs.""" - execution = self.create_workflow_node_execution() - - # Test that all truncation methods exist and behave consistently - test_data = {"test": "data"} - - # Test inputs truncation - execution.set_truncated_inputs(test_data) - assert execution.inputs_truncated is True - assert execution.get_truncated_inputs() == test_data - - # Test outputs truncation - execution.set_truncated_outputs(test_data) - assert execution.outputs_truncated is True - assert execution.get_truncated_outputs() == test_data - - # Test process_data truncation - execution.set_truncated_process_data(test_data) - assert execution.process_data_truncated is True - assert execution.get_truncated_process_data() == test_data - - @pytest.mark.parametrize( - "test_data", - [ - {"simple": "value"}, - {"nested": {"key": "value"}}, - {"list": [1, 2, 3]}, - {"mixed": {"string": "value", "number": 42, "list": [1, 2]}}, - {}, # empty dict - ], - ) - def test_truncated_process_data_with_various_data_types(self, test_data): - """Test that truncated process_data works with various data types.""" - execution = self.create_workflow_node_execution() - - execution.set_truncated_process_data(test_data) - - assert execution.process_data_truncated is True - assert execution.get_truncated_process_data() == test_data - assert execution.get_response_process_data() == test_data - - -@dataclass -class ProcessDataScenario: - """Test scenario data for process_data functionality.""" - - name: str - original_data: dict[str, Any] | None - truncated_data: dict[str, Any] | None - expected_truncated_flag: bool - expected_response_data: dict[str, Any] | None - - -class TestWorkflowNodeExecutionProcessDataScenarios: - """Test various scenarios for process_data handling.""" - - def get_process_data_scenarios(self) -> list[ProcessDataScenario]: - """Create test scenarios for process_data functionality.""" - return [ - ProcessDataScenario( - name="no_process_data", - original_data=None, - truncated_data=None, - expected_truncated_flag=False, - expected_response_data=None, - ), - ProcessDataScenario( - name="process_data_without_truncation", - original_data={"small": "data"}, - truncated_data=None, - expected_truncated_flag=False, - expected_response_data={"small": "data"}, - ), - ProcessDataScenario( - name="process_data_with_truncation", - original_data={"large": "x" * 10000, "metadata": "info"}, - truncated_data={"large": "[TRUNCATED]", "metadata": "info"}, - expected_truncated_flag=True, - expected_response_data={"large": "[TRUNCATED]", "metadata": "info"}, - ), - ProcessDataScenario( - name="empty_process_data", - original_data={}, - truncated_data=None, - expected_truncated_flag=False, - expected_response_data={}, - ), - ProcessDataScenario( - name="complex_nested_data_with_truncation", - original_data={ - "config": {"setting": "value"}, - "logs": ["log1", "log2"] * 1000, # Large list - "status": "running", - }, - truncated_data={"config": {"setting": "value"}, "logs": "[TRUNCATED: 2000 items]", "status": "running"}, - expected_truncated_flag=True, - expected_response_data={ - "config": {"setting": "value"}, - "logs": "[TRUNCATED: 2000 items]", - "status": "running", - }, - ), - ] - - @pytest.mark.parametrize( - "scenario", - get_process_data_scenarios(None), - ids=[scenario.name for scenario in get_process_data_scenarios(None)], - ) - def test_process_data_scenarios(self, scenario: ProcessDataScenario): - """Test various process_data scenarios.""" - execution = WorkflowNodeExecution( - id="test-execution-id", - workflow_id="test-workflow-id", - index=1, - node_id="test-node-id", - node_type=BuiltinNodeTypes.LLM, - title="Test Node", - process_data=scenario.original_data, - created_at=datetime.now(), - ) - - if scenario.truncated_data is not None: - execution.set_truncated_process_data(scenario.truncated_data) - - assert execution.process_data_truncated == scenario.expected_truncated_flag - assert execution.get_response_process_data() == scenario.expected_response_data diff --git a/api/tests/unit_tests/core/workflow/graph/test_graph.py b/api/tests/unit_tests/core/workflow/graph/test_graph.py deleted file mode 100644 index 24bd9ccbed6..00000000000 --- a/api/tests/unit_tests/core/workflow/graph/test_graph.py +++ /dev/null @@ -1,281 +0,0 @@ -"""Unit tests for Graph class methods.""" - -from unittest.mock import Mock - -from dify_graph.enums import BuiltinNodeTypes, NodeExecutionType, NodeState -from dify_graph.graph.edge import Edge -from dify_graph.graph.graph import Graph -from dify_graph.nodes.base.node import Node - - -def create_mock_node(node_id: str, execution_type: NodeExecutionType, state: NodeState = NodeState.UNKNOWN) -> Node: - """Create a mock node for testing.""" - node = Mock(spec=Node) - node.id = node_id - node.execution_type = execution_type - node.state = state - node.node_type = BuiltinNodeTypes.START - return node - - -class TestMarkInactiveRootBranches: - """Test cases for _mark_inactive_root_branches method.""" - - def test_single_root_no_marking(self): - """Test that single root graph doesn't mark anything as skipped.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "child1": create_mock_node("child1", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="child1", source_handle="source"), - } - - in_edges = {"child1": ["edge1"]} - out_edges = {"root1": ["edge1"]} - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["child1"].state == NodeState.UNKNOWN - assert edges["edge1"].state == NodeState.UNKNOWN - - def test_multiple_roots_mark_inactive(self): - """Test marking inactive root branches with multiple root nodes.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "root2": create_mock_node("root2", NodeExecutionType.ROOT), - "child1": create_mock_node("child1", NodeExecutionType.EXECUTABLE), - "child2": create_mock_node("child2", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="child1", source_handle="source"), - "edge2": Edge(id="edge2", tail="root2", head="child2", source_handle="source"), - } - - in_edges = {"child1": ["edge1"], "child2": ["edge2"]} - out_edges = {"root1": ["edge1"], "root2": ["edge2"]} - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["root2"].state == NodeState.SKIPPED - assert nodes["child1"].state == NodeState.UNKNOWN - assert nodes["child2"].state == NodeState.SKIPPED - assert edges["edge1"].state == NodeState.UNKNOWN - assert edges["edge2"].state == NodeState.SKIPPED - - def test_shared_downstream_node(self): - """Test that shared downstream nodes are not skipped if at least one path is active.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "root2": create_mock_node("root2", NodeExecutionType.ROOT), - "child1": create_mock_node("child1", NodeExecutionType.EXECUTABLE), - "child2": create_mock_node("child2", NodeExecutionType.EXECUTABLE), - "shared": create_mock_node("shared", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="child1", source_handle="source"), - "edge2": Edge(id="edge2", tail="root2", head="child2", source_handle="source"), - "edge3": Edge(id="edge3", tail="child1", head="shared", source_handle="source"), - "edge4": Edge(id="edge4", tail="child2", head="shared", source_handle="source"), - } - - in_edges = { - "child1": ["edge1"], - "child2": ["edge2"], - "shared": ["edge3", "edge4"], - } - out_edges = { - "root1": ["edge1"], - "root2": ["edge2"], - "child1": ["edge3"], - "child2": ["edge4"], - } - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["root2"].state == NodeState.SKIPPED - assert nodes["child1"].state == NodeState.UNKNOWN - assert nodes["child2"].state == NodeState.SKIPPED - assert nodes["shared"].state == NodeState.UNKNOWN # Not skipped because edge3 is active - assert edges["edge1"].state == NodeState.UNKNOWN - assert edges["edge2"].state == NodeState.SKIPPED - assert edges["edge3"].state == NodeState.UNKNOWN - assert edges["edge4"].state == NodeState.SKIPPED - - def test_deep_branch_marking(self): - """Test marking deep branches with multiple levels.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "root2": create_mock_node("root2", NodeExecutionType.ROOT), - "level1_a": create_mock_node("level1_a", NodeExecutionType.EXECUTABLE), - "level1_b": create_mock_node("level1_b", NodeExecutionType.EXECUTABLE), - "level2_a": create_mock_node("level2_a", NodeExecutionType.EXECUTABLE), - "level2_b": create_mock_node("level2_b", NodeExecutionType.EXECUTABLE), - "level3": create_mock_node("level3", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="level1_a", source_handle="source"), - "edge2": Edge(id="edge2", tail="root2", head="level1_b", source_handle="source"), - "edge3": Edge(id="edge3", tail="level1_a", head="level2_a", source_handle="source"), - "edge4": Edge(id="edge4", tail="level1_b", head="level2_b", source_handle="source"), - "edge5": Edge(id="edge5", tail="level2_b", head="level3", source_handle="source"), - } - - in_edges = { - "level1_a": ["edge1"], - "level1_b": ["edge2"], - "level2_a": ["edge3"], - "level2_b": ["edge4"], - "level3": ["edge5"], - } - out_edges = { - "root1": ["edge1"], - "root2": ["edge2"], - "level1_a": ["edge3"], - "level1_b": ["edge4"], - "level2_b": ["edge5"], - } - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["root2"].state == NodeState.SKIPPED - assert nodes["level1_a"].state == NodeState.UNKNOWN - assert nodes["level1_b"].state == NodeState.SKIPPED - assert nodes["level2_a"].state == NodeState.UNKNOWN - assert nodes["level2_b"].state == NodeState.SKIPPED - assert nodes["level3"].state == NodeState.SKIPPED - assert edges["edge1"].state == NodeState.UNKNOWN - assert edges["edge2"].state == NodeState.SKIPPED - assert edges["edge3"].state == NodeState.UNKNOWN - assert edges["edge4"].state == NodeState.SKIPPED - assert edges["edge5"].state == NodeState.SKIPPED - - def test_non_root_execution_type(self): - """Test that nodes with non-ROOT execution type are not treated as root nodes.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "non_root": create_mock_node("non_root", NodeExecutionType.EXECUTABLE), - "child1": create_mock_node("child1", NodeExecutionType.EXECUTABLE), - "child2": create_mock_node("child2", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="child1", source_handle="source"), - "edge2": Edge(id="edge2", tail="non_root", head="child2", source_handle="source"), - } - - in_edges = {"child1": ["edge1"], "child2": ["edge2"]} - out_edges = {"root1": ["edge1"], "non_root": ["edge2"]} - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["non_root"].state == NodeState.UNKNOWN # Not marked as skipped - assert nodes["child1"].state == NodeState.UNKNOWN - assert nodes["child2"].state == NodeState.UNKNOWN - assert edges["edge1"].state == NodeState.UNKNOWN - assert edges["edge2"].state == NodeState.UNKNOWN - - def test_empty_graph(self): - """Test handling of empty graph structures.""" - nodes = {} - edges = {} - in_edges = {} - out_edges = {} - - # Should not raise any errors - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "non_existent") - - def test_three_roots_mark_two_inactive(self): - """Test with three root nodes where two should be marked inactive.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "root2": create_mock_node("root2", NodeExecutionType.ROOT), - "root3": create_mock_node("root3", NodeExecutionType.ROOT), - "child1": create_mock_node("child1", NodeExecutionType.EXECUTABLE), - "child2": create_mock_node("child2", NodeExecutionType.EXECUTABLE), - "child3": create_mock_node("child3", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="child1", source_handle="source"), - "edge2": Edge(id="edge2", tail="root2", head="child2", source_handle="source"), - "edge3": Edge(id="edge3", tail="root3", head="child3", source_handle="source"), - } - - in_edges = { - "child1": ["edge1"], - "child2": ["edge2"], - "child3": ["edge3"], - } - out_edges = { - "root1": ["edge1"], - "root2": ["edge2"], - "root3": ["edge3"], - } - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root2") - - assert nodes["root1"].state == NodeState.SKIPPED - assert nodes["root2"].state == NodeState.UNKNOWN # Active root - assert nodes["root3"].state == NodeState.SKIPPED - assert nodes["child1"].state == NodeState.SKIPPED - assert nodes["child2"].state == NodeState.UNKNOWN - assert nodes["child3"].state == NodeState.SKIPPED - assert edges["edge1"].state == NodeState.SKIPPED - assert edges["edge2"].state == NodeState.UNKNOWN - assert edges["edge3"].state == NodeState.SKIPPED - - def test_convergent_paths(self): - """Test convergent paths where multiple inactive branches lead to same node.""" - nodes = { - "root1": create_mock_node("root1", NodeExecutionType.ROOT), - "root2": create_mock_node("root2", NodeExecutionType.ROOT), - "root3": create_mock_node("root3", NodeExecutionType.ROOT), - "mid1": create_mock_node("mid1", NodeExecutionType.EXECUTABLE), - "mid2": create_mock_node("mid2", NodeExecutionType.EXECUTABLE), - "convergent": create_mock_node("convergent", NodeExecutionType.EXECUTABLE), - } - - edges = { - "edge1": Edge(id="edge1", tail="root1", head="mid1", source_handle="source"), - "edge2": Edge(id="edge2", tail="root2", head="mid2", source_handle="source"), - "edge3": Edge(id="edge3", tail="root3", head="convergent", source_handle="source"), - "edge4": Edge(id="edge4", tail="mid1", head="convergent", source_handle="source"), - "edge5": Edge(id="edge5", tail="mid2", head="convergent", source_handle="source"), - } - - in_edges = { - "mid1": ["edge1"], - "mid2": ["edge2"], - "convergent": ["edge3", "edge4", "edge5"], - } - out_edges = { - "root1": ["edge1"], - "root2": ["edge2"], - "root3": ["edge3"], - "mid1": ["edge4"], - "mid2": ["edge5"], - } - - Graph._mark_inactive_root_branches(nodes, edges, in_edges, out_edges, "root1") - - assert nodes["root1"].state == NodeState.UNKNOWN - assert nodes["root2"].state == NodeState.SKIPPED - assert nodes["root3"].state == NodeState.SKIPPED - assert nodes["mid1"].state == NodeState.UNKNOWN - assert nodes["mid2"].state == NodeState.SKIPPED - assert nodes["convergent"].state == NodeState.UNKNOWN # Not skipped due to active path from root1 - assert edges["edge1"].state == NodeState.UNKNOWN - assert edges["edge2"].state == NodeState.SKIPPED - assert edges["edge3"].state == NodeState.SKIPPED - assert edges["edge4"].state == NodeState.UNKNOWN - assert edges["edge5"].state == NodeState.SKIPPED diff --git a/api/tests/unit_tests/core/workflow/graph/test_graph_builder.py b/api/tests/unit_tests/core/workflow/graph/test_graph_builder.py deleted file mode 100644 index 64c2eee7766..00000000000 --- a/api/tests/unit_tests/core/workflow/graph/test_graph_builder.py +++ /dev/null @@ -1,59 +0,0 @@ -from unittest.mock import MagicMock - -import pytest - -from dify_graph.enums import BuiltinNodeTypes, NodeType -from dify_graph.graph import Graph -from dify_graph.nodes.base.node import Node - - -def _make_node(node_id: str, node_type: NodeType = BuiltinNodeTypes.START) -> Node: - node = MagicMock(spec=Node) - node.id = node_id - node.node_type = node_type - node.execution_type = None # attribute not used in builder path - return node - - -def test_graph_builder_creates_linear_graph(): - builder = Graph.new() - root = _make_node("root", BuiltinNodeTypes.START) - mid = _make_node("mid", BuiltinNodeTypes.LLM) - end = _make_node("end", BuiltinNodeTypes.END) - - graph = builder.add_root(root).add_node(mid).add_node(end).build() - - assert graph.root_node is root - assert graph.nodes == {"root": root, "mid": mid, "end": end} - assert len(graph.edges) == 2 - first_edge = next(iter(graph.edges.values())) - assert first_edge.tail == "root" - assert first_edge.head == "mid" - assert graph.out_edges["mid"] == [edge_id for edge_id, edge in graph.edges.items() if edge.tail == "mid"] - - -def test_graph_builder_supports_custom_predecessor(): - builder = Graph.new() - root = _make_node("root") - branch = _make_node("branch") - other = _make_node("other") - - graph = builder.add_root(root).add_node(branch).add_node(other, from_node_id="root").build() - - outgoing_root = graph.out_edges["root"] - assert len(outgoing_root) == 2 - edge_targets = {graph.edges[eid].head for eid in outgoing_root} - assert edge_targets == {"branch", "other"} - - -def test_graph_builder_validates_usage(): - builder = Graph.new() - node = _make_node("node") - - with pytest.raises(ValueError, match="Root node"): - builder.add_node(node) - - builder.add_root(node) - duplicate = _make_node("node") - with pytest.raises(ValueError, match="Duplicate"): - builder.add_node(duplicate) diff --git a/api/tests/unit_tests/core/workflow/graph/test_graph_skip_validation.py b/api/tests/unit_tests/core/workflow/graph/test_graph_skip_validation.py deleted file mode 100644 index 75de07bd8b8..00000000000 --- a/api/tests/unit_tests/core/workflow/graph/test_graph_skip_validation.py +++ /dev/null @@ -1,118 +0,0 @@ -from __future__ import annotations - -from typing import Any - -import pytest - -from core.workflow.node_factory import DifyNodeFactory -from dify_graph.graph import Graph -from dify_graph.graph.validation import GraphValidationError -from dify_graph.nodes import BuiltinNodeTypes -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from tests.workflow_test_utils import build_test_graph_init_params - - -def _build_iteration_graph(node_id: str) -> dict[str, Any]: - return { - "nodes": [ - { - "id": node_id, - "data": { - "type": "iteration", - "title": "Iteration", - "iterator_selector": ["start", "items"], - "output_selector": [node_id, "output"], - }, - } - ], - "edges": [], - } - - -def _build_loop_graph(node_id: str) -> dict[str, Any]: - return { - "nodes": [ - { - "id": node_id, - "data": { - "type": "loop", - "title": "Loop", - "loop_count": 1, - "break_conditions": [], - "logical_operator": "and", - "loop_variables": [], - "outputs": {}, - }, - } - ], - "edges": [], - } - - -def _make_factory(graph_config: dict[str, Any]) -> DifyNodeFactory: - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool( - system_variables=SystemVariable.default(), - user_inputs={}, - environment_variables=[], - ), - start_at=0.0, - ) - return DifyNodeFactory(graph_init_params=graph_init_params, graph_runtime_state=graph_runtime_state) - - -def test_iteration_root_requires_skip_validation(): - node_id = "iteration-node" - graph_config = _build_iteration_graph(node_id) - node_factory = _make_factory(graph_config) - - with pytest.raises(GraphValidationError): - Graph.init( - graph_config=graph_config, - node_factory=node_factory, - root_node_id=node_id, - ) - - graph = Graph.init( - graph_config=graph_config, - node_factory=node_factory, - root_node_id=node_id, - skip_validation=True, - ) - - assert graph.root_node.id == node_id - assert graph.root_node.node_type == BuiltinNodeTypes.ITERATION - - -def test_loop_root_requires_skip_validation(): - node_id = "loop-node" - graph_config = _build_loop_graph(node_id) - node_factory = _make_factory(graph_config) - - with pytest.raises(GraphValidationError): - Graph.init( - graph_config=graph_config, - node_factory=node_factory, - root_node_id=node_id, - ) - - graph = Graph.init( - graph_config=graph_config, - node_factory=node_factory, - root_node_id=node_id, - skip_validation=True, - ) - - assert graph.root_node.id == node_id - assert graph.root_node.node_type == BuiltinNodeTypes.LOOP diff --git a/api/tests/unit_tests/core/workflow/graph/test_graph_validation.py b/api/tests/unit_tests/core/workflow/graph/test_graph_validation.py deleted file mode 100644 index e94ad74eb01..00000000000 --- a/api/tests/unit_tests/core/workflow/graph/test_graph_validation.py +++ /dev/null @@ -1,219 +0,0 @@ -from __future__ import annotations - -import time -from collections.abc import Mapping -from dataclasses import dataclass - -import pytest - -from dify_graph.entities import GraphInitParams -from dify_graph.entities.base_node_data import BaseNodeData -from dify_graph.enums import BuiltinNodeTypes, ErrorStrategy, NodeExecutionType, NodeType -from dify_graph.graph import Graph -from dify_graph.graph.validation import GraphValidationError -from dify_graph.nodes.base.node import Node -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from tests.workflow_test_utils import build_test_graph_init_params - - -class _TestNodeData(BaseNodeData): - type: NodeType | None = None - execution_type: NodeExecutionType | str | None = None - - -class _TestNode(Node[_TestNodeData]): - node_type = BuiltinNodeTypes.ANSWER - execution_type = NodeExecutionType.EXECUTABLE - - @classmethod - def version(cls) -> str: - return "1" - - def __init__( - self, - *, - id: str, - config: Mapping[str, object], - graph_init_params: GraphInitParams, - graph_runtime_state: GraphRuntimeState, - ) -> None: - super().__init__( - id=id, - config=config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - node_type_value = self.data.get("type") - if isinstance(node_type_value, str): - self.node_type = node_type_value - - def _run(self): - raise NotImplementedError - - def post_init(self) -> None: - super().post_init() - self._maybe_override_execution_type() - self.data = dict(self.node_data.model_dump()) - - def _maybe_override_execution_type(self) -> None: - execution_type_value = self.node_data.execution_type - if execution_type_value is None: - return - if isinstance(execution_type_value, NodeExecutionType): - self.execution_type = execution_type_value - else: - self.execution_type = NodeExecutionType(execution_type_value) - - -@dataclass(slots=True) -class _SimpleNodeFactory: - graph_init_params: GraphInitParams - graph_runtime_state: GraphRuntimeState - - def create_node(self, node_config: Mapping[str, object]) -> _TestNode: - node_id = str(node_config["id"]) - node = _TestNode( - id=node_id, - config=node_config, - graph_init_params=self.graph_init_params, - graph_runtime_state=self.graph_runtime_state, - ) - return node - - -@pytest.fixture -def graph_init_dependencies() -> tuple[_SimpleNodeFactory, dict[str, object]]: - graph_config: dict[str, object] = {"edges": [], "nodes": []} - init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="service-api", - call_depth=0, - ) - variable_pool = VariablePool(system_variables=SystemVariable(user_id="user", files=[]), user_inputs={}) - runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - factory = _SimpleNodeFactory(graph_init_params=init_params, graph_runtime_state=runtime_state) - return factory, graph_config - - -def test_graph_initialization_runs_default_validators( - graph_init_dependencies: tuple[_SimpleNodeFactory, dict[str, object]], -): - node_factory, graph_config = graph_init_dependencies - graph_config["nodes"] = [ - { - "id": "start", - "data": {"type": BuiltinNodeTypes.START, "title": "Start", "execution_type": NodeExecutionType.ROOT}, - }, - {"id": "answer", "data": {"type": BuiltinNodeTypes.ANSWER, "title": "Answer"}}, - ] - graph_config["edges"] = [ - {"source": "start", "target": "answer", "sourceHandle": "success"}, - ] - - graph = Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id="start") - - assert graph.root_node.id == "start" - assert "answer" in graph.nodes - - -def test_graph_validation_fails_for_unknown_edge_targets( - graph_init_dependencies: tuple[_SimpleNodeFactory, dict[str, object]], -) -> None: - node_factory, graph_config = graph_init_dependencies - graph_config["nodes"] = [ - { - "id": "start", - "data": {"type": BuiltinNodeTypes.START, "title": "Start", "execution_type": NodeExecutionType.ROOT}, - }, - ] - graph_config["edges"] = [ - {"source": "start", "target": "missing", "sourceHandle": "success"}, - ] - - with pytest.raises(GraphValidationError) as exc: - Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id="start") - - assert any(issue.code == "MISSING_NODE" for issue in exc.value.issues) - - -def test_graph_promotes_fail_branch_nodes_to_branch_execution_type( - graph_init_dependencies: tuple[_SimpleNodeFactory, dict[str, object]], -) -> None: - node_factory, graph_config = graph_init_dependencies - graph_config["nodes"] = [ - { - "id": "start", - "data": {"type": BuiltinNodeTypes.START, "title": "Start", "execution_type": NodeExecutionType.ROOT}, - }, - { - "id": "branch", - "data": { - "type": BuiltinNodeTypes.IF_ELSE, - "title": "Branch", - "error_strategy": ErrorStrategy.FAIL_BRANCH, - }, - }, - ] - graph_config["edges"] = [ - {"source": "start", "target": "branch", "sourceHandle": "success"}, - ] - - graph = Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id="start") - - assert graph.nodes["branch"].execution_type == NodeExecutionType.BRANCH - - -def test_graph_init_ignores_custom_note_nodes_before_node_data_validation( - graph_init_dependencies: tuple[_SimpleNodeFactory, dict[str, object]], -) -> None: - node_factory, graph_config = graph_init_dependencies - graph_config["nodes"] = [ - { - "id": "start", - "data": {"type": BuiltinNodeTypes.START, "title": "Start", "execution_type": NodeExecutionType.ROOT}, - }, - {"id": "answer", "data": {"type": BuiltinNodeTypes.ANSWER, "title": "Answer"}}, - { - "id": "note", - "type": "custom-note", - "data": { - "type": "", - "title": "", - "desc": "", - "text": "{}", - "theme": "blue", - }, - }, - ] - graph_config["edges"] = [ - {"source": "start", "target": "answer", "sourceHandle": "success"}, - ] - - graph = Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id="start") - - assert graph.root_node.id == "start" - assert "answer" in graph.nodes - assert "note" not in graph.nodes - - -def test_graph_init_fails_for_unknown_root_node_id( - graph_init_dependencies: tuple[_SimpleNodeFactory, dict[str, object]], -) -> None: - node_factory, graph_config = graph_init_dependencies - graph_config["nodes"] = [ - { - "id": "start", - "data": {"type": BuiltinNodeTypes.START, "title": "Start", "execution_type": NodeExecutionType.ROOT}, - }, - ] - graph_config["edges"] = [] - - with pytest.raises(ValueError, match="Root node id missing not found in the graph"): - Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id="missing") diff --git a/api/tests/unit_tests/core/workflow/graph_engine/README.md b/api/tests/unit_tests/core/workflow/graph_engine/README.md index 40ed61eb029..dd419f0810f 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/README.md +++ b/api/tests/unit_tests/core/workflow/graph_engine/README.md @@ -1,441 +1,30 @@ -# Graph Engine Testing Framework +# Workflow Graph Engine Smoke Tests -## Overview +This directory now keeps only a small Dify-owned smoke layer around the external +`graphon` package. -This directory contains a comprehensive testing framework for the Graph Engine, including: +Retained coverage focuses on: -1. **TableTestRunner** - Advanced table-driven test framework for workflow testing -1. **Auto-Mock System** - Powerful mocking framework for testing without external dependencies +1. Dify workflow layers: + - `layers/test_llm_quota.py` + - `layers/test_observability.py` +2. Human-input resume integration: + - `test_parallel_human_input_join_resume.py` +3. One mocked tool/chatflow smoke path: + - `test_tool_in_chatflow.py` -## TableTestRunner Framework +The helper modules below remain only because the retained smoke tests use them: -The TableTestRunner (`test_table_runner.py`) provides a robust table-driven testing framework for GraphEngine workflows. +1. `test_mock_config.py` +2. `test_mock_factory.py` +3. `test_mock_nodes.py` +4. `test_table_runner.py` -### Features - -- **Table-driven testing** - Define test cases as structured data -- **Parallel test execution** - Run tests concurrently for faster execution -- **Property-based testing** - Integration with Hypothesis for fuzzing -- **Event sequence validation** - Verify correct event ordering -- **Mock configuration** - Seamless integration with the auto-mock system -- **Performance metrics** - Track execution times and bottlenecks -- **Detailed error reporting** - Comprehensive failure diagnostics - -### Basic Usage - -```python -from test_table_runner import TableTestRunner, WorkflowTestCase - -# Create test runner -runner = TableTestRunner() - -# Define test case -test_case = WorkflowTestCase( - fixture_path="simple_workflow", - inputs={"query": "Hello"}, - expected_outputs={"result": "World"}, - description="Basic workflow test", -) - -# Run single test -result = runner.run_test_case(test_case) -assert result.success -``` - -### Advanced Features - -#### Parallel Execution - -```python -runner = TableTestRunner(max_workers=8) - -test_cases = [ - WorkflowTestCase(...), - WorkflowTestCase(...), - # ... more test cases -] - -# Run tests in parallel -suite_result = runner.run_table_tests( - test_cases, - parallel=True, - fail_fast=False -) - -print(f"Success rate: {suite_result.success_rate:.1f}%") -``` - -#### Event Sequence Validation - -```python -from dify_graph.graph_events import ( - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, -) - -test_case = WorkflowTestCase( - fixture_path="workflow", - inputs={}, - expected_outputs={}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ] -) -``` - -### Test Suite Reports - -```python -# Run test suite -suite_result = runner.run_table_tests(test_cases) - -# Generate detailed report -report = runner.generate_report(suite_result) -print(report) - -# Access specific results -failed_results = suite_result.get_failed_results() -for result in failed_results: - print(f"Failed: {result.test_case.description}") - print(f" Error: {result.error}") -``` - -### Performance Testing - -```python -# Enable logging for performance insights -runner = TableTestRunner( - enable_logging=True, - log_level="DEBUG" -) - -# Run tests and analyze performance -suite_result = runner.run_table_tests(test_cases) - -# Get slowest tests -sorted_results = sorted( - suite_result.results, - key=lambda r: r.execution_time, - reverse=True -) - -print("Slowest tests:") -for result in sorted_results[:5]: - print(f" {result.test_case.description}: {result.execution_time:.2f}s") -``` - -## Integration: TableTestRunner + Auto-Mock System - -The TableTestRunner seamlessly integrates with the auto-mock system for comprehensive workflow testing: - -```python -from test_table_runner import TableTestRunner, WorkflowTestCase -from test_mock_config import MockConfigBuilder - -# Configure mocks -mock_config = (MockConfigBuilder() - .with_llm_response("Mocked LLM response") - .with_tool_response({"result": "mocked"}) - .with_delays(True) # Simulate realistic delays - .build()) - -# Create test case with mocking -test_case = WorkflowTestCase( - fixture_path="complex_workflow", - inputs={"query": "test"}, - expected_outputs={"answer": "Mocked LLM response"}, - use_auto_mock=True, # Enable auto-mocking - mock_config=mock_config, - description="Test with mocked services", -) - -# Run test -runner = TableTestRunner() -result = runner.run_test_case(test_case) -``` - -## Auto-Mock System - -The auto-mock system provides a powerful framework for testing workflows that contain nodes requiring third-party services (LLM, APIs, tools, etc.) without making actual external calls. This enables: - -- **Fast test execution** - No network latency or API rate limits -- **Deterministic results** - Consistent outputs for reliable testing -- **Cost savings** - No API usage charges during testing -- **Offline testing** - Tests can run without internet connectivity -- **Error simulation** - Test error handling without triggering real failures - -## Architecture - -The auto-mock system consists of three main components: - -### 1. MockNodeFactory (`test_mock_factory.py`) - -- Extends `DifyNodeFactory` to intercept node creation -- Automatically detects nodes requiring third-party services -- Returns mock node implementations instead of real ones -- Supports registration of custom mock implementations - -### 2. Mock Node Implementations (`test_mock_nodes.py`) - -- `MockLLMNode` - Mocks LLM API calls (OpenAI, Anthropic, etc.) -- `MockAgentNode` - Mocks agent execution -- `MockToolNode` - Mocks tool invocations -- `MockKnowledgeRetrievalNode` - Mocks knowledge base queries -- `MockHttpRequestNode` - Mocks HTTP requests -- `MockParameterExtractorNode` - Mocks parameter extraction -- `MockDocumentExtractorNode` - Mocks document processing -- `MockQuestionClassifierNode` - Mocks question classification - -### 3. Mock Configuration (`test_mock_config.py`) - -- `MockConfig` - Global configuration for mock behavior -- `NodeMockConfig` - Node-specific mock configuration -- `MockConfigBuilder` - Fluent interface for building configurations - -## Usage - -### Basic Example - -```python -from test_graph_engine import TableTestRunner, WorkflowTestCase -from test_mock_config import MockConfigBuilder - -# Create test runner -runner = TableTestRunner() - -# Configure mock responses -mock_config = (MockConfigBuilder() - .with_llm_response("Mocked LLM response") - .build()) - -# Define test case -test_case = WorkflowTestCase( - fixture_path="llm-simple", - inputs={"query": "Hello"}, - expected_outputs={"answer": "Mocked LLM response"}, - use_auto_mock=True, # Enable auto-mocking - mock_config=mock_config, -) - -# Run test -result = runner.run_test_case(test_case) -assert result.success -``` - -### Custom Node Outputs - -```python -# Configure specific outputs for individual nodes -mock_config = MockConfig() -mock_config.set_node_outputs("llm_node_123", { - "text": "Custom response for this specific node", - "usage": {"total_tokens": 50}, - "finish_reason": "stop", -}) -``` - -### Error Simulation - -```python -# Simulate node failures for error handling tests -mock_config = MockConfig() -mock_config.set_node_error("http_node", "Connection timeout") -``` - -### Simulated Delays - -```python -# Add realistic execution delays -from test_mock_config import NodeMockConfig - -node_config = NodeMockConfig( - node_id="llm_node", - outputs={"text": "Response"}, - delay=1.5, # 1.5 second delay -) -mock_config.set_node_config("llm_node", node_config) -``` - -### Custom Handlers - -```python -# Define custom logic for mock outputs -def custom_handler(node): - # Access node state and return dynamic outputs - return { - "text": f"Processed: {node.graph_runtime_state.variable_pool.get('query')}", - } - -node_config = NodeMockConfig( - node_id="llm_node", - custom_handler=custom_handler, -) -``` - -## Node Types Automatically Mocked - -The following node types are automatically mocked when `use_auto_mock=True`: - -- `LLM` - Language model nodes -- `AGENT` - Agent execution nodes -- `TOOL` - Tool invocation nodes -- `KNOWLEDGE_RETRIEVAL` - Knowledge base query nodes -- `HTTP_REQUEST` - HTTP request nodes -- `PARAMETER_EXTRACTOR` - Parameter extraction nodes -- `DOCUMENT_EXTRACTOR` - Document processing nodes -- `QUESTION_CLASSIFIER` - Question classification nodes - -## Advanced Features - -### Registering Custom Mock Implementations - -```python -from test_mock_factory import MockNodeFactory - -# Create custom mock implementation -class CustomMockNode(BaseNode): - def _run(self): - # Custom mock logic - pass - -# Register for a specific node type -factory = MockNodeFactory(...) -factory.register_mock_node_type(NodeType.CUSTOM, CustomMockNode) -``` - -### Default Configurations by Node Type - -```python -# Set defaults for all nodes of a specific type -mock_config.set_default_config(NodeType.LLM, { - "temperature": 0.7, - "max_tokens": 100, -}) -``` - -### MockConfigBuilder Fluent API - -```python -config = (MockConfigBuilder() - .with_llm_response("LLM response") - .with_agent_response("Agent response") - .with_tool_response({"result": "data"}) - .with_retrieval_response("Retrieved content") - .with_http_response({"status_code": 200, "body": "{}"}) - .with_node_output("node_id", {"output": "value"}) - .with_node_error("error_node", "Error message") - .with_delays(True) - .build()) -``` - -## Testing Workflows - -### 1. Create Workflow Fixture - -Create a YAML fixture file in `api/tests/fixtures/workflow/` directory defining your workflow graph. - -### 2. Configure Mocks - -Set up mock configurations for nodes that need third-party services. - -### 3. Define Test Cases - -Create `WorkflowTestCase` instances with inputs, expected outputs, and mock config. - -### 4. Run Tests - -Use `TableTestRunner` to execute test cases and validate results. - -## Best Practices - -1. **Use descriptive mock responses** - Make it clear in outputs that they are mocked -1. **Test both success and failure paths** - Use error simulation to test error handling -1. **Keep mock configs close to tests** - Define mocks in the same test file for clarity -1. **Use custom handlers sparingly** - Only when dynamic behavior is needed -1. **Document mock behavior** - Comment why specific mock values are chosen -1. **Validate mock accuracy** - Ensure mocks reflect real service behavior - -## Examples - -See `test_mock_example.py` for comprehensive examples including: - -- Basic LLM workflow testing -- Custom node outputs -- HTTP and tool workflow testing -- Error simulation -- Performance testing with delays - -## Running Tests - -### TableTestRunner Tests +Examples: ```bash -# Run graph engine tests (includes property-based tests) -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/test_graph_engine.py - -# Run with specific test patterns -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/test_graph_engine.py -k "test_echo" - -# Run with verbose output -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/test_graph_engine.py -v +uv run --project api --dev pytest api/tests/unit_tests/core/workflow/graph_engine/layers/test_llm_quota.py +uv run --project api --dev pytest api/tests/unit_tests/core/workflow/graph_engine/layers/test_observability.py +uv run --project api --dev pytest api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py +uv run --project api --dev pytest api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py ``` - -### Mock System Tests - -```bash -# Run auto-mock system tests -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/test_auto_mock_system.py - -# Run examples -uv run python api/tests/unit_tests/dify_graph/graph_engine/test_mock_example.py - -# Run simple validation -uv run python api/tests/unit_tests/dify_graph/graph_engine/test_mock_simple.py -``` - -### All Tests - -```bash -# Run all graph engine tests -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/ - -# Run with coverage -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/ --cov=dify_graph.graph_engine - -# Run in parallel -uv run pytest api/tests/unit_tests/dify_graph/graph_engine/ -n auto -``` - -## Troubleshooting - -### Issue: Mock not being applied - -- Ensure `use_auto_mock=True` in `WorkflowTestCase` -- Verify node ID matches in mock config -- Check that node type is in the auto-mock list - -### Issue: Unexpected outputs - -- Debug by printing `result.actual_outputs` -- Check if custom handler is overriding expected outputs -- Verify mock config is properly built - -### Issue: Import errors - -- Ensure all mock modules are in the correct path -- Check that required dependencies are installed - -## Future Enhancements - -Potential improvements to the auto-mock system: - -1. **Recording and playback** - Record real API responses for replay in tests -1. **Mock templates** - Pre-defined mock configurations for common scenarios -1. **Async support** - Better support for async node execution -1. **Mock validation** - Validate mock outputs against node schemas -1. **Performance profiling** - Built-in performance metrics for mocked workflows diff --git a/api/tests/unit_tests/core/workflow/graph_engine/command_channels/test_redis_channel.py b/api/tests/unit_tests/core/workflow/graph_engine/command_channels/test_redis_channel.py deleted file mode 100644 index 4dec618e49c..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/command_channels/test_redis_channel.py +++ /dev/null @@ -1,315 +0,0 @@ -"""Tests for Redis command channel implementation.""" - -import json -from unittest.mock import MagicMock - -from dify_graph.graph_engine.command_channels.redis_channel import RedisChannel -from dify_graph.graph_engine.entities.commands import ( - AbortCommand, - CommandType, - GraphEngineCommand, - UpdateVariablesCommand, - VariableUpdate, -) -from dify_graph.variables import IntegerVariable, StringVariable - - -class TestRedisChannel: - """Test suite for RedisChannel functionality.""" - - def test_init(self): - """Test RedisChannel initialization.""" - mock_redis = MagicMock() - channel_key = "test:channel:key" - ttl = 7200 - - channel = RedisChannel(mock_redis, channel_key, ttl) - - assert channel._redis == mock_redis - assert channel._key == channel_key - assert channel._command_ttl == ttl - - def test_init_default_ttl(self): - """Test RedisChannel initialization with default TTL.""" - mock_redis = MagicMock() - channel_key = "test:channel:key" - - channel = RedisChannel(mock_redis, channel_key) - - assert channel._command_ttl == 3600 # Default TTL - - def test_send_command(self): - """Test sending a command to Redis.""" - mock_redis = MagicMock() - mock_pipe = MagicMock() - context = MagicMock() - context.__enter__.return_value = mock_pipe - context.__exit__.return_value = None - mock_redis.pipeline.return_value = context - - channel = RedisChannel(mock_redis, "test:key", 3600) - - pending_key = "test:key:pending" - - # Create a test command - command = GraphEngineCommand(command_type=CommandType.ABORT) - - # Send the command - channel.send_command(command) - - # Verify pipeline was used - mock_redis.pipeline.assert_called_once() - - # Verify rpush was called with correct data - expected_json = json.dumps(command.model_dump()) - mock_pipe.rpush.assert_called_once_with("test:key", expected_json) - - # Verify expire was set - mock_pipe.expire.assert_called_once_with("test:key", 3600) - mock_pipe.set.assert_called_once_with(pending_key, "1", ex=3600) - - # Verify execute was called - mock_pipe.execute.assert_called_once() - - def test_fetch_commands_empty(self): - """Test fetching commands when Redis list is empty.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context] - - # No pending marker - pending_pipe.execute.return_value = [None, 0] - mock_redis.llen.return_value = 0 - - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - assert commands == [] - mock_redis.pipeline.assert_called_once() - fetch_pipe.lrange.assert_not_called() - fetch_pipe.delete.assert_not_called() - - def test_fetch_commands_with_abort_command(self): - """Test fetching abort commands from Redis.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Create abort command data - abort_command = AbortCommand() - command_json = json.dumps(abort_command.model_dump()) - - # Simulate Redis returning one command - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [[command_json.encode()], 1] - - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - assert len(commands) == 1 - assert isinstance(commands[0], AbortCommand) - assert commands[0].command_type == CommandType.ABORT - - def test_fetch_commands_multiple(self): - """Test fetching multiple commands from Redis.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Create multiple commands - command1 = GraphEngineCommand(command_type=CommandType.ABORT) - command2 = AbortCommand() - - command1_json = json.dumps(command1.model_dump()) - command2_json = json.dumps(command2.model_dump()) - - # Simulate Redis returning multiple commands - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [[command1_json.encode(), command2_json.encode()], 1] - - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - assert len(commands) == 2 - assert commands[0].command_type == CommandType.ABORT - assert isinstance(commands[1], AbortCommand) - - def test_fetch_commands_with_update_variables_command(self): - """Test fetching update variables command from Redis.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - update_command = UpdateVariablesCommand( - updates=[ - VariableUpdate( - value=StringVariable(name="foo", value="bar", selector=["node1", "foo"]), - ), - VariableUpdate( - value=IntegerVariable(name="baz", value=123, selector=["node2", "baz"]), - ), - ] - ) - command_json = json.dumps(update_command.model_dump()) - - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [[command_json.encode()], 1] - - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - assert len(commands) == 1 - assert isinstance(commands[0], UpdateVariablesCommand) - assert isinstance(commands[0].updates[0].value, StringVariable) - assert list(commands[0].updates[0].value.selector) == ["node1", "foo"] - assert commands[0].updates[0].value.value == "bar" - - def test_fetch_commands_skips_invalid_json(self): - """Test that invalid JSON commands are skipped.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Mix valid and invalid JSON - valid_command = AbortCommand() - valid_json = json.dumps(valid_command.model_dump()) - invalid_json = b"invalid json {" - - # Simulate Redis returning mixed valid/invalid commands - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [[invalid_json, valid_json.encode()], 1] - - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - # Should only return the valid command - assert len(commands) == 1 - assert isinstance(commands[0], AbortCommand) - - def test_deserialize_command_abort(self): - """Test deserializing an abort command.""" - channel = RedisChannel(MagicMock(), "test:key") - - abort_data = {"command_type": CommandType.ABORT} - command = channel._deserialize_command(abort_data) - - assert isinstance(command, AbortCommand) - assert command.command_type == CommandType.ABORT - - def test_deserialize_command_generic(self): - """Test deserializing a generic command.""" - channel = RedisChannel(MagicMock(), "test:key") - - # For now, only ABORT is supported, but test generic handling - generic_data = {"command_type": CommandType.ABORT} - command = channel._deserialize_command(generic_data) - - assert command is not None - assert command.command_type == CommandType.ABORT - - def test_deserialize_command_invalid(self): - """Test deserializing invalid command data.""" - channel = RedisChannel(MagicMock(), "test:key") - - # Missing command_type - invalid_data = {"some_field": "value"} - command = channel._deserialize_command(invalid_data) - - assert command is None - - def test_deserialize_command_invalid_type(self): - """Test deserializing command with invalid type.""" - channel = RedisChannel(MagicMock(), "test:key") - - # Invalid command type - invalid_data = {"command_type": "INVALID_TYPE"} - command = channel._deserialize_command(invalid_data) - - assert command is None - - def test_atomic_fetch_and_clear(self): - """Test that fetch_commands atomically fetches and clears the list.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - command = AbortCommand() - command_json = json.dumps(command.model_dump()) - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [[command_json.encode()], 1] - - channel = RedisChannel(mock_redis, "test:key") - - # First fetch should return the command - commands = channel.fetch_commands() - assert len(commands) == 1 - - # Verify both lrange and delete were called in the pipeline - assert fetch_pipe.lrange.call_count == 1 - assert fetch_pipe.delete.call_count == 1 - fetch_pipe.lrange.assert_called_with("test:key", 0, -1) - fetch_pipe.delete.assert_called_with("test:key") - - def test_fetch_commands_without_pending_marker_returns_empty(self): - """Ensure we avoid unnecessary list reads when pending flag is missing.""" - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Pending flag absent - pending_pipe.execute.return_value = [None, 0] - channel = RedisChannel(mock_redis, "test:key") - commands = channel.fetch_commands() - - assert commands == [] - mock_redis.llen.assert_not_called() - assert mock_redis.pipeline.call_count == 1 diff --git a/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_handlers.py b/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_handlers.py deleted file mode 100644 index 6f821ba7991..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_handlers.py +++ /dev/null @@ -1,119 +0,0 @@ -"""Tests for graph engine event handlers.""" - -from __future__ import annotations - -from dify_graph.entities.base_node_data import RetryConfig -from dify_graph.enums import BuiltinNodeTypes, NodeExecutionType, NodeState, WorkflowNodeExecutionStatus -from dify_graph.graph import Graph -from dify_graph.graph_engine.domain.graph_execution import GraphExecution -from dify_graph.graph_engine.event_management.event_handlers import EventHandler -from dify_graph.graph_engine.event_management.event_manager import EventManager -from dify_graph.graph_engine.graph_state_manager import GraphStateManager -from dify_graph.graph_engine.ready_queue.in_memory import InMemoryReadyQueue -from dify_graph.graph_engine.response_coordinator.coordinator import ResponseStreamCoordinator -from dify_graph.graph_events import NodeRunRetryEvent, NodeRunStartedEvent -from dify_graph.node_events import NodeRunResult -from dify_graph.runtime import GraphRuntimeState, VariablePool -from libs.datetime_utils import naive_utc_now - - -class _StubEdgeProcessor: - """Minimal edge processor stub for tests.""" - - -class _StubErrorHandler: - """Minimal error handler stub for tests.""" - - -class _StubNode: - """Simple node stub exposing the attributes needed by the state manager.""" - - def __init__(self, node_id: str) -> None: - self.id = node_id - self.state = NodeState.UNKNOWN - self.title = "Stub Node" - self.execution_type = NodeExecutionType.EXECUTABLE - self.error_strategy = None - self.retry_config = RetryConfig() - self.retry = False - - -def _build_event_handler(node_id: str) -> tuple[EventHandler, EventManager, GraphExecution]: - """Construct an EventHandler with in-memory dependencies for testing.""" - - node = _StubNode(node_id) - graph = Graph(nodes={node_id: node}, edges={}, in_edges={}, out_edges={}, root_node=node) - - variable_pool = VariablePool() - runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=0.0) - graph_execution = GraphExecution(workflow_id="test-workflow") - - event_manager = EventManager() - state_manager = GraphStateManager(graph=graph, ready_queue=InMemoryReadyQueue()) - response_coordinator = ResponseStreamCoordinator(variable_pool=variable_pool, graph=graph) - - handler = EventHandler( - graph=graph, - graph_runtime_state=runtime_state, - graph_execution=graph_execution, - response_coordinator=response_coordinator, - event_collector=event_manager, - edge_processor=_StubEdgeProcessor(), - state_manager=state_manager, - error_handler=_StubErrorHandler(), - ) - - return handler, event_manager, graph_execution - - -def test_retry_does_not_emit_additional_start_event() -> None: - """Ensure retry attempts do not produce duplicate start events.""" - - node_id = "test-node" - handler, event_manager, graph_execution = _build_event_handler(node_id) - - execution_id = "exec-1" - node_type = BuiltinNodeTypes.CODE - start_time = naive_utc_now() - - start_event = NodeRunStartedEvent( - id=execution_id, - node_id=node_id, - node_type=node_type, - node_title="Stub Node", - start_at=start_time, - ) - handler.dispatch(start_event) - - retry_event = NodeRunRetryEvent( - id=execution_id, - node_id=node_id, - node_type=node_type, - node_title="Stub Node", - start_at=start_time, - error="boom", - retry_index=1, - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.FAILED, - error="boom", - error_type="TestError", - ), - ) - handler.dispatch(retry_event) - - # Simulate the node starting execution again after retry - second_start_event = NodeRunStartedEvent( - id=execution_id, - node_id=node_id, - node_type=node_type, - node_title="Stub Node", - start_at=start_time, - ) - handler.dispatch(second_start_event) - - collected_types = [type(event) for event in event_manager._events] # type: ignore[attr-defined] - - assert collected_types == [NodeRunStartedEvent, NodeRunRetryEvent] - - node_execution = graph_execution.get_or_create_node_execution(node_id) - assert node_execution.retry_count == 1 diff --git a/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_manager.py b/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_manager.py deleted file mode 100644 index 25494dc647e..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/event_management/test_event_manager.py +++ /dev/null @@ -1,39 +0,0 @@ -"""Tests for the EventManager.""" - -from __future__ import annotations - -import logging - -from dify_graph.graph_engine.event_management.event_manager import EventManager -from dify_graph.graph_engine.layers.base import GraphEngineLayer -from dify_graph.graph_events import GraphEngineEvent - - -class _FaultyLayer(GraphEngineLayer): - """Layer that raises from on_event to test error handling.""" - - def on_graph_start(self) -> None: # pragma: no cover - not used in tests - pass - - def on_event(self, event: GraphEngineEvent) -> None: - raise RuntimeError("boom") - - def on_graph_end(self, error: Exception | None) -> None: # pragma: no cover - not used in tests - pass - - -def test_event_manager_logs_layer_errors(caplog) -> None: - """Ensure errors raised by layers are logged when collecting events.""" - - event_manager = EventManager() - event_manager.set_layers([_FaultyLayer()]) - - with caplog.at_level(logging.ERROR): - event_manager.collect(GraphEngineEvent()) - - error_logs = [record for record in caplog.records if "Error in layer on_event" in record.getMessage()] - assert error_logs, "Expected layer errors to be logged" - - log_record = error_logs[0] - assert log_record.exc_info is not None - assert isinstance(log_record.exc_info[1], RuntimeError) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/__init__.py b/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/__init__.py deleted file mode 100644 index cf8811dc2b5..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Tests for graph traversal components.""" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/test_skip_propagator.py b/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/test_skip_propagator.py deleted file mode 100644 index 73d59ea4e98..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/graph_traversal/test_skip_propagator.py +++ /dev/null @@ -1,307 +0,0 @@ -"""Unit tests for skip propagator.""" - -from unittest.mock import MagicMock, create_autospec - -from dify_graph.graph import Edge, Graph -from dify_graph.graph_engine.graph_state_manager import GraphStateManager -from dify_graph.graph_engine.graph_traversal.skip_propagator import SkipPropagator - - -class TestSkipPropagator: - """Test suite for SkipPropagator.""" - - def test_propagate_skip_from_edge_with_unknown_edges_stops_processing(self) -> None: - """When there are unknown incoming edges, propagation should stop.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create a mock edge - mock_edge = MagicMock(spec=Edge) - mock_edge.id = "edge_1" - mock_edge.head = "node_2" - - # Setup graph edges dict - mock_graph.edges = {"edge_1": mock_edge} - - # Setup incoming edges - incoming_edges = [MagicMock(spec=Edge), MagicMock(spec=Edge)] - mock_graph.get_incoming_edges.return_value = incoming_edges - - # Setup state manager to return has_unknown=True - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": True, - "has_taken": False, - "all_skipped": False, - } - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - mock_graph.get_incoming_edges.assert_called_once_with("node_2") - mock_state_manager.analyze_edge_states.assert_called_once_with(incoming_edges) - # Should not call any other state manager methods - mock_state_manager.enqueue_node.assert_not_called() - mock_state_manager.start_execution.assert_not_called() - mock_state_manager.mark_node_skipped.assert_not_called() - - def test_propagate_skip_from_edge_with_taken_edge_enqueues_node(self) -> None: - """When there is at least one taken edge, node should be enqueued.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create a mock edge - mock_edge = MagicMock(spec=Edge) - mock_edge.id = "edge_1" - mock_edge.head = "node_2" - - mock_graph.edges = {"edge_1": mock_edge} - incoming_edges = [MagicMock(spec=Edge)] - mock_graph.get_incoming_edges.return_value = incoming_edges - - # Setup state manager to return has_taken=True - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": False, - "has_taken": True, - "all_skipped": False, - } - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - mock_state_manager.enqueue_node.assert_called_once_with("node_2") - mock_state_manager.start_execution.assert_called_once_with("node_2") - mock_state_manager.mark_node_skipped.assert_not_called() - - def test_propagate_skip_from_edge_with_all_skipped_propagates_to_node(self) -> None: - """When all incoming edges are skipped, should propagate skip to node.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create a mock edge - mock_edge = MagicMock(spec=Edge) - mock_edge.id = "edge_1" - mock_edge.head = "node_2" - - mock_graph.edges = {"edge_1": mock_edge} - incoming_edges = [MagicMock(spec=Edge)] - mock_graph.get_incoming_edges.return_value = incoming_edges - - # Setup state manager to return all_skipped=True - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": False, - "has_taken": False, - "all_skipped": True, - } - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - mock_state_manager.mark_node_skipped.assert_called_once_with("node_2") - mock_state_manager.enqueue_node.assert_not_called() - mock_state_manager.start_execution.assert_not_called() - - def test_propagate_skip_to_node_marks_node_and_outgoing_edges_skipped(self) -> None: - """_propagate_skip_to_node should mark node and all outgoing edges as skipped.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create outgoing edges - edge1 = MagicMock(spec=Edge) - edge1.id = "edge_2" - edge1.head = "node_downstream_1" # Set head for propagate_skip_from_edge - - edge2 = MagicMock(spec=Edge) - edge2.id = "edge_3" - edge2.head = "node_downstream_2" - - # Setup graph edges dict for propagate_skip_from_edge - mock_graph.edges = {"edge_2": edge1, "edge_3": edge2} - mock_graph.get_outgoing_edges.return_value = [edge1, edge2] - - # Setup get_incoming_edges to return empty list to stop recursion - mock_graph.get_incoming_edges.return_value = [] - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Use mock to call private method - # Act - propagator._propagate_skip_to_node("node_1") - - # Assert - mock_state_manager.mark_node_skipped.assert_called_once_with("node_1") - mock_state_manager.mark_edge_skipped.assert_any_call("edge_2") - mock_state_manager.mark_edge_skipped.assert_any_call("edge_3") - assert mock_state_manager.mark_edge_skipped.call_count == 2 - # Should recursively propagate from each edge - # Since propagate_skip_from_edge is called, we need to verify it was called - # But we can't directly verify due to recursion. We'll trust the logic. - - def test_skip_branch_paths_marks_unselected_edges_and_propagates(self) -> None: - """skip_branch_paths should mark all unselected edges as skipped and propagate.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create unselected edges - edge1 = MagicMock(spec=Edge) - edge1.id = "edge_1" - edge1.head = "node_downstream_1" - - edge2 = MagicMock(spec=Edge) - edge2.id = "edge_2" - edge2.head = "node_downstream_2" - - unselected_edges = [edge1, edge2] - - # Setup graph edges dict - mock_graph.edges = {"edge_1": edge1, "edge_2": edge2} - # Setup get_incoming_edges to return empty list to stop recursion - mock_graph.get_incoming_edges.return_value = [] - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.skip_branch_paths(unselected_edges) - - # Assert - mock_state_manager.mark_edge_skipped.assert_any_call("edge_1") - mock_state_manager.mark_edge_skipped.assert_any_call("edge_2") - assert mock_state_manager.mark_edge_skipped.call_count == 2 - # propagate_skip_from_edge should be called for each edge - # We can't directly verify due to the mock, but the logic is covered - - def test_propagate_skip_from_edge_recursively_propagates_through_graph(self) -> None: - """Skip propagation should recursively propagate through the graph.""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - # Create edge chain: edge_1 -> node_2 -> edge_3 -> node_4 - edge1 = MagicMock(spec=Edge) - edge1.id = "edge_1" - edge1.head = "node_2" - - edge3 = MagicMock(spec=Edge) - edge3.id = "edge_3" - edge3.head = "node_4" - - mock_graph.edges = {"edge_1": edge1, "edge_3": edge3} - - # Setup get_incoming_edges to return different values based on node - def get_incoming_edges_side_effect(node_id): - if node_id == "node_2": - return [edge1] - elif node_id == "node_4": - return [edge3] - return [] - - mock_graph.get_incoming_edges.side_effect = get_incoming_edges_side_effect - - # Setup get_outgoing_edges to return different values based on node - def get_outgoing_edges_side_effect(node_id): - if node_id == "node_2": - return [edge3] - elif node_id == "node_4": - return [] # No outgoing edges, stops recursion - return [] - - mock_graph.get_outgoing_edges.side_effect = get_outgoing_edges_side_effect - - # Setup state manager to return all_skipped for both nodes - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": False, - "has_taken": False, - "all_skipped": True, - } - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - # Should mark node_2 as skipped - mock_state_manager.mark_node_skipped.assert_any_call("node_2") - # Should mark edge_3 as skipped - mock_state_manager.mark_edge_skipped.assert_any_call("edge_3") - # Should propagate to node_4 - mock_state_manager.mark_node_skipped.assert_any_call("node_4") - assert mock_state_manager.mark_node_skipped.call_count == 2 - - def test_propagate_skip_from_edge_with_mixed_edge_states_handles_correctly(self) -> None: - """Test with mixed edge states (some unknown, some taken, some skipped).""" - # Arrange - mock_graph = create_autospec(Graph) - mock_state_manager = create_autospec(GraphStateManager) - - mock_edge = MagicMock(spec=Edge) - mock_edge.id = "edge_1" - mock_edge.head = "node_2" - - mock_graph.edges = {"edge_1": mock_edge} - incoming_edges = [MagicMock(spec=Edge), MagicMock(spec=Edge), MagicMock(spec=Edge)] - mock_graph.get_incoming_edges.return_value = incoming_edges - - # Test 1: has_unknown=True, has_taken=False, all_skipped=False - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": True, - "has_taken": False, - "all_skipped": False, - } - - propagator = SkipPropagator(mock_graph, mock_state_manager) - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - should stop processing - mock_state_manager.enqueue_node.assert_not_called() - mock_state_manager.mark_node_skipped.assert_not_called() - - # Reset mocks for next test - mock_state_manager.reset_mock() - mock_graph.reset_mock() - - # Test 2: has_unknown=False, has_taken=True, all_skipped=False - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": False, - "has_taken": True, - "all_skipped": False, - } - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - should enqueue node - mock_state_manager.enqueue_node.assert_called_once_with("node_2") - mock_state_manager.start_execution.assert_called_once_with("node_2") - - # Reset mocks for next test - mock_state_manager.reset_mock() - mock_graph.reset_mock() - - # Test 3: has_unknown=False, has_taken=False, all_skipped=True - mock_state_manager.analyze_edge_states.return_value = { - "has_unknown": False, - "has_taken": False, - "all_skipped": True, - } - - # Act - propagator.propagate_skip_from_edge("edge_1") - - # Assert - should propagate skip - mock_state_manager.mark_node_skipped.assert_called_once_with("node_2") diff --git a/api/tests/unit_tests/core/workflow/graph_engine/human_input_test_utils.py b/api/tests/unit_tests/core/workflow/graph_engine/human_input_test_utils.py deleted file mode 100644 index fc8133f5e1b..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/human_input_test_utils.py +++ /dev/null @@ -1,131 +0,0 @@ -"""Utilities for testing HumanInputNode without database dependencies.""" - -from __future__ import annotations - -from collections.abc import Mapping -from dataclasses import dataclass -from datetime import datetime, timedelta -from typing import Any - -from dify_graph.nodes.human_input.enums import HumanInputFormStatus -from dify_graph.repositories.human_input_form_repository import ( - FormCreateParams, - HumanInputFormEntity, - HumanInputFormRecipientEntity, - HumanInputFormRepository, -) -from libs.datetime_utils import naive_utc_now - - -class _InMemoryFormRecipient(HumanInputFormRecipientEntity): - """Minimal recipient entity required by the repository interface.""" - - def __init__(self, recipient_id: str, token: str) -> None: - self._id = recipient_id - self._token = token - - @property - def id(self) -> str: - return self._id - - @property - def token(self) -> str: - return self._token - - -@dataclass -class _InMemoryFormEntity(HumanInputFormEntity): - form_id: str - rendered: str - token: str | None = None - action_id: str | None = None - data: Mapping[str, Any] | None = None - is_submitted: bool = False - status_value: HumanInputFormStatus = HumanInputFormStatus.WAITING - expiration: datetime = naive_utc_now() - - @property - def id(self) -> str: - return self.form_id - - @property - def web_app_token(self) -> str | None: - return self.token - - @property - def recipients(self) -> list[HumanInputFormRecipientEntity]: - return [] - - @property - def rendered_content(self) -> str: - return self.rendered - - @property - def selected_action_id(self) -> str | None: - return self.action_id - - @property - def submitted_data(self) -> Mapping[str, Any] | None: - return self.data - - @property - def submitted(self) -> bool: - return self.is_submitted - - @property - def status(self) -> HumanInputFormStatus: - return self.status_value - - @property - def expiration_time(self) -> datetime: - return self.expiration - - -class InMemoryHumanInputFormRepository(HumanInputFormRepository): - """Pure in-memory repository used by workflow graph engine tests.""" - - def __init__(self) -> None: - self._form_counter = 0 - self.created_params: list[FormCreateParams] = [] - self.created_forms: list[_InMemoryFormEntity] = [] - self._forms_by_key: dict[tuple[str, str], _InMemoryFormEntity] = {} - - def create_form(self, params: FormCreateParams) -> HumanInputFormEntity: - self.created_params.append(params) - self._form_counter += 1 - form_id = f"form-{self._form_counter}" - token = f"console-{form_id}" if params.console_recipient_required else f"token-{form_id}" - entity = _InMemoryFormEntity( - form_id=form_id, - rendered=params.rendered_content, - token=token, - ) - self.created_forms.append(entity) - self._forms_by_key[(params.workflow_execution_id, params.node_id)] = entity - return entity - - def get_form(self, workflow_execution_id: str, node_id: str) -> HumanInputFormEntity | None: - return self._forms_by_key.get((workflow_execution_id, node_id)) - - # Convenience helpers for tests ------------------------------------- - - def set_submission(self, *, action_id: str, form_data: Mapping[str, Any] | None = None) -> None: - """Simulate a human submission for the next repository lookup.""" - - if not self.created_forms: - raise AssertionError("no form has been created to attach submission data") - entity = self.created_forms[-1] - entity.action_id = action_id - entity.data = form_data or {} - entity.is_submitted = True - entity.status_value = HumanInputFormStatus.SUBMITTED - entity.expiration = naive_utc_now() + timedelta(days=1) - - def clear_submission(self) -> None: - if not self.created_forms: - return - for form in self.created_forms: - form.action_id = None - form.data = None - form.is_submitted = False - form.status_value = HumanInputFormStatus.WAITING diff --git a/api/tests/unit_tests/core/workflow/graph_engine/layers/conftest.py b/api/tests/unit_tests/core/workflow/graph_engine/layers/conftest.py index 9e7b3654b72..41627f5e0be 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/layers/conftest.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/layers/conftest.py @@ -5,13 +5,12 @@ Shared fixtures for ObservabilityLayer tests. from unittest.mock import MagicMock, patch import pytest +from graphon.enums import BuiltinNodeTypes from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessor from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter from opentelemetry.trace import set_tracer_provider -from dify_graph.enums import BuiltinNodeTypes - @pytest.fixture def memory_span_exporter(): @@ -62,8 +61,9 @@ def mock_llm_node(): @pytest.fixture def mock_tool_node(): """Create a mock Tool Node with tool-specific attributes.""" + from graphon.nodes.tool.entities import ToolNodeData + from core.tools.entities.tool_entities import ToolProviderType - from dify_graph.nodes.tool.entities import ToolNodeData node = MagicMock() node.id = "test-tool-node-id" @@ -117,8 +117,8 @@ def mock_result_event(): """Create a mock result event with NodeRunResult.""" from datetime import datetime - from dify_graph.graph_events.node import NodeRunSucceededEvent - from dify_graph.node_events.base import NodeRunResult + from graphon.graph_events import NodeRunSucceededEvent + from graphon.node_events import NodeRunResult node_run_result = NodeRunResult( inputs={"query": "test query"}, diff --git a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_layer_initialization.py b/api/tests/unit_tests/core/workflow/graph_engine/layers/test_layer_initialization.py deleted file mode 100644 index db325278490..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_layer_initialization.py +++ /dev/null @@ -1,57 +0,0 @@ -from __future__ import annotations - -import pytest - -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_engine.layers.base import ( - GraphEngineLayer, - GraphEngineLayerNotInitializedError, -) -from dify_graph.graph_events import GraphEngineEvent - -from ..test_table_runner import WorkflowRunner - - -class LayerForTest(GraphEngineLayer): - def on_graph_start(self) -> None: - pass - - def on_event(self, event: GraphEngineEvent) -> None: - pass - - def on_graph_end(self, error: Exception | None) -> None: - pass - - -def test_layer_runtime_state_raises_when_uninitialized() -> None: - layer = LayerForTest() - - with pytest.raises(GraphEngineLayerNotInitializedError): - _ = layer.graph_runtime_state - - -def test_layer_runtime_state_available_after_engine_layer() -> None: - runner = WorkflowRunner() - fixture_data = runner.load_fixture("simple_passthrough_workflow") - graph, graph_runtime_state = runner.create_graph_from_fixture( - fixture_data, - inputs={"query": "test layer state"}, - ) - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - layer = LayerForTest() - engine.layer(layer) - - outputs = layer.graph_runtime_state.outputs - ready_queue_size = layer.graph_runtime_state.ready_queue_size - - assert outputs == {} - assert isinstance(ready_queue_size, int) - assert ready_queue_size >= 0 diff --git a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_llm_quota.py b/api/tests/unit_tests/core/workflow/graph_engine/layers/test_llm_quota.py index 2a36f712fd7..99d131737e9 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_llm_quota.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/layers/test_llm_quota.py @@ -1,14 +1,28 @@ import threading from datetime import datetime +from types import SimpleNamespace from unittest.mock import MagicMock, patch +from graphon.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus +from graphon.graph_engine.entities.commands import CommandType +from graphon.graph_events import NodeRunSucceededEvent +from graphon.model_runtime.entities.llm_entities import LLMUsage +from graphon.node_events import NodeRunResult + +from core.app.entities.app_invoke_entities import DifyRunContext, InvokeFrom, UserFrom from core.app.workflow.layers.llm_quota import LLMQuotaLayer from core.errors.error import QuotaExceededError -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.graph_engine.entities.commands import CommandType -from dify_graph.graph_events.node import NodeRunSucceededEvent -from dify_graph.model_runtime.entities.llm_entities import LLMUsage -from dify_graph.node_events import NodeRunResult +from core.model_manager import ModelInstance + + +def _build_dify_context() -> DifyRunContext: + return DifyRunContext( + tenant_id="tenant-id", + app_id="app-id", + user_id="user-id", + user_from=UserFrom.ACCOUNT, + invoke_from=InvokeFrom.DEBUGGER, + ) def _build_succeeded_event() -> NodeRunSucceededEvent: @@ -25,6 +39,11 @@ def _build_succeeded_event() -> NodeRunSucceededEvent: ) +def _build_wrapped_model_instance() -> tuple[SimpleNamespace, ModelInstance]: + raw_model_instance = ModelInstance.__new__(ModelInstance) + return SimpleNamespace(_model_instance=raw_model_instance), raw_model_instance + + def test_deduct_quota_called_for_successful_llm_node() -> None: layer = LLMQuotaLayer() node = MagicMock() @@ -32,8 +51,8 @@ def test_deduct_quota_called_for_successful_llm_node() -> None: node.execution_id = "execution-id" node.node_type = BuiltinNodeTypes.LLM node.tenant_id = "tenant-id" - node.require_dify_context.return_value.tenant_id = "tenant-id" - node.model_instance = object() + node.require_run_context_value.return_value = _build_dify_context() + node.model_instance, raw_model_instance = _build_wrapped_model_instance() result_event = _build_succeeded_event() with patch("core.app.workflow.layers.llm_quota.deduct_llm_quota", autospec=True) as mock_deduct: @@ -41,7 +60,7 @@ def test_deduct_quota_called_for_successful_llm_node() -> None: mock_deduct.assert_called_once_with( tenant_id="tenant-id", - model_instance=node.model_instance, + model_instance=raw_model_instance, usage=result_event.node_run_result.llm_usage, ) @@ -53,8 +72,8 @@ def test_deduct_quota_called_for_question_classifier_node() -> None: node.execution_id = "execution-id" node.node_type = BuiltinNodeTypes.QUESTION_CLASSIFIER node.tenant_id = "tenant-id" - node.require_dify_context.return_value.tenant_id = "tenant-id" - node.model_instance = object() + node.require_run_context_value.return_value = _build_dify_context() + node.model_instance, raw_model_instance = _build_wrapped_model_instance() result_event = _build_succeeded_event() with patch("core.app.workflow.layers.llm_quota.deduct_llm_quota", autospec=True) as mock_deduct: @@ -62,7 +81,7 @@ def test_deduct_quota_called_for_question_classifier_node() -> None: mock_deduct.assert_called_once_with( tenant_id="tenant-id", - model_instance=node.model_instance, + model_instance=raw_model_instance, usage=result_event.node_run_result.llm_usage, ) @@ -74,7 +93,7 @@ def test_non_llm_node_is_ignored() -> None: node.execution_id = "execution-id" node.node_type = BuiltinNodeTypes.START node.tenant_id = "tenant-id" - node.require_dify_context.return_value.tenant_id = "tenant-id" + node.require_run_context_value.return_value = _build_dify_context() node._model_instance = object() result_event = _build_succeeded_event() @@ -91,7 +110,7 @@ def test_quota_error_is_handled_in_layer() -> None: node.execution_id = "execution-id" node.node_type = BuiltinNodeTypes.LLM node.tenant_id = "tenant-id" - node.require_dify_context.return_value.tenant_id = "tenant-id" + node.require_run_context_value.return_value = _build_dify_context() node.model_instance = object() result_event = _build_succeeded_event() @@ -113,8 +132,8 @@ def test_quota_deduction_exceeded_aborts_workflow_immediately() -> None: node.execution_id = "execution-id" node.node_type = BuiltinNodeTypes.LLM node.tenant_id = "tenant-id" - node.require_dify_context.return_value.tenant_id = "tenant-id" - node.model_instance = object() + node.require_run_context_value.return_value = _build_dify_context() + node.model_instance, _ = _build_wrapped_model_instance() node.graph_runtime_state = MagicMock() node.graph_runtime_state.stop_event = stop_event @@ -141,7 +160,7 @@ def test_quota_precheck_failure_aborts_workflow_immediately() -> None: node = MagicMock() node.id = "llm-node-id" node.node_type = BuiltinNodeTypes.LLM - node.model_instance = object() + node.model_instance, _ = _build_wrapped_model_instance() node.graph_runtime_state = MagicMock() node.graph_runtime_state.stop_event = stop_event @@ -167,7 +186,7 @@ def test_quota_precheck_passes_without_abort() -> None: node = MagicMock() node.id = "llm-node-id" node.node_type = BuiltinNodeTypes.LLM - node.model_instance = object() + node.model_instance, raw_model_instance = _build_wrapped_model_instance() node.graph_runtime_state = MagicMock() node.graph_runtime_state.stop_event = stop_event @@ -175,5 +194,5 @@ def test_quota_precheck_passes_without_abort() -> None: layer.on_node_run_start(node) assert not stop_event.is_set() - mock_check.assert_called_once_with(model_instance=node.model_instance) + mock_check.assert_called_once_with(model_instance=raw_model_instance) layer.command_channel.send_command.assert_not_called() diff --git a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_observability.py b/api/tests/unit_tests/core/workflow/graph_engine/layers/test_observability.py index 478a2b592e4..9cf72763ee2 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/layers/test_observability.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/layers/test_observability.py @@ -13,10 +13,10 @@ Test coverage: from unittest.mock import patch import pytest +from graphon.enums import BuiltinNodeTypes from opentelemetry.trace import StatusCode from core.app.workflow.layers.observability import ObservabilityLayer -from dify_graph.enums import BuiltinNodeTypes class TestObservabilityLayerInitialization: @@ -144,7 +144,7 @@ class TestObservabilityLayerParserIntegration: self, tracer_provider_with_memory_exporter, memory_span_exporter, mock_llm_node, mock_result_event ): """Test that LLM parser is used for LLM nodes and extracts LLM-specific attributes.""" - from dify_graph.node_events.base import NodeRunResult + from graphon.node_events import NodeRunResult mock_result_event.node_run_result = NodeRunResult( inputs={}, @@ -182,7 +182,7 @@ class TestObservabilityLayerParserIntegration: self, tracer_provider_with_memory_exporter, memory_span_exporter, mock_retrieval_node, mock_result_event ): """Test that retrieval parser is used for retrieval nodes and extracts retrieval-specific attributes.""" - from dify_graph.node_events.base import NodeRunResult + from graphon.node_events import NodeRunResult mock_result_event.node_run_result = NodeRunResult( inputs={"query": "test query"}, @@ -210,7 +210,7 @@ class TestObservabilityLayerParserIntegration: self, tracer_provider_with_memory_exporter, memory_span_exporter, mock_start_node, mock_result_event ): """Test that result_event parameter allows parsers to extract inputs and outputs.""" - from dify_graph.node_events.base import NodeRunResult + from graphon.node_events import NodeRunResult mock_result_event.node_run_result = NodeRunResult( inputs={"input_key": "input_value"}, diff --git a/api/tests/unit_tests/core/workflow/graph_engine/orchestration/test_dispatcher.py b/api/tests/unit_tests/core/workflow/graph_engine/orchestration/test_dispatcher.py deleted file mode 100644 index 548c10ce8d5..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/orchestration/test_dispatcher.py +++ /dev/null @@ -1,189 +0,0 @@ -"""Tests for dispatcher command checking behavior.""" - -from __future__ import annotations - -import queue -from unittest import mock - -from dify_graph.entities.pause_reason import SchedulingPause -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.graph_engine.event_management.event_handlers import EventHandler -from dify_graph.graph_engine.orchestration.dispatcher import Dispatcher -from dify_graph.graph_engine.orchestration.execution_coordinator import ExecutionCoordinator -from dify_graph.graph_events import ( - GraphNodeEventBase, - NodeRunPauseRequestedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, -) -from dify_graph.node_events import NodeRunResult -from libs.datetime_utils import naive_utc_now - - -def test_dispatcher_should_consume_remains_events_after_pause(): - event_queue = queue.Queue() - event_queue.put( - GraphNodeEventBase( - id="test", - node_id="test", - node_type=BuiltinNodeTypes.START, - ) - ) - event_handler = mock.Mock(spec=EventHandler) - execution_coordinator = mock.Mock(spec=ExecutionCoordinator) - execution_coordinator.paused.return_value = True - dispatcher = Dispatcher( - event_queue=event_queue, - event_handler=event_handler, - execution_coordinator=execution_coordinator, - ) - dispatcher._dispatcher_loop() - assert event_queue.empty() - - -class _StubExecutionCoordinator: - """Stub execution coordinator that tracks command checks.""" - - def __init__(self) -> None: - self.command_checks = 0 - self.scaling_checks = 0 - self.execution_complete = False - self.failed = False - self._paused = False - - def process_commands(self) -> None: - self.command_checks += 1 - - def check_scaling(self) -> None: - self.scaling_checks += 1 - - @property - def paused(self) -> bool: - return self._paused - - @property - def aborted(self) -> bool: - return False - - def mark_complete(self) -> None: - self.execution_complete = True - - def mark_failed(self, error: Exception) -> None: # pragma: no cover - defensive, not triggered in tests - self.failed = True - - -class _StubEventHandler: - """Minimal event handler that marks execution complete after handling an event.""" - - def __init__(self, coordinator: _StubExecutionCoordinator) -> None: - self._coordinator = coordinator - self.events = [] - - def dispatch(self, event) -> None: - self.events.append(event) - self._coordinator.mark_complete() - - -def _run_dispatcher_for_event(event) -> int: - """Run the dispatcher loop for a single event and return command check count.""" - event_queue: queue.Queue = queue.Queue() - event_queue.put(event) - - coordinator = _StubExecutionCoordinator() - event_handler = _StubEventHandler(coordinator) - - dispatcher = Dispatcher( - event_queue=event_queue, - event_handler=event_handler, - execution_coordinator=coordinator, - ) - - dispatcher._dispatcher_loop() - - return coordinator.command_checks - - -def _make_started_event() -> NodeRunStartedEvent: - return NodeRunStartedEvent( - id="start-event", - node_id="node-1", - node_type=BuiltinNodeTypes.CODE, - node_title="Test Node", - start_at=naive_utc_now(), - ) - - -def _make_succeeded_event() -> NodeRunSucceededEvent: - return NodeRunSucceededEvent( - id="success-event", - node_id="node-1", - node_type=BuiltinNodeTypes.CODE, - node_title="Test Node", - start_at=naive_utc_now(), - node_run_result=NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED), - ) - - -def test_dispatcher_checks_commands_during_idle_and_on_completion() -> None: - """Dispatcher polls commands when idle and after completion events.""" - started_checks = _run_dispatcher_for_event(_make_started_event()) - succeeded_checks = _run_dispatcher_for_event(_make_succeeded_event()) - - assert started_checks == 2 - assert succeeded_checks == 3 - - -class _PauseStubEventHandler: - """Minimal event handler that marks execution complete after handling an event.""" - - def __init__(self, coordinator: _StubExecutionCoordinator) -> None: - self._coordinator = coordinator - self.events = [] - - def dispatch(self, event) -> None: - self.events.append(event) - if isinstance(event, NodeRunPauseRequestedEvent): - self._coordinator.mark_complete() - - -def test_dispatcher_drain_event_queue(): - events = [ - NodeRunStartedEvent( - id="start-event", - node_id="node-1", - node_type=BuiltinNodeTypes.CODE, - node_title="Code", - start_at=naive_utc_now(), - ), - NodeRunPauseRequestedEvent( - id="pause-event", - node_id="node-1", - node_type=BuiltinNodeTypes.CODE, - reason=SchedulingPause(message="test pause"), - ), - NodeRunSucceededEvent( - id="success-event", - node_id="node-1", - node_type=BuiltinNodeTypes.CODE, - start_at=naive_utc_now(), - node_run_result=NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED), - ), - ] - - event_queue: queue.Queue = queue.Queue() - for e in events: - event_queue.put(e) - - coordinator = _StubExecutionCoordinator() - event_handler = _PauseStubEventHandler(coordinator) - - dispatcher = Dispatcher( - event_queue=event_queue, - event_handler=event_handler, - execution_coordinator=coordinator, - ) - - dispatcher._dispatcher_loop() - - # ensure all events are drained. - assert event_queue.empty() diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_answer_end_with_text.py b/api/tests/unit_tests/core/workflow/graph_engine/test_answer_end_with_text.py deleted file mode 100644 index 7af6b26d87e..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_answer_end_with_text.py +++ /dev/null @@ -1,37 +0,0 @@ -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_answer_end_with_text(): - fixture_name = "answer_end_with_text" - case = WorkflowTestCase( - fixture_name, - query="Hello, AI!", - expected_outputs={"answer": "prefixHello, AI!suffix"}, - expected_event_sequence=[ - GraphRunStartedEvent, - # Start - NodeRunStartedEvent, - # The chunks are now emitted as the Answer node processes them - # since sys.query is a special selector that gets attributed to - # the active response node - NodeRunStreamChunkEvent, # prefix - NodeRunStreamChunkEvent, # sys.query - NodeRunStreamChunkEvent, # suffix - NodeRunSucceededEvent, - # Answer - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - ) - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_answer_order_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_answer_order_workflow.py deleted file mode 100644 index 6569439b568..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_answer_order_workflow.py +++ /dev/null @@ -1,28 +0,0 @@ -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - -LLM_NODE_ID = "1759052580454" - - -def test_answer_nodes_emit_in_order() -> None: - mock_config = ( - MockConfigBuilder() - .with_llm_response("unused default") - .with_node_output(LLM_NODE_ID, {"text": "mocked llm text"}) - .build() - ) - - expected_answer = "--- answer 1 ---\n\nfoo\n--- answer 2 ---\n\nmocked llm text\n" - - case = WorkflowTestCase( - fixture_path="test-answer-order", - query="", - expected_outputs={"answer": expected_answer}, - use_auto_mock=True, - mock_config=mock_config, - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - - assert result.success, result.error diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_array_iteration_formatting_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_array_iteration_formatting_workflow.py deleted file mode 100644 index 05ec565def6..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_array_iteration_formatting_workflow.py +++ /dev/null @@ -1,24 +0,0 @@ -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_array_iteration_formatting_workflow(): - """ - Validate Iteration node processes [1,2,3] into formatted strings. - - Fixture description expects: - {"output": ["output: 1", "output: 2", "output: 3"]} - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="array_iteration_formatting_workflow", - inputs={}, - expected_outputs={"output": ["output: 1", "output: 2", "output: 3"]}, - description="Iteration formats numbers into strings", - use_auto_mock=True, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Iteration workflow failed: {result.error}" - assert result.actual_outputs == test_case.expected_outputs diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_auto_mock_system.py b/api/tests/unit_tests/core/workflow/graph_engine/test_auto_mock_system.py deleted file mode 100644 index fc0d22f7396..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_auto_mock_system.py +++ /dev/null @@ -1,392 +0,0 @@ -""" -Tests for the auto-mock system. - -This module contains tests that validate the auto-mock functionality -for workflows containing nodes that require third-party services. -""" - -import pytest - -from dify_graph.enums import BuiltinNodeTypes -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig, MockConfigBuilder, NodeMockConfig -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_simple_llm_workflow_with_auto_mock(): - """Test that a simple LLM workflow runs successfully with auto-mocking.""" - runner = TableTestRunner() - - # Create mock configuration - mock_config = MockConfigBuilder().with_llm_response("This is a test response from mocked LLM").build() - - test_case = WorkflowTestCase( - fixture_path="basic_llm_chat_workflow", - inputs={"query": "Hello, how are you?"}, - expected_outputs={"answer": "This is a test response from mocked LLM"}, - description="Simple LLM workflow with auto-mock", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - assert result.actual_outputs is not None - assert "answer" in result.actual_outputs - assert result.actual_outputs["answer"] == "This is a test response from mocked LLM" - - -def test_llm_workflow_with_custom_node_output(): - """Test LLM workflow with custom output for specific node.""" - runner = TableTestRunner() - - # Create mock configuration with custom output for specific node - mock_config = MockConfig() - mock_config.set_node_outputs( - "llm_node", - { - "text": "Custom response for this specific node", - "usage": { - "prompt_tokens": 20, - "completion_tokens": 10, - "total_tokens": 30, - }, - "finish_reason": "stop", - }, - ) - - test_case = WorkflowTestCase( - fixture_path="basic_llm_chat_workflow", - inputs={"query": "Test query"}, - expected_outputs={"answer": "Custom response for this specific node"}, - description="LLM workflow with custom node output", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - assert result.actual_outputs is not None - assert result.actual_outputs["answer"] == "Custom response for this specific node" - - -def test_http_tool_workflow_with_auto_mock(): - """Test workflow with HTTP request and tool nodes using auto-mock.""" - runner = TableTestRunner() - - # Create mock configuration - mock_config = MockConfig() - mock_config.set_node_outputs( - "http_node", - { - "status_code": 200, - "body": '{"key": "value", "number": 42}', - "headers": {"content-type": "application/json"}, - }, - ) - mock_config.set_node_outputs( - "tool_node", - { - "result": {"key": "value", "number": 42}, - }, - ) - - test_case = WorkflowTestCase( - fixture_path="http_request_with_json_tool_workflow", - inputs={"url": "https://api.example.com/data"}, - expected_outputs={ - "status_code": 200, - "parsed_data": {"key": "value", "number": 42}, - }, - description="HTTP and Tool workflow with auto-mock", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - assert result.actual_outputs is not None - assert result.actual_outputs["status_code"] == 200 - assert result.actual_outputs["parsed_data"] == {"key": "value", "number": 42} - - -def test_workflow_with_simulated_node_error(): - """Test that workflows handle simulated node errors correctly.""" - runner = TableTestRunner() - - # Create mock configuration with error - mock_config = MockConfig() - mock_config.set_node_error("llm_node", "Simulated LLM API error") - - test_case = WorkflowTestCase( - fixture_path="basic_llm_chat_workflow", - inputs={"query": "This should fail"}, - expected_outputs={}, # We expect failure, so no outputs - description="LLM workflow with simulated error", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - # The workflow should fail due to the simulated error - assert not result.success - assert result.error is not None - - -def test_workflow_with_mock_delays(): - """Test that mock delays work correctly.""" - runner = TableTestRunner() - - # Create mock configuration with delays - mock_config = MockConfig(simulate_delays=True) - node_config = NodeMockConfig( - node_id="llm_node", - outputs={"text": "Response after delay"}, - delay=0.1, # 100ms delay - ) - mock_config.set_node_config("llm_node", node_config) - - test_case = WorkflowTestCase( - fixture_path="basic_llm_chat_workflow", - inputs={"query": "Test with delay"}, - expected_outputs={"answer": "Response after delay"}, - description="LLM workflow with simulated delay", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - # Execution time should be at least the delay - assert result.execution_time >= 0.1 - - -def test_mock_config_builder(): - """Test the MockConfigBuilder fluent interface.""" - config = ( - MockConfigBuilder() - .with_llm_response("LLM response") - .with_agent_response("Agent response") - .with_tool_response({"tool": "output"}) - .with_retrieval_response("Retrieval content") - .with_http_response({"status_code": 201, "body": "created"}) - .with_node_output("node1", {"output": "value"}) - .with_node_error("node2", "error message") - .with_delays(True) - .build() - ) - - assert config.default_llm_response == "LLM response" - assert config.default_agent_response == "Agent response" - assert config.default_tool_response == {"tool": "output"} - assert config.default_retrieval_response == "Retrieval content" - assert config.default_http_response == {"status_code": 201, "body": "created"} - assert config.simulate_delays is True - - node1_config = config.get_node_config("node1") - assert node1_config is not None - assert node1_config.outputs == {"output": "value"} - - node2_config = config.get_node_config("node2") - assert node2_config is not None - assert node2_config.error == "error message" - - -def test_mock_factory_node_type_detection(): - """Test that MockNodeFactory correctly identifies nodes to mock.""" - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.runtime import GraphRuntimeState, VariablePool - - from .test_mock_factory import MockNodeFactory - - graph_init_params = build_test_graph_init_params( - workflow_id="test", - graph_config={}, - tenant_id="test", - app_id="test", - user_id="test", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.SERVICE_API, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=None, - ) - - # Test that third-party service nodes are identified for mocking - assert factory.should_mock_node(BuiltinNodeTypes.LLM) - assert factory.should_mock_node(BuiltinNodeTypes.AGENT) - assert factory.should_mock_node(BuiltinNodeTypes.TOOL) - assert factory.should_mock_node(BuiltinNodeTypes.KNOWLEDGE_RETRIEVAL) - assert factory.should_mock_node(BuiltinNodeTypes.HTTP_REQUEST) - assert factory.should_mock_node(BuiltinNodeTypes.PARAMETER_EXTRACTOR) - assert factory.should_mock_node(BuiltinNodeTypes.DOCUMENT_EXTRACTOR) - - # Test that CODE and TEMPLATE_TRANSFORM are mocked (they require SSRF proxy) - assert factory.should_mock_node(BuiltinNodeTypes.CODE) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Test that non-service nodes are not mocked - assert not factory.should_mock_node(BuiltinNodeTypes.START) - assert not factory.should_mock_node(BuiltinNodeTypes.END) - assert not factory.should_mock_node(BuiltinNodeTypes.IF_ELSE) - assert not factory.should_mock_node(BuiltinNodeTypes.VARIABLE_AGGREGATOR) - - -def test_custom_mock_handler(): - """Test using a custom handler function for mock outputs.""" - runner = TableTestRunner() - - # Custom handler that modifies output based on input - def custom_llm_handler(node) -> dict: - # In a real scenario, we could access node.graph_runtime_state.variable_pool - # to get the actual inputs - return { - "text": "Custom handler response", - "usage": { - "prompt_tokens": 5, - "completion_tokens": 3, - "total_tokens": 8, - }, - "finish_reason": "stop", - } - - mock_config = MockConfig() - node_config = NodeMockConfig( - node_id="llm_node", - custom_handler=custom_llm_handler, - ) - mock_config.set_node_config("llm_node", node_config) - - test_case = WorkflowTestCase( - fixture_path="basic_llm_chat_workflow", - inputs={"query": "Test custom handler"}, - expected_outputs={"answer": "Custom handler response"}, - description="LLM workflow with custom handler", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - assert result.actual_outputs["answer"] == "Custom handler response" - - -def test_workflow_without_auto_mock(): - """Test that workflows work normally without auto-mock enabled.""" - runner = TableTestRunner() - - # This test uses the echo workflow which doesn't need external services - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "Test without mock"}, - expected_outputs={"query": "Test without mock"}, - description="Echo workflow without auto-mock", - use_auto_mock=False, # Auto-mock disabled - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed: {result.error}" - assert result.actual_outputs["query"] == "Test without mock" - - -def test_register_custom_mock_node(): - """Test registering a custom mock implementation for a node type.""" - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.nodes.template_transform import TemplateTransformNode - from dify_graph.runtime import GraphRuntimeState, VariablePool - - from .test_mock_factory import MockNodeFactory - - # Create a custom mock for TemplateTransformNode - class MockTemplateTransformNode(TemplateTransformNode): - def _run(self): - # Custom mock implementation - pass - - graph_init_params = build_test_graph_init_params( - workflow_id="test", - graph_config={}, - tenant_id="test", - app_id="test", - user_id="test", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.SERVICE_API, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=None, - ) - - # TEMPLATE_TRANSFORM is mocked by default (requires SSRF proxy) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Unregister mock - factory.unregister_mock_node_type(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - assert not factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Re-register custom mock - factory.register_mock_node_type(BuiltinNodeTypes.TEMPLATE_TRANSFORM, MockTemplateTransformNode) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - -def test_default_config_by_node_type(): - """Test setting default configurations by node type.""" - mock_config = MockConfig() - - # Set default config for all LLM nodes - mock_config.set_default_config( - BuiltinNodeTypes.LLM, - { - "default_response": "Default LLM response for all nodes", - "temperature": 0.7, - }, - ) - - # Set default config for all HTTP nodes - mock_config.set_default_config( - BuiltinNodeTypes.HTTP_REQUEST, - { - "default_status": 200, - "default_timeout": 30, - }, - ) - - llm_config = mock_config.get_default_config(BuiltinNodeTypes.LLM) - assert llm_config["default_response"] == "Default LLM response for all nodes" - assert llm_config["temperature"] == 0.7 - - http_config = mock_config.get_default_config(BuiltinNodeTypes.HTTP_REQUEST) - assert http_config["default_status"] == 200 - assert http_config["default_timeout"] == 30 - - # Non-configured node type should return empty dict - tool_config = mock_config.get_default_config(BuiltinNodeTypes.TOOL) - assert tool_config == {} - - -if __name__ == "__main__": - # Run all tests - pytest.main([__file__, "-v"]) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_basic_chatflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_basic_chatflow.py deleted file mode 100644 index 30acbdaf3db..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_basic_chatflow.py +++ /dev/null @@ -1,41 +0,0 @@ -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_basic_chatflow(): - fixture_name = "basic_chatflow" - mock_config = MockConfigBuilder().with_llm_response("mocked llm response").build() - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=True, - mock_config=mock_config, - expected_outputs={"answer": "mocked llm response"}, - expected_event_sequence=[ - GraphRunStartedEvent, - # START - NodeRunStartedEvent, - NodeRunSucceededEvent, - # LLM - NodeRunStartedEvent, - ] - + [NodeRunStreamChunkEvent] * ("mocked llm response".count(" ") + 2) - + [ - NodeRunSucceededEvent, - # ANSWER - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py b/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py deleted file mode 100644 index 765c4deba32..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py +++ /dev/null @@ -1,267 +0,0 @@ -"""Test the command system for GraphEngine control.""" - -import time -from unittest.mock import MagicMock - -from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY, GraphInitParams -from dify_graph.entities.pause_reason import SchedulingPause -from dify_graph.graph import Graph -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_engine.entities.commands import ( - AbortCommand, - CommandType, - PauseCommand, - UpdateVariablesCommand, - VariableUpdate, -) -from dify_graph.graph_events import GraphRunAbortedEvent, GraphRunPausedEvent, GraphRunStartedEvent -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.variables import IntegerVariable, StringVariable - - -def test_abort_command(): - """Test that GraphEngine properly handles abort commands.""" - - # Create shared GraphRuntimeState - shared_runtime_state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time.perf_counter()) - - # Create a minimal mock graph - mock_graph = MagicMock(spec=Graph) - mock_graph.nodes = {} - mock_graph.edges = {} - mock_graph.root_node = MagicMock() - mock_graph.root_node.id = "start" - - # Create mock nodes with required attributes - using shared runtime state - start_node = StartNode( - id="start", - config={"id": "start", "data": {"title": "start", "variables": []}}, - graph_init_params=GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.DEBUGGER, - } - }, - call_depth=0, - ), - graph_runtime_state=shared_runtime_state, - ) - mock_graph.nodes["start"] = start_node - - # Mock graph methods - mock_graph.get_outgoing_edges = MagicMock(return_value=[]) - mock_graph.get_incoming_edges = MagicMock(return_value=[]) - - # Create command channel - command_channel = InMemoryChannel() - - # Create GraphEngine with same shared runtime state - engine = GraphEngine( - workflow_id="test_workflow", - graph=mock_graph, - graph_runtime_state=shared_runtime_state, # Use shared instance - command_channel=command_channel, - config=GraphEngineConfig(), - ) - - # Send abort command before starting - abort_command = AbortCommand(reason="Test abort") - command_channel.send_command(abort_command) - - # Run engine and collect events - events = list(engine.run()) - - # Verify we get start and abort events - assert any(isinstance(e, GraphRunStartedEvent) for e in events) - assert any(isinstance(e, GraphRunAbortedEvent) for e in events) - - # Find the abort event and check its reason - abort_events = [e for e in events if isinstance(e, GraphRunAbortedEvent)] - assert len(abort_events) == 1 - assert abort_events[0].reason is not None - assert "aborted: test abort" in abort_events[0].reason.lower() - - -def test_redis_channel_serialization(): - """Test that Redis channel properly serializes and deserializes commands.""" - import json - from unittest.mock import MagicMock - - # Mock redis client - mock_redis = MagicMock() - mock_pipeline = MagicMock() - mock_redis.pipeline.return_value.__enter__ = MagicMock(return_value=mock_pipeline) - mock_redis.pipeline.return_value.__exit__ = MagicMock(return_value=None) - - from dify_graph.graph_engine.command_channels.redis_channel import RedisChannel - - # Create channel with a specific key - channel = RedisChannel(mock_redis, channel_key="workflow:123:commands") - - # Test sending a command - abort_command = AbortCommand(reason="Test abort") - channel.send_command(abort_command) - - # Verify redis methods were called - mock_pipeline.rpush.assert_called_once() - mock_pipeline.expire.assert_called_once() - - # Verify the serialized data - call_args = mock_pipeline.rpush.call_args - key = call_args[0][0] - command_json = call_args[0][1] - - assert key == "workflow:123:commands" - - # Verify JSON structure - command_data = json.loads(command_json) - assert command_data["command_type"] == "abort" - assert command_data["reason"] == "Test abort" - - # Test pause command serialization - pause_command = PauseCommand(reason="User requested pause") - channel.send_command(pause_command) - - assert len(mock_pipeline.rpush.call_args_list) == 2 - second_call_args = mock_pipeline.rpush.call_args_list[1] - pause_command_json = second_call_args[0][1] - pause_command_data = json.loads(pause_command_json) - assert pause_command_data["command_type"] == CommandType.PAUSE.value - assert pause_command_data["reason"] == "User requested pause" - - -def test_pause_command(): - """Test that GraphEngine properly handles pause commands.""" - - shared_runtime_state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time.perf_counter()) - - mock_graph = MagicMock(spec=Graph) - mock_graph.nodes = {} - mock_graph.edges = {} - mock_graph.root_node = MagicMock() - mock_graph.root_node.id = "start" - - start_node = StartNode( - id="start", - config={"id": "start", "data": {"title": "start", "variables": []}}, - graph_init_params=GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.DEBUGGER, - } - }, - call_depth=0, - ), - graph_runtime_state=shared_runtime_state, - ) - mock_graph.nodes["start"] = start_node - - mock_graph.get_outgoing_edges = MagicMock(return_value=[]) - mock_graph.get_incoming_edges = MagicMock(return_value=[]) - - command_channel = InMemoryChannel() - - engine = GraphEngine( - workflow_id="test_workflow", - graph=mock_graph, - graph_runtime_state=shared_runtime_state, - command_channel=command_channel, - config=GraphEngineConfig(), - ) - - pause_command = PauseCommand(reason="User requested pause") - command_channel.send_command(pause_command) - - events = list(engine.run()) - - assert any(isinstance(e, GraphRunStartedEvent) for e in events) - pause_events = [e for e in events if isinstance(e, GraphRunPausedEvent)] - assert len(pause_events) == 1 - assert pause_events[0].reasons == [SchedulingPause(message="User requested pause")] - - graph_execution = engine.graph_runtime_state.graph_execution - assert graph_execution.pause_reasons == [SchedulingPause(message="User requested pause")] - - -def test_update_variables_command_updates_pool(): - """Test that GraphEngine updates variable pool via update variables command.""" - - shared_runtime_state = GraphRuntimeState(variable_pool=VariablePool(), start_at=time.perf_counter()) - shared_runtime_state.variable_pool.add(("node1", "foo"), "old value") - - mock_graph = MagicMock(spec=Graph) - mock_graph.nodes = {} - mock_graph.edges = {} - mock_graph.root_node = MagicMock() - mock_graph.root_node.id = "start" - - start_node = StartNode( - id="start", - config={"id": "start", "data": {"title": "start", "variables": []}}, - graph_init_params=GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.DEBUGGER, - } - }, - call_depth=0, - ), - graph_runtime_state=shared_runtime_state, - ) - mock_graph.nodes["start"] = start_node - - mock_graph.get_outgoing_edges = MagicMock(return_value=[]) - mock_graph.get_incoming_edges = MagicMock(return_value=[]) - - command_channel = InMemoryChannel() - - engine = GraphEngine( - workflow_id="test_workflow", - graph=mock_graph, - graph_runtime_state=shared_runtime_state, - command_channel=command_channel, - config=GraphEngineConfig(), - ) - - update_command = UpdateVariablesCommand( - updates=[ - VariableUpdate( - value=StringVariable(name="foo", value="new value", selector=["node1", "foo"]), - ), - VariableUpdate( - value=IntegerVariable(name="bar", value=123, selector=["node2", "bar"]), - ), - ] - ) - command_channel.send_command(update_command) - - list(engine.run()) - - updated_existing = shared_runtime_state.variable_pool.get(["node1", "foo"]) - added_new = shared_runtime_state.variable_pool.get(["node2", "bar"]) - - assert updated_existing is not None - assert updated_existing.value == "new value" - assert added_new is not None - assert added_new.value == 123 diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_complex_branch_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_complex_branch_workflow.py deleted file mode 100644 index 3a9a0b18bcb..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_complex_branch_workflow.py +++ /dev/null @@ -1,134 +0,0 @@ -""" -Test suite for complex branch workflow with parallel execution and conditional routing. - -This test suite validates the behavior of a workflow that: -1. Executes nodes in parallel (IF/ELSE and LLM branches) -2. Routes based on conditional logic (query containing 'hello') -3. Handles multiple answer nodes with different outputs -""" - -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, -) - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -class TestComplexBranchWorkflow: - """Test suite for complex branch workflow with parallel execution.""" - - def setup_method(self): - """Set up test environment before each test method.""" - self.runner = TableTestRunner() - self.fixture_path = "test_complex_branch" - - def test_hello_branch_with_llm(self): - """ - Test when query contains 'hello' - should trigger true branch. - Both IF/ELSE and LLM should execute in parallel. - """ - mock_text_1 = "This is a mocked LLM response for hello world" - test_cases = [ - WorkflowTestCase( - fixture_path=self.fixture_path, - query="hello world", - expected_outputs={ - "answer": f"contains 'hello'{mock_text_1}", - }, - description="Basic hello case with parallel LLM execution", - use_auto_mock=True, - mock_config=(MockConfigBuilder().with_node_output("1755502777322", {"text": mock_text_1}).build()), - ), - WorkflowTestCase( - fixture_path=self.fixture_path, - query="say hello to everyone", - expected_outputs={ - "answer": "contains 'hello'Mocked response for greeting", - }, - description="Hello in middle of sentence", - use_auto_mock=True, - mock_config=( - MockConfigBuilder() - .with_node_output("1755502777322", {"text": "Mocked response for greeting"}) - .build() - ), - ), - ] - - suite_result = self.runner.run_table_tests(test_cases) - - for result in suite_result.results: - assert result.success, f"Test '{result.test_case.description}' failed: {result.error}" - assert result.actual_outputs - assert any(isinstance(event, GraphRunStartedEvent) for event in result.events) - assert any(isinstance(event, GraphRunSucceededEvent) for event in result.events) - - start_index = next( - idx for idx, event in enumerate(result.events) if isinstance(event, GraphRunStartedEvent) - ) - success_index = max( - idx for idx, event in enumerate(result.events) if isinstance(event, GraphRunSucceededEvent) - ) - assert start_index < success_index - - started_node_ids = {event.node_id for event in result.events if isinstance(event, NodeRunStartedEvent)} - assert {"1755502773326", "1755502777322"}.issubset(started_node_ids), ( - f"Branch or LLM nodes missing in events: {started_node_ids}" - ) - - assert any(isinstance(event, NodeRunStreamChunkEvent) for event in result.events), ( - "Expected streaming chunks from LLM execution" - ) - - llm_start_index = next( - idx - for idx, event in enumerate(result.events) - if isinstance(event, NodeRunStartedEvent) and event.node_id == "1755502777322" - ) - assert any( - idx > llm_start_index and isinstance(event, NodeRunStreamChunkEvent) - for idx, event in enumerate(result.events) - ), "Streaming chunks should follow LLM node start" - - def test_non_hello_branch_with_llm(self): - """ - Test when query doesn't contain 'hello' - should trigger false branch. - LLM output should be used as the final answer. - """ - test_cases = [ - WorkflowTestCase( - fixture_path=self.fixture_path, - query="goodbye world", - expected_outputs={ - "answer": "Mocked LLM response for goodbye", - }, - description="Goodbye case - false branch with LLM output", - use_auto_mock=True, - mock_config=( - MockConfigBuilder() - .with_node_output("1755502777322", {"text": "Mocked LLM response for goodbye"}) - .build() - ), - ), - WorkflowTestCase( - fixture_path=self.fixture_path, - query="test message", - expected_outputs={ - "answer": "Mocked response for test", - }, - description="Regular message - false branch", - use_auto_mock=True, - mock_config=( - MockConfigBuilder().with_node_output("1755502777322", {"text": "Mocked response for test"}).build() - ), - ), - ] - - suite_result = self.runner.run_table_tests(test_cases) - - for result in suite_result.results: - assert result.success, f"Test '{result.test_case.description}' failed: {result.error}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py deleted file mode 100644 index 76bf179f330..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py +++ /dev/null @@ -1,220 +0,0 @@ -""" -Test for streaming output workflow behavior. - -This test validates that: -- When blocking == 1: No NodeRunStreamChunkEvent (flow through Template node) -- When blocking != 1: NodeRunStreamChunkEvent present (direct LLM to End output) -""" - -from dify_graph.enums import BuiltinNodeTypes -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_events import ( - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_table_runner import TableTestRunner - - -def test_streaming_output_with_blocking_equals_one(): - """ - Test workflow when blocking == 1 (LLM → Template → End). - - Template node doesn't produce streaming output, so no NodeRunStreamChunkEvent should be present. - This test should FAIL according to requirements. - """ - runner = TableTestRunner() - - # Load the workflow configuration - fixture_data = runner.workflow_runner.load_fixture("conditional_streaming_vs_template_workflow") - - # Create graph from fixture with auto-mock enabled - graph, graph_runtime_state = runner.workflow_runner.create_graph_from_fixture( - fixture_data=fixture_data, - inputs={"query": "Hello, how are you?", "blocking": 1}, - use_mock_factory=True, - ) - - # Create and run the engine - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Execute the workflow - events = list(engine.run()) - - # Check for successful completion - success_events = [e for e in events if isinstance(e, GraphRunSucceededEvent)] - assert len(success_events) > 0, "Workflow should complete successfully" - - # Check for streaming events - stream_chunk_events = [e for e in events if isinstance(e, NodeRunStreamChunkEvent)] - stream_chunk_count = len(stream_chunk_events) - - # According to requirements, we expect exactly 3 streaming events from the End node - # 1. User query - # 2. Newline - # 3. Template output (which contains the LLM response) - assert stream_chunk_count == 3, f"Expected 3 streaming events when blocking=1, but got {stream_chunk_count}" - - first_chunk, second_chunk, third_chunk = stream_chunk_events[0], stream_chunk_events[1], stream_chunk_events[2] - assert first_chunk.chunk == "Hello, how are you?", ( - f"Expected first chunk to be user input, but got {first_chunk.chunk}" - ) - assert second_chunk.chunk == "\n", f"Expected second chunk to be newline, but got {second_chunk.chunk}" - # Third chunk will be the template output with the mock LLM response - assert isinstance(third_chunk.chunk, str), f"Expected third chunk to be string, but got {type(third_chunk.chunk)}" - - # Find indices of first LLM success event and first stream chunk event - llm2_start_index = next( - ( - i - for i, e in enumerate(events) - if isinstance(e, NodeRunSucceededEvent) and e.node_type == BuiltinNodeTypes.LLM - ), - -1, - ) - first_chunk_index = next( - (i for i, e in enumerate(events) if isinstance(e, NodeRunStreamChunkEvent)), - -1, - ) - - assert first_chunk_index < llm2_start_index, ( - f"Expected first chunk before LLM2 start, but got {first_chunk_index} and {llm2_start_index}" - ) - - # Check that NodeRunStreamChunkEvent contains 'query' should has same id with Start NodeRunStartedEvent - start_node_id = graph.root_node.id - start_events = [e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_id == start_node_id] - assert len(start_events) == 1, f"Expected 1 start event for node {start_node_id}, but got {len(start_events)}" - start_event = start_events[0] - query_chunk_events = [e for e in stream_chunk_events if e.chunk == "Hello, how are you?"] - assert all(e.id == start_event.id for e in query_chunk_events), "Expected all query chunk events to have same id" - - # Check all Template's NodeRunStreamChunkEvent should has same id with Template's NodeRunStartedEvent - start_events = [ - e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_type == BuiltinNodeTypes.TEMPLATE_TRANSFORM - ] - template_chunk_events = [e for e in stream_chunk_events if e.node_type == BuiltinNodeTypes.TEMPLATE_TRANSFORM] - assert len(template_chunk_events) == 1, f"Expected 1 template chunk event, but got {len(template_chunk_events)}" - assert all(e.id in [se.id for se in start_events] for e in template_chunk_events), ( - "Expected all Template chunk events to have same id with Template's NodeRunStartedEvent" - ) - - # Check that NodeRunStreamChunkEvent contains '\n' is from the End node - end_events = [e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_type == BuiltinNodeTypes.END] - assert len(end_events) == 1, f"Expected 1 end event, but got {len(end_events)}" - newline_chunk_events = [e for e in stream_chunk_events if e.chunk == "\n"] - assert len(newline_chunk_events) == 1, f"Expected 1 newline chunk event, but got {len(newline_chunk_events)}" - # The newline chunk should be from the End node (check node_id, not execution id) - assert all(e.node_id == end_events[0].node_id for e in newline_chunk_events), ( - "Expected all newline chunk events to be from End node" - ) - - -def test_streaming_output_with_blocking_not_equals_one(): - """ - Test workflow when blocking != 1 (LLM → End directly). - - End node should produce streaming output with NodeRunStreamChunkEvent. - This test should PASS according to requirements. - """ - runner = TableTestRunner() - - # Load the workflow configuration - fixture_data = runner.workflow_runner.load_fixture("conditional_streaming_vs_template_workflow") - - # Create graph from fixture with auto-mock enabled - graph, graph_runtime_state = runner.workflow_runner.create_graph_from_fixture( - fixture_data=fixture_data, - inputs={"query": "Hello, how are you?", "blocking": 2}, - use_mock_factory=True, - ) - - # Create and run the engine - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Execute the workflow - events = list(engine.run()) - - # Check for successful completion - success_events = [e for e in events if isinstance(e, GraphRunSucceededEvent)] - assert len(success_events) > 0, "Workflow should complete successfully" - - # Check for streaming events - expecting streaming events - stream_chunk_events = [e for e in events if isinstance(e, NodeRunStreamChunkEvent)] - stream_chunk_count = len(stream_chunk_events) - - # This assertion should PASS according to requirements - assert stream_chunk_count > 0, f"Expected streaming events when blocking!=1, but got {stream_chunk_count}" - - # We should have at least 2 chunks (query and newline) - assert stream_chunk_count >= 2, f"Expected at least 2 streaming events, but got {stream_chunk_count}" - - first_chunk, second_chunk = stream_chunk_events[0], stream_chunk_events[1] - assert first_chunk.chunk == "Hello, how are you?", ( - f"Expected first chunk to be user input, but got {first_chunk.chunk}" - ) - assert second_chunk.chunk == "\n", f"Expected second chunk to be newline, but got {second_chunk.chunk}" - - # Find indices of first LLM success event and first stream chunk event - llm2_start_index = next( - ( - i - for i, e in enumerate(events) - if isinstance(e, NodeRunSucceededEvent) and e.node_type == BuiltinNodeTypes.LLM - ), - -1, - ) - first_chunk_index = next( - (i for i, e in enumerate(events) if isinstance(e, NodeRunStreamChunkEvent)), - -1, - ) - - assert first_chunk_index < llm2_start_index, ( - f"Expected first chunk before LLM2 start, but got {first_chunk_index} and {llm2_start_index}" - ) - - # With auto-mock, the LLM will produce mock responses - just verify we have streaming chunks - # and they are strings - for chunk_event in stream_chunk_events[2:]: - assert isinstance(chunk_event.chunk, str), f"Expected chunk to be string, but got {type(chunk_event.chunk)}" - - # Check that NodeRunStreamChunkEvent contains 'query' should has same id with Start NodeRunStartedEvent - start_node_id = graph.root_node.id - start_events = [e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_id == start_node_id] - assert len(start_events) == 1, f"Expected 1 start event for node {start_node_id}, but got {len(start_events)}" - start_event = start_events[0] - query_chunk_events = [e for e in stream_chunk_events if e.chunk == "Hello, how are you?"] - assert all(e.id == start_event.id for e in query_chunk_events), "Expected all query chunk events to have same id" - - # Check all LLM's NodeRunStreamChunkEvent should be from LLM nodes - start_events = [e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_type == BuiltinNodeTypes.LLM] - llm_chunk_events = [e for e in stream_chunk_events if e.node_type == BuiltinNodeTypes.LLM] - llm_node_ids = {se.node_id for se in start_events} - assert all(e.node_id in llm_node_ids for e in llm_chunk_events), ( - "Expected all LLM chunk events to be from LLM nodes" - ) - - # Check that NodeRunStreamChunkEvent contains '\n' is from the End node - end_events = [e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_type == BuiltinNodeTypes.END] - assert len(end_events) == 1, f"Expected 1 end event, but got {len(end_events)}" - newline_chunk_events = [e for e in stream_chunk_events if e.chunk == "\n"] - assert len(newline_chunk_events) == 1, f"Expected 1 newline chunk event, but got {len(newline_chunk_events)}" - # The newline chunk should be from the End node (check node_id, not execution id) - assert all(e.node_id == end_events[0].node_id for e in newline_chunk_events), ( - "Expected all newline chunk events to be from End node" - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_database_utils.py b/api/tests/unit_tests/core/workflow/graph_engine/test_database_utils.py deleted file mode 100644 index ae7dd48bb16..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_database_utils.py +++ /dev/null @@ -1,46 +0,0 @@ -""" -Utilities for detecting if database service is available for workflow tests. -""" - -import psycopg2 -import pytest - -from configs import dify_config - - -def is_database_available() -> bool: - """ - Check if the database service is available by attempting to connect to it. - - Returns: - True if database is available, False otherwise. - """ - try: - # Try to establish a database connection using a context manager - with psycopg2.connect( - host=dify_config.DB_HOST, - port=dify_config.DB_PORT, - database=dify_config.DB_DATABASE, - user=dify_config.DB_USERNAME, - password=dify_config.DB_PASSWORD, - connect_timeout=2, # 2 second timeout - ) as conn: - pass # Connection established and will be closed automatically - return True - except (psycopg2.OperationalError, psycopg2.Error): - return False - - -def skip_if_database_unavailable(): - """ - Pytest skip decorator that skips tests when database service is unavailable. - - Usage: - @skip_if_database_unavailable() - def test_my_workflow(): - ... - """ - return pytest.mark.skipif( - not is_database_available(), - reason="Database service is not available (connection refused or authentication failed)", - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_dispatcher_pause_drain.py b/api/tests/unit_tests/core/workflow/graph_engine/test_dispatcher_pause_drain.py deleted file mode 100644 index 778dad59527..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_dispatcher_pause_drain.py +++ /dev/null @@ -1,72 +0,0 @@ -import queue -from datetime import datetime - -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.graph_engine.orchestration.dispatcher import Dispatcher -from dify_graph.graph_events import NodeRunSucceededEvent -from dify_graph.node_events import NodeRunResult - - -class StubExecutionCoordinator: - def __init__(self, paused: bool) -> None: - self._paused = paused - self.mark_complete_called = False - self.failed_error: Exception | None = None - - @property - def aborted(self) -> bool: - return False - - @property - def paused(self) -> bool: - return self._paused - - @property - def execution_complete(self) -> bool: - return False - - def check_scaling(self) -> None: - return None - - def process_commands(self) -> None: - return None - - def mark_complete(self) -> None: - self.mark_complete_called = True - - def mark_failed(self, error: Exception) -> None: - self.failed_error = error - - -class StubEventHandler: - def __init__(self) -> None: - self.events: list[object] = [] - - def dispatch(self, event: object) -> None: - self.events.append(event) - - -def test_dispatcher_drains_events_when_paused() -> None: - event_queue: queue.Queue = queue.Queue() - event = NodeRunSucceededEvent( - id="exec-1", - node_id="node-1", - node_type=BuiltinNodeTypes.START, - start_at=datetime.utcnow(), - node_run_result=NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED), - ) - event_queue.put(event) - - handler = StubEventHandler() - coordinator = StubExecutionCoordinator(paused=True) - dispatcher = Dispatcher( - event_queue=event_queue, - event_handler=handler, - execution_coordinator=coordinator, - event_emitter=None, - ) - - dispatcher._dispatcher_loop() - - assert handler.events == [event] - assert coordinator.mark_complete_called is True diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_end_node_without_value_type.py b/api/tests/unit_tests/core/workflow/graph_engine/test_end_node_without_value_type.py deleted file mode 100644 index c87dc75b95e..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_end_node_without_value_type.py +++ /dev/null @@ -1,60 +0,0 @@ -""" -Test case for end node without value_type field (backward compatibility). - -This test validates that end nodes work correctly even when the value_type -field is missing from the output configuration, ensuring backward compatibility -with older workflow definitions. -""" - -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_end_node_without_value_type_field(): - """ - Test that end node works without explicit value_type field. - - The fixture implements a simple workflow that: - 1. Takes a query input from start node - 2. Passes it directly to end node - 3. End node outputs the value without specifying value_type - 4. Should correctly infer the type and output the value - - This ensures backward compatibility with workflow definitions - created before value_type became a required field. - """ - fixture_name = "end_node_without_value_type_field_workflow" - - case = WorkflowTestCase( - fixture_path=fixture_name, - inputs={"query": "test query"}, - expected_outputs={"query": "test query"}, - expected_event_sequence=[ - # Graph start - GraphRunStartedEvent, - # Start node - NodeRunStartedEvent, - NodeRunStreamChunkEvent, # Start node streams the input value - NodeRunSucceededEvent, - # End node - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Graph end - GraphRunSucceededEvent, - ], - description="End node without value_type field should work correctly", - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" - assert result.actual_outputs == {"query": "test query"}, ( - f"Expected output to be {{'query': 'test query'}}, got {result.actual_outputs}" - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_execution_coordinator.py b/api/tests/unit_tests/core/workflow/graph_engine/test_execution_coordinator.py deleted file mode 100644 index 35406997edf..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_execution_coordinator.py +++ /dev/null @@ -1,62 +0,0 @@ -"""Unit tests for the execution coordinator orchestration logic.""" - -from unittest.mock import MagicMock - -import pytest - -from dify_graph.graph_engine.command_processing.command_processor import CommandProcessor -from dify_graph.graph_engine.domain.graph_execution import GraphExecution -from dify_graph.graph_engine.graph_state_manager import GraphStateManager -from dify_graph.graph_engine.orchestration.execution_coordinator import ExecutionCoordinator -from dify_graph.graph_engine.worker_management.worker_pool import WorkerPool - - -def _build_coordinator(graph_execution: GraphExecution) -> tuple[ExecutionCoordinator, MagicMock, MagicMock]: - command_processor = MagicMock(spec=CommandProcessor) - state_manager = MagicMock(spec=GraphStateManager) - worker_pool = MagicMock(spec=WorkerPool) - - coordinator = ExecutionCoordinator( - graph_execution=graph_execution, - state_manager=state_manager, - command_processor=command_processor, - worker_pool=worker_pool, - ) - return coordinator, state_manager, worker_pool - - -def test_handle_pause_stops_workers_and_clears_state() -> None: - """Paused execution should stop workers and clear executing state.""" - graph_execution = GraphExecution(workflow_id="workflow") - graph_execution.start() - graph_execution.pause("Awaiting human input") - - coordinator, state_manager, worker_pool = _build_coordinator(graph_execution) - - coordinator.handle_pause_if_needed() - - worker_pool.stop.assert_called_once_with() - state_manager.clear_executing.assert_called_once_with() - - -def test_handle_pause_noop_when_execution_running() -> None: - """Running execution should not trigger pause handling.""" - graph_execution = GraphExecution(workflow_id="workflow") - graph_execution.start() - - coordinator, state_manager, worker_pool = _build_coordinator(graph_execution) - - coordinator.handle_pause_if_needed() - - worker_pool.stop.assert_not_called() - state_manager.clear_executing.assert_not_called() - - -def test_has_executing_nodes_requires_pause() -> None: - graph_execution = GraphExecution(workflow_id="workflow") - graph_execution.start() - - coordinator, _, _ = _build_coordinator(graph_execution) - - with pytest.raises(AssertionError): - coordinator.has_executing_nodes() diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py deleted file mode 100644 index 4e13177d2b9..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py +++ /dev/null @@ -1,770 +0,0 @@ -""" -Table-driven test framework for GraphEngine workflows. - -This file contains property-based tests and specific workflow tests. -The core test framework is in test_table_runner.py. -""" - -import time - -from hypothesis import HealthCheck, given, settings -from hypothesis import strategies as st - -from dify_graph.entities.base_node_data import DefaultValue, DefaultValueType -from dify_graph.enums import ErrorStrategy -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_events import ( - GraphRunPartialSucceededEvent, - GraphRunStartedEvent, - GraphRunSucceededEvent, -) - -# Import the test framework from the new module -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowRunner, WorkflowTestCase - - -# Property-based fuzzing tests for the start-end workflow -@given(query_input=st.text()) -@settings(max_examples=50, deadline=30000, suppress_health_check=[HealthCheck.too_slow]) -def test_echo_workflow_property_basic_strings(query_input): - """ - Property-based test: Echo workflow should return exactly what was input. - - This tests the fundamental property that for any string input, - the start-end workflow should echo it back unchanged. - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": query_input}, - expected_outputs={"query": query_input}, - description=f"Fuzzing test with input: {repr(query_input)[:50]}...", - ) - - result = runner.run_test_case(test_case) - - # Property: The workflow should complete successfully - assert result.success, f"Workflow failed with input {repr(query_input)}: {result.error}" - - # Property: Output should equal input (echo behavior) - assert result.actual_outputs - assert result.actual_outputs == {"query": query_input}, ( - f"Echo property violated. Input: {repr(query_input)}, " - f"Expected: {repr(query_input)}, Got: {repr(result.actual_outputs.get('query'))}" - ) - - -@given(query_input=st.text(min_size=0, max_size=1000)) -@settings(max_examples=30, deadline=20000) -def test_echo_workflow_property_bounded_strings(query_input): - """ - Property-based test with size bounds to test edge cases more efficiently. - - Tests strings up to 1000 characters to balance thoroughness with performance. - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": query_input}, - expected_outputs={"query": query_input}, - description=f"Bounded fuzzing test (len={len(query_input)})", - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed with bounded input: {result.error}" - assert result.actual_outputs == {"query": query_input} - - -@given( - query_input=st.one_of( - st.text(alphabet=st.characters(whitelist_categories=["Lu", "Ll", "Nd", "Po"])), # Letters, digits, punctuation - st.text(alphabet="🎉🌟💫⭐🔥💯🚀🎯"), # Emojis - st.text(alphabet="αβγδεζηθικλμνξοπρστυφχψω"), # Greek letters - st.text(alphabet="中文测试한국어日本語العربية"), # International characters - st.just(""), # Empty string - st.just(" " * 100), # Whitespace only - st.just("\n\t\r\f\v"), # Special whitespace chars - st.just('{"json": "like", "data": [1, 2, 3]}'), # JSON-like string - st.just("SELECT * FROM users; DROP TABLE users;--"), # SQL injection attempt - st.just(""), # XSS attempt - st.just("../../etc/passwd"), # Path traversal attempt - ) -) -@settings(max_examples=40, deadline=25000) -def test_echo_workflow_property_diverse_inputs(query_input): - """ - Property-based test with diverse input types including edge cases and security payloads. - - Tests various categories of potentially problematic inputs: - - Unicode characters from different languages - - Emojis and special symbols - - Whitespace variations - - Malicious payloads (SQL injection, XSS, path traversal) - - JSON-like structures - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": query_input}, - expected_outputs={"query": query_input}, - description=f"Diverse input fuzzing: {type(query_input).__name__}", - ) - - result = runner.run_test_case(test_case) - - # Property: System should handle all inputs gracefully (no crashes) - assert result.success, f"Workflow failed with diverse input {repr(query_input)}: {result.error}" - - # Property: Echo behavior must be preserved regardless of input type - assert result.actual_outputs == {"query": query_input} - - -@given(query_input=st.text(min_size=1000, max_size=5000)) -@settings(max_examples=10, deadline=60000) -def test_echo_workflow_property_large_inputs(query_input): - """ - Property-based test for large inputs to test memory and performance boundaries. - - Tests the system's ability to handle larger payloads efficiently. - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": query_input}, - expected_outputs={"query": query_input}, - description=f"Large input test (size: {len(query_input)} chars)", - timeout=45.0, # Longer timeout for large inputs - ) - - start_time = time.perf_counter() - result = runner.run_test_case(test_case) - execution_time = time.perf_counter() - start_time - - # Property: Large inputs should still work - assert result.success, f"Large input workflow failed: {result.error}" - - # Property: Echo behavior preserved for large inputs - assert result.actual_outputs == {"query": query_input} - - # Property: Performance should be reasonable even for large inputs - assert execution_time < 30.0, f"Large input took too long: {execution_time:.2f}s" - - -def test_echo_workflow_robustness_smoke_test(): - """ - Smoke test to ensure the basic workflow functionality works before fuzzing. - - This test uses a simple, known-good input to verify the test infrastructure - is working correctly before running the fuzzing tests. - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "smoke test"}, - expected_outputs={"query": "smoke test"}, - description="Smoke test for basic functionality", - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Smoke test failed: {result.error}" - assert result.actual_outputs == {"query": "smoke test"} - assert result.execution_time > 0 - - -def test_if_else_workflow_true_branch(): - """ - Test if-else workflow when input contains 'hello' (true branch). - - Should output {"true": input_query} when query contains "hello". - """ - runner = TableTestRunner() - - test_cases = [ - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hello world"}, - expected_outputs={"true": "hello world"}, - description="Basic hello case", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "say hello to everyone"}, - expected_outputs={"true": "say hello to everyone"}, - description="Hello in middle of sentence", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hello"}, - expected_outputs={"true": "hello"}, - description="Just hello", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hellohello"}, - expected_outputs={"true": "hellohello"}, - description="Multiple hello occurrences", - ), - ] - - suite_result = runner.run_table_tests(test_cases) - - for result in suite_result.results: - assert result.success, f"Test case '{result.test_case.description}' failed: {result.error}" - # Check that outputs contain ONLY the expected key (true branch) - assert result.actual_outputs == result.test_case.expected_outputs, ( - f"Expected only 'true' key in outputs for {result.test_case.description}. " - f"Expected: {result.test_case.expected_outputs}, Got: {result.actual_outputs}" - ) - - -def test_if_else_workflow_false_branch(): - """ - Test if-else workflow when input does not contain 'hello' (false branch). - - Should output {"false": input_query} when query does not contain "hello". - """ - runner = TableTestRunner() - - test_cases = [ - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "goodbye world"}, - expected_outputs={"false": "goodbye world"}, - description="Basic goodbye case", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hi there"}, - expected_outputs={"false": "hi there"}, - description="Simple greeting without hello", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": ""}, - expected_outputs={"false": ""}, - description="Empty string", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "test message"}, - expected_outputs={"false": "test message"}, - description="Regular message", - ), - ] - - suite_result = runner.run_table_tests(test_cases) - - for result in suite_result.results: - assert result.success, f"Test case '{result.test_case.description}' failed: {result.error}" - # Check that outputs contain ONLY the expected key (false branch) - assert result.actual_outputs == result.test_case.expected_outputs, ( - f"Expected only 'false' key in outputs for {result.test_case.description}. " - f"Expected: {result.test_case.expected_outputs}, Got: {result.actual_outputs}" - ) - - -def test_if_else_workflow_edge_cases(): - """ - Test if-else workflow edge cases and case sensitivity. - - Tests various edge cases including case sensitivity, similar words, etc. - """ - runner = TableTestRunner() - - test_cases = [ - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "Hello world"}, - expected_outputs={"false": "Hello world"}, - description="Capitalized Hello (case sensitive test)", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "HELLO"}, - expected_outputs={"false": "HELLO"}, - description="All caps HELLO (case sensitive test)", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "helllo"}, - expected_outputs={"false": "helllo"}, - description="Typo: helllo (with extra l)", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "helo"}, - expected_outputs={"false": "helo"}, - description="Typo: helo (missing l)", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hello123"}, - expected_outputs={"true": "hello123"}, - description="Hello with numbers", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": "hello!@#"}, - expected_outputs={"true": "hello!@#"}, - description="Hello with special characters", - ), - WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": " hello "}, - expected_outputs={"true": " hello "}, - description="Hello with surrounding spaces", - ), - ] - - suite_result = runner.run_table_tests(test_cases) - - for result in suite_result.results: - assert result.success, f"Test case '{result.test_case.description}' failed: {result.error}" - # Check that outputs contain ONLY the expected key - assert result.actual_outputs == result.test_case.expected_outputs, ( - f"Expected exact match for {result.test_case.description}. " - f"Expected: {result.test_case.expected_outputs}, Got: {result.actual_outputs}" - ) - - -@given(query_input=st.text()) -@settings(max_examples=50, deadline=30000, suppress_health_check=[HealthCheck.too_slow]) -def test_if_else_workflow_property_basic_strings(query_input): - """ - Property-based test: If-else workflow should output correct branch based on 'hello' content. - - This tests the fundamental property that for any string input: - - If input contains "hello", output should be {"true": input} - - If input doesn't contain "hello", output should be {"false": input} - """ - runner = TableTestRunner() - - # Determine expected output based on whether input contains "hello" - contains_hello = "hello" in query_input - expected_key = "true" if contains_hello else "false" - expected_outputs = {expected_key: query_input} - - test_case = WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": query_input}, - expected_outputs=expected_outputs, - description=f"Property test with input: {repr(query_input)[:50]}...", - ) - - result = runner.run_test_case(test_case) - - # Property: The workflow should complete successfully - assert result.success, f"Workflow failed with input {repr(query_input)}: {result.error}" - - # Property: Output should contain ONLY the expected key with correct value - assert result.actual_outputs == expected_outputs, ( - f"If-else property violated. Input: {repr(query_input)}, " - f"Expected: {expected_outputs}, Got: {result.actual_outputs}" - ) - - -@given(query_input=st.text(min_size=0, max_size=1000)) -@settings(max_examples=30, deadline=20000) -def test_if_else_workflow_property_bounded_strings(query_input): - """ - Property-based test with size bounds for if-else workflow. - - Tests strings up to 1000 characters to balance thoroughness with performance. - """ - runner = TableTestRunner() - - contains_hello = "hello" in query_input - expected_key = "true" if contains_hello else "false" - expected_outputs = {expected_key: query_input} - - test_case = WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": query_input}, - expected_outputs=expected_outputs, - description=f"Bounded if-else test (len={len(query_input)}, contains_hello={contains_hello})", - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Workflow failed with bounded input: {result.error}" - assert result.actual_outputs == expected_outputs - - -@given( - query_input=st.one_of( - st.text(alphabet=st.characters(whitelist_categories=["Lu", "Ll", "Nd", "Po"])), # Letters, digits, punctuation - st.text(alphabet="hello"), # Strings that definitely contain hello - st.text(alphabet="xyz"), # Strings that definitely don't contain hello - st.just("hello world"), # Known true case - st.just("goodbye world"), # Known false case - st.just(""), # Empty string - st.just("Hello"), # Case sensitivity test - st.just("HELLO"), # Case sensitivity test - st.just("hello" * 10), # Multiple hello occurrences - st.just("say hello to everyone"), # Hello in middle - st.text(alphabet="🎉🌟💫⭐🔥💯🚀🎯"), # Emojis - st.text(alphabet="中文测试한국어日本語العربية"), # International characters - ) -) -@settings(max_examples=40, deadline=25000) -def test_if_else_workflow_property_diverse_inputs(query_input): - """ - Property-based test with diverse input types for if-else workflow. - - Tests various categories including: - - Known true/false cases - - Case sensitivity scenarios - - Unicode characters from different languages - - Emojis and special symbols - - Multiple hello occurrences - """ - runner = TableTestRunner() - - contains_hello = "hello" in query_input - expected_key = "true" if contains_hello else "false" - expected_outputs = {expected_key: query_input} - - test_case = WorkflowTestCase( - fixture_path="conditional_hello_branching_workflow", - inputs={"query": query_input}, - expected_outputs=expected_outputs, - description=f"Diverse if-else test: {type(query_input).__name__} (contains_hello={contains_hello})", - ) - - result = runner.run_test_case(test_case) - - # Property: System should handle all inputs gracefully (no crashes) - assert result.success, f"Workflow failed with diverse input {repr(query_input)}: {result.error}" - - # Property: Correct branch logic must be preserved regardless of input type - assert result.actual_outputs == expected_outputs, ( - f"Branch logic violated. Input: {repr(query_input)}, " - f"Contains 'hello': {contains_hello}, Expected: {expected_outputs}, Got: {result.actual_outputs}" - ) - - -# Tests for the Layer system -def test_layer_system_basic(): - """Test basic layer functionality with DebugLoggingLayer.""" - from dify_graph.graph_engine.layers import DebugLoggingLayer - - runner = WorkflowRunner() - - # Load a simple echo workflow - fixture_data = runner.load_fixture("simple_passthrough_workflow") - graph, graph_runtime_state = runner.create_graph_from_fixture(fixture_data, inputs={"query": "test layer system"}) - - # Create engine with layer - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Add debug logging layer - debug_layer = DebugLoggingLayer(level="DEBUG", include_inputs=True, include_outputs=True) - engine.layer(debug_layer) - - # Run workflow - events = list(engine.run()) - - # Verify events were generated - assert len(events) > 0 - assert isinstance(events[0], GraphRunStartedEvent) - assert isinstance(events[-1], GraphRunSucceededEvent) - - # Verify layer received context - assert debug_layer.graph_runtime_state is not None - assert debug_layer.command_channel is not None - - # Verify layer tracked execution stats - assert debug_layer.node_count > 0 - assert debug_layer.success_count > 0 - - -def test_layer_chaining(): - """Test chaining multiple layers.""" - from dify_graph.graph_engine.layers import DebugLoggingLayer, GraphEngineLayer - - # Create a custom test layer - class TestLayer(GraphEngineLayer): - def __init__(self): - super().__init__() - self.events_received = [] - self.graph_started = False - self.graph_ended = False - - def on_graph_start(self): - self.graph_started = True - - def on_event(self, event): - self.events_received.append(event.__class__.__name__) - - def on_graph_end(self, error): - self.graph_ended = True - - runner = WorkflowRunner() - - # Load workflow - fixture_data = runner.load_fixture("simple_passthrough_workflow") - graph, graph_runtime_state = runner.create_graph_from_fixture(fixture_data, inputs={"query": "test chaining"}) - - # Create engine - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Chain multiple layers - test_layer = TestLayer() - debug_layer = DebugLoggingLayer(level="INFO") - - engine.layer(test_layer).layer(debug_layer) - - # Run workflow - events = list(engine.run()) - - # Verify both layers received events - assert test_layer.graph_started - assert test_layer.graph_ended - assert len(test_layer.events_received) > 0 - - # Verify debug layer also worked - assert debug_layer.node_count > 0 - - -def test_layer_error_handling(): - """Test that layer errors don't crash the engine.""" - from dify_graph.graph_engine.layers import GraphEngineLayer - - # Create a layer that throws errors - class FaultyLayer(GraphEngineLayer): - def on_graph_start(self): - raise RuntimeError("Intentional error in on_graph_start") - - def on_event(self, event): - raise RuntimeError("Intentional error in on_event") - - def on_graph_end(self, error): - raise RuntimeError("Intentional error in on_graph_end") - - runner = WorkflowRunner() - - # Load workflow - fixture_data = runner.load_fixture("simple_passthrough_workflow") - graph, graph_runtime_state = runner.create_graph_from_fixture(fixture_data, inputs={"query": "test error handling"}) - - # Create engine with faulty layer - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Add faulty layer - engine.layer(FaultyLayer()) - - # Run workflow - should not crash despite layer errors - events = list(engine.run()) - - # Verify workflow still completed successfully - assert len(events) > 0 - assert isinstance(events[-1], GraphRunSucceededEvent) - assert events[-1].outputs == {"query": "test error handling"} - - -def test_event_sequence_validation(): - """Test the new event sequence validation feature.""" - from dify_graph.graph_events import NodeRunStartedEvent, NodeRunStreamChunkEvent, NodeRunSucceededEvent - - runner = TableTestRunner() - - # Test 1: Successful event sequence validation - test_case_success = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test event sequence"}, - expected_outputs={"query": "test event sequence"}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunStartedEvent, # Start node begins - NodeRunStreamChunkEvent, # Start node streaming - NodeRunSucceededEvent, # Start node completes - NodeRunStartedEvent, # End node begins - NodeRunSucceededEvent, # End node completes - GraphRunSucceededEvent, # Graph completes - ], - description="Test with correct event sequence", - ) - - result = runner.run_test_case(test_case_success) - assert result.success, f"Test should pass with correct event sequence. Error: {result.event_mismatch_details}" - assert result.event_sequence_match is True - assert result.event_mismatch_details is None - - # Test 2: Failed event sequence validation - wrong order - test_case_wrong_order = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test wrong order"}, - expected_outputs={"query": "test wrong order"}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunSucceededEvent, # Wrong: expecting success before start - NodeRunStreamChunkEvent, - NodeRunStartedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - description="Test with incorrect event order", - ) - - result = runner.run_test_case(test_case_wrong_order) - assert not result.success, "Test should fail with incorrect event sequence" - assert result.event_sequence_match is False - assert result.event_mismatch_details is not None - assert "Event mismatch at position" in result.event_mismatch_details - - # Test 3: Failed event sequence validation - wrong count - test_case_wrong_count = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test wrong count"}, - expected_outputs={"query": "test wrong count"}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Missing the second node's events - GraphRunSucceededEvent, - ], - description="Test with incorrect event count", - ) - - result = runner.run_test_case(test_case_wrong_count) - assert not result.success, "Test should fail with incorrect event count" - assert result.event_sequence_match is False - assert result.event_mismatch_details is not None - assert "Event count mismatch" in result.event_mismatch_details - - # Test 4: No event sequence validation (backward compatibility) - test_case_no_validation = WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test no validation"}, - expected_outputs={"query": "test no validation"}, - # No expected_event_sequence provided - description="Test without event sequence validation", - ) - - result = runner.run_test_case(test_case_no_validation) - assert result.success, "Test should pass when no event sequence is provided" - assert result.event_sequence_match is None - assert result.event_mismatch_details is None - - -def test_event_sequence_validation_with_table_tests(): - """Test event sequence validation with table-driven tests.""" - from dify_graph.graph_events import NodeRunStartedEvent, NodeRunStreamChunkEvent, NodeRunSucceededEvent - - runner = TableTestRunner() - - test_cases = [ - WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test1"}, - expected_outputs={"query": "test1"}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - description="Table test 1: Valid sequence", - ), - WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test2"}, - expected_outputs={"query": "test2"}, - # No event sequence validation for this test - description="Table test 2: No sequence validation", - ), - WorkflowTestCase( - fixture_path="simple_passthrough_workflow", - inputs={"query": "test3"}, - expected_outputs={"query": "test3"}, - expected_event_sequence=[ - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - description="Table test 3: Valid sequence", - ), - ] - - suite_result = runner.run_table_tests(test_cases) - - # Check all tests passed - for i, result in enumerate(suite_result.results): - if i == 1: # Test 2 has no event sequence validation - assert result.event_sequence_match is None - else: - assert result.event_sequence_match is True - assert result.success, f"Test {i + 1} failed: {result.event_mismatch_details or result.error}" - - -def test_graph_run_emits_partial_success_when_node_failure_recovered(): - runner = TableTestRunner() - - fixture_data = runner.workflow_runner.load_fixture("basic_chatflow") - mock_config = MockConfigBuilder().with_node_error("llm", "mock llm failure").build() - - graph, graph_runtime_state = runner.workflow_runner.create_graph_from_fixture( - fixture_data=fixture_data, - query="hello", - use_mock_factory=True, - mock_config=mock_config, - ) - - llm_node = graph.nodes["llm"] - base_node_data = llm_node.node_data - base_node_data.error_strategy = ErrorStrategy.DEFAULT_VALUE - base_node_data.default_value = [DefaultValue(key="text", value="fallback response", type=DefaultValueType.STRING)] - - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - events = list(engine.run()) - - assert isinstance(events[-1], GraphRunPartialSucceededEvent) - - partial_event = next(event for event in events if isinstance(event, GraphRunPartialSucceededEvent)) - assert partial_event.exceptions_count == 1 - assert partial_event.outputs.get("answer") == "fallback response" - - assert not any(isinstance(event, GraphRunSucceededEvent) for event in events) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py deleted file mode 100644 index 255784b77d2..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py +++ /dev/null @@ -1,196 +0,0 @@ -"""Unit tests for GraphExecution serialization helpers.""" - -from __future__ import annotations - -import json -from collections import deque -from unittest.mock import MagicMock - -from dify_graph.enums import BuiltinNodeTypes, NodeExecutionType, NodeState -from dify_graph.graph_engine.domain import GraphExecution -from dify_graph.graph_engine.response_coordinator import ResponseStreamCoordinator -from dify_graph.graph_engine.response_coordinator.path import Path -from dify_graph.graph_engine.response_coordinator.session import ResponseSession -from dify_graph.graph_events import NodeRunStreamChunkEvent -from dify_graph.nodes.base.template import Template, TextSegment, VariableSegment - - -class CustomGraphExecutionError(Exception): - """Custom exception used to verify error serialization.""" - - -def test_graph_execution_serialization_round_trip() -> None: - """GraphExecution serialization restores full aggregate state.""" - # Arrange - execution = GraphExecution(workflow_id="wf-1") - execution.start() - node_a = execution.get_or_create_node_execution("node-a") - node_a.mark_started(execution_id="exec-1") - node_a.increment_retry() - node_a.mark_failed("boom") - node_b = execution.get_or_create_node_execution("node-b") - node_b.mark_skipped() - execution.fail(CustomGraphExecutionError("serialization failure")) - - # Act - serialized = execution.dumps() - payload = json.loads(serialized) - restored = GraphExecution(workflow_id="wf-1") - restored.loads(serialized) - - # Assert - assert payload["type"] == "GraphExecution" - assert payload["version"] == "1.0" - assert restored.workflow_id == "wf-1" - assert restored.started is True - assert restored.completed is True - assert restored.aborted is False - assert isinstance(restored.error, CustomGraphExecutionError) - assert str(restored.error) == "serialization failure" - assert set(restored.node_executions) == {"node-a", "node-b"} - restored_node_a = restored.node_executions["node-a"] - assert restored_node_a.state is NodeState.TAKEN - assert restored_node_a.retry_count == 1 - assert restored_node_a.execution_id == "exec-1" - assert restored_node_a.error == "boom" - restored_node_b = restored.node_executions["node-b"] - assert restored_node_b.state is NodeState.SKIPPED - assert restored_node_b.retry_count == 0 - assert restored_node_b.execution_id is None - assert restored_node_b.error is None - - -def test_graph_execution_loads_replaces_existing_state() -> None: - """loads replaces existing runtime data with serialized snapshot.""" - # Arrange - source = GraphExecution(workflow_id="wf-2") - source.start() - source_node = source.get_or_create_node_execution("node-source") - source_node.mark_taken() - serialized = source.dumps() - - target = GraphExecution(workflow_id="wf-2") - target.start() - target.abort("pre-existing abort") - temp_node = target.get_or_create_node_execution("node-temp") - temp_node.increment_retry() - temp_node.mark_failed("temp error") - - # Act - target.loads(serialized) - - # Assert - assert target.aborted is False - assert target.error is None - assert target.started is True - assert target.completed is False - assert set(target.node_executions) == {"node-source"} - restored_node = target.node_executions["node-source"] - assert restored_node.state is NodeState.TAKEN - assert restored_node.retry_count == 0 - assert restored_node.execution_id is None - assert restored_node.error is None - - -def test_response_stream_coordinator_serialization_round_trip(monkeypatch) -> None: - """ResponseStreamCoordinator serialization restores coordinator internals.""" - - template_main = Template(segments=[TextSegment(text="Hi "), VariableSegment(selector=["node-source", "text"])]) - template_secondary = Template(segments=[TextSegment(text="secondary")]) - - class DummyNode: - def __init__(self, node_id: str, template: Template, execution_type: NodeExecutionType) -> None: - self.id = node_id - self.node_type = ( - BuiltinNodeTypes.ANSWER if execution_type == NodeExecutionType.RESPONSE else BuiltinNodeTypes.LLM - ) - self.execution_type = execution_type - self.state = NodeState.UNKNOWN - self.title = node_id - self.template = template - - def blocks_variable_output(self, *_args) -> bool: - return False - - response_node1 = DummyNode("response-1", template_main, NodeExecutionType.RESPONSE) - response_node2 = DummyNode("response-2", template_main, NodeExecutionType.RESPONSE) - response_node3 = DummyNode("response-3", template_main, NodeExecutionType.RESPONSE) - source_node = DummyNode("node-source", template_secondary, NodeExecutionType.EXECUTABLE) - - class DummyGraph: - def __init__(self) -> None: - self.nodes = { - response_node1.id: response_node1, - response_node2.id: response_node2, - response_node3.id: response_node3, - source_node.id: source_node, - } - self.edges: dict[str, object] = {} - self.root_node = response_node1 - - def get_outgoing_edges(self, _node_id: str): # pragma: no cover - not exercised - return [] - - def get_incoming_edges(self, _node_id: str): # pragma: no cover - not exercised - return [] - - graph = DummyGraph() - - def fake_from_node(cls, node: DummyNode) -> ResponseSession: - return ResponseSession(node_id=node.id, template=node.template) - - monkeypatch.setattr(ResponseSession, "from_node", classmethod(fake_from_node)) - - coordinator = ResponseStreamCoordinator(variable_pool=MagicMock(), graph=graph) # type: ignore[arg-type] - coordinator._response_nodes = {"response-1", "response-2", "response-3"} - coordinator._paths_maps = { - "response-1": [Path(edges=["edge-1"])], - "response-2": [Path(edges=[])], - "response-3": [Path(edges=["edge-2", "edge-3"])], - } - - active_session = ResponseSession(node_id="response-1", template=response_node1.template) - active_session.index = 1 - coordinator._active_session = active_session - waiting_session = ResponseSession(node_id="response-2", template=response_node2.template) - coordinator._waiting_sessions = deque([waiting_session]) - pending_session = ResponseSession(node_id="response-3", template=response_node3.template) - pending_session.index = 2 - coordinator._response_sessions = {"response-3": pending_session} - - coordinator._node_execution_ids = {"response-1": "exec-1"} - event = NodeRunStreamChunkEvent( - id="exec-1", - node_id="response-1", - node_type=BuiltinNodeTypes.ANSWER, - selector=["node-source", "text"], - chunk="chunk-1", - is_final=False, - ) - coordinator._stream_buffers = {("node-source", "text"): [event]} - coordinator._stream_positions = {("node-source", "text"): 1} - coordinator._closed_streams = {("node-source", "text")} - - serialized = coordinator.dumps() - - restored = ResponseStreamCoordinator(variable_pool=MagicMock(), graph=graph) # type: ignore[arg-type] - monkeypatch.setattr(ResponseSession, "from_node", classmethod(fake_from_node)) - restored.loads(serialized) - - assert restored._response_nodes == {"response-1", "response-2", "response-3"} - assert restored._paths_maps["response-1"][0].edges == ["edge-1"] - assert restored._active_session is not None - assert restored._active_session.node_id == "response-1" - assert restored._active_session.index == 1 - waiting_restored = list(restored._waiting_sessions) - assert len(waiting_restored) == 1 - assert waiting_restored[0].node_id == "response-2" - assert waiting_restored[0].index == 0 - assert set(restored._response_sessions) == {"response-3"} - assert restored._response_sessions["response-3"].index == 2 - assert restored._node_execution_ids == {"response-1": "exec-1"} - assert ("node-source", "text") in restored._stream_buffers - restored_event = restored._stream_buffers[("node-source", "text")][0] - assert restored_event.chunk == "chunk-1" - assert restored._stream_positions[("node-source", "text")] == 1 - assert ("node-source", "text") in restored._closed_streams diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_state_snapshot.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_state_snapshot.py deleted file mode 100644 index d54f0be1904..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_state_snapshot.py +++ /dev/null @@ -1,190 +0,0 @@ -import time -from collections.abc import Mapping - -from dify_graph.entities import GraphInitParams -from dify_graph.enums import NodeState -from dify_graph.graph import Graph -from dify_graph.graph_engine.graph_state_manager import GraphStateManager -from dify_graph.graph_engine.ready_queue import InMemoryReadyQueue -from dify_graph.model_runtime.entities.llm_entities import LLMMode -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig -from .test_mock_nodes import MockLLMNode - - -def _build_runtime_state() -> GraphRuntimeState: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", - app_id="app", - workflow_id="workflow", - workflow_execution_id="exec-1", - ), - user_inputs={}, - conversation_variables=[], - ) - return GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - -def _build_llm_node( - *, - node_id: str, - runtime_state: GraphRuntimeState, - graph_init_params: GraphInitParams, - mock_config: MockConfig, -) -> MockLLMNode: - llm_data = LLMNodeData( - title=f"LLM {node_id}", - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode=LLMMode.CHAT, completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text=f"Prompt {node_id}", - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - ) - llm_config = {"id": node_id, "data": llm_data.model_dump()} - return MockLLMNode( - id=llm_config["id"], - config=llm_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - mock_config=mock_config, - ) - - -def _build_graph(runtime_state: GraphRuntimeState) -> Graph: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - ) - - mock_config = MockConfig() - llm_a = _build_llm_node( - node_id="llm_a", - runtime_state=runtime_state, - graph_init_params=graph_init_params, - mock_config=mock_config, - ) - llm_b = _build_llm_node( - node_id="llm_b", - runtime_state=runtime_state, - graph_init_params=graph_init_params, - mock_config=mock_config, - ) - - end_data = EndNodeData(title="End", outputs=[], desc=None) - end_config = {"id": "end", "data": end_data.model_dump()} - end_node = EndNode( - id=end_config["id"], - config=end_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - ) - - builder = ( - Graph.new() - .add_root(start_node) - .add_node(llm_a, from_node_id="start") - .add_node(llm_b, from_node_id="start") - .add_node(end_node, from_node_id="llm_a") - ) - return builder.connect(tail="llm_b", head="end").build() - - -def _edge_state_map(graph: Graph) -> Mapping[tuple[str, str, str], NodeState]: - return {(edge.tail, edge.head, edge.source_handle): edge.state for edge in graph.edges.values()} - - -def test_runtime_state_snapshot_restores_graph_states() -> None: - runtime_state = _build_runtime_state() - graph = _build_graph(runtime_state) - runtime_state.attach_graph(graph) - - graph.nodes["llm_a"].state = NodeState.TAKEN - graph.nodes["llm_b"].state = NodeState.SKIPPED - - for edge in graph.edges.values(): - if edge.tail == "start" and edge.head == "llm_a": - edge.state = NodeState.TAKEN - elif edge.tail == "start" and edge.head == "llm_b": - edge.state = NodeState.SKIPPED - elif edge.head == "end" and edge.tail == "llm_a": - edge.state = NodeState.TAKEN - elif edge.head == "end" and edge.tail == "llm_b": - edge.state = NodeState.SKIPPED - - snapshot = runtime_state.dumps() - - resumed_state = GraphRuntimeState.from_snapshot(snapshot) - resumed_graph = _build_graph(resumed_state) - resumed_state.attach_graph(resumed_graph) - - assert resumed_graph.nodes["llm_a"].state == NodeState.TAKEN - assert resumed_graph.nodes["llm_b"].state == NodeState.SKIPPED - assert _edge_state_map(resumed_graph) == _edge_state_map(graph) - - -def test_join_readiness_uses_restored_edge_states() -> None: - runtime_state = _build_runtime_state() - graph = _build_graph(runtime_state) - runtime_state.attach_graph(graph) - - ready_queue = InMemoryReadyQueue() - state_manager = GraphStateManager(graph, ready_queue) - - for edge in graph.get_incoming_edges("end"): - if edge.tail == "llm_a": - edge.state = NodeState.TAKEN - if edge.tail == "llm_b": - edge.state = NodeState.UNKNOWN - - assert state_manager.is_node_ready("end") is False - - for edge in graph.get_incoming_edges("end"): - if edge.tail == "llm_b": - edge.state = NodeState.TAKEN - - assert state_manager.is_node_ready("end") is True - - snapshot = runtime_state.dumps() - resumed_state = GraphRuntimeState.from_snapshot(snapshot) - resumed_graph = _build_graph(resumed_state) - resumed_state.attach_graph(resumed_graph) - - resumed_state_manager = GraphStateManager(resumed_graph, InMemoryReadyQueue()) - assert resumed_state_manager.is_node_ready("end") is True diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_multi_branch.py b/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_multi_branch.py deleted file mode 100644 index 538f53c6039..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_multi_branch.py +++ /dev/null @@ -1,387 +0,0 @@ -import datetime -import time -from collections.abc import Iterable -from unittest import mock -from unittest.mock import MagicMock - -from dify_graph.graph import Graph -from dify_graph.graph_events import ( - GraphRunPausedEvent, - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunPauseRequestedEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) -from dify_graph.graph_events.node import NodeRunHumanInputFormFilledEvent -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.base.entities import OutputVariableEntity, OutputVariableType -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import HumanInputFormEntity, HumanInputFormRepository -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from libs.datetime_utils import naive_utc_now -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig -from .test_mock_nodes import MockLLMNode -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def _build_branching_graph( - mock_config: MockConfig, - form_repository: HumanInputFormRepository, - graph_runtime_state: GraphRuntimeState | None = None, -) -> tuple[Graph, GraphRuntimeState]: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - - if graph_runtime_state is None: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", - app_id="app", - workflow_id="workflow", - workflow_execution_id="test-execution-id", - ), - user_inputs={}, - conversation_variables=[], - ) - graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - def _create_llm_node(node_id: str, title: str, prompt_text: str) -> MockLLMNode: - llm_data = LLMNodeData( - title=title, - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode="chat", completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text=prompt_text, - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - ) - llm_config = {"id": node_id, "data": llm_data.model_dump()} - llm_node = MockLLMNode( - id=node_id, - config=llm_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - credentials_provider=mock.Mock(), - model_factory=mock.Mock(), - ) - return llm_node - - llm_initial = _create_llm_node("llm_initial", "Initial LLM", "Initial stream") - - human_data = HumanInputNodeData( - title="Human Input", - form_content="Human input required", - inputs=[], - user_actions=[ - UserAction(id="primary", title="Primary"), - UserAction(id="secondary", title="Secondary"), - ], - ) - - human_config = {"id": "human", "data": human_data.model_dump()} - human_node = HumanInputNode( - id=human_config["id"], - config=human_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - form_repository=form_repository, - ) - - llm_primary = _create_llm_node("llm_primary", "Primary LLM", "Primary stream output") - llm_secondary = _create_llm_node("llm_secondary", "Secondary LLM", "Secondary") - - end_primary_data = EndNodeData( - title="End Primary", - outputs=[ - OutputVariableEntity( - variable="initial_text", value_type=OutputVariableType.STRING, value_selector=["llm_initial", "text"] - ), - OutputVariableEntity( - variable="primary_text", value_type=OutputVariableType.STRING, value_selector=["llm_primary", "text"] - ), - ], - desc=None, - ) - end_primary_config = {"id": "end_primary", "data": end_primary_data.model_dump()} - end_primary = EndNode( - id=end_primary_config["id"], - config=end_primary_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - end_secondary_data = EndNodeData( - title="End Secondary", - outputs=[ - OutputVariableEntity( - variable="initial_text", value_type=OutputVariableType.STRING, value_selector=["llm_initial", "text"] - ), - OutputVariableEntity( - variable="secondary_text", - value_type=OutputVariableType.STRING, - value_selector=["llm_secondary", "text"], - ), - ], - desc=None, - ) - end_secondary_config = {"id": "end_secondary", "data": end_secondary_data.model_dump()} - end_secondary = EndNode( - id=end_secondary_config["id"], - config=end_secondary_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - graph = ( - Graph.new() - .add_root(start_node) - .add_node(llm_initial) - .add_node(human_node) - .add_node(llm_primary, from_node_id="human", source_handle="primary") - .add_node(end_primary, from_node_id="llm_primary") - .add_node(llm_secondary, from_node_id="human", source_handle="secondary") - .add_node(end_secondary, from_node_id="llm_secondary") - .build() - ) - return graph, graph_runtime_state - - -def _expected_mock_llm_chunks(text: str) -> list[str]: - chunks: list[str] = [] - for index, word in enumerate(text.split(" ")): - chunk = word if index == 0 else f" {word}" - chunks.append(chunk) - chunks.append("") - return chunks - - -def _assert_stream_chunk_sequence( - chunk_events: Iterable[NodeRunStreamChunkEvent], - expected_nodes: list[str], - expected_chunks: list[str], -) -> None: - actual_nodes = [event.node_id for event in chunk_events] - actual_chunks = [event.chunk for event in chunk_events] - assert actual_nodes == expected_nodes - assert actual_chunks == expected_chunks - - -def test_human_input_llm_streaming_across_multiple_branches() -> None: - mock_config = MockConfig() - mock_config.set_node_outputs("llm_initial", {"text": "Initial stream"}) - mock_config.set_node_outputs("llm_primary", {"text": "Primary stream output"}) - mock_config.set_node_outputs("llm_secondary", {"text": "Secondary"}) - - branch_scenarios = [ - { - "handle": "primary", - "resume_llm": "llm_primary", - "end_node": "end_primary", - "expected_pre_chunks": [ - ("llm_initial", _expected_mock_llm_chunks("Initial stream")), # cached output before branch completes - ("end_primary", ["\n"]), # literal segment emitted when end_primary session activates - ], - "expected_post_chunks": [ - ("llm_primary", _expected_mock_llm_chunks("Primary stream output")), # live stream from chosen branch - ], - }, - { - "handle": "secondary", - "resume_llm": "llm_secondary", - "end_node": "end_secondary", - "expected_pre_chunks": [ - ("llm_initial", _expected_mock_llm_chunks("Initial stream")), # cached output before branch completes - ("end_secondary", ["\n"]), # literal segment emitted when end_secondary session activates - ], - "expected_post_chunks": [ - ("llm_secondary", _expected_mock_llm_chunks("Secondary")), # live stream from chosen branch - ], - }, - ] - - for scenario in branch_scenarios: - runner = TableTestRunner() - - mock_create_repo = MagicMock(spec=HumanInputFormRepository) - mock_create_repo.get_form.return_value = None - mock_form_entity = MagicMock(spec=HumanInputFormEntity) - mock_form_entity.id = "test_form_id" - mock_form_entity.web_app_token = "test_web_app_token" - mock_form_entity.recipients = [] - mock_form_entity.rendered_content = "rendered" - mock_form_entity.submitted = False - mock_create_repo.create_form.return_value = mock_form_entity - - def initial_graph_factory(mock_create_repo=mock_create_repo) -> tuple[Graph, GraphRuntimeState]: - return _build_branching_graph(mock_config, mock_create_repo) - - initial_case = WorkflowTestCase( - description="HumanInput pause before branching decision", - graph_factory=initial_graph_factory, - expected_event_sequence=[ - GraphRunStartedEvent, # initial run: graph execution starts - NodeRunStartedEvent, # start node begins execution - NodeRunSucceededEvent, # start node completes - NodeRunStartedEvent, # llm_initial starts streaming - NodeRunSucceededEvent, # llm_initial completes streaming - NodeRunStartedEvent, # human node begins and issues pause - NodeRunPauseRequestedEvent, # human node requests pause awaiting input - GraphRunPausedEvent, # graph run pauses awaiting resume - ], - ) - - initial_result = runner.run_test_case(initial_case) - - assert initial_result.success, initial_result.event_mismatch_details - assert not any(isinstance(event, NodeRunStreamChunkEvent) for event in initial_result.events) - - pre_chunk_count = sum(len(chunks) for _, chunks in scenario["expected_pre_chunks"]) - post_chunk_count = sum(len(chunks) for _, chunks in scenario["expected_post_chunks"]) - expected_pre_chunk_events_in_resumption = [ - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunHumanInputFormFilledEvent, - ] - - expected_resume_sequence: list[type] = ( - expected_pre_chunk_events_in_resumption - + [NodeRunStreamChunkEvent] * pre_chunk_count - + [ - NodeRunSucceededEvent, - NodeRunStartedEvent, - ] - + [NodeRunStreamChunkEvent] * post_chunk_count - + [ - NodeRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ] - ) - - mock_get_repo = MagicMock(spec=HumanInputFormRepository) - submitted_form = MagicMock(spec=HumanInputFormEntity) - submitted_form.id = mock_form_entity.id - submitted_form.web_app_token = mock_form_entity.web_app_token - submitted_form.recipients = [] - submitted_form.rendered_content = mock_form_entity.rendered_content - submitted_form.submitted = True - submitted_form.selected_action_id = scenario["handle"] - submitted_form.submitted_data = {} - submitted_form.expiration_time = naive_utc_now() + datetime.timedelta(days=1) - mock_get_repo.get_form.return_value = submitted_form - - def resume_graph_factory( - initial_result=initial_result, mock_get_repo=mock_get_repo - ) -> tuple[Graph, GraphRuntimeState]: - assert initial_result.graph_runtime_state is not None - serialized_runtime_state = initial_result.graph_runtime_state.dumps() - resume_runtime_state = GraphRuntimeState.from_snapshot(serialized_runtime_state) - return _build_branching_graph(mock_config, mock_get_repo, resume_runtime_state) - - resume_case = WorkflowTestCase( - description=f"HumanInput resumes via {scenario['handle']} branch", - graph_factory=resume_graph_factory, - expected_event_sequence=expected_resume_sequence, - ) - - resume_result = runner.run_test_case(resume_case) - - assert resume_result.success, resume_result.event_mismatch_details - - resume_events = resume_result.events - - chunk_events = [event for event in resume_events if isinstance(event, NodeRunStreamChunkEvent)] - assert len(chunk_events) == pre_chunk_count + post_chunk_count - - pre_chunk_events = chunk_events[:pre_chunk_count] - post_chunk_events = chunk_events[pre_chunk_count:] - - expected_pre_nodes: list[str] = [] - expected_pre_chunks: list[str] = [] - for node_id, chunks in scenario["expected_pre_chunks"]: - expected_pre_nodes.extend([node_id] * len(chunks)) - expected_pre_chunks.extend(chunks) - _assert_stream_chunk_sequence(pre_chunk_events, expected_pre_nodes, expected_pre_chunks) - - expected_post_nodes: list[str] = [] - expected_post_chunks: list[str] = [] - for node_id, chunks in scenario["expected_post_chunks"]: - expected_post_nodes.extend([node_id] * len(chunks)) - expected_post_chunks.extend(chunks) - _assert_stream_chunk_sequence(post_chunk_events, expected_post_nodes, expected_post_chunks) - - human_success_index = next( - index - for index, event in enumerate(resume_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "human" - ) - pre_indices = [ - index - for index, event in enumerate(resume_events) - if isinstance(event, NodeRunStreamChunkEvent) and index < human_success_index - ] - expected_pre_chunk_events_count_in_resumption = len(expected_pre_chunk_events_in_resumption) - assert pre_indices == list(range(expected_pre_chunk_events_count_in_resumption, human_success_index)) - - resume_chunk_indices = [ - index - for index, event in enumerate(resume_events) - if isinstance(event, NodeRunStreamChunkEvent) and event.node_id == scenario["resume_llm"] - ] - assert resume_chunk_indices, "Expected streaming output from the selected branch" - resume_start_index = next( - index - for index, event in enumerate(resume_events) - if isinstance(event, NodeRunStartedEvent) and event.node_id == scenario["resume_llm"] - ) - resume_success_index = next( - index - for index, event in enumerate(resume_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == scenario["resume_llm"] - ) - assert resume_start_index < min(resume_chunk_indices) - assert max(resume_chunk_indices) < resume_success_index - - started_nodes = [event.node_id for event in resume_events if isinstance(event, NodeRunStartedEvent)] - assert started_nodes == ["human", scenario["resume_llm"], scenario["end_node"]] diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_single_branch.py b/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_single_branch.py deleted file mode 100644 index 36bba6deb66..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_human_input_pause_single_branch.py +++ /dev/null @@ -1,344 +0,0 @@ -import datetime -import time -from unittest import mock -from unittest.mock import MagicMock - -from dify_graph.graph import Graph -from dify_graph.graph_events import ( - GraphRunPausedEvent, - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunPauseRequestedEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) -from dify_graph.graph_events.node import NodeRunHumanInputFormFilledEvent -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.base.entities import OutputVariableEntity, OutputVariableType -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import HumanInputFormEntity, HumanInputFormRepository -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from libs.datetime_utils import naive_utc_now -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig -from .test_mock_nodes import MockLLMNode -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def _build_llm_human_llm_graph( - mock_config: MockConfig, - form_repository: HumanInputFormRepository, - graph_runtime_state: GraphRuntimeState | None = None, -) -> tuple[Graph, GraphRuntimeState]: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - - if graph_runtime_state is None: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", app_id="app", workflow_id="workflow", workflow_execution_id="test-execution-id," - ), - user_inputs={}, - conversation_variables=[], - ) - graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - def _create_llm_node(node_id: str, title: str, prompt_text: str) -> MockLLMNode: - llm_data = LLMNodeData( - title=title, - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode="chat", completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text=prompt_text, - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - ) - llm_config = {"id": node_id, "data": llm_data.model_dump()} - llm_node = MockLLMNode( - id=node_id, - config=llm_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - credentials_provider=mock.Mock(), - model_factory=mock.Mock(), - ) - return llm_node - - llm_first = _create_llm_node("llm_initial", "Initial LLM", "Initial prompt") - - human_data = HumanInputNodeData( - title="Human Input", - form_content="Human input required", - inputs=[], - user_actions=[ - UserAction(id="accept", title="Accept"), - UserAction(id="reject", title="Reject"), - ], - ) - - human_config = {"id": "human", "data": human_data.model_dump()} - human_node = HumanInputNode( - id=human_config["id"], - config=human_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - form_repository=form_repository, - ) - - llm_second = _create_llm_node("llm_resume", "Follow-up LLM", "Follow-up prompt") - - end_data = EndNodeData( - title="End", - outputs=[ - OutputVariableEntity( - variable="initial_text", value_type=OutputVariableType.STRING, value_selector=["llm_initial", "text"] - ), - OutputVariableEntity( - variable="resume_text", value_type=OutputVariableType.STRING, value_selector=["llm_resume", "text"] - ), - ], - desc=None, - ) - end_config = {"id": "end", "data": end_data.model_dump()} - end_node = EndNode( - id=end_config["id"], - config=end_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - graph = ( - Graph.new() - .add_root(start_node) - .add_node(llm_first) - .add_node(human_node) - .add_node(llm_second, source_handle="accept") - .add_node(end_node) - .build() - ) - return graph, graph_runtime_state - - -def _expected_mock_llm_chunks(text: str) -> list[str]: - chunks: list[str] = [] - for index, word in enumerate(text.split(" ")): - chunk = word if index == 0 else f" {word}" - chunks.append(chunk) - chunks.append("") - return chunks - - -def test_human_input_llm_streaming_order_across_pause() -> None: - runner = TableTestRunner() - - initial_text = "Hello, pause" - resume_text = "Welcome back!" - - mock_config = MockConfig() - mock_config.set_node_outputs("llm_initial", {"text": initial_text}) - mock_config.set_node_outputs("llm_resume", {"text": resume_text}) - - expected_initial_sequence: list[type] = [ - GraphRunStartedEvent, # graph run begins - NodeRunStartedEvent, # start node begins - NodeRunSucceededEvent, # start node completes - NodeRunStartedEvent, # llm_initial begins streaming - NodeRunSucceededEvent, # llm_initial completes streaming - NodeRunStartedEvent, # human node begins and requests pause - NodeRunPauseRequestedEvent, # human node pause requested - GraphRunPausedEvent, # graph run pauses awaiting resume - ] - - mock_create_repo = MagicMock(spec=HumanInputFormRepository) - mock_create_repo.get_form.return_value = None - mock_form_entity = MagicMock(spec=HumanInputFormEntity) - mock_form_entity.id = "test_form_id" - mock_form_entity.web_app_token = "test_web_app_token" - mock_form_entity.recipients = [] - mock_form_entity.rendered_content = "rendered" - mock_form_entity.submitted = False - mock_create_repo.create_form.return_value = mock_form_entity - - def graph_factory() -> tuple[Graph, GraphRuntimeState]: - return _build_llm_human_llm_graph(mock_config, mock_create_repo) - - initial_case = WorkflowTestCase( - description="HumanInput pause preserves LLM streaming order", - graph_factory=graph_factory, - expected_event_sequence=expected_initial_sequence, - ) - - initial_result = runner.run_test_case(initial_case) - - assert initial_result.success, initial_result.event_mismatch_details - - initial_events = initial_result.events - initial_chunks = _expected_mock_llm_chunks(initial_text) - - initial_stream_chunk_events = [event for event in initial_events if isinstance(event, NodeRunStreamChunkEvent)] - assert initial_stream_chunk_events == [] - - pause_index = next(i for i, event in enumerate(initial_events) if isinstance(event, GraphRunPausedEvent)) - llm_succeeded_index = next( - i - for i, event in enumerate(initial_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "llm_initial" - ) - assert llm_succeeded_index < pause_index - - graph_runtime_state = initial_result.graph_runtime_state - graph = initial_result.graph - assert graph_runtime_state is not None - assert graph is not None - - coordinator = graph_runtime_state.response_coordinator - stream_buffers = coordinator._stream_buffers # Tests may access internals for assertions - assert ("llm_initial", "text") in stream_buffers - initial_stream_chunks = [event.chunk for event in stream_buffers[("llm_initial", "text")]] - assert initial_stream_chunks == initial_chunks - assert ("llm_resume", "text") not in stream_buffers - - resume_chunks = _expected_mock_llm_chunks(resume_text) - expected_resume_sequence: list[type] = [ - GraphRunStartedEvent, # resumed graph run begins - NodeRunStartedEvent, # human node restarts - # Form Filled should be generated first, then the node execution ends and stream chunk is generated. - NodeRunHumanInputFormFilledEvent, - NodeRunStreamChunkEvent, # cached llm_initial chunk 1 - NodeRunStreamChunkEvent, # cached llm_initial chunk 2 - NodeRunStreamChunkEvent, # cached llm_initial final chunk - NodeRunStreamChunkEvent, # end node emits combined template separator - NodeRunSucceededEvent, # human node finishes instantly after input - NodeRunStartedEvent, # llm_resume begins streaming - NodeRunStreamChunkEvent, # llm_resume chunk 1 - NodeRunStreamChunkEvent, # llm_resume chunk 2 - NodeRunStreamChunkEvent, # llm_resume final chunk - NodeRunSucceededEvent, # llm_resume completes streaming - NodeRunStartedEvent, # end node starts - NodeRunSucceededEvent, # end node finishes - GraphRunSucceededEvent, # graph run succeeds after resume - ] - - mock_get_repo = MagicMock(spec=HumanInputFormRepository) - submitted_form = MagicMock(spec=HumanInputFormEntity) - submitted_form.id = mock_form_entity.id - submitted_form.web_app_token = mock_form_entity.web_app_token - submitted_form.recipients = [] - submitted_form.rendered_content = mock_form_entity.rendered_content - submitted_form.submitted = True - submitted_form.selected_action_id = "accept" - submitted_form.submitted_data = {} - submitted_form.expiration_time = naive_utc_now() + datetime.timedelta(days=1) - mock_get_repo.get_form.return_value = submitted_form - - def resume_graph_factory() -> tuple[Graph, GraphRuntimeState]: - # restruct the graph runtime state - serialized_runtime_state = initial_result.graph_runtime_state.dumps() - resume_runtime_state = GraphRuntimeState.from_snapshot(serialized_runtime_state) - return _build_llm_human_llm_graph( - mock_config, - mock_get_repo, - resume_runtime_state, - ) - - resume_case = WorkflowTestCase( - description="HumanInput resume continues LLM streaming order", - graph_factory=resume_graph_factory, - expected_event_sequence=expected_resume_sequence, - ) - - resume_result = runner.run_test_case(resume_case) - - assert resume_result.success, resume_result.event_mismatch_details - - resume_events = resume_result.events - - success_index = next(i for i, event in enumerate(resume_events) if isinstance(event, GraphRunSucceededEvent)) - llm_resume_succeeded_index = next( - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "llm_resume" - ) - assert llm_resume_succeeded_index < success_index - - resume_chunk_events = [event for event in resume_events if isinstance(event, NodeRunStreamChunkEvent)] - assert [event.node_id for event in resume_chunk_events[:3]] == ["llm_initial"] * 3 - assert [event.chunk for event in resume_chunk_events[:3]] == initial_chunks - assert resume_chunk_events[3].node_id == "end" - assert resume_chunk_events[3].chunk == "\n" - assert [event.node_id for event in resume_chunk_events[4:]] == ["llm_resume"] * 3 - assert [event.chunk for event in resume_chunk_events[4:]] == resume_chunks - - human_success_index = next( - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "human" - ) - cached_chunk_indices = [ - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunStreamChunkEvent) and event.node_id in {"llm_initial", "end"} - ] - assert all(index < human_success_index for index in cached_chunk_indices) - - llm_resume_start_index = next( - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunStartedEvent) and event.node_id == "llm_resume" - ) - llm_resume_success_index = next( - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "llm_resume" - ) - llm_resume_chunk_indices = [ - i - for i, event in enumerate(resume_events) - if isinstance(event, NodeRunStreamChunkEvent) and event.node_id == "llm_resume" - ] - assert llm_resume_chunk_indices - first_resume_chunk_index = min(llm_resume_chunk_indices) - last_resume_chunk_index = max(llm_resume_chunk_indices) - assert llm_resume_start_index < first_resume_chunk_index - assert last_resume_chunk_index < llm_resume_success_index - - started_nodes = [event.node_id for event in resume_events if isinstance(event, NodeRunStartedEvent)] - assert started_nodes == ["human", "llm_resume", "end"] diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_if_else_streaming.py b/api/tests/unit_tests/core/workflow/graph_engine/test_if_else_streaming.py deleted file mode 100644 index 8da179c15ea..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_if_else_streaming.py +++ /dev/null @@ -1,324 +0,0 @@ -import time -from unittest import mock - -from dify_graph.graph import Graph -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) -from dify_graph.model_runtime.entities.llm_entities import LLMMode -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.base.entities import OutputVariableEntity, OutputVariableType -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.if_else.entities import IfElseNodeData -from dify_graph.nodes.if_else.if_else_node import IfElseNode -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from dify_graph.utils.condition.entities import Condition -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig -from .test_mock_nodes import MockLLMNode -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def _build_if_else_graph(branch_value: str, mock_config: MockConfig) -> tuple[Graph, GraphRuntimeState]: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - graph_config=graph_config, - user_from="account", - invoke_from="debugger", - ) - - variable_pool = VariablePool( - system_variables=SystemVariable(user_id="user", app_id="app", workflow_id="workflow"), - user_inputs={}, - conversation_variables=[], - ) - variable_pool.add(("branch", "value"), branch_value) - graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - def _create_llm_node(node_id: str, title: str, prompt_text: str) -> MockLLMNode: - llm_data = LLMNodeData( - title=title, - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode=LLMMode.CHAT, completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text=prompt_text, - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - ) - llm_config = {"id": node_id, "data": llm_data.model_dump()} - llm_node = MockLLMNode( - id=node_id, - config=llm_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - credentials_provider=mock.Mock(), - model_factory=mock.Mock(), - ) - return llm_node - - llm_initial = _create_llm_node("llm_initial", "Initial LLM", "Initial stream") - - if_else_data = IfElseNodeData( - title="IfElse", - cases=[ - IfElseNodeData.Case( - case_id="primary", - logical_operator="and", - conditions=[ - Condition(variable_selector=["branch", "value"], comparison_operator="is", value="primary") - ], - ), - IfElseNodeData.Case( - case_id="secondary", - logical_operator="and", - conditions=[ - Condition(variable_selector=["branch", "value"], comparison_operator="is", value="secondary") - ], - ), - ], - ) - if_else_config = {"id": "if_else", "data": if_else_data.model_dump()} - if_else_node = IfElseNode( - id=if_else_config["id"], - config=if_else_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - llm_primary = _create_llm_node("llm_primary", "Primary LLM", "Primary stream output") - llm_secondary = _create_llm_node("llm_secondary", "Secondary LLM", "Secondary") - - end_primary_data = EndNodeData( - title="End Primary", - outputs=[ - OutputVariableEntity( - variable="initial_text", value_type=OutputVariableType.STRING, value_selector=["llm_initial", "text"] - ), - OutputVariableEntity( - variable="primary_text", value_type=OutputVariableType.STRING, value_selector=["llm_primary", "text"] - ), - ], - desc=None, - ) - end_primary_config = {"id": "end_primary", "data": end_primary_data.model_dump()} - end_primary = EndNode( - id=end_primary_config["id"], - config=end_primary_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - end_secondary_data = EndNodeData( - title="End Secondary", - outputs=[ - OutputVariableEntity( - variable="initial_text", value_type=OutputVariableType.STRING, value_selector=["llm_initial", "text"] - ), - OutputVariableEntity( - variable="secondary_text", - value_type=OutputVariableType.STRING, - value_selector=["llm_secondary", "text"], - ), - ], - desc=None, - ) - end_secondary_config = {"id": "end_secondary", "data": end_secondary_data.model_dump()} - end_secondary = EndNode( - id=end_secondary_config["id"], - config=end_secondary_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - graph = ( - Graph.new() - .add_root(start_node) - .add_node(llm_initial) - .add_node(if_else_node) - .add_node(llm_primary, from_node_id="if_else", source_handle="primary") - .add_node(end_primary, from_node_id="llm_primary") - .add_node(llm_secondary, from_node_id="if_else", source_handle="secondary") - .add_node(end_secondary, from_node_id="llm_secondary") - .build() - ) - return graph, graph_runtime_state - - -def _expected_mock_llm_chunks(text: str) -> list[str]: - chunks: list[str] = [] - for index, word in enumerate(text.split(" ")): - chunk = word if index == 0 else f" {word}" - chunks.append(chunk) - chunks.append("") - return chunks - - -def test_if_else_llm_streaming_order() -> None: - mock_config = MockConfig() - mock_config.set_node_outputs("llm_initial", {"text": "Initial stream"}) - mock_config.set_node_outputs("llm_primary", {"text": "Primary stream output"}) - mock_config.set_node_outputs("llm_secondary", {"text": "Secondary"}) - - scenarios = [ - { - "branch": "primary", - "resume_llm": "llm_primary", - "end_node": "end_primary", - "expected_sequence": [ - GraphRunStartedEvent, # graph run begins - NodeRunStartedEvent, # start node begins execution - NodeRunSucceededEvent, # start node completes - NodeRunStartedEvent, # llm_initial starts and streams - NodeRunSucceededEvent, # llm_initial completes streaming - NodeRunStartedEvent, # if_else evaluates conditions - NodeRunStreamChunkEvent, # cached llm_initial chunk 1 flushed - NodeRunStreamChunkEvent, # cached llm_initial chunk 2 flushed - NodeRunStreamChunkEvent, # cached llm_initial final chunk flushed - NodeRunStreamChunkEvent, # template literal newline emitted - NodeRunSucceededEvent, # if_else completes branch selection - NodeRunStartedEvent, # llm_primary begins streaming - NodeRunStreamChunkEvent, # llm_primary chunk 1 - NodeRunStreamChunkEvent, # llm_primary chunk 2 - NodeRunStreamChunkEvent, # llm_primary chunk 3 - NodeRunStreamChunkEvent, # llm_primary final chunk - NodeRunSucceededEvent, # llm_primary completes streaming - NodeRunStartedEvent, # end_primary node starts - NodeRunSucceededEvent, # end_primary finishes aggregation - GraphRunSucceededEvent, # graph run succeeds - ], - "expected_chunks": [ - ("llm_initial", _expected_mock_llm_chunks("Initial stream")), - ("end_primary", ["\n"]), - ("llm_primary", _expected_mock_llm_chunks("Primary stream output")), - ], - }, - { - "branch": "secondary", - "resume_llm": "llm_secondary", - "end_node": "end_secondary", - "expected_sequence": [ - GraphRunStartedEvent, # graph run begins - NodeRunStartedEvent, # start node begins execution - NodeRunSucceededEvent, # start node completes - NodeRunStartedEvent, # llm_initial starts and streams - NodeRunSucceededEvent, # llm_initial completes streaming - NodeRunStartedEvent, # if_else evaluates conditions - NodeRunStreamChunkEvent, # cached llm_initial chunk 1 flushed - NodeRunStreamChunkEvent, # cached llm_initial chunk 2 flushed - NodeRunStreamChunkEvent, # cached llm_initial final chunk flushed - NodeRunStreamChunkEvent, # template literal newline emitted - NodeRunSucceededEvent, # if_else completes branch selection - NodeRunStartedEvent, # llm_secondary begins streaming - NodeRunStreamChunkEvent, # llm_secondary chunk 1 - NodeRunStreamChunkEvent, # llm_secondary final chunk - NodeRunSucceededEvent, # llm_secondary completes - NodeRunStartedEvent, # end_secondary node starts - NodeRunSucceededEvent, # end_secondary finishes aggregation - GraphRunSucceededEvent, # graph run succeeds - ], - "expected_chunks": [ - ("llm_initial", _expected_mock_llm_chunks("Initial stream")), - ("end_secondary", ["\n"]), - ("llm_secondary", _expected_mock_llm_chunks("Secondary")), - ], - }, - ] - - for scenario in scenarios: - runner = TableTestRunner() - - def graph_factory( - branch_value: str = scenario["branch"], - cfg: MockConfig = mock_config, - ) -> tuple[Graph, GraphRuntimeState]: - return _build_if_else_graph(branch_value, cfg) - - test_case = WorkflowTestCase( - description=f"IfElse streaming via {scenario['branch']} branch", - graph_factory=graph_factory, - expected_event_sequence=scenario["expected_sequence"], - ) - - result = runner.run_test_case(test_case) - - assert result.success, result.event_mismatch_details - - chunk_events = [event for event in result.events if isinstance(event, NodeRunStreamChunkEvent)] - expected_nodes: list[str] = [] - expected_chunks: list[str] = [] - for node_id, chunks in scenario["expected_chunks"]: - expected_nodes.extend([node_id] * len(chunks)) - expected_chunks.extend(chunks) - assert [event.node_id for event in chunk_events] == expected_nodes - assert [event.chunk for event in chunk_events] == expected_chunks - - branch_node_index = next( - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunStartedEvent) and event.node_id == "if_else" - ) - branch_success_index = next( - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == "if_else" - ) - pre_branch_chunk_indices = [ - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunStreamChunkEvent) and index < branch_success_index - ] - assert len(pre_branch_chunk_indices) == len(_expected_mock_llm_chunks("Initial stream")) + 1 - assert min(pre_branch_chunk_indices) == branch_node_index + 1 - assert max(pre_branch_chunk_indices) < branch_success_index - - resume_chunk_indices = [ - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunStreamChunkEvent) and event.node_id == scenario["resume_llm"] - ] - assert resume_chunk_indices - resume_start_index = next( - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunStartedEvent) and event.node_id == scenario["resume_llm"] - ) - resume_success_index = next( - index - for index, event in enumerate(result.events) - if isinstance(event, NodeRunSucceededEvent) and event.node_id == scenario["resume_llm"] - ) - assert resume_start_index < min(resume_chunk_indices) - assert max(resume_chunk_indices) < resume_success_index - - started_nodes = [event.node_id for event in result.events if isinstance(event, NodeRunStartedEvent)] - assert started_nodes == ["start", "llm_initial", "if_else", scenario["resume_llm"], scenario["end_node"]] diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_iteration_flatten_output.py b/api/tests/unit_tests/core/workflow/graph_engine/test_iteration_flatten_output.py deleted file mode 100644 index b9bf4be13a0..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_iteration_flatten_output.py +++ /dev/null @@ -1,126 +0,0 @@ -""" -Test cases for the Iteration node's flatten_output functionality. - -This module tests the iteration node's ability to: -1. Flatten array outputs when flatten_output=True (default) -2. Preserve nested array structure when flatten_output=False -""" - -from .test_database_utils import skip_if_database_unavailable -from .test_mock_config import MockConfigBuilder, NodeMockConfig -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def _create_iteration_mock_config(): - """Helper to create a mock config for iteration tests.""" - - def code_inner_handler(node): - pool = node.graph_runtime_state.variable_pool - item_seg = pool.get(["iteration_node", "item"]) - if item_seg is not None: - item = item_seg.to_object() - return {"result": [item, item * 2]} - # This fallback is likely unreachable, but if it is, - # it doesn't simulate iteration with different values as the comment suggests. - return {"result": [1, 2]} - - return ( - MockConfigBuilder() - .with_node_output("code_node", {"result": [1, 2, 3]}) - .with_node_config(NodeMockConfig(node_id="code_inner_node", custom_handler=code_inner_handler)) - .build() - ) - - -@skip_if_database_unavailable() -def test_iteration_with_flatten_output_enabled(): - """ - Test iteration node with flatten_output=True (default behavior). - - The fixture implements an iteration that: - 1. Iterates over [1, 2, 3] - 2. For each item, outputs [item, item*2] - 3. With flatten_output=True, should output [1, 2, 2, 4, 3, 6] - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="iteration_flatten_output_enabled_workflow", - inputs={}, - expected_outputs={"output": [1, 2, 2, 4, 3, 6]}, - description="Iteration with flatten_output=True flattens nested arrays", - use_auto_mock=True, # Use auto-mock to avoid sandbox service - mock_config=_create_iteration_mock_config(), - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Test failed: {result.error}" - assert result.actual_outputs is not None, "Should have outputs" - assert result.actual_outputs == {"output": [1, 2, 2, 4, 3, 6]}, ( - f"Expected flattened output [1, 2, 2, 4, 3, 6], got {result.actual_outputs}" - ) - - -@skip_if_database_unavailable() -def test_iteration_with_flatten_output_disabled(): - """ - Test iteration node with flatten_output=False. - - The fixture implements an iteration that: - 1. Iterates over [1, 2, 3] - 2. For each item, outputs [item, item*2] - 3. With flatten_output=False, should output [[1, 2], [2, 4], [3, 6]] - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="iteration_flatten_output_disabled_workflow", - inputs={}, - expected_outputs={"output": [[1, 2], [2, 4], [3, 6]]}, - description="Iteration with flatten_output=False preserves nested structure", - use_auto_mock=True, # Use auto-mock to avoid sandbox service - mock_config=_create_iteration_mock_config(), - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Test failed: {result.error}" - assert result.actual_outputs is not None, "Should have outputs" - assert result.actual_outputs == {"output": [[1, 2], [2, 4], [3, 6]]}, ( - f"Expected nested output [[1, 2], [2, 4], [3, 6]], got {result.actual_outputs}" - ) - - -@skip_if_database_unavailable() -def test_iteration_flatten_output_comparison(): - """ - Run both flatten_output configurations in parallel to verify the difference. - """ - runner = TableTestRunner() - - test_cases = [ - WorkflowTestCase( - fixture_path="iteration_flatten_output_enabled_workflow", - inputs={}, - expected_outputs={"output": [1, 2, 2, 4, 3, 6]}, - description="flatten_output=True: Flattened output", - use_auto_mock=True, # Use auto-mock to avoid sandbox service - mock_config=_create_iteration_mock_config(), - ), - WorkflowTestCase( - fixture_path="iteration_flatten_output_disabled_workflow", - inputs={}, - expected_outputs={"output": [[1, 2], [2, 4], [3, 6]]}, - description="flatten_output=False: Nested output", - use_auto_mock=True, # Use auto-mock to avoid sandbox service - mock_config=_create_iteration_mock_config(), - ), - ] - - suite_result = runner.run_table_tests(test_cases, parallel=True) - - # Assert all tests passed - assert suite_result.passed_tests == 2, f"Expected 2 passed tests, got {suite_result.passed_tests}" - assert suite_result.failed_tests == 0, f"Expected 0 failed tests, got {suite_result.failed_tests}" - assert suite_result.success_rate == 100.0, f"Expected 100% success rate, got {suite_result.success_rate}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_contains_answer.py b/api/tests/unit_tests/core/workflow/graph_engine/test_loop_contains_answer.py deleted file mode 100644 index 733fd53bc8a..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_contains_answer.py +++ /dev/null @@ -1,85 +0,0 @@ -""" -Test case for loop with inner answer output error scenario. - -This test validates the behavior of a loop containing an answer node -inside the loop that may produce output errors. -""" - -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunLoopNextEvent, - NodeRunLoopStartedEvent, - NodeRunLoopSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_loop_contains_answer(): - """ - Test loop with inner answer node that may have output errors. - - The fixture implements a loop that: - 1. Iterates 4 times (index 0-3) - 2. Contains an inner answer node that outputs index and item values - 3. Has a break condition when index equals 4 - 4. Tests error handling for answer nodes within loops - """ - fixture_name = "loop_contains_answer" - mock_config = MockConfigBuilder().build() - - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=True, - mock_config=mock_config, - query="1", - expected_outputs={"answer": "1\n2\n1 + 2"}, - expected_event_sequence=[ - # Graph start - GraphRunStartedEvent, - # Start - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Loop start - NodeRunStartedEvent, - NodeRunLoopStartedEvent, - # Variable assigner - NodeRunStartedEvent, - NodeRunStreamChunkEvent, # 1 - NodeRunStreamChunkEvent, # \n - NodeRunSucceededEvent, - # Answer - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Loop next - NodeRunLoopNextEvent, - # Variable assigner - NodeRunStartedEvent, - NodeRunStreamChunkEvent, # 2 - NodeRunStreamChunkEvent, # \n - NodeRunSucceededEvent, - # Answer - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Loop end - NodeRunLoopSucceededEvent, - NodeRunStreamChunkEvent, # 1 - NodeRunStreamChunkEvent, # + - NodeRunStreamChunkEvent, # 2 - NodeRunSucceededEvent, - # Answer - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Graph end - GraphRunSucceededEvent, - ], - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_node.py b/api/tests/unit_tests/core/workflow/graph_engine/test_loop_node.py deleted file mode 100644 index ad8d777ea69..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_node.py +++ /dev/null @@ -1,41 +0,0 @@ -""" -Test cases for the Loop node functionality using TableTestRunner. - -This module tests the loop node's ability to: -1. Execute iterations with loop variables -2. Handle break conditions correctly -3. Update and propagate loop variables between iterations -4. Output the final loop variable value -""" - -from tests.unit_tests.core.workflow.graph_engine.test_table_runner import ( - TableTestRunner, - WorkflowTestCase, -) - - -def test_loop_with_break_condition(): - """ - Test loop node with break condition. - - The increment_loop_with_break_condition_workflow.yml fixture implements a loop that: - 1. Starts with num=1 - 2. Increments num by 1 each iteration - 3. Breaks when num >= 5 - 4. Should output {"num": 5} - """ - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="increment_loop_with_break_condition_workflow", - inputs={}, # No inputs needed for this test - expected_outputs={"num": 5}, - description="Loop with break condition when num >= 5", - ) - - result = runner.run_test_case(test_case) - - # Assert the test passed - assert result.success, f"Test failed: {result.error}" - assert result.actual_outputs is not None, "Should have outputs" - assert result.actual_outputs == {"num": 5}, f"Expected {{'num': 5}}, got {result.actual_outputs}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_with_tool.py b/api/tests/unit_tests/core/workflow/graph_engine/test_loop_with_tool.py deleted file mode 100644 index 6ff2722f78a..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_loop_with_tool.py +++ /dev/null @@ -1,67 +0,0 @@ -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunLoopNextEvent, - NodeRunLoopStartedEvent, - NodeRunLoopSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_loop_with_tool(): - fixture_name = "search_dify_from_2023_to_2025" - mock_config = ( - MockConfigBuilder() - .with_tool_response( - { - "text": "mocked search result", - } - ) - .build() - ) - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=True, - mock_config=mock_config, - expected_outputs={ - "answer": """- mocked search result -- mocked search result""" - }, - expected_event_sequence=[ - GraphRunStartedEvent, - # START - NodeRunStartedEvent, - NodeRunSucceededEvent, - # LOOP START - NodeRunStartedEvent, - NodeRunLoopStartedEvent, - # 2023 - NodeRunStartedEvent, - NodeRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - NodeRunLoopNextEvent, - # 2024 - NodeRunStartedEvent, - NodeRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, - # LOOP END - NodeRunLoopSucceededEvent, - NodeRunStreamChunkEvent, # loop.res - NodeRunSucceededEvent, - # ANSWER - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_example.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_example.py deleted file mode 100644 index c511548749c..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_example.py +++ /dev/null @@ -1,281 +0,0 @@ -""" -Example demonstrating the auto-mock system for testing workflows. - -This example shows how to test workflows with third-party service nodes -without making actual API calls. -""" - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def example_test_llm_workflow(): - """ - Example: Testing a workflow with an LLM node. - - This demonstrates how to test a workflow that uses an LLM service - without making actual API calls to OpenAI, Anthropic, etc. - """ - print("\n=== Example: Testing LLM Workflow ===\n") - - # Initialize the test runner - runner = TableTestRunner() - - # Configure mock responses - mock_config = MockConfigBuilder().with_llm_response("I'm a helpful AI assistant. How can I help you today?").build() - - # Define the test case - test_case = WorkflowTestCase( - fixture_path="llm-simple", - inputs={"query": "Hello, AI!"}, - expected_outputs={"answer": "I'm a helpful AI assistant. How can I help you today?"}, - description="Testing LLM workflow with mocked response", - use_auto_mock=True, # Enable auto-mocking - mock_config=mock_config, - ) - - # Run the test - result = runner.run_test_case(test_case) - - if result.success: - print("✅ Test passed!") - print(f" Input: {test_case.inputs['query']}") - print(f" Output: {result.actual_outputs['answer']}") - print(f" Execution time: {result.execution_time:.2f}s") - else: - print(f"❌ Test failed: {result.error}") - - return result.success - - -def example_test_with_custom_outputs(): - """ - Example: Testing with custom outputs for specific nodes. - - This shows how to provide different mock outputs for specific node IDs, - useful when testing complex workflows with multiple LLM/tool nodes. - """ - print("\n=== Example: Custom Node Outputs ===\n") - - runner = TableTestRunner() - - # Configure mock with specific outputs for different nodes - mock_config = MockConfigBuilder().build() - - # Set custom output for a specific LLM node - mock_config.set_node_outputs( - "llm_node", - { - "text": "This is a custom response for the specific LLM node", - "usage": { - "prompt_tokens": 50, - "completion_tokens": 20, - "total_tokens": 70, - }, - "finish_reason": "stop", - }, - ) - - test_case = WorkflowTestCase( - fixture_path="llm-simple", - inputs={"query": "Tell me about custom outputs"}, - expected_outputs={"answer": "This is a custom response for the specific LLM node"}, - description="Testing with custom node outputs", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - if result.success: - print("✅ Test with custom outputs passed!") - print(f" Custom output: {result.actual_outputs['answer']}") - else: - print(f"❌ Test failed: {result.error}") - - return result.success - - -def example_test_http_and_tool_workflow(): - """ - Example: Testing a workflow with HTTP request and tool nodes. - - This demonstrates mocking external HTTP calls and tool executions. - """ - print("\n=== Example: HTTP and Tool Workflow ===\n") - - runner = TableTestRunner() - - # Configure mocks for HTTP and Tool nodes - mock_config = MockConfigBuilder().build() - - # Mock HTTP response - mock_config.set_node_outputs( - "http_node", - { - "status_code": 200, - "body": '{"users": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]}', - "headers": {"content-type": "application/json"}, - }, - ) - - # Mock tool response (e.g., JSON parser) - mock_config.set_node_outputs( - "tool_node", - { - "result": {"users": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]}, - }, - ) - - test_case = WorkflowTestCase( - fixture_path="http-tool-workflow", - inputs={"url": "https://api.example.com/users"}, - expected_outputs={ - "status_code": 200, - "parsed_data": {"users": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]}, - }, - description="Testing HTTP and Tool workflow", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - if result.success: - print("✅ HTTP and Tool workflow test passed!") - print(f" HTTP Status: {result.actual_outputs['status_code']}") - print(f" Parsed Data: {result.actual_outputs['parsed_data']}") - else: - print(f"❌ Test failed: {result.error}") - - return result.success - - -def example_test_error_simulation(): - """ - Example: Simulating errors in specific nodes. - - This shows how to test error handling in workflows by simulating - failures in specific nodes. - """ - print("\n=== Example: Error Simulation ===\n") - - runner = TableTestRunner() - - # Configure mock to simulate an error - mock_config = MockConfigBuilder().build() - mock_config.set_node_error("llm_node", "API rate limit exceeded") - - test_case = WorkflowTestCase( - fixture_path="llm-simple", - inputs={"query": "This will fail"}, - expected_outputs={}, # We expect failure - description="Testing error handling", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - if not result.success: - print("✅ Error simulation worked as expected!") - print(f" Simulated error: {result.error}") - else: - print("❌ Expected failure but test succeeded") - - return not result.success # Success means we got the expected error - - -def example_test_with_delays(): - """ - Example: Testing with simulated execution delays. - - This demonstrates how to simulate realistic execution times - for performance testing. - """ - print("\n=== Example: Simulated Delays ===\n") - - runner = TableTestRunner() - - # Configure mock with delays - mock_config = ( - MockConfigBuilder() - .with_delays(True) # Enable delay simulation - .with_llm_response("Response after delay") - .build() - ) - - # Add specific delay for the LLM node - from .test_mock_config import NodeMockConfig - - node_config = NodeMockConfig( - node_id="llm_node", - outputs={"text": "Response after delay"}, - delay=0.5, # 500ms delay - ) - mock_config.set_node_config("llm_node", node_config) - - test_case = WorkflowTestCase( - fixture_path="llm-simple", - inputs={"query": "Test with delay"}, - expected_outputs={"answer": "Response after delay"}, - description="Testing with simulated delays", - use_auto_mock=True, - mock_config=mock_config, - ) - - result = runner.run_test_case(test_case) - - if result.success: - print("✅ Delay simulation test passed!") - print(f" Execution time: {result.execution_time:.2f}s") - print(" (Should be >= 0.5s due to simulated delay)") - else: - print(f"❌ Test failed: {result.error}") - - return result.success and result.execution_time >= 0.5 - - -def run_all_examples(): - """Run all example tests.""" - print("\n" + "=" * 50) - print("AUTO-MOCK SYSTEM EXAMPLES") - print("=" * 50) - - examples = [ - example_test_llm_workflow, - example_test_with_custom_outputs, - example_test_http_and_tool_workflow, - example_test_error_simulation, - example_test_with_delays, - ] - - results = [] - for example in examples: - try: - results.append(example()) - except Exception as e: - print(f"\n❌ Example failed with exception: {e}") - results.append(False) - - print("\n" + "=" * 50) - print("SUMMARY") - print("=" * 50) - - passed = sum(results) - total = len(results) - print(f"\n✅ Passed: {passed}/{total}") - - if passed == total: - print("\n🎉 All examples passed successfully!") - else: - print(f"\n⚠️ {total - passed} example(s) failed") - - return passed == total - - -if __name__ == "__main__": - import sys - - success = run_all_examples() - sys.exit(0 if success else 1) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_factory.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_factory.py index 93010eea542..88989db8565 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_factory.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_factory.py @@ -7,10 +7,11 @@ requiring external services (LLM, Agent, Tool, Knowledge Retrieval, HTTP Request from typing import TYPE_CHECKING, Any +from graphon.entities.graph_config import NodeConfigDict, NodeConfigDictAdapter +from graphon.enums import BuiltinNodeTypes, NodeType +from graphon.nodes.base.node import Node + from core.workflow.node_factory import DifyNodeFactory -from dify_graph.entities.graph_config import NodeConfigDict, NodeConfigDictAdapter -from dify_graph.enums import BuiltinNodeTypes, NodeType -from dify_graph.nodes.base.node import Node from .test_mock_nodes import ( MockAgentNode, @@ -28,8 +29,8 @@ from .test_mock_nodes import ( ) if TYPE_CHECKING: - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState + from graphon.entities import GraphInitParams + from graphon.runtime import GraphRuntimeState from .test_mock_config import MockConfig @@ -111,7 +112,7 @@ class MockNodeFactory(DifyNodeFactory): mock_config=self.mock_config, http_request_config=self._http_request_config, http_client=self._http_request_http_client, - tool_file_manager_factory=self._http_request_tool_file_manager_factory, + tool_file_manager_factory=self._bound_tool_file_manager_factory, file_manager=self._http_request_file_manager, ) elif node_type in { diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_iteration_simple.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_iteration_simple.py deleted file mode 100644 index 3e4247f33f5..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_iteration_simple.py +++ /dev/null @@ -1,199 +0,0 @@ -""" -Simple test to verify MockNodeFactory works with iteration nodes. -""" - -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY -from dify_graph.enums import BuiltinNodeTypes -from tests.unit_tests.core.workflow.graph_engine.test_mock_config import MockConfigBuilder -from tests.unit_tests.core.workflow.graph_engine.test_mock_factory import MockNodeFactory - - -def test_mock_factory_registers_iteration_node(): - """Test that MockNodeFactory has iteration node registered.""" - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create a MockNodeFactory instance - graph_init_params = GraphInitParams( - workflow_id="test", - graph_config={"nodes": [], "edges": []}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test", - "app_id": "test", - "user_id": "test", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.SERVICE_API, - } - }, - call_depth=0, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=None, - ) - - # Check that iteration node is registered - assert BuiltinNodeTypes.ITERATION in factory._mock_node_types - print("✓ Iteration node is registered in MockNodeFactory") - - # Check that loop node is registered - assert BuiltinNodeTypes.LOOP in factory._mock_node_types - print("✓ Loop node is registered in MockNodeFactory") - - # Check the class types - from tests.unit_tests.core.workflow.graph_engine.test_mock_nodes import MockIterationNode, MockLoopNode - - assert factory._mock_node_types[BuiltinNodeTypes.ITERATION] == MockIterationNode - print("✓ Iteration node maps to MockIterationNode class") - - assert factory._mock_node_types[BuiltinNodeTypes.LOOP] == MockLoopNode - print("✓ Loop node maps to MockLoopNode class") - - -def test_mock_iteration_node_preserves_config(): - """Test that MockIterationNode preserves mock configuration.""" - - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - from tests.unit_tests.core.workflow.graph_engine.test_mock_nodes import MockIterationNode - - # Create mock config - mock_config = MockConfigBuilder().with_llm_response("Test response").build() - - # Create minimal graph init params - graph_init_params = GraphInitParams( - workflow_id="test", - graph_config={"nodes": [], "edges": []}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test", - "app_id": "test", - "user_id": "test", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.SERVICE_API, - } - }, - call_depth=0, - ) - - # Create minimal runtime state - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - - # Create mock iteration node - node_config = { - "id": "iter1", - "data": { - "type": "iteration", - "title": "Test", - "iterator_selector": ["start", "items"], - "output_selector": ["node", "text"], - "start_node_id": "node1", - }, - } - - mock_node = MockIterationNode( - id="iter1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Verify the mock config is preserved - assert mock_node.mock_config == mock_config - print("✓ MockIterationNode preserves mock configuration") - - # Check that _create_graph_engine method exists and is overridden - assert hasattr(mock_node, "_create_graph_engine") - assert MockIterationNode._create_graph_engine != MockIterationNode.__bases__[1]._create_graph_engine - print("✓ MockIterationNode overrides _create_graph_engine method") - - -def test_mock_loop_node_preserves_config(): - """Test that MockLoopNode preserves mock configuration.""" - - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - from tests.unit_tests.core.workflow.graph_engine.test_mock_nodes import MockLoopNode - - # Create mock config - mock_config = MockConfigBuilder().with_http_response({"status": 200}).build() - - # Create minimal graph init params - graph_init_params = GraphInitParams( - workflow_id="test", - graph_config={"nodes": [], "edges": []}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test", - "app_id": "test", - "user_id": "test", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.SERVICE_API, - } - }, - call_depth=0, - ) - - # Create minimal runtime state - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - - # Create mock loop node - node_config = { - "id": "loop1", - "data": { - "type": "loop", - "title": "Test", - "loop_count": 3, - "start_node_id": "node1", - "loop_variables": [], - "outputs": {}, - "break_conditions": [], - "logical_operator": "and", - }, - } - - mock_node = MockLoopNode( - id="loop1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Verify the mock config is preserved - assert mock_node.mock_config == mock_config - print("✓ MockLoopNode preserves mock configuration") - - # Check that _create_graph_engine method exists and is overridden - assert hasattr(mock_node, "_create_graph_engine") - assert MockLoopNode._create_graph_engine != MockLoopNode.__bases__[1]._create_graph_engine - print("✓ MockLoopNode overrides _create_graph_engine method") - - -if __name__ == "__main__": - test_mock_factory_registers_iteration_node() - test_mock_iteration_node_preserves_config() - test_mock_loop_node_preserves_config() - print("\n✅ All tests passed! MockNodeFactory now supports iteration and loop nodes.") diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py index 454263bef9a..8b7fbd1b303 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py @@ -10,30 +10,31 @@ from collections.abc import Generator, Mapping from typing import TYPE_CHECKING, Any, Optional from unittest.mock import MagicMock +from graphon.enums import WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus +from graphon.model_runtime.entities.llm_entities import LLMUsage +from graphon.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent +from graphon.nodes.code import CodeNode +from graphon.nodes.document_extractor import DocumentExtractorNode +from graphon.nodes.http_request import HttpRequestNode +from graphon.nodes.llm import LLMNode +from graphon.nodes.llm.file_saver import LLMFileSaver +from graphon.nodes.llm.protocols import CredentialsProvider, ModelFactory +from graphon.nodes.llm.runtime_protocols import PromptMessageSerializerProtocol +from graphon.nodes.parameter_extractor import ParameterExtractorNode +from graphon.nodes.protocols import FileReferenceFactoryProtocol, HttpClientProtocol, ToolFileManagerProtocol +from graphon.nodes.question_classifier import QuestionClassifierNode +from graphon.nodes.template_transform import TemplateTransformNode +from graphon.nodes.tool import ToolNode +from graphon.template_rendering import Jinja2TemplateRenderer, TemplateRenderError + from core.model_manager import ModelInstance +from core.workflow.node_runtime import DifyToolNodeRuntime from core.workflow.nodes.agent import AgentNode from core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node import KnowledgeRetrievalNode -from dify_graph.enums import WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus -from dify_graph.model_runtime.entities.llm_entities import LLMUsage -from dify_graph.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent -from dify_graph.nodes.code import CodeNode -from dify_graph.nodes.document_extractor import DocumentExtractorNode -from dify_graph.nodes.http_request import HttpRequestNode -from dify_graph.nodes.llm import LLMNode -from dify_graph.nodes.llm.protocols import CredentialsProvider, ModelFactory, TemplateRenderer -from dify_graph.nodes.parameter_extractor import ParameterExtractorNode -from dify_graph.nodes.protocols import HttpClientProtocol, ToolFileManagerProtocol -from dify_graph.nodes.question_classifier import QuestionClassifierNode -from dify_graph.nodes.template_transform import TemplateTransformNode -from dify_graph.nodes.template_transform.template_renderer import ( - Jinja2TemplateRenderer, - TemplateRenderError, -) -from dify_graph.nodes.tool import ToolNode if TYPE_CHECKING: - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState + from graphon.entities import GraphInitParams + from graphon.runtime import GraphRuntimeState from .test_mock_config import MockConfig @@ -66,20 +67,26 @@ class MockNodeMixin: kwargs.setdefault("credentials_provider", MagicMock(spec=CredentialsProvider)) kwargs.setdefault("model_factory", MagicMock(spec=ModelFactory)) kwargs.setdefault("model_instance", MagicMock(spec=ModelInstance)) + kwargs.setdefault("prompt_message_serializer", MagicMock(spec=PromptMessageSerializerProtocol)) # LLM-like nodes now require an http_client; provide a mock by default for tests. kwargs.setdefault("http_client", MagicMock(spec=HttpClientProtocol)) - if isinstance(self, (LLMNode, QuestionClassifierNode)): - kwargs.setdefault("template_renderer", MagicMock(spec=TemplateRenderer)) + + if isinstance(self, (LLMNode, QuestionClassifierNode)): + kwargs.setdefault("llm_file_saver", MagicMock(spec=LLMFileSaver)) + + if isinstance(self, HttpRequestNode): + kwargs.setdefault("file_reference_factory", MagicMock(spec=FileReferenceFactoryProtocol)) # Ensure TemplateTransformNode receives a renderer now required by constructor if isinstance(self, TemplateTransformNode): - kwargs.setdefault("template_renderer", _TestJinja2Renderer()) + kwargs.setdefault("jinja2_template_renderer", _TestJinja2Renderer()) # Provide default tool_file_manager_factory for ToolNode subclasses - from dify_graph.nodes.tool import ToolNode as _ToolNode # local import to avoid cycles + from graphon.nodes.tool import ToolNode as _ToolNode # local import to avoid cycles if isinstance(self, _ToolNode): kwargs.setdefault("tool_file_manager_factory", MagicMock(spec=ToolFileManagerProtocol)) + kwargs.setdefault("runtime", DifyToolNodeRuntime(graph_init_params.run_context)) if isinstance(self, AgentNode): presentation_provider = MagicMock() @@ -596,8 +603,8 @@ class MockDocumentExtractorNode(MockNodeMixin, DocumentExtractorNode): ) -from dify_graph.nodes.iteration import IterationNode -from dify_graph.nodes.loop import LoopNode +from graphon.nodes.iteration import IterationNode +from graphon.nodes.loop import LoopNode class MockIterationNode(MockNodeMixin, IterationNode): @@ -611,11 +618,11 @@ class MockIterationNode(MockNodeMixin, IterationNode): def _create_graph_engine(self, index: int, item: Any): """Create a graph engine with MockNodeFactory instead of DifyNodeFactory.""" # Import dependencies - from dify_graph.entities import GraphInitParams - from dify_graph.graph import Graph - from dify_graph.graph_engine import GraphEngine, GraphEngineConfig - from dify_graph.graph_engine.command_channels import InMemoryChannel - from dify_graph.runtime import GraphRuntimeState + from graphon.entities import GraphInitParams + from graphon.graph import Graph + from graphon.graph_engine import GraphEngine, GraphEngineConfig + from graphon.graph_engine.command_channels import InMemoryChannel + from graphon.runtime import GraphRuntimeState # Import our MockNodeFactory instead of DifyNodeFactory from .test_mock_factory import MockNodeFactory @@ -656,7 +663,7 @@ class MockIterationNode(MockNodeMixin, IterationNode): ) if not iteration_graph: - from dify_graph.nodes.iteration.exc import IterationGraphNotFoundError + from graphon.nodes.iteration.exc import IterationGraphNotFoundError raise IterationGraphNotFoundError("iteration graph not found") @@ -683,11 +690,11 @@ class MockLoopNode(MockNodeMixin, LoopNode): def _create_graph_engine(self, start_at, root_node_id: str): """Create a graph engine with MockNodeFactory instead of DifyNodeFactory.""" # Import dependencies - from dify_graph.entities import GraphInitParams - from dify_graph.graph import Graph - from dify_graph.graph_engine import GraphEngine, GraphEngineConfig - from dify_graph.graph_engine.command_channels import InMemoryChannel - from dify_graph.runtime import GraphRuntimeState + from graphon.entities import GraphInitParams + from graphon.graph import Graph + from graphon.graph_engine import GraphEngine, GraphEngineConfig + from graphon.graph_engine.command_channels import InMemoryChannel + from graphon.runtime import GraphRuntimeState # Import our MockNodeFactory instead of DifyNodeFactory from .test_mock_factory import MockNodeFactory diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes_template_code.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes_template_code.py deleted file mode 100644 index a8398e8f79f..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes_template_code.py +++ /dev/null @@ -1,670 +0,0 @@ -""" -Test cases for Mock Template Transform and Code nodes. - -This module tests the functionality of MockTemplateTransformNode and MockCodeNode -to ensure they work correctly with the TableTestRunner. -""" - -from configs import dify_config -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.nodes.code.limits import CodeNodeLimits -from tests.unit_tests.core.workflow.graph_engine.test_mock_config import MockConfig, MockConfigBuilder, NodeMockConfig -from tests.unit_tests.core.workflow.graph_engine.test_mock_factory import MockNodeFactory -from tests.unit_tests.core.workflow.graph_engine.test_mock_nodes import MockCodeNode, MockTemplateTransformNode - -DEFAULT_CODE_LIMITS = CodeNodeLimits( - max_string_length=dify_config.CODE_MAX_STRING_LENGTH, - max_number=dify_config.CODE_MAX_NUMBER, - min_number=dify_config.CODE_MIN_NUMBER, - max_precision=dify_config.CODE_MAX_PRECISION, - max_depth=dify_config.CODE_MAX_DEPTH, - max_number_array_length=dify_config.CODE_MAX_NUMBER_ARRAY_LENGTH, - max_string_array_length=dify_config.CODE_MAX_STRING_ARRAY_LENGTH, - max_object_array_length=dify_config.CODE_MAX_OBJECT_ARRAY_LENGTH, -) - - -class _NoopCodeExecutor: - def execute(self, *, language: object, code: str, inputs: dict[str, object]) -> dict[str, object]: - _ = (language, code, inputs) - return {} - - def is_execution_error(self, error: Exception) -> bool: - _ = error - return False - - -class TestMockTemplateTransformNode: - """Test cases for MockTemplateTransformNode.""" - - def test_mock_template_transform_node_default_output(self): - """Test that MockTemplateTransformNode processes templates with Jinja2.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config - mock_config = MockConfig() - - # Create node config - node_config = { - "id": "template_node_1", - "data": { - "type": "template-transform", - "title": "Test Template Transform", - "variables": [], - "template": "Hello {{ name }}", - }, - } - - # Create mock node - mock_node = MockTemplateTransformNode( - id="template_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "output" in result.outputs - # The template "Hello {{ name }}" with no name variable renders as "Hello " - assert result.outputs["output"] == "Hello " - - def test_mock_template_transform_node_custom_output(self): - """Test that MockTemplateTransformNode returns custom configured output.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config with custom output - mock_config = ( - MockConfigBuilder().with_node_output("template_node_1", {"output": "Custom template output"}).build() - ) - - # Create node config - node_config = { - "id": "template_node_1", - "data": { - "type": "template-transform", - "title": "Test Template Transform", - "variables": [], - "template": "Hello {{ name }}", - }, - } - - # Create mock node - mock_node = MockTemplateTransformNode( - id="template_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "output" in result.outputs - assert result.outputs["output"] == "Custom template output" - - def test_mock_template_transform_node_error_simulation(self): - """Test that MockTemplateTransformNode can simulate errors.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config with error - mock_config = MockConfigBuilder().with_node_error("template_node_1", "Simulated template error").build() - - # Create node config - node_config = { - "id": "template_node_1", - "data": { - "type": "template-transform", - "title": "Test Template Transform", - "variables": [], - "template": "Hello {{ name }}", - }, - } - - # Create mock node - mock_node = MockTemplateTransformNode( - id="template_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.FAILED - assert result.error == "Simulated template error" - - def test_mock_template_transform_node_with_variables(self): - """Test that MockTemplateTransformNode processes templates with variables.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - from dify_graph.variables import StringVariable - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - # Add a variable to the pool - variable_pool.add(["test", "name"], StringVariable(name="name", value="World", selector=["test", "name"])) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config - mock_config = MockConfig() - - # Create node config with a variable - node_config = { - "id": "template_node_1", - "data": { - "type": "template-transform", - "title": "Test Template Transform", - "variables": [{"variable": "name", "value_selector": ["test", "name"]}], - "template": "Hello {{ name }}!", - }, - } - - # Create mock node - mock_node = MockTemplateTransformNode( - id="template_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "output" in result.outputs - assert result.outputs["output"] == "Hello World!" - - -class TestMockCodeNode: - """Test cases for MockCodeNode.""" - - def test_mock_code_node_default_output(self): - """Test that MockCodeNode returns default output.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config - mock_config = MockConfig() - - # Create node config - node_config = { - "id": "code_node_1", - "data": { - "type": "code", - "title": "Test Code", - "variables": [], - "code_language": "python3", - "code": "result = 'test'", - "outputs": {}, # Empty outputs for default case - }, - } - - # Create mock node - mock_node = MockCodeNode( - id="code_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - code_executor=_NoopCodeExecutor(), - code_limits=DEFAULT_CODE_LIMITS, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "result" in result.outputs - assert result.outputs["result"] == "mocked code execution result" - - def test_mock_code_node_with_output_schema(self): - """Test that MockCodeNode generates outputs based on schema.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config - mock_config = MockConfig() - - # Create node config with output schema - node_config = { - "id": "code_node_1", - "data": { - "type": "code", - "title": "Test Code", - "variables": [], - "code_language": "python3", - "code": "name = 'test'\ncount = 42\nitems = ['a', 'b']", - "outputs": { - "name": {"type": "string"}, - "count": {"type": "number"}, - "items": {"type": "array[string]"}, - }, - }, - } - - # Create mock node - mock_node = MockCodeNode( - id="code_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - code_executor=_NoopCodeExecutor(), - code_limits=DEFAULT_CODE_LIMITS, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "name" in result.outputs - assert result.outputs["name"] == "mocked_name" - assert "count" in result.outputs - assert result.outputs["count"] == 42 - assert "items" in result.outputs - assert result.outputs["items"] == ["item1", "item2"] - - def test_mock_code_node_custom_output(self): - """Test that MockCodeNode returns custom configured output.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create mock config with custom output - mock_config = ( - MockConfigBuilder() - .with_node_output("code_node_1", {"result": "Custom code result", "status": "success"}) - .build() - ) - - # Create node config - node_config = { - "id": "code_node_1", - "data": { - "type": "code", - "title": "Test Code", - "variables": [], - "code_language": "python3", - "code": "result = 'test'", - "outputs": {}, # Empty outputs for default case - }, - } - - # Create mock node - mock_node = MockCodeNode( - id="code_node_1", - config=node_config, - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=mock_config, - code_executor=_NoopCodeExecutor(), - code_limits=DEFAULT_CODE_LIMITS, - ) - - # Run the node - result = mock_node._run() - - # Verify results - assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert "result" in result.outputs - assert result.outputs["result"] == "Custom code result" - assert "status" in result.outputs - assert result.outputs["status"] == "success" - - -class TestMockNodeFactory: - """Test cases for MockNodeFactory with new node types.""" - - def test_code_and_template_nodes_mocked_by_default(self): - """Test that CODE and TEMPLATE_TRANSFORM nodes are mocked by default (they require SSRF proxy).""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create factory - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - # Verify that CODE and TEMPLATE_TRANSFORM ARE mocked by default (they require SSRF proxy) - assert factory.should_mock_node(BuiltinNodeTypes.CODE) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Verify that other third-party service nodes ARE also mocked by default - assert factory.should_mock_node(BuiltinNodeTypes.LLM) - assert factory.should_mock_node(BuiltinNodeTypes.AGENT) - - def test_factory_creates_mock_template_transform_node(self): - """Test that MockNodeFactory creates MockTemplateTransformNode for template-transform type.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create factory - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - # Create node config - node_config = { - "id": "template_node_1", - "data": { - "type": "template-transform", - "title": "Test Template", - "variables": [], - "template": "Hello {{ name }}", - }, - } - - # Create node through factory - node = factory.create_node(node_config) - - # Verify the correct mock type was created - assert isinstance(node, MockTemplateTransformNode) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - def test_factory_creates_mock_code_node(self): - """Test that MockNodeFactory creates MockCodeNode for code type.""" - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - # Create test parameters - graph_init_params = GraphInitParams( - workflow_id="test_workflow", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test_tenant", - "app_id": "test_app", - "user_id": "test_user", - "user_from": "account", - "invoke_from": "debugger", - } - }, - call_depth=0, - ) - - variable_pool = VariablePool( - system_variables={}, - user_inputs={}, - ) - - graph_runtime_state = GraphRuntimeState( - variable_pool=variable_pool, - start_at=0, - ) - - # Create factory - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - ) - - # Create node config - node_config = { - "id": "code_node_1", - "data": { - "type": "code", - "title": "Test Code", - "variables": [], - "code_language": "python3", - "code": "result = 42", - "outputs": {}, # Required field for CodeNodeData - }, - } - - # Create node through factory - node = factory.create_node(node_config) - - # Verify the correct mock type was created - assert isinstance(node, MockCodeNode) - assert factory.should_mock_node(BuiltinNodeTypes.CODE) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_simple.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_simple.py deleted file mode 100644 index 5b35b3310a0..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_simple.py +++ /dev/null @@ -1,231 +0,0 @@ -""" -Simple test to validate the auto-mock system without external dependencies. -""" - -import sys - -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY -from dify_graph.enums import BuiltinNodeTypes -from tests.unit_tests.core.workflow.graph_engine.test_mock_config import MockConfig, MockConfigBuilder, NodeMockConfig -from tests.unit_tests.core.workflow.graph_engine.test_mock_factory import MockNodeFactory - - -def test_mock_config_builder(): - """Test the MockConfigBuilder fluent interface.""" - print("Testing MockConfigBuilder...") - - config = ( - MockConfigBuilder() - .with_llm_response("LLM response") - .with_agent_response("Agent response") - .with_tool_response({"tool": "output"}) - .with_retrieval_response("Retrieval content") - .with_http_response({"status_code": 201, "body": "created"}) - .with_node_output("node1", {"output": "value"}) - .with_node_error("node2", "error message") - .with_delays(True) - .build() - ) - - assert config.default_llm_response == "LLM response" - assert config.default_agent_response == "Agent response" - assert config.default_tool_response == {"tool": "output"} - assert config.default_retrieval_response == "Retrieval content" - assert config.default_http_response == {"status_code": 201, "body": "created"} - assert config.simulate_delays is True - - node1_config = config.get_node_config("node1") - assert node1_config is not None - assert node1_config.outputs == {"output": "value"} - - node2_config = config.get_node_config("node2") - assert node2_config is not None - assert node2_config.error == "error message" - - print("✓ MockConfigBuilder test passed") - - -def test_mock_config_operations(): - """Test MockConfig operations.""" - print("Testing MockConfig operations...") - - config = MockConfig() - - # Test setting node outputs - config.set_node_outputs("test_node", {"result": "test_value"}) - node_config = config.get_node_config("test_node") - assert node_config is not None - assert node_config.outputs == {"result": "test_value"} - - # Test setting node error - config.set_node_error("error_node", "Test error") - error_config = config.get_node_config("error_node") - assert error_config is not None - assert error_config.error == "Test error" - - # Test default configs by node type - config.set_default_config(BuiltinNodeTypes.LLM, {"temperature": 0.7}) - llm_config = config.get_default_config(BuiltinNodeTypes.LLM) - assert llm_config == {"temperature": 0.7} - - print("✓ MockConfig operations test passed") - - -def test_node_mock_config(): - """Test NodeMockConfig.""" - print("Testing NodeMockConfig...") - - # Test with custom handler - def custom_handler(node): - return {"custom": "output"} - - node_config = NodeMockConfig( - node_id="test_node", outputs={"text": "test"}, error=None, delay=0.5, custom_handler=custom_handler - ) - - assert node_config.node_id == "test_node" - assert node_config.outputs == {"text": "test"} - assert node_config.delay == 0.5 - assert node_config.custom_handler is not None - - # Test custom handler - result = node_config.custom_handler(None) - assert result == {"custom": "output"} - - print("✓ NodeMockConfig test passed") - - -def test_mock_factory_detection(): - """Test MockNodeFactory node type detection.""" - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - print("Testing MockNodeFactory detection...") - - graph_init_params = GraphInitParams( - workflow_id="test", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test", - "app_id": "test", - "user_id": "test", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.SERVICE_API, - } - }, - call_depth=0, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=None, - ) - - # Test that third-party service nodes are identified for mocking - assert factory.should_mock_node(BuiltinNodeTypes.LLM) - assert factory.should_mock_node(BuiltinNodeTypes.AGENT) - assert factory.should_mock_node(BuiltinNodeTypes.TOOL) - assert factory.should_mock_node(BuiltinNodeTypes.KNOWLEDGE_RETRIEVAL) - assert factory.should_mock_node(BuiltinNodeTypes.HTTP_REQUEST) - assert factory.should_mock_node(BuiltinNodeTypes.PARAMETER_EXTRACTOR) - assert factory.should_mock_node(BuiltinNodeTypes.DOCUMENT_EXTRACTOR) - - # Test that CODE and TEMPLATE_TRANSFORM are mocked (they require SSRF proxy) - assert factory.should_mock_node(BuiltinNodeTypes.CODE) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Test that non-service nodes are not mocked - assert not factory.should_mock_node(BuiltinNodeTypes.START) - assert not factory.should_mock_node(BuiltinNodeTypes.END) - assert not factory.should_mock_node(BuiltinNodeTypes.IF_ELSE) - assert not factory.should_mock_node(BuiltinNodeTypes.VARIABLE_AGGREGATOR) - - print("✓ MockNodeFactory detection test passed") - - -def test_mock_factory_registration(): - """Test registering and unregistering mock node types.""" - from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom - from dify_graph.entities import GraphInitParams - from dify_graph.runtime import GraphRuntimeState, VariablePool - - print("Testing MockNodeFactory registration...") - - graph_init_params = GraphInitParams( - workflow_id="test", - graph_config={}, - run_context={ - DIFY_RUN_CONTEXT_KEY: { - "tenant_id": "test", - "app_id": "test", - "user_id": "test", - "user_from": UserFrom.ACCOUNT, - "invoke_from": InvokeFrom.SERVICE_API, - } - }, - call_depth=0, - ) - graph_runtime_state = GraphRuntimeState( - variable_pool=VariablePool(environment_variables=[], conversation_variables=[], user_inputs={}), - start_at=0, - total_tokens=0, - node_run_steps=0, - ) - factory = MockNodeFactory( - graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, - mock_config=None, - ) - - # TEMPLATE_TRANSFORM is mocked by default (requires SSRF proxy) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Unregister mock - factory.unregister_mock_node_type(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - assert not factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - # Register custom mock (using a dummy class for testing) - class DummyMockNode: - pass - - factory.register_mock_node_type(BuiltinNodeTypes.TEMPLATE_TRANSFORM, DummyMockNode) - assert factory.should_mock_node(BuiltinNodeTypes.TEMPLATE_TRANSFORM) - - print("✓ MockNodeFactory registration test passed") - - -def run_all_tests(): - """Run all tests.""" - print("\n=== Running Auto-Mock System Tests ===\n") - - try: - test_mock_config_builder() - test_mock_config_operations() - test_node_mock_config() - test_mock_factory_detection() - test_mock_factory_registration() - - print("\n=== All tests passed! ✅ ===\n") - return True - except AssertionError as e: - print(f"\n❌ Test failed: {e}") - return False - except Exception as e: - print(f"\n❌ Unexpected error: {e}") - import traceback - - traceback.print_exc() - return False - - -if __name__ == "__main__": - success = run_all_tests() - sys.exit(0 if success else 1) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py index e681b39cc75..8311a1e847a 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py @@ -4,32 +4,33 @@ from dataclasses import dataclass from datetime import datetime, timedelta from typing import Any, Protocol -from dify_graph.entities.workflow_start_reason import WorkflowStartReason -from dify_graph.graph import Graph -from dify_graph.graph_engine.command_channels.in_memory_channel import InMemoryChannel -from dify_graph.graph_engine.config import GraphEngineConfig -from dify_graph.graph_engine.graph_engine import GraphEngine -from dify_graph.graph_events import ( +from graphon.entities import WorkflowStartReason +from graphon.graph import Graph +from graphon.graph_engine import GraphEngine, GraphEngineConfig +from graphon.graph_engine.command_channels import InMemoryChannel +from graphon.graph_events import ( GraphRunPausedEvent, GraphRunStartedEvent, GraphRunSucceededEvent, NodeRunSucceededEvent, ) -from dify_graph.nodes.base.entities import OutputVariableEntity -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.enums import HumanInputFormStatus -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import ( +from graphon.nodes.base.entities import OutputVariableEntity +from graphon.nodes.end.end_node import EndNode +from graphon.nodes.end.entities import EndNodeData +from graphon.nodes.human_input.entities import HumanInputNodeData, UserAction +from graphon.nodes.human_input.enums import HumanInputFormStatus +from graphon.nodes.human_input.human_input_node import HumanInputNode +from graphon.nodes.start.entities import StartNodeData +from graphon.nodes.start.start_node import StartNode +from graphon.runtime import GraphRuntimeState, VariablePool + +from core.repositories.human_input_repository import ( FormCreateParams, HumanInputFormEntity, HumanInputFormRepository, ) -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable +from core.workflow.node_runtime import DifyHumanInputNodeRuntime +from core.workflow.system_variables import build_system_variables from libs.datetime_utils import naive_utc_now from tests.workflow_test_utils import build_test_graph_init_params @@ -67,7 +68,7 @@ class StaticForm(HumanInputFormEntity): return self.form_id @property - def web_app_token(self) -> str | None: + def submission_token(self) -> str | None: return "token" @property @@ -103,7 +104,7 @@ class StaticRepo(HumanInputFormRepository): def __init__(self, forms_by_node_id: Mapping[str, HumanInputFormEntity]) -> None: self._forms_by_node_id = dict(forms_by_node_id) - def get_form(self, workflow_execution_id: str, node_id: str) -> HumanInputFormEntity | None: + def get_form(self, node_id: str) -> HumanInputFormEntity | None: return self._forms_by_node_id.get(node_id) def create_form(self, params: FormCreateParams) -> HumanInputFormEntity: @@ -112,7 +113,7 @@ class StaticRepo(HumanInputFormRepository): def _build_runtime_state() -> GraphRuntimeState: variable_pool = VariablePool( - system_variables=SystemVariable( + system_variables=build_system_variables( user_id="user", app_id="app", workflow_id="workflow", @@ -159,6 +160,7 @@ def _build_graph(runtime_state: GraphRuntimeState, repo: HumanInputFormRepositor graph_init_params=graph_init_params, graph_runtime_state=runtime_state, form_repository=repo, + runtime=DifyHumanInputNodeRuntime(graph_init_params.run_context), ) human_b_config = {"id": "human_b", "data": human_data.model_dump()} @@ -168,6 +170,7 @@ def _build_graph(runtime_state: GraphRuntimeState, repo: HumanInputFormRepositor graph_init_params=graph_init_params, graph_runtime_state=runtime_state, form_repository=repo, + runtime=DifyHumanInputNodeRuntime(graph_init_params.run_context), ) end_data = EndNodeData( diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_pause_missing_finish.py b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_pause_missing_finish.py deleted file mode 100644 index 60167c0441a..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_pause_missing_finish.py +++ /dev/null @@ -1,333 +0,0 @@ -import time -from collections.abc import Mapping -from dataclasses import dataclass -from datetime import datetime, timedelta -from typing import Any - -from dify_graph.entities.workflow_start_reason import WorkflowStartReason -from dify_graph.graph import Graph -from dify_graph.graph_engine.command_channels.in_memory_channel import InMemoryChannel -from dify_graph.graph_engine.config import GraphEngineConfig -from dify_graph.graph_engine.graph_engine import GraphEngine -from dify_graph.graph_events import ( - GraphRunPausedEvent, - GraphRunStartedEvent, - NodeRunPauseRequestedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, -) -from dify_graph.model_runtime.entities.llm_entities import LLMMode -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.enums import HumanInputFormStatus -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import ( - FormCreateParams, - HumanInputFormEntity, - HumanInputFormRepository, -) -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from libs.datetime_utils import naive_utc_now -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig, NodeMockConfig -from .test_mock_nodes import MockLLMNode - - -@dataclass -class StaticForm(HumanInputFormEntity): - form_id: str - rendered: str - is_submitted: bool - action_id: str | None = None - data: Mapping[str, Any] | None = None - status_value: HumanInputFormStatus = HumanInputFormStatus.WAITING - expiration: datetime = naive_utc_now() + timedelta(days=1) - - @property - def id(self) -> str: - return self.form_id - - @property - def web_app_token(self) -> str | None: - return "token" - - @property - def recipients(self) -> list: - return [] - - @property - def rendered_content(self) -> str: - return self.rendered - - @property - def selected_action_id(self) -> str | None: - return self.action_id - - @property - def submitted_data(self) -> Mapping[str, Any] | None: - return self.data - - @property - def submitted(self) -> bool: - return self.is_submitted - - @property - def status(self) -> HumanInputFormStatus: - return self.status_value - - @property - def expiration_time(self) -> datetime: - return self.expiration - - -class StaticRepo(HumanInputFormRepository): - def __init__(self, forms_by_node_id: Mapping[str, HumanInputFormEntity]) -> None: - self._forms_by_node_id = dict(forms_by_node_id) - - def get_form(self, workflow_execution_id: str, node_id: str) -> HumanInputFormEntity | None: - return self._forms_by_node_id.get(node_id) - - def create_form(self, params: FormCreateParams) -> HumanInputFormEntity: - raise AssertionError("create_form should not be called in resume scenario") - - -class DelayedHumanInputNode(HumanInputNode): - def __init__(self, delay_seconds: float, **kwargs: Any) -> None: - super().__init__(**kwargs) - self._delay_seconds = delay_seconds - - def _run(self): - if self._delay_seconds > 0: - time.sleep(self._delay_seconds) - yield from super()._run() - - -def _build_runtime_state() -> GraphRuntimeState: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", - app_id="app", - workflow_id="workflow", - workflow_execution_id="exec-1", - ), - user_inputs={}, - conversation_variables=[], - ) - return GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - -def _build_graph(runtime_state: GraphRuntimeState, repo: HumanInputFormRepository, mock_config: MockConfig) -> Graph: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - ) - - human_data = HumanInputNodeData( - title="Human Input", - form_content="Human input required", - inputs=[], - user_actions=[UserAction(id="approve", title="Approve")], - ) - - human_a_config = {"id": "human_a", "data": human_data.model_dump()} - human_a = HumanInputNode( - id=human_a_config["id"], - config=human_a_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - form_repository=repo, - ) - - human_b_config = {"id": "human_b", "data": human_data.model_dump()} - human_b = DelayedHumanInputNode( - id=human_b_config["id"], - config=human_b_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - form_repository=repo, - delay_seconds=0.2, - ) - - llm_data = LLMNodeData( - title="LLM A", - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode=LLMMode.CHAT, completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text="Prompt A", - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - structured_output_enabled=False, - ) - llm_config = {"id": "llm_a", "data": llm_data.model_dump()} - llm_a = MockLLMNode( - id=llm_config["id"], - config=llm_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - mock_config=mock_config, - ) - - return ( - Graph.new() - .add_root(start_node) - .add_node(human_a, from_node_id="start") - .add_node(human_b, from_node_id="start") - .add_node(llm_a, from_node_id="human_a", source_handle="approve") - .build() - ) - - -def test_parallel_human_input_pause_preserves_node_finished() -> None: - runtime_state = _build_runtime_state() - - runtime_state.graph_execution.start() - runtime_state.register_paused_node("human_a") - runtime_state.register_paused_node("human_b") - - submitted = StaticForm( - form_id="form-a", - rendered="rendered", - is_submitted=True, - action_id="approve", - data={}, - status_value=HumanInputFormStatus.SUBMITTED, - ) - pending = StaticForm( - form_id="form-b", - rendered="rendered", - is_submitted=False, - action_id=None, - data=None, - status_value=HumanInputFormStatus.WAITING, - ) - repo = StaticRepo({"human_a": submitted, "human_b": pending}) - - mock_config = MockConfig() - mock_config.simulate_delays = True - mock_config.set_node_config( - "llm_a", - NodeMockConfig(node_id="llm_a", outputs={"text": "LLM A output"}, delay=0.5), - ) - - graph = _build_graph(runtime_state, repo, mock_config) - engine = GraphEngine( - workflow_id="workflow", - graph=graph, - graph_runtime_state=runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig( - min_workers=2, - max_workers=2, - scale_up_threshold=1, - scale_down_idle_time=30.0, - ), - ) - - events = list(engine.run()) - - llm_started = any(isinstance(e, NodeRunStartedEvent) and e.node_id == "llm_a" for e in events) - llm_succeeded = any(isinstance(e, NodeRunSucceededEvent) and e.node_id == "llm_a" for e in events) - human_b_pause = any(isinstance(e, NodeRunPauseRequestedEvent) and e.node_id == "human_b" for e in events) - graph_paused = any(isinstance(e, GraphRunPausedEvent) for e in events) - graph_started = any(isinstance(e, GraphRunStartedEvent) for e in events) - - assert graph_started - assert graph_paused - assert human_b_pause - assert llm_started - assert llm_succeeded - - -def test_parallel_human_input_pause_preserves_node_finished_after_snapshot_resume() -> None: - base_state = _build_runtime_state() - base_state.graph_execution.start() - base_state.register_paused_node("human_a") - base_state.register_paused_node("human_b") - snapshot = base_state.dumps() - - resumed_state = GraphRuntimeState.from_snapshot(snapshot) - - submitted = StaticForm( - form_id="form-a", - rendered="rendered", - is_submitted=True, - action_id="approve", - data={}, - status_value=HumanInputFormStatus.SUBMITTED, - ) - pending = StaticForm( - form_id="form-b", - rendered="rendered", - is_submitted=False, - action_id=None, - data=None, - status_value=HumanInputFormStatus.WAITING, - ) - repo = StaticRepo({"human_a": submitted, "human_b": pending}) - - mock_config = MockConfig() - mock_config.simulate_delays = True - mock_config.set_node_config( - "llm_a", - NodeMockConfig(node_id="llm_a", outputs={"text": "LLM A output"}, delay=0.5), - ) - - graph = _build_graph(resumed_state, repo, mock_config) - engine = GraphEngine( - workflow_id="workflow", - graph=graph, - graph_runtime_state=resumed_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig( - min_workers=2, - max_workers=2, - scale_up_threshold=1, - scale_down_idle_time=30.0, - ), - ) - - events = list(engine.run()) - - start_event = next(e for e in events if isinstance(e, GraphRunStartedEvent)) - assert start_event.reason is WorkflowStartReason.RESUMPTION - - llm_started = any(isinstance(e, NodeRunStartedEvent) and e.node_id == "llm_a" for e in events) - llm_succeeded = any(isinstance(e, NodeRunSucceededEvent) and e.node_id == "llm_a" for e in events) - human_b_pause = any(isinstance(e, NodeRunPauseRequestedEvent) and e.node_id == "human_b" for e in events) - graph_paused = any(isinstance(e, GraphRunPausedEvent) for e in events) - - assert graph_paused - assert human_b_pause - assert llm_started - assert llm_succeeded diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py deleted file mode 100644 index b954a4faaca..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py +++ /dev/null @@ -1,286 +0,0 @@ -""" -Test for parallel streaming workflow behavior. - -This test validates that: -- LLM 1 always speaks English -- LLM 2 always speaks Chinese -- 2 LLMs run parallel, but LLM 2 will output before LLM 1 -- All chunks should be sent before Answer Node started -""" - -import time -from unittest.mock import MagicMock, patch -from uuid import uuid4 - -from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom -from core.model_manager import ModelInstance -from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.graph import Graph -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_events import ( - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) -from dify_graph.node_events import NodeRunResult, StreamCompletedEvent -from dify_graph.nodes.llm.node import LLMNode -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_table_runner import TableTestRunner - - -def create_llm_generator_with_delay(chunks: list[str], delay: float = 0.1): - """Create a generator that simulates LLM streaming output with delay""" - - def llm_generator(self): - for i, chunk in enumerate(chunks): - time.sleep(delay) # Simulate network delay - yield NodeRunStreamChunkEvent( - id=str(uuid4()), - node_id=self.id, - node_type=self.node_type, - selector=[self.id, "text"], - chunk=chunk, - is_final=i == len(chunks) - 1, - ) - - # Complete response - full_text = "".join(chunks) - yield StreamCompletedEvent( - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={"text": full_text}, - ) - ) - - return llm_generator - - -def test_parallel_streaming_workflow(): - """ - Test parallel streaming workflow to verify: - 1. All chunks from LLM 2 are output before LLM 1 - 2. At least one chunk from LLM 2 is output before LLM 1 completes (Success) - 3. At least one chunk from LLM 1 is output before LLM 2 completes (EXPECTED TO FAIL) - 4. All chunks are output before End begins - 5. The final output content matches the order defined in the Answer - - Test setup: - - LLM 1 outputs English (slower) - - LLM 2 outputs Chinese (faster) - - Both run in parallel - - This test is expected to FAIL because chunks are currently buffered - until after node completion instead of streaming during execution. - """ - runner = TableTestRunner() - - # Load the workflow configuration - fixture_data = runner.workflow_runner.load_fixture("multilingual_parallel_llm_streaming_workflow") - workflow_config = fixture_data.get("workflow", {}) - graph_config = workflow_config.get("graph", {}) - - # Create graph initialization parameters - init_params = build_test_graph_init_params( - workflow_id="test_workflow", - graph_config=graph_config, - tenant_id="test_tenant", - app_id="test_app", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, - ) - - # Create variable pool with system variables - system_variables = SystemVariable( - user_id="test_user", - app_id="test_app", - workflow_id=init_params.workflow_id, - files=[], - query="Tell me about yourself", # User query - ) - variable_pool = VariablePool( - system_variables=system_variables, - user_inputs={}, - ) - - # Create graph runtime state - graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - # Create node factory and graph - node_factory = DifyNodeFactory(graph_init_params=init_params, graph_runtime_state=graph_runtime_state) - with patch.object( - DifyNodeFactory, "_build_model_instance_for_llm_node", return_value=MagicMock(spec=ModelInstance), autospec=True - ): - graph = Graph.init( - graph_config=graph_config, - node_factory=node_factory, - root_node_id=get_default_root_node_id(graph_config), - ) - - # Create the graph engine - engine = GraphEngine( - workflow_id="test_workflow", - graph=graph, - graph_runtime_state=graph_runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig(), - ) - - # Define LLM outputs - llm1_chunks = ["Hello", ", ", "I", " ", "am", " ", "an", " ", "AI", " ", "assistant", "."] # English (slower) - llm2_chunks = ["你好", "，", "我", "是", "AI", "助手", "。"] # Chinese (faster) - - # Create generators with different delays (LLM 2 is faster) - llm1_generator = create_llm_generator_with_delay(llm1_chunks, delay=0.05) # Slower - llm2_generator = create_llm_generator_with_delay(llm2_chunks, delay=0.01) # Faster - - # Track which LLM node is being called - llm_call_order = [] - generators = { - "1754339718571": llm1_generator, # LLM 1 node ID - "1754339725656": llm2_generator, # LLM 2 node ID - } - - def mock_llm_run(self): - llm_call_order.append(self.id) - generator = generators.get(self.id) - if generator: - yield from generator(self) - else: - raise Exception(f"Unexpected LLM node ID: {self.id}") - - # Execute with mocked LLMs - with patch.object(LLMNode, "_run", new=mock_llm_run): - events = list(engine.run()) - - # Check for successful completion - success_events = [e for e in events if isinstance(e, GraphRunSucceededEvent)] - assert len(success_events) > 0, "Workflow should complete successfully" - - # Get all streaming chunk events - stream_chunk_events = [e for e in events if isinstance(e, NodeRunStreamChunkEvent)] - - # Get Answer node start event - answer_start_events = [ - e for e in events if isinstance(e, NodeRunStartedEvent) and e.node_type == BuiltinNodeTypes.ANSWER - ] - assert len(answer_start_events) == 1, f"Expected 1 Answer node start event, got {len(answer_start_events)}" - answer_start_event = answer_start_events[0] - - # Find the index of Answer node start - answer_start_index = events.index(answer_start_event) - - # Collect chunk events by node - llm1_chunks_events = [e for e in stream_chunk_events if e.node_id == "1754339718571"] - llm2_chunks_events = [e for e in stream_chunk_events if e.node_id == "1754339725656"] - - # Verify both LLMs produced chunks - assert len(llm1_chunks_events) == len(llm1_chunks), ( - f"Expected {len(llm1_chunks)} chunks from LLM 1, got {len(llm1_chunks_events)}" - ) - assert len(llm2_chunks_events) == len(llm2_chunks), ( - f"Expected {len(llm2_chunks)} chunks from LLM 2, got {len(llm2_chunks_events)}" - ) - - # 1. Verify chunk ordering based on actual implementation - llm1_chunk_indices = [events.index(e) for e in llm1_chunks_events] - llm2_chunk_indices = [events.index(e) for e in llm2_chunks_events] - - # In the current implementation, chunks may be interleaved or in a specific order - # Update this based on actual behavior observed - if llm1_chunk_indices and llm2_chunk_indices: - # Check the actual ordering - if LLM 2 chunks come first (as seen in debug) - assert max(llm2_chunk_indices) < min(llm1_chunk_indices), ( - f"All LLM 2 chunks should be output before LLM 1 chunks. " - f"LLM 2 chunk indices: {llm2_chunk_indices}, LLM 1 chunk indices: {llm1_chunk_indices}" - ) - - # Get indices of all chunk events - chunk_indices = [events.index(e) for e in stream_chunk_events if e in llm1_chunks_events + llm2_chunks_events] - - # 4. Verify all chunks were sent before Answer node started - assert all(idx < answer_start_index for idx in chunk_indices), ( - "All LLM chunks should be sent before Answer node starts" - ) - - # The test has successfully verified: - # 1. Both LLMs run in parallel (they start at the same time) - # 2. LLM 2 (Chinese) outputs all its chunks before LLM 1 (English) due to faster processing - # 3. All LLM chunks are sent before the Answer node starts - - # Get LLM completion events - llm_completed_events = [ - (i, e) - for i, e in enumerate(events) - if isinstance(e, NodeRunSucceededEvent) and e.node_type == BuiltinNodeTypes.LLM - ] - - # Check LLM completion order - in the current implementation, LLMs run sequentially - # LLM 1 completes first, then LLM 2 runs and completes - assert len(llm_completed_events) == 2, f"Expected 2 LLM completion events, got {len(llm_completed_events)}" - llm2_complete_idx = next((i for i, e in llm_completed_events if e.node_id == "1754339725656"), None) - llm1_complete_idx = next((i for i, e in llm_completed_events if e.node_id == "1754339718571"), None) - assert llm2_complete_idx is not None, "LLM 2 completion event not found" - assert llm1_complete_idx is not None, "LLM 1 completion event not found" - # In the actual implementation, LLM 1 completes before LLM 2 (sequential execution) - assert llm1_complete_idx < llm2_complete_idx, ( - f"LLM 1 should complete before LLM 2 in sequential execution, but LLM 1 completed at {llm1_complete_idx} " - f"and LLM 2 completed at {llm2_complete_idx}" - ) - - # 2. In sequential execution, LLM 2 chunks appear AFTER LLM 1 completes - if llm2_chunk_indices: - # LLM 1 completes first, then LLM 2 starts streaming - assert min(llm2_chunk_indices) > llm1_complete_idx, ( - f"LLM 2 chunks should appear after LLM 1 completes in sequential execution. " - f"First LLM 2 chunk at index {min(llm2_chunk_indices)}, LLM 1 completed at index {llm1_complete_idx}" - ) - - # 3. In the current implementation, LLM 1 chunks appear after LLM 2 completes - # This is because chunks are buffered and output after both nodes complete - if llm1_chunk_indices and llm2_complete_idx: - # Check if LLM 1 chunks exist and where they appear relative to LLM 2 completion - # In current behavior, LLM 1 chunks typically appear after LLM 2 completes - pass # Skipping this check as the chunk ordering is implementation-dependent - - # CURRENT BEHAVIOR: Chunks are buffered and appear after node completion - # In the sequential execution, LLM 1 completes first without streaming, - # then LLM 2 streams its chunks - assert stream_chunk_events, "Expected streaming events, but got none" - - first_chunk_index = events.index(stream_chunk_events[0]) - llm_success_indices = [i for i, e in llm_completed_events] - - # Current implementation: LLM 1 completes first, then chunks start appearing - # This is the actual behavior we're testing - if llm_success_indices: - # At least one LLM (LLM 1) completes before any chunks appear - assert min(llm_success_indices) < first_chunk_index, ( - f"In current implementation, LLM 1 completes before chunks start streaming. " - f"First chunk at index {first_chunk_index}, LLM 1 completed at index {min(llm_success_indices)}" - ) - - # 5. Verify final output content matches the order defined in Answer node - # According to Answer node configuration: '{{#1754339725656.text#}}{{#1754339718571.text#}}' - # This means LLM 2 output should come first, then LLM 1 output - answer_complete_events = [ - e for e in events if isinstance(e, NodeRunSucceededEvent) and e.node_type == BuiltinNodeTypes.ANSWER - ] - assert len(answer_complete_events) == 1, f"Expected 1 Answer completion event, got {len(answer_complete_events)}" - - answer_outputs = answer_complete_events[0].node_run_result.outputs - expected_answer_text = "你好，我是AI助手。Hello, I am an AI assistant." - - if "answer" in answer_outputs: - actual_answer_text = answer_outputs["answer"] - assert actual_answer_text == expected_answer_text, ( - f"Answer content should match the order defined in Answer node. " - f"Expected: '{expected_answer_text}', Got: '{actual_answer_text}'" - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_pause_deferred_ready_nodes.py b/api/tests/unit_tests/core/workflow/graph_engine/test_pause_deferred_ready_nodes.py deleted file mode 100644 index 7328ce443f2..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_pause_deferred_ready_nodes.py +++ /dev/null @@ -1,309 +0,0 @@ -import time -from collections.abc import Mapping -from dataclasses import dataclass -from datetime import datetime, timedelta -from typing import Any - -from dify_graph.entities.workflow_start_reason import WorkflowStartReason -from dify_graph.graph import Graph -from dify_graph.graph_engine.command_channels.in_memory_channel import InMemoryChannel -from dify_graph.graph_engine.config import GraphEngineConfig -from dify_graph.graph_engine.graph_engine import GraphEngine -from dify_graph.graph_events import ( - GraphRunPausedEvent, - GraphRunStartedEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, -) -from dify_graph.model_runtime.entities.llm_entities import LLMMode -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.enums import HumanInputFormStatus -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.llm.entities import ( - ContextConfig, - LLMNodeChatModelMessage, - LLMNodeData, - ModelConfig, - VisionConfig, -) -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import ( - FormCreateParams, - HumanInputFormEntity, - HumanInputFormRepository, -) -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from libs.datetime_utils import naive_utc_now -from tests.workflow_test_utils import build_test_graph_init_params - -from .test_mock_config import MockConfig, NodeMockConfig -from .test_mock_nodes import MockLLMNode - - -@dataclass -class StaticForm(HumanInputFormEntity): - form_id: str - rendered: str - is_submitted: bool - action_id: str | None = None - data: Mapping[str, Any] | None = None - status_value: HumanInputFormStatus = HumanInputFormStatus.WAITING - expiration: datetime = naive_utc_now() + timedelta(days=1) - - @property - def id(self) -> str: - return self.form_id - - @property - def web_app_token(self) -> str | None: - return "token" - - @property - def recipients(self) -> list: - return [] - - @property - def rendered_content(self) -> str: - return self.rendered - - @property - def selected_action_id(self) -> str | None: - return self.action_id - - @property - def submitted_data(self) -> Mapping[str, Any] | None: - return self.data - - @property - def submitted(self) -> bool: - return self.is_submitted - - @property - def status(self) -> HumanInputFormStatus: - return self.status_value - - @property - def expiration_time(self) -> datetime: - return self.expiration - - -class StaticRepo(HumanInputFormRepository): - def __init__(self, form: HumanInputFormEntity) -> None: - self._form = form - - def get_form(self, workflow_execution_id: str, node_id: str) -> HumanInputFormEntity | None: - if node_id != "human_pause": - return None - return self._form - - def create_form(self, params: FormCreateParams) -> HumanInputFormEntity: - raise AssertionError("create_form should not be called in this test") - - -def _build_runtime_state() -> GraphRuntimeState: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", - app_id="app", - workflow_id="workflow", - workflow_execution_id="exec-1", - ), - user_inputs={}, - conversation_variables=[], - ) - return GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - -def _build_graph(runtime_state: GraphRuntimeState, repo: HumanInputFormRepository, mock_config: MockConfig) -> Graph: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - graph_init_params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="debugger", - call_depth=0, - ) - - start_config = {"id": "start", "data": StartNodeData(title="Start", variables=[]).model_dump()} - start_node = StartNode( - id=start_config["id"], - config=start_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - ) - - llm_a_data = LLMNodeData( - title="LLM A", - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode=LLMMode.CHAT, completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text="Prompt A", - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - structured_output_enabled=False, - ) - llm_a_config = {"id": "llm_a", "data": llm_a_data.model_dump()} - llm_a = MockLLMNode( - id=llm_a_config["id"], - config=llm_a_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - mock_config=mock_config, - ) - - llm_b_data = LLMNodeData( - title="LLM B", - model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode=LLMMode.CHAT, completion_params={}), - prompt_template=[ - LLMNodeChatModelMessage( - text="Prompt B", - role=PromptMessageRole.USER, - edition_type="basic", - ) - ], - context=ContextConfig(enabled=False, variable_selector=None), - vision=VisionConfig(enabled=False), - reasoning_format="tagged", - structured_output_enabled=False, - ) - llm_b_config = {"id": "llm_b", "data": llm_b_data.model_dump()} - llm_b = MockLLMNode( - id=llm_b_config["id"], - config=llm_b_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - mock_config=mock_config, - ) - - human_data = HumanInputNodeData( - title="Human Input", - form_content="Pause here", - inputs=[], - user_actions=[UserAction(id="approve", title="Approve")], - ) - human_config = {"id": "human_pause", "data": human_data.model_dump()} - human_node = HumanInputNode( - id=human_config["id"], - config=human_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - form_repository=repo, - ) - - end_human_data = EndNodeData(title="End Human", outputs=[], desc=None) - end_human_config = {"id": "end_human", "data": end_human_data.model_dump()} - end_human = EndNode( - id=end_human_config["id"], - config=end_human_config, - graph_init_params=graph_init_params, - graph_runtime_state=runtime_state, - ) - - return ( - Graph.new() - .add_root(start_node) - .add_node(llm_a, from_node_id="start") - .add_node(human_node, from_node_id="start") - .add_node(llm_b, from_node_id="llm_a") - .add_node(end_human, from_node_id="human_pause", source_handle="approve") - .build() - ) - - -def _get_node_started_event(events: list[object], node_id: str) -> NodeRunStartedEvent | None: - for event in events: - if isinstance(event, NodeRunStartedEvent) and event.node_id == node_id: - return event - return None - - -def test_pause_defers_ready_nodes_until_resume() -> None: - runtime_state = _build_runtime_state() - - paused_form = StaticForm( - form_id="form-pause", - rendered="rendered", - is_submitted=False, - status_value=HumanInputFormStatus.WAITING, - ) - pause_repo = StaticRepo(paused_form) - - mock_config = MockConfig() - mock_config.simulate_delays = True - mock_config.set_node_config( - "llm_a", - NodeMockConfig(node_id="llm_a", outputs={"text": "LLM A output"}, delay=0.5), - ) - mock_config.set_node_config( - "llm_b", - NodeMockConfig(node_id="llm_b", outputs={"text": "LLM B output"}, delay=0.0), - ) - - graph = _build_graph(runtime_state, pause_repo, mock_config) - engine = GraphEngine( - workflow_id="workflow", - graph=graph, - graph_runtime_state=runtime_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig( - min_workers=2, - max_workers=2, - scale_up_threshold=1, - scale_down_idle_time=30.0, - ), - ) - - paused_events = list(engine.run()) - - assert any(isinstance(e, GraphRunPausedEvent) for e in paused_events) - assert any(isinstance(e, NodeRunSucceededEvent) and e.node_id == "llm_a" for e in paused_events) - assert _get_node_started_event(paused_events, "llm_b") is None - - snapshot = runtime_state.dumps() - resumed_state = GraphRuntimeState.from_snapshot(snapshot) - - submitted_form = StaticForm( - form_id="form-pause", - rendered="rendered", - is_submitted=True, - action_id="approve", - data={}, - status_value=HumanInputFormStatus.SUBMITTED, - ) - resume_repo = StaticRepo(submitted_form) - - resumed_graph = _build_graph(resumed_state, resume_repo, mock_config) - resumed_engine = GraphEngine( - workflow_id="workflow", - graph=resumed_graph, - graph_runtime_state=resumed_state, - command_channel=InMemoryChannel(), - config=GraphEngineConfig( - min_workers=2, - max_workers=2, - scale_up_threshold=1, - scale_down_idle_time=30.0, - ), - ) - - resumed_events = list(resumed_engine.run()) - - start_event = next(e for e in resumed_events if isinstance(e, GraphRunStartedEvent)) - assert start_event.reason is WorkflowStartReason.RESUMPTION - - llm_b_started = _get_node_started_event(resumed_events, "llm_b") - assert llm_b_started is not None - assert any(isinstance(e, NodeRunSucceededEvent) and e.node_id == "llm_b" for e in resumed_events) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_pause_resume_state.py b/api/tests/unit_tests/core/workflow/graph_engine/test_pause_resume_state.py deleted file mode 100644 index 15a7de3c521..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_pause_resume_state.py +++ /dev/null @@ -1,217 +0,0 @@ -import datetime -import time -from typing import Any -from unittest.mock import MagicMock - -from dify_graph.entities.workflow_start_reason import WorkflowStartReason -from dify_graph.graph import Graph -from dify_graph.graph_engine.command_channels.in_memory_channel import InMemoryChannel -from dify_graph.graph_engine.graph_engine import GraphEngine -from dify_graph.graph_events import ( - GraphEngineEvent, - GraphRunPausedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunSucceededEvent, -) -from dify_graph.graph_events.graph import GraphRunStartedEvent -from dify_graph.nodes.base.entities import OutputVariableEntity -from dify_graph.nodes.end.end_node import EndNode -from dify_graph.nodes.end.entities import EndNodeData -from dify_graph.nodes.human_input.entities import HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.human_input_node import HumanInputNode -from dify_graph.nodes.start.entities import StartNodeData -from dify_graph.nodes.start.start_node import StartNode -from dify_graph.repositories.human_input_form_repository import ( - HumanInputFormEntity, - HumanInputFormRepository, -) -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from libs.datetime_utils import naive_utc_now -from tests.workflow_test_utils import build_test_graph_init_params - - -def _build_runtime_state() -> GraphRuntimeState: - variable_pool = VariablePool( - system_variables=SystemVariable( - user_id="user", - app_id="app", - workflow_id="workflow", - workflow_execution_id="test-execution-id", - ), - user_inputs={}, - conversation_variables=[], - ) - return GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) - - -def _mock_form_repository_with_submission(action_id: str) -> HumanInputFormRepository: - repo = MagicMock(spec=HumanInputFormRepository) - form_entity = MagicMock(spec=HumanInputFormEntity) - form_entity.id = "test-form-id" - form_entity.web_app_token = "test-form-token" - form_entity.recipients = [] - form_entity.rendered_content = "rendered" - form_entity.submitted = True - form_entity.selected_action_id = action_id - form_entity.submitted_data = {} - form_entity.expiration_time = naive_utc_now() + datetime.timedelta(days=1) - repo.get_form.return_value = form_entity - return repo - - -def _mock_form_repository_without_submission() -> HumanInputFormRepository: - repo = MagicMock(spec=HumanInputFormRepository) - form_entity = MagicMock(spec=HumanInputFormEntity) - form_entity.id = "test-form-id" - form_entity.web_app_token = "test-form-token" - form_entity.recipients = [] - form_entity.rendered_content = "rendered" - form_entity.submitted = False - repo.create_form.return_value = form_entity - repo.get_form.return_value = None - return repo - - -def _build_human_input_graph( - runtime_state: GraphRuntimeState, - form_repository: HumanInputFormRepository, -) -> Graph: - graph_config: dict[str, object] = {"nodes": [], "edges": []} - params = build_test_graph_init_params( - workflow_id="workflow", - graph_config=graph_config, - tenant_id="tenant", - app_id="app", - user_id="user", - user_from="account", - invoke_from="service-api", - call_depth=0, - ) - - start_data = StartNodeData(title="start", variables=[]) - start_node = StartNode( - id="start", - config={"id": "start", "data": start_data.model_dump()}, - graph_init_params=params, - graph_runtime_state=runtime_state, - ) - - human_data = HumanInputNodeData( - title="human", - form_content="Awaiting human input", - inputs=[], - user_actions=[ - UserAction(id="continue", title="Continue"), - ], - ) - human_node = HumanInputNode( - id="human", - config={"id": "human", "data": human_data.model_dump()}, - graph_init_params=params, - graph_runtime_state=runtime_state, - form_repository=form_repository, - ) - - end_data = EndNodeData( - title="end", - outputs=[ - OutputVariableEntity(variable="result", value_selector=["human", "action_id"]), - ], - desc=None, - ) - end_node = EndNode( - id="end", - config={"id": "end", "data": end_data.model_dump()}, - graph_init_params=params, - graph_runtime_state=runtime_state, - ) - - return ( - Graph.new() - .add_root(start_node) - .add_node(human_node) - .add_node(end_node, from_node_id="human", source_handle="continue") - .build() - ) - - -def _run_graph(graph: Graph, runtime_state: GraphRuntimeState) -> list[GraphEngineEvent]: - engine = GraphEngine( - workflow_id="workflow", - graph=graph, - graph_runtime_state=runtime_state, - command_channel=InMemoryChannel(), - ) - return list(engine.run()) - - -def _node_successes(events: list[GraphEngineEvent]) -> list[str]: - return [event.node_id for event in events if isinstance(event, NodeRunSucceededEvent)] - - -def _node_start_event(events: list[GraphEngineEvent], node_id: str) -> NodeRunStartedEvent | None: - for event in events: - if isinstance(event, NodeRunStartedEvent) and event.node_id == node_id: - return event - return None - - -def _segment_value(variable_pool: VariablePool, selector: tuple[str, str]) -> Any: - segment = variable_pool.get(selector) - assert segment is not None - return getattr(segment, "value", segment) - - -def test_engine_resume_restores_state_and_completion(): - # Baseline run without pausing - baseline_state = _build_runtime_state() - baseline_repo = _mock_form_repository_with_submission(action_id="continue") - baseline_graph = _build_human_input_graph(baseline_state, baseline_repo) - baseline_events = _run_graph(baseline_graph, baseline_state) - assert baseline_events - first_paused_event = baseline_events[0] - assert isinstance(first_paused_event, GraphRunStartedEvent) - assert first_paused_event.reason is WorkflowStartReason.INITIAL - assert isinstance(baseline_events[-1], GraphRunSucceededEvent) - baseline_success_nodes = _node_successes(baseline_events) - - # Run with pause - paused_state = _build_runtime_state() - pause_repo = _mock_form_repository_without_submission() - paused_graph = _build_human_input_graph(paused_state, pause_repo) - paused_events = _run_graph(paused_graph, paused_state) - assert paused_events - first_paused_event = paused_events[0] - assert isinstance(first_paused_event, GraphRunStartedEvent) - assert first_paused_event.reason is WorkflowStartReason.INITIAL - assert isinstance(paused_events[-1], GraphRunPausedEvent) - snapshot = paused_state.dumps() - - # Resume from snapshot - resumed_state = GraphRuntimeState.from_snapshot(snapshot) - resume_repo = _mock_form_repository_with_submission(action_id="continue") - resumed_graph = _build_human_input_graph(resumed_state, resume_repo) - resumed_events = _run_graph(resumed_graph, resumed_state) - assert resumed_events - first_resumed_event = resumed_events[0] - assert isinstance(first_resumed_event, GraphRunStartedEvent) - assert first_resumed_event.reason is WorkflowStartReason.RESUMPTION - assert isinstance(resumed_events[-1], GraphRunSucceededEvent) - - combined_success_nodes = _node_successes(paused_events) + _node_successes(resumed_events) - assert combined_success_nodes == baseline_success_nodes - - paused_human_started = _node_start_event(paused_events, "human") - resumed_human_started = _node_start_event(resumed_events, "human") - assert paused_human_started is not None - assert resumed_human_started is not None - assert paused_human_started.id == resumed_human_started.id - - assert baseline_state.outputs == resumed_state.outputs - assert _segment_value(baseline_state.variable_pool, ("human", "__action_id")) == _segment_value( - resumed_state.variable_pool, ("human", "__action_id") - ) - assert baseline_state.graph_execution.completed - assert resumed_state.graph_execution.completed diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_redis_stop_integration.py b/api/tests/unit_tests/core/workflow/graph_engine/test_redis_stop_integration.py deleted file mode 100644 index 9c84f42db6a..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_redis_stop_integration.py +++ /dev/null @@ -1,268 +0,0 @@ -""" -Unit tests for Redis-based stop functionality in GraphEngine. - -Tests the integration of Redis command channel for stopping workflows -without user permission checks. -""" - -import json -from unittest.mock import MagicMock, Mock, patch - -import pytest -import redis - -from core.app.apps.base_app_queue_manager import AppQueueManager -from dify_graph.graph_engine.command_channels.redis_channel import RedisChannel -from dify_graph.graph_engine.entities.commands import AbortCommand, CommandType, PauseCommand -from dify_graph.graph_engine.manager import GraphEngineManager - - -class TestRedisStopIntegration: - """Test suite for Redis-based workflow stop functionality.""" - - def test_graph_engine_manager_sends_abort_command(self): - """Test that GraphEngineManager correctly sends abort command through Redis.""" - # Setup - task_id = "test-task-123" - expected_channel_key = f"workflow:{task_id}:commands" - - # Mock redis client - mock_redis = MagicMock() - mock_pipeline = MagicMock() - mock_redis.pipeline.return_value.__enter__ = Mock(return_value=mock_pipeline) - mock_redis.pipeline.return_value.__exit__ = Mock(return_value=None) - - manager = GraphEngineManager(mock_redis) - - # Execute - manager.send_stop_command(task_id, reason="Test stop") - - # Verify - mock_redis.pipeline.assert_called_once() - - # Check that rpush was called with correct arguments - calls = mock_pipeline.rpush.call_args_list - assert len(calls) == 1 - - # Verify the channel key - assert calls[0][0][0] == expected_channel_key - - # Verify the command data - command_json = calls[0][0][1] - command_data = json.loads(command_json) - assert command_data["command_type"] == CommandType.ABORT - assert command_data["reason"] == "Test stop" - - def test_graph_engine_manager_sends_pause_command(self): - """Test that GraphEngineManager correctly sends pause command through Redis.""" - task_id = "test-task-pause-123" - expected_channel_key = f"workflow:{task_id}:commands" - - mock_redis = MagicMock() - mock_pipeline = MagicMock() - mock_redis.pipeline.return_value.__enter__ = Mock(return_value=mock_pipeline) - mock_redis.pipeline.return_value.__exit__ = Mock(return_value=None) - - manager = GraphEngineManager(mock_redis) - manager.send_pause_command(task_id, reason="Awaiting resources") - - mock_redis.pipeline.assert_called_once() - calls = mock_pipeline.rpush.call_args_list - assert len(calls) == 1 - assert calls[0][0][0] == expected_channel_key - - command_json = calls[0][0][1] - command_data = json.loads(command_json) - assert command_data["command_type"] == CommandType.PAUSE.value - assert command_data["reason"] == "Awaiting resources" - - def test_graph_engine_manager_handles_redis_failure_gracefully(self): - """Test that GraphEngineManager handles Redis failures without raising exceptions.""" - task_id = "test-task-456" - - # Mock redis client to raise exception - mock_redis = MagicMock() - mock_redis.pipeline.side_effect = redis.ConnectionError("Redis connection failed") - manager = GraphEngineManager(mock_redis) - - # Should not raise exception - try: - manager.send_stop_command(task_id) - except Exception as e: - pytest.fail(f"GraphEngineManager.send_stop_command raised {e} unexpectedly") - - def test_app_queue_manager_no_user_check(self): - """Test that AppQueueManager.set_stop_flag_no_user_check works without user validation.""" - task_id = "test-task-789" - expected_cache_key = f"generate_task_stopped:{task_id}" - - # Mock redis client - mock_redis = MagicMock() - - with patch("core.app.apps.base_app_queue_manager.redis_client", mock_redis): - # Execute - AppQueueManager.set_stop_flag_no_user_check(task_id) - - # Verify - mock_redis.setex.assert_called_once_with(expected_cache_key, 600, 1) - - def test_app_queue_manager_no_user_check_with_empty_task_id(self): - """Test that AppQueueManager.set_stop_flag_no_user_check handles empty task_id.""" - # Mock redis client - mock_redis = MagicMock() - - with patch("core.app.apps.base_app_queue_manager.redis_client", mock_redis): - # Execute with empty task_id - AppQueueManager.set_stop_flag_no_user_check("") - - # Verify redis was not called - mock_redis.setex.assert_not_called() - - def test_redis_channel_send_abort_command(self): - """Test RedisChannel correctly serializes and sends AbortCommand.""" - # Setup - mock_redis = MagicMock() - mock_pipeline = MagicMock() - mock_redis.pipeline.return_value.__enter__ = Mock(return_value=mock_pipeline) - mock_redis.pipeline.return_value.__exit__ = Mock(return_value=None) - - channel_key = "workflow:test:commands" - channel = RedisChannel(mock_redis, channel_key) - - # Create commands - abort_command = AbortCommand(reason="User requested stop") - pause_command = PauseCommand(reason="User requested pause") - - # Execute - channel.send_command(abort_command) - channel.send_command(pause_command) - - # Verify - mock_redis.pipeline.assert_called() - - # Check rpush was called - calls = mock_pipeline.rpush.call_args_list - assert len(calls) == 2 - assert calls[0][0][0] == channel_key - assert calls[1][0][0] == channel_key - - # Verify serialized commands - abort_command_json = calls[0][0][1] - abort_command_data = json.loads(abort_command_json) - assert abort_command_data["command_type"] == CommandType.ABORT.value - assert abort_command_data["reason"] == "User requested stop" - - pause_command_json = calls[1][0][1] - pause_command_data = json.loads(pause_command_json) - assert pause_command_data["command_type"] == CommandType.PAUSE.value - assert pause_command_data["reason"] == "User requested pause" - - # Check expire was set for each - assert mock_pipeline.expire.call_count == 2 - mock_pipeline.expire.assert_any_call(channel_key, 3600) - - def test_redis_channel_fetch_commands(self): - """Test RedisChannel correctly fetches and deserializes commands.""" - # Setup - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Mock command data - abort_command_json = json.dumps( - {"command_type": CommandType.ABORT.value, "reason": "Test abort", "payload": None} - ) - pause_command_json = json.dumps( - {"command_type": CommandType.PAUSE.value, "reason": "Pause requested", "payload": None} - ) - - # Mock pipeline execute to return commands - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [ - [abort_command_json.encode(), pause_command_json.encode()], # lrange result - True, # delete result - ] - - channel_key = "workflow:test:commands" - channel = RedisChannel(mock_redis, channel_key) - - # Execute - commands = channel.fetch_commands() - - # Verify - assert len(commands) == 2 - assert isinstance(commands[0], AbortCommand) - assert commands[0].command_type == CommandType.ABORT - assert commands[0].reason == "Test abort" - assert isinstance(commands[1], PauseCommand) - assert commands[1].command_type == CommandType.PAUSE - assert commands[1].reason == "Pause requested" - - # Verify Redis operations - pending_pipe.get.assert_called_once_with(f"{channel_key}:pending") - pending_pipe.delete.assert_called_once_with(f"{channel_key}:pending") - fetch_pipe.lrange.assert_called_once_with(channel_key, 0, -1) - fetch_pipe.delete.assert_called_once_with(channel_key) - assert mock_redis.pipeline.call_count == 2 - - def test_redis_channel_fetch_commands_handles_invalid_json(self): - """Test RedisChannel gracefully handles invalid JSON in commands.""" - # Setup - mock_redis = MagicMock() - pending_pipe = MagicMock() - fetch_pipe = MagicMock() - pending_context = MagicMock() - fetch_context = MagicMock() - pending_context.__enter__.return_value = pending_pipe - pending_context.__exit__.return_value = None - fetch_context.__enter__.return_value = fetch_pipe - fetch_context.__exit__.return_value = None - mock_redis.pipeline.side_effect = [pending_context, fetch_context] - - # Mock invalid command data - pending_pipe.execute.return_value = [b"1", 1] - fetch_pipe.execute.return_value = [ - [b"invalid json", b'{"command_type": "invalid_type"}'], # lrange result - True, # delete result - ] - - channel_key = "workflow:test:commands" - channel = RedisChannel(mock_redis, channel_key) - - # Execute - commands = channel.fetch_commands() - - # Should return empty list due to invalid commands - assert len(commands) == 0 - - def test_dual_stop_mechanism_compatibility(self): - """Test that both stop mechanisms can work together.""" - task_id = "test-task-dual" - - # Mock redis client - mock_redis = MagicMock() - mock_pipeline = MagicMock() - mock_redis.pipeline.return_value.__enter__ = Mock(return_value=mock_pipeline) - mock_redis.pipeline.return_value.__exit__ = Mock(return_value=None) - - with patch("core.app.apps.base_app_queue_manager.redis_client", mock_redis): - # Execute both stop mechanisms - AppQueueManager.set_stop_flag_no_user_check(task_id) - GraphEngineManager(mock_redis).send_stop_command(task_id) - - # Verify legacy stop flag was set - expected_stop_flag_key = f"generate_task_stopped:{task_id}" - mock_redis.setex.assert_called_once_with(expected_stop_flag_key, 600, 1) - - # Verify command was sent through Redis channel - mock_redis.pipeline.assert_called() - calls = mock_pipeline.rpush.call_args_list - assert len(calls) == 1 - assert calls[0][0][0] == f"workflow:{task_id}:commands" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_response_session.py b/api/tests/unit_tests/core/workflow/graph_engine/test_response_session.py deleted file mode 100644 index cd9d56f683d..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_response_session.py +++ /dev/null @@ -1,55 +0,0 @@ -"""Unit tests for response session creation.""" - -from __future__ import annotations - -import pytest - -from dify_graph.enums import BuiltinNodeTypes, NodeExecutionType, NodeState, NodeType -from dify_graph.graph_engine.response_coordinator.session import ResponseSession -from dify_graph.nodes.base.template import Template, TextSegment - - -class DummyResponseNode: - """Minimal response-capable node for session tests.""" - - def __init__(self, *, node_id: str, node_type: NodeType, template: Template) -> None: - self.id = node_id - self.node_type = node_type - self.execution_type = NodeExecutionType.RESPONSE - self.state = NodeState.UNKNOWN - self._template = template - - def get_streaming_template(self) -> Template: - return self._template - - -class DummyNodeWithoutStreamingTemplate: - """Minimal node that violates the response-session contract.""" - - def __init__(self, *, node_id: str, node_type: NodeType) -> None: - self.id = node_id - self.node_type = node_type - self.execution_type = NodeExecutionType.RESPONSE - self.state = NodeState.UNKNOWN - - -def test_response_session_from_node_accepts_nodes_outside_previous_allowlist() -> None: - """Session creation depends on the streaming-template contract rather than node type.""" - node = DummyResponseNode( - node_id="llm-node", - node_type=BuiltinNodeTypes.LLM, - template=Template(segments=[TextSegment(text="hello")]), - ) - - session = ResponseSession.from_node(node) - - assert session.node_id == "llm-node" - assert session.template.segments == [TextSegment(text="hello")] - - -def test_response_session_from_node_requires_streaming_template_method() -> None: - """Allowed node types still need to implement the streaming-template contract.""" - node = DummyNodeWithoutStreamingTemplate(node_id="answer-node", node_type=BuiltinNodeTypes.ANSWER) - - with pytest.raises(TypeError, match="get_streaming_template"): - ResponseSession.from_node(node) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_streaming_conversation_variables.py b/api/tests/unit_tests/core/workflow/graph_engine/test_streaming_conversation_variables.py deleted file mode 100644 index 4f1741d4fb8..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_streaming_conversation_variables.py +++ /dev/null @@ -1,77 +0,0 @@ -from dify_graph.graph_events import ( - GraphRunStartedEvent, - GraphRunSucceededEvent, - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, -) - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_streaming_conversation_variables(): - fixture_name = "test_streaming_conversation_variables" - - # The test expects the workflow to output the input query - # Since the workflow assigns sys.query to conversation variable "str" and then answers with it - input_query = "Hello, this is my test query" - - mock_config = MockConfigBuilder().build() - - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=False, # Don't use auto mock since we want to test actual variable assignment - mock_config=mock_config, - query=input_query, # Pass query as the sys.query value - inputs={}, # No additional inputs needed - expected_outputs={"answer": input_query}, # Expecting the input query to be output - expected_event_sequence=[ - GraphRunStartedEvent, - # START node - NodeRunStartedEvent, - NodeRunSucceededEvent, - # Variable Assigner node - NodeRunStartedEvent, - NodeRunStreamChunkEvent, - NodeRunSucceededEvent, - # ANSWER node - NodeRunStartedEvent, - NodeRunSucceededEvent, - GraphRunSucceededEvent, - ], - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" - - -def test_streaming_conversation_variables_v1_overwrite_waits_for_assignment(): - fixture_name = "test_streaming_conversation_variables_v1_overwrite" - input_query = "overwrite-value" - - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=False, - mock_config=MockConfigBuilder().build(), - query=input_query, - inputs={}, - expected_outputs={"answer": f"Current Value Of `conv_var` is:{input_query}"}, - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - assert result.success, f"Test failed: {result.error}" - - events = result.events - conv_var_chunk_events = [ - event - for event in events - if isinstance(event, NodeRunStreamChunkEvent) and tuple(event.selector) == ("conversation", "conv_var") - ] - - assert conv_var_chunk_events, "Expected conversation variable chunk events to be emitted" - assert all(event.chunk == input_query for event in conv_var_chunk_events), ( - "Expected streamed conversation variable value to match the input query" - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py b/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py index ab8fb346b8f..b11f9576777 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py @@ -12,29 +12,24 @@ This module provides a robust table-driven testing framework with support for: import logging import time -from collections.abc import Callable, Mapping, Sequence +from collections.abc import Callable, Sequence from concurrent.futures import ThreadPoolExecutor, as_completed from dataclasses import dataclass, field from functools import lru_cache from pathlib import Path -from typing import Any, cast +from typing import Any -from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom -from core.tools.utils.yaml_utils import _load_yaml_file -from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY, GraphInitParams -from dify_graph.graph import Graph -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_engine.layers.base import GraphEngineLayer -from dify_graph.graph_events import ( +from graphon.entities import GraphInitParams +from graphon.graph import Graph +from graphon.graph_engine import GraphEngine, GraphEngineConfig +from graphon.graph_engine.command_channels import InMemoryChannel +from graphon.graph_events import ( GraphEngineEvent, GraphRunStartedEvent, GraphRunSucceededEvent, ) -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable -from dify_graph.variables import ( +from graphon.runtime import GraphRuntimeState, VariablePool +from graphon.variables import ( ArrayNumberVariable, ArrayObjectVariable, ArrayStringVariable, @@ -44,6 +39,12 @@ from dify_graph.variables import ( StringVariable, ) +from core.app.entities.app_invoke_entities import DIFY_RUN_CONTEXT_KEY, InvokeFrom, UserFrom +from core.tools.utils.yaml_utils import _load_yaml_file +from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id +from core.workflow.system_variables import build_bootstrap_variables, build_system_variables +from core.workflow.variable_pool_initializer import add_node_inputs_to_pool, add_variables_to_pool + from .test_mock_config import MockConfig from .test_mock_factory import MockNodeFactory @@ -60,20 +61,28 @@ class _TableTestChildEngineBuilder: *, workflow_id: str, graph_init_params: GraphInitParams, - graph_runtime_state: GraphRuntimeState, - graph_config: Mapping[str, Any], + parent_graph_runtime_state: GraphRuntimeState, root_node_id: str, - layers: Sequence[object] = (), + variable_pool: VariablePool | None = None, ) -> GraphEngine: + child_graph_runtime_state = GraphRuntimeState( + variable_pool=variable_pool if variable_pool is not None else parent_graph_runtime_state.variable_pool, + start_at=time.perf_counter(), + execution_context=parent_graph_runtime_state.execution_context, + ) if self._use_mock_factory: node_factory = MockNodeFactory( graph_init_params=graph_init_params, - graph_runtime_state=graph_runtime_state, + graph_runtime_state=child_graph_runtime_state, mock_config=self._mock_config, ) else: - node_factory = DifyNodeFactory(graph_init_params=graph_init_params, graph_runtime_state=graph_runtime_state) + node_factory = DifyNodeFactory( + graph_init_params=graph_init_params, + graph_runtime_state=child_graph_runtime_state, + ) + graph_config = graph_init_params.graph_config child_graph = Graph.init(graph_config=graph_config, node_factory=node_factory, root_node_id=root_node_id) if not child_graph: raise ValueError("child graph not found") @@ -81,13 +90,11 @@ class _TableTestChildEngineBuilder: child_engine = GraphEngine( workflow_id=workflow_id, graph=child_graph, - graph_runtime_state=graph_runtime_state, + graph_runtime_state=child_graph_runtime_state, command_channel=InMemoryChannel(), config=GraphEngineConfig(), child_engine_builder=self, ) - for layer in layers: - child_engine.layer(cast(GraphEngineLayer, layer)) return child_engine @@ -206,14 +213,15 @@ class WorkflowRunner: call_depth=0, ) - system_variables = SystemVariable( + system_variables = build_system_variables( user_id="test_user", app_id="test_app", workflow_id=graph_init_params.workflow_id, files=[], query=query, ) - user_inputs = inputs if inputs is not None else {} + root_node_inputs = dict(inputs or {}) + root_node_inputs.setdefault("query", query) # Extract conversation variables from workflow config conversation_variables = [] @@ -242,11 +250,16 @@ class WorkflowRunner: ) conversation_variables.append(var) - variable_pool = VariablePool( - system_variables=system_variables, - user_inputs=user_inputs, - conversation_variables=conversation_variables, + root_node_id = get_default_root_node_id(graph_config) + variable_pool = VariablePool() + add_variables_to_pool( + variable_pool, + build_bootstrap_variables( + system_variables=system_variables, + conversation_variables=conversation_variables, + ), ) + add_node_inputs_to_pool(variable_pool, node_id=root_node_id, inputs=root_node_inputs) graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) @@ -260,7 +273,7 @@ class WorkflowRunner: graph = Graph.init( graph_config=graph_config, node_factory=node_factory, - root_node_id=get_default_root_node_id(graph_config), + root_node_id=root_node_id, ) return graph, graph_runtime_state diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py index 7f26bc11a72..12aec6edf24 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py @@ -1,6 +1,6 @@ -from dify_graph.graph_engine import GraphEngine, GraphEngineConfig -from dify_graph.graph_engine.command_channels import InMemoryChannel -from dify_graph.graph_events import ( +from graphon.graph_engine import GraphEngine, GraphEngineConfig +from graphon.graph_engine.command_channels import InMemoryChannel +from graphon.graph_events import ( GraphRunSucceededEvent, NodeRunStreamChunkEvent, ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_update_conversation_variable_iteration.py b/api/tests/unit_tests/core/workflow/graph_engine/test_update_conversation_variable_iteration.py deleted file mode 100644 index a7309f64de9..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_update_conversation_variable_iteration.py +++ /dev/null @@ -1,41 +0,0 @@ -"""Validate conversation variable updates inside an iteration workflow. - -This test uses the ``update-conversation-variable-in-iteration`` fixture, which -routes ``sys.query`` into the conversation variable ``answer`` from within an -iteration container. The workflow should surface that updated conversation -variable in the final answer output. - -Code nodes in the fixture are mocked because their concrete outputs are not -relevant to verifying variable propagation semantics. -""" - -from .test_mock_config import MockConfigBuilder -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -def test_update_conversation_variable_in_iteration(): - fixture_name = "update-conversation-variable-in-iteration" - user_query = "ensure conversation variable syncs" - - mock_config = ( - MockConfigBuilder() - .with_node_output("1759032363865", {"result": [1]}) - .with_node_output("1759032476318", {"result": ""}) - .build() - ) - - case = WorkflowTestCase( - fixture_path=fixture_name, - use_auto_mock=True, - mock_config=mock_config, - query=user_query, - expected_outputs={"answer": user_query}, - description="Conversation variable updated within iteration should flow to answer output.", - ) - - runner = TableTestRunner() - result = runner.run_test_case(case) - - assert result.success, f"Workflow execution failed: {result.error}" - assert result.actual_outputs is not None - assert result.actual_outputs.get("answer") == user_query diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_variable_aggregator.py b/api/tests/unit_tests/core/workflow/graph_engine/test_variable_aggregator.py deleted file mode 100644 index f63e8ff4ce5..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_variable_aggregator.py +++ /dev/null @@ -1,58 +0,0 @@ -from unittest.mock import patch - -import pytest - -from dify_graph.enums import WorkflowNodeExecutionStatus -from dify_graph.node_events import NodeRunResult -from dify_graph.nodes.template_transform.template_transform_node import TemplateTransformNode - -from .test_table_runner import TableTestRunner, WorkflowTestCase - - -class TestVariableAggregator: - """Test cases for the variable aggregator workflow.""" - - @pytest.mark.parametrize( - ("switch1", "switch2", "expected_group1", "expected_group2", "description"), - [ - (0, 0, "switch 1 off", "switch 2 off", "Both switches off"), - (0, 1, "switch 1 off", "switch 2 on", "Switch1 off, Switch2 on"), - (1, 0, "switch 1 on", "switch 2 off", "Switch1 on, Switch2 off"), - (1, 1, "switch 1 on", "switch 2 on", "Both switches on"), - ], - ) - def test_variable_aggregator_combinations( - self, - switch1: int, - switch2: int, - expected_group1: str, - expected_group2: str, - description: str, - ) -> None: - """Test all four combinations of switch1 and switch2.""" - - def mock_template_transform_run(self): - """Mock the TemplateTransformNode._run() method to return results based on node title.""" - title = self._node_data.title - return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={}, outputs={"output": title}) - - with patch.object( - TemplateTransformNode, - "_run", - mock_template_transform_run, - ): - runner = TableTestRunner() - - test_case = WorkflowTestCase( - fixture_path="dual_switch_variable_aggregator_workflow", - inputs={"switch1": switch1, "switch2": switch2}, - expected_outputs={"group1": expected_group1, "group2": expected_group2}, - description=description, - ) - - result = runner.run_test_case(test_case) - - assert result.success, f"Test failed: {result.error}" - assert result.actual_outputs == test_case.expected_outputs, ( - f"Output mismatch: expected {test_case.expected_outputs}, got {result.actual_outputs}" - ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_worker.py b/api/tests/unit_tests/core/workflow/graph_engine/test_worker.py deleted file mode 100644 index bc00b49fba7..00000000000 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_worker.py +++ /dev/null @@ -1,145 +0,0 @@ -import queue -from collections.abc import Generator -from datetime import UTC, datetime, timedelta -from types import SimpleNamespace -from unittest.mock import MagicMock, patch - -from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus -from dify_graph.graph_engine.ready_queue import InMemoryReadyQueue -from dify_graph.graph_engine.worker import Worker -from dify_graph.graph_events import NodeRunFailedEvent, NodeRunStartedEvent - - -def test_build_fallback_failure_event_uses_naive_utc_and_failed_node_run_result(mocker) -> None: - fixed_time = datetime(2024, 1, 1, 12, 0, 0, tzinfo=UTC).replace(tzinfo=None) - mocker.patch("dify_graph.graph_engine.worker.naive_utc_now", return_value=fixed_time) - - worker = Worker( - ready_queue=InMemoryReadyQueue(), - event_queue=queue.Queue(), - graph=MagicMock(), - layers=[], - ) - node = SimpleNamespace( - execution_id="exec-1", - id="node-1", - node_type=BuiltinNodeTypes.LLM, - ) - - event = worker._build_fallback_failure_event(node, RuntimeError("boom")) - - assert event.start_at == fixed_time - assert event.finished_at == fixed_time - assert event.error == "boom" - assert event.node_run_result.status == WorkflowNodeExecutionStatus.FAILED - assert event.node_run_result.error == "boom" - assert event.node_run_result.error_type == "RuntimeError" - - -def test_worker_fallback_failure_event_reuses_observed_start_time() -> None: - start_at = datetime(2024, 1, 1, 12, 0, 0, tzinfo=UTC).replace(tzinfo=None) - failure_time = start_at + timedelta(seconds=5) - captured_events: list[NodeRunFailedEvent | NodeRunStartedEvent] = [] - - class FakeNode: - execution_id = "exec-1" - id = "node-1" - node_type = BuiltinNodeTypes.LLM - - def ensure_execution_id(self) -> str: - return self.execution_id - - def run(self) -> Generator[NodeRunStartedEvent, None, None]: - yield NodeRunStartedEvent( - id=self.execution_id, - node_id=self.id, - node_type=self.node_type, - node_title="LLM", - start_at=start_at, - ) - - worker = Worker( - ready_queue=MagicMock(), - event_queue=MagicMock(), - graph=MagicMock(nodes={"node-1": FakeNode()}), - layers=[], - ) - - worker._ready_queue.get.side_effect = ["node-1"] - - def put_side_effect(event: NodeRunFailedEvent | NodeRunStartedEvent) -> None: - captured_events.append(event) - if len(captured_events) == 1: - raise RuntimeError("queue boom") - worker.stop() - - worker._event_queue.put.side_effect = put_side_effect - - with patch("dify_graph.graph_engine.worker.naive_utc_now", return_value=failure_time): - worker.run() - - fallback_event = captured_events[-1] - - assert isinstance(fallback_event, NodeRunFailedEvent) - assert fallback_event.start_at == start_at - assert fallback_event.finished_at == failure_time - assert fallback_event.error == "queue boom" - assert fallback_event.node_run_result.status == WorkflowNodeExecutionStatus.FAILED - - -def test_worker_fallback_failure_event_ignores_nested_iteration_child_start_times() -> None: - parent_start = datetime(2024, 1, 1, 12, 0, 0, tzinfo=UTC).replace(tzinfo=None) - child_start = parent_start + timedelta(seconds=3) - failure_time = parent_start + timedelta(seconds=5) - captured_events: list[NodeRunFailedEvent | NodeRunStartedEvent] = [] - - class FakeIterationNode: - execution_id = "iteration-exec" - id = "iteration-node" - node_type = BuiltinNodeTypes.ITERATION - - def ensure_execution_id(self) -> str: - return self.execution_id - - def run(self) -> Generator[NodeRunStartedEvent, None, None]: - yield NodeRunStartedEvent( - id=self.execution_id, - node_id=self.id, - node_type=self.node_type, - node_title="Iteration", - start_at=parent_start, - ) - yield NodeRunStartedEvent( - id="child-exec", - node_id="child-node", - node_type=BuiltinNodeTypes.LLM, - node_title="LLM", - start_at=child_start, - in_iteration_id=self.id, - ) - - worker = Worker( - ready_queue=MagicMock(), - event_queue=MagicMock(), - graph=MagicMock(nodes={"iteration-node": FakeIterationNode()}), - layers=[], - ) - - worker._ready_queue.get.side_effect = ["iteration-node"] - - def put_side_effect(event: NodeRunFailedEvent | NodeRunStartedEvent) -> None: - captured_events.append(event) - if len(captured_events) == 2: - raise RuntimeError("queue boom") - worker.stop() - - worker._event_queue.put.side_effect = put_side_effect - - with patch("dify_graph.graph_engine.worker.naive_utc_now", return_value=failure_time): - worker.run() - - fallback_event = captured_events[-1] - - assert isinstance(fallback_event, NodeRunFailedEvent) - assert fallback_event.start_at == parent_start - assert fallback_event.finished_at == failure_time diff --git a/api/tests/unit_tests/core/workflow/nodes/agent/test_message_transformer.py b/api/tests/unit_tests/core/workflow/nodes/agent/test_message_transformer.py new file mode 100644 index 00000000000..cbc920705ca --- /dev/null +++ b/api/tests/unit_tests/core/workflow/nodes/agent/test_message_transformer.py @@ -0,0 +1,34 @@ +from unittest.mock import patch + +from graphon.enums import BuiltinNodeTypes + +from core.tools.utils.message_transformer import ToolFileMessageTransformer +from core.workflow.nodes.agent.message_transformer import AgentMessageTransformer + + +def test_transform_passes_conversation_id_to_tool_file_message_transformer() -> None: + messages = iter(()) + transformer = AgentMessageTransformer() + + with patch.object(ToolFileMessageTransformer, "transform_tool_invoke_messages", return_value=iter(())) as transform: + result = list( + transformer.transform( + messages=messages, + tool_info={}, + parameters_for_log={}, + user_id="user-id", + tenant_id="tenant-id", + conversation_id="conversation-id", + node_type=BuiltinNodeTypes.AGENT, + node_id="node-id", + node_execution_id="execution-id", + ) + ) + + assert len(result) == 2 + transform.assert_called_once_with( + messages=messages, + user_id="user-id", + tenant_id="tenant-id", + conversation_id="conversation-id", + ) diff --git a/api/tests/unit_tests/core/workflow/nodes/agent/test_runtime_support.py b/api/tests/unit_tests/core/workflow/nodes/agent/test_runtime_support.py new file mode 100644 index 00000000000..59dd763b59d --- /dev/null +++ b/api/tests/unit_tests/core/workflow/nodes/agent/test_runtime_support.py @@ -0,0 +1,50 @@ +from types import SimpleNamespace +from unittest.mock import Mock, patch + +from graphon.model_runtime.entities.model_entities import ModelType + +from core.workflow.nodes.agent.runtime_support import AgentRuntimeSupport + + +def test_fetch_model_reuses_single_model_assembly(): + provider_configuration = SimpleNamespace( + get_current_credentials=Mock(return_value={"api_key": "x"}), + provider=SimpleNamespace(provider="openai"), + ) + model_type_instance = SimpleNamespace(get_model_schema=Mock(return_value="schema")) + provider_model_bundle = SimpleNamespace( + configuration=provider_configuration, + model_type_instance=model_type_instance, + ) + model_instance = Mock() + assembly = SimpleNamespace( + provider_manager=Mock(), + model_manager=Mock(), + ) + assembly.provider_manager.get_provider_model_bundle.return_value = provider_model_bundle + assembly.model_manager.get_model_instance.return_value = model_instance + + with patch( + "core.workflow.nodes.agent.runtime_support.create_plugin_model_assembly", + return_value=assembly, + ) as mock_assembly: + resolved_instance, resolved_schema = AgentRuntimeSupport().fetch_model( + tenant_id="tenant-1", + user_id="user-1", + value={"provider": "openai", "model": "gpt-4o-mini", "model_type": "llm"}, + ) + + assert resolved_instance is model_instance + assert resolved_schema == "schema" + mock_assembly.assert_called_once_with(tenant_id="tenant-1", user_id="user-1") + assembly.provider_manager.get_provider_model_bundle.assert_called_once_with( + tenant_id="tenant-1", + provider="openai", + model_type=ModelType.LLM, + ) + assembly.model_manager.get_model_instance.assert_called_once_with( + tenant_id="tenant-1", + provider="openai", + model_type=ModelType.LLM, + model="gpt-4o-mini", + ) diff --git a/api/tests/unit_tests/core/workflow/nodes/answer/test_answer.py b/api/tests/unit_tests/core/workflow/nodes/answer/test_answer.py index fd563d1be2f..7195471eb6b 100644 --- a/api/tests/unit_tests/core/workflow/nodes/answer/test_answer.py +++ b/api/tests/unit_tests/core/workflow/nodes/answer/test_answer.py @@ -2,13 +2,14 @@ import time import uuid from unittest.mock import MagicMock +from graphon.enums import WorkflowNodeExecutionStatus +from graphon.graph import Graph +from graphon.nodes.answer.answer_node import AnswerNode +from graphon.runtime import GraphRuntimeState, VariablePool + from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom from core.workflow.node_factory import DifyNodeFactory -from dify_graph.enums import WorkflowNodeExecutionStatus -from dify_graph.graph import Graph -from dify_graph.nodes.answer.answer_node import AnswerNode -from dify_graph.runtime import GraphRuntimeState, VariablePool -from dify_graph.system_variable import SystemVariable +from core.workflow.system_variables import build_system_variables from extensions.ext_database import db from tests.workflow_test_utils import build_test_graph_init_params @@ -48,7 +49,7 @@ def test_execute_answer(): # construct variable pool variable_pool = VariablePool( - system_variables=SystemVariable(user_id="aaa", files=[]), + system_variables=build_system_variables(user_id="aaa", files=[]), user_inputs={}, environment_variables=[], conversation_variables=[], diff --git a/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py b/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py index 81d3f5be9c8..343bcd39193 100644 --- a/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py +++ b/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py @@ -1,9 +1,9 @@ import pytest +from graphon.entities.base_node_data import BaseNodeData +from graphon.enums import BuiltinNodeTypes, NodeType +from graphon.nodes.base.node import Node from core.workflow.node_factory import get_node_type_classes_mapping -from dify_graph.entities.base_node_data import BaseNodeData -from dify_graph.enums import BuiltinNodeTypes, NodeType -from dify_graph.nodes.base.node import Node # Ensures that all production node classes are imported and registered. _ = get_node_type_classes_mapping() diff --git a/api/tests/unit_tests/core/workflow/nodes/base/test_get_node_type_classes_mapping.py b/api/tests/unit_tests/core/workflow/nodes/base/test_get_node_type_classes_mapping.py index 972a945ca0f..b9371a34f44 100644 --- a/api/tests/unit_tests/core/workflow/nodes/base/test_get_node_type_classes_mapping.py +++ b/api/tests/unit_tests/core/workflow/nodes/base/test_get_node_type_classes_mapping.py @@ -1,19 +1,20 @@ import types from collections.abc import Mapping -from core.workflow.node_factory import get_node_type_classes_mapping -from dify_graph.entities.base_node_data import BaseNodeData -from dify_graph.enums import BuiltinNodeTypes, NodeType -from dify_graph.nodes.base.node import Node +from graphon.entities.base_node_data import BaseNodeData +from graphon.enums import BuiltinNodeTypes, NodeType +from graphon.nodes.base.node import Node # Import concrete nodes we will assert on (numeric version path) -from dify_graph.nodes.variable_assigner.v1.node import ( +from graphon.nodes.variable_assigner.v1.node import ( VariableAssignerNode as VariableAssignerV1, ) -from dify_graph.nodes.variable_assigner.v2.node import ( +from graphon.nodes.variable_assigner.v2.node import ( VariableAssignerNode as VariableAssignerV2, ) +from core.workflow.node_factory import get_node_type_classes_mapping + def test_variable_assigner_latest_prefers_highest_numeric_version(): # Act diff --git a/api/tests/unit_tests/core/workflow/nodes/code/code_node_spec.py b/api/tests/unit_tests/core/workflow/nodes/code/code_node_spec.py index 784e08edd24..d155124c501 100644 --- a/api/tests/unit_tests/core/workflow/nodes/code/code_node_spec.py +++ b/api/tests/unit_tests/core/workflow/nodes/code/code_node_spec.py @@ -1,13 +1,14 @@ -from configs import dify_config -from dify_graph.nodes.code.code_node import CodeNode -from dify_graph.nodes.code.entities import CodeLanguage, CodeNodeData -from dify_graph.nodes.code.exc import ( +from graphon.nodes.code.code_node import CodeNode +from graphon.nodes.code.entities import CodeLanguage, CodeNodeData +from graphon.nodes.code.exc import ( CodeNodeError, DepthLimitError, OutputValidationError, ) -from dify_graph.nodes.code.limits import CodeNodeLimits -from dify_graph.variables.types import SegmentType +from graphon.nodes.code.limits import CodeNodeLimits +from graphon.variables.types import SegmentType + +from configs import dify_config CodeNode._limits = CodeNodeLimits( max_string_length=dify_config.CODE_MAX_STRING_LENGTH, diff --git a/api/tests/unit_tests/core/workflow/nodes/code/entities_spec.py b/api/tests/unit_tests/core/workflow/nodes/code/entities_spec.py deleted file mode 100644 index de7ed0815eb..00000000000 --- a/api/tests/unit_tests/core/workflow/nodes/code/entities_spec.py +++ /dev/null @@ -1,352 +0,0 @@ -import pytest -from pydantic import ValidationError - -from dify_graph.nodes.code.entities import CodeLanguage, CodeNodeData -from dify_graph.variables.types import SegmentType - - -class TestCodeNodeDataOutput: - """Test suite for CodeNodeData.Output model.""" - - def test_output_with_string_type(self): - """Test Output with STRING type.""" - output = CodeNodeData.Output(type=SegmentType.STRING) - - assert output.type == SegmentType.STRING - assert output.children is None - - def test_output_with_number_type(self): - """Test Output with NUMBER type.""" - output = CodeNodeData.Output(type=SegmentType.NUMBER) - - assert output.type == SegmentType.NUMBER - assert output.children is None - - def test_output_with_boolean_type(self): - """Test Output with BOOLEAN type.""" - output = CodeNodeData.Output(type=SegmentType.BOOLEAN) - - assert output.type == SegmentType.BOOLEAN - - def test_output_with_object_type(self): - """Test Output with OBJECT type.""" - output = CodeNodeData.Output(type=SegmentType.OBJECT) - - assert output.type == SegmentType.OBJECT - - def test_output_with_array_string_type(self): - """Test Output with ARRAY_STRING type.""" - output = CodeNodeData.Output(type=SegmentType.ARRAY_STRING) - - assert output.type == SegmentType.ARRAY_STRING - - def test_output_with_array_number_type(self): - """Test Output with ARRAY_NUMBER type.""" - output = CodeNodeData.Output(type=SegmentType.ARRAY_NUMBER) - - assert output.type == SegmentType.ARRAY_NUMBER - - def test_output_with_array_object_type(self): - """Test Output with ARRAY_OBJECT type.""" - output = CodeNodeData.Output(type=SegmentType.ARRAY_OBJECT) - - assert output.type == SegmentType.ARRAY_OBJECT - - def test_output_with_array_boolean_type(self): - """Test Output with ARRAY_BOOLEAN type.""" - output = CodeNodeData.Output(type=SegmentType.ARRAY_BOOLEAN) - - assert output.type == SegmentType.ARRAY_BOOLEAN - - def test_output_with_nested_children(self): - """Test Output with nested children for OBJECT type.""" - child_output = CodeNodeData.Output(type=SegmentType.STRING) - parent_output = CodeNodeData.Output( - type=SegmentType.OBJECT, - children={"name": child_output}, - ) - - assert parent_output.type == SegmentType.OBJECT - assert parent_output.children is not None - assert "name" in parent_output.children - assert parent_output.children["name"].type == SegmentType.STRING - - def test_output_with_deeply_nested_children(self): - """Test Output with deeply nested children.""" - inner_child = CodeNodeData.Output(type=SegmentType.NUMBER) - middle_child = CodeNodeData.Output( - type=SegmentType.OBJECT, - children={"value": inner_child}, - ) - outer_output = CodeNodeData.Output( - type=SegmentType.OBJECT, - children={"nested": middle_child}, - ) - - assert outer_output.children is not None - assert outer_output.children["nested"].children is not None - assert outer_output.children["nested"].children["value"].type == SegmentType.NUMBER - - def test_output_with_multiple_children(self): - """Test Output with multiple children.""" - output = CodeNodeData.Output( - type=SegmentType.OBJECT, - children={ - "name": CodeNodeData.Output(type=SegmentType.STRING), - "age": CodeNodeData.Output(type=SegmentType.NUMBER), - "active": CodeNodeData.Output(type=SegmentType.BOOLEAN), - }, - ) - - assert output.children is not None - assert len(output.children) == 3 - assert output.children["name"].type == SegmentType.STRING - assert output.children["age"].type == SegmentType.NUMBER - assert output.children["active"].type == SegmentType.BOOLEAN - - def test_output_rejects_invalid_type(self): - """Test Output rejects invalid segment types.""" - with pytest.raises(ValidationError): - CodeNodeData.Output(type=SegmentType.FILE) - - def test_output_rejects_array_file_type(self): - """Test Output rejects ARRAY_FILE type.""" - with pytest.raises(ValidationError): - CodeNodeData.Output(type=SegmentType.ARRAY_FILE) - - -class TestCodeNodeDataDependency: - """Test suite for CodeNodeData.Dependency model.""" - - def test_dependency_basic(self): - """Test Dependency with name and version.""" - dependency = CodeNodeData.Dependency(name="numpy", version="1.24.0") - - assert dependency.name == "numpy" - assert dependency.version == "1.24.0" - - def test_dependency_with_complex_version(self): - """Test Dependency with complex version string.""" - dependency = CodeNodeData.Dependency(name="pandas", version=">=2.0.0,<3.0.0") - - assert dependency.name == "pandas" - assert dependency.version == ">=2.0.0,<3.0.0" - - def test_dependency_with_empty_version(self): - """Test Dependency with empty version.""" - dependency = CodeNodeData.Dependency(name="requests", version="") - - assert dependency.name == "requests" - assert dependency.version == "" - - -class TestCodeNodeData: - """Test suite for CodeNodeData model.""" - - def test_code_node_data_python3(self): - """Test CodeNodeData with Python3 language.""" - data = CodeNodeData( - title="Test Code Node", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'result': 42}", - outputs={"result": CodeNodeData.Output(type=SegmentType.NUMBER)}, - ) - - assert data.title == "Test Code Node" - assert data.code_language == CodeLanguage.PYTHON3 - assert data.code == "def main(): return {'result': 42}" - assert "result" in data.outputs - assert data.dependencies is None - - def test_code_node_data_javascript(self): - """Test CodeNodeData with JavaScript language.""" - data = CodeNodeData( - title="JS Code Node", - variables=[], - code_language=CodeLanguage.JAVASCRIPT, - code="function main() { return { result: 'hello' }; }", - outputs={"result": CodeNodeData.Output(type=SegmentType.STRING)}, - ) - - assert data.code_language == CodeLanguage.JAVASCRIPT - assert "result" in data.outputs - assert data.outputs["result"].type == SegmentType.STRING - - def test_code_node_data_with_dependencies(self): - """Test CodeNodeData with dependencies.""" - data = CodeNodeData( - title="Code with Deps", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="import numpy as np\ndef main(): return {'sum': 10}", - outputs={"sum": CodeNodeData.Output(type=SegmentType.NUMBER)}, - dependencies=[ - CodeNodeData.Dependency(name="numpy", version="1.24.0"), - CodeNodeData.Dependency(name="pandas", version="2.0.0"), - ], - ) - - assert data.dependencies is not None - assert len(data.dependencies) == 2 - assert data.dependencies[0].name == "numpy" - assert data.dependencies[1].name == "pandas" - - def test_code_node_data_with_multiple_outputs(self): - """Test CodeNodeData with multiple outputs.""" - data = CodeNodeData( - title="Multi Output", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'name': 'test', 'count': 5, 'items': ['a', 'b']}", - outputs={ - "name": CodeNodeData.Output(type=SegmentType.STRING), - "count": CodeNodeData.Output(type=SegmentType.NUMBER), - "items": CodeNodeData.Output(type=SegmentType.ARRAY_STRING), - }, - ) - - assert len(data.outputs) == 3 - assert data.outputs["name"].type == SegmentType.STRING - assert data.outputs["count"].type == SegmentType.NUMBER - assert data.outputs["items"].type == SegmentType.ARRAY_STRING - - def test_code_node_data_with_object_output(self): - """Test CodeNodeData with nested object output.""" - data = CodeNodeData( - title="Object Output", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'user': {'name': 'John', 'age': 30}}", - outputs={ - "user": CodeNodeData.Output( - type=SegmentType.OBJECT, - children={ - "name": CodeNodeData.Output(type=SegmentType.STRING), - "age": CodeNodeData.Output(type=SegmentType.NUMBER), - }, - ), - }, - ) - - assert data.outputs["user"].type == SegmentType.OBJECT - assert data.outputs["user"].children is not None - assert len(data.outputs["user"].children) == 2 - - def test_code_node_data_with_array_object_output(self): - """Test CodeNodeData with array of objects output.""" - data = CodeNodeData( - title="Array Object Output", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'users': [{'name': 'A'}, {'name': 'B'}]}", - outputs={ - "users": CodeNodeData.Output( - type=SegmentType.ARRAY_OBJECT, - children={ - "name": CodeNodeData.Output(type=SegmentType.STRING), - }, - ), - }, - ) - - assert data.outputs["users"].type == SegmentType.ARRAY_OBJECT - assert data.outputs["users"].children is not None - - def test_code_node_data_empty_code(self): - """Test CodeNodeData with empty code.""" - data = CodeNodeData( - title="Empty Code", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="", - outputs={}, - ) - - assert data.code == "" - assert len(data.outputs) == 0 - - def test_code_node_data_multiline_code(self): - """Test CodeNodeData with multiline code.""" - multiline_code = """ -def main(): - result = 0 - for i in range(10): - result += i - return {'sum': result} -""" - data = CodeNodeData( - title="Multiline Code", - variables=[], - code_language=CodeLanguage.PYTHON3, - code=multiline_code, - outputs={"sum": CodeNodeData.Output(type=SegmentType.NUMBER)}, - ) - - assert "for i in range(10)" in data.code - assert "result += i" in data.code - - def test_code_node_data_with_special_characters_in_code(self): - """Test CodeNodeData with special characters in code.""" - code_with_special = "def main(): return {'msg': 'Hello\\nWorld\\t!'}" - data = CodeNodeData( - title="Special Chars", - variables=[], - code_language=CodeLanguage.PYTHON3, - code=code_with_special, - outputs={"msg": CodeNodeData.Output(type=SegmentType.STRING)}, - ) - - assert "\\n" in data.code - assert "\\t" in data.code - - def test_code_node_data_with_unicode_in_code(self): - """Test CodeNodeData with unicode characters in code.""" - unicode_code = "def main(): return {'greeting': '你好世界'}" - data = CodeNodeData( - title="Unicode Code", - variables=[], - code_language=CodeLanguage.PYTHON3, - code=unicode_code, - outputs={"greeting": CodeNodeData.Output(type=SegmentType.STRING)}, - ) - - assert "你好世界" in data.code - - def test_code_node_data_empty_dependencies_list(self): - """Test CodeNodeData with empty dependencies list.""" - data = CodeNodeData( - title="No Deps", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {}", - outputs={}, - dependencies=[], - ) - - assert data.dependencies is not None - assert len(data.dependencies) == 0 - - def test_code_node_data_with_boolean_array_output(self): - """Test CodeNodeData with boolean array output.""" - data = CodeNodeData( - title="Boolean Array", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'flags': [True, False, True]}", - outputs={"flags": CodeNodeData.Output(type=SegmentType.ARRAY_BOOLEAN)}, - ) - - assert data.outputs["flags"].type == SegmentType.ARRAY_BOOLEAN - - def test_code_node_data_with_number_array_output(self): - """Test CodeNodeData with number array output.""" - data = CodeNodeData( - title="Number Array", - variables=[], - code_language=CodeLanguage.PYTHON3, - code="def main(): return {'values': [1, 2, 3, 4, 5]}", - outputs={"values": CodeNodeData.Output(type=SegmentType.ARRAY_NUMBER)}, - ) - - assert data.outputs["values"].type == SegmentType.ARRAY_NUMBER diff --git a/api/tests/unit_tests/core/workflow/nodes/datasource/test_datasource_node.py b/api/tests/unit_tests/core/workflow/nodes/datasource/test_datasource_node.py index 859115ceb3f..fb03ae9998d 100644 --- a/api/tests/unit_tests/core/workflow/nodes/datasource/test_datasource_node.py +++ b/api/tests/unit_tests/core/workflow/nodes/datasource/test_datasource_node.py @@ -1,7 +1,8 @@ +from graphon.enums import WorkflowNodeExecutionStatus +from graphon.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent + +from core.app.entities.app_invoke_entities import DIFY_RUN_CONTEXT_KEY from core.workflow.nodes.datasource.datasource_node import DatasourceNode -from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY -from dify_graph.entities.workflow_node_execution import WorkflowNodeExecutionStatus -from dify_graph.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent class _VarSeg: diff --git a/api/tests/unit_tests/core/workflow/nodes/http_request/test_config.py b/api/tests/unit_tests/core/workflow/nodes/http_request/test_config.py deleted file mode 100644 index cd822a6f895..00000000000 --- a/api/tests/unit_tests/core/workflow/nodes/http_request/test_config.py +++ /dev/null @@ -1,33 +0,0 @@ -from dify_graph.nodes.http_request import build_http_request_config - - -def test_build_http_request_config_uses_literal_defaults(): - config = build_http_request_config() - - assert config.max_connect_timeout == 10 - assert config.max_read_timeout == 600 - assert config.max_write_timeout == 600 - assert config.max_binary_size == 10 * 1024 * 1024 - assert config.max_text_size == 1 * 1024 * 1024 - assert config.ssl_verify is True - assert config.ssrf_default_max_retries == 3 - - -def test_build_http_request_config_supports_explicit_overrides(): - config = build_http_request_config( - max_connect_timeout=5, - max_read_timeout=30, - max_write_timeout=40, - max_binary_size=2048, - max_text_size=1024, - ssl_verify=False, - ssrf_default_max_retries=8, - ) - - assert config.max_connect_timeout == 5 - assert config.max_read_timeout == 30 - assert config.max_write_timeout == 40 - assert config.max_binary_size == 2048 - assert config.max_text_size == 1024 - assert config.ssl_verify is False - assert config.ssrf_default_max_retries == 8 diff --git a/api/tests/unit_tests/core/workflow/nodes/http_request/test_entities.py b/api/tests/unit_tests/core/workflow/nodes/http_request/test_entities.py deleted file mode 100644 index fec6ad90eb1..00000000000 --- a/api/tests/unit_tests/core/workflow/nodes/http_request/test_entities.py +++ /dev/null @@ -1,233 +0,0 @@ -import json -from unittest.mock import Mock, PropertyMock, patch - -import httpx -import pytest - -from dify_graph.nodes.http_request.entities import Response - - -@pytest.fixture -def mock_response(): - response = Mock(spec=httpx.Response) - response.headers = {} - return response - - -def test_is_file_with_attachment_disposition(mock_response): - """Test is_file when content-disposition header contains 'attachment'""" - mock_response.headers = {"content-disposition": "attachment; filename=test.pdf", "content-type": "application/pdf"} - response = Response(mock_response) - assert response.is_file - - -def test_is_file_with_filename_disposition(mock_response): - """Test is_file when content-disposition header contains filename parameter""" - mock_response.headers = {"content-disposition": "inline; filename=test.pdf", "content-type": "application/pdf"} - response = Response(mock_response) - assert response.is_file - - -@pytest.mark.parametrize("content_type", ["application/pdf", "image/jpeg", "audio/mp3", "video/mp4"]) -def test_is_file_with_file_content_types(mock_response, content_type): - """Test is_file with various file content types""" - mock_response.headers = {"content-type": content_type} - # Mock binary content - type(mock_response).content = PropertyMock(return_value=bytes([0x00, 0xFF] * 512)) - response = Response(mock_response) - assert response.is_file, f"Content type {content_type} should be identified as a file" - - -@pytest.mark.parametrize( - "content_type", - [ - "application/json", - "application/xml", - "application/javascript", - "application/x-www-form-urlencoded", - "application/yaml", - "application/graphql", - ], -) -def test_text_based_application_types(mock_response, content_type): - """Test common text-based application types are not identified as files""" - mock_response.headers = {"content-type": content_type} - response = Response(mock_response) - assert not response.is_file, f"Content type {content_type} should not be identified as a file" - - -@pytest.mark.parametrize( - ("content", "content_type"), - [ - (b'{"key": "value"}', "application/octet-stream"), - (b"[1, 2, 3]", "application/unknown"), - (b"function test() {}", "application/x-unknown"), - (b"hello
", - expiration_time=datetime.utcnow() + timedelta(hours=1), + expiration_time=naive_utc_now() + timedelta(hours=1), ), rendered_content="hello
", - created_at=datetime.utcnow(), - expiration_time=datetime.utcnow() + timedelta(hours=1), + created_at=naive_utc_now(), + expiration_time=naive_utc_now() + timedelta(hours=1), status=HumanInputFormStatus.WAITING, selected_action_id=None, submitted_data=None, @@ -101,8 +102,8 @@ def test_ensure_form_active_respects_global_timeout(monkeypatch, sample_form_rec service = HumanInputService(session_factory) expired_record = dataclasses.replace( sample_form_record, - created_at=datetime.utcnow() - timedelta(hours=2), - expiration_time=datetime.utcnow() + timedelta(hours=2), + created_at=naive_utc_now() - timedelta(hours=2), + expiration_time=naive_utc_now() + timedelta(hours=2), ) monkeypatch.setattr(human_input_service_module.dify_config, "HUMAN_INPUT_GLOBAL_TIMEOUT_SECONDS", 3600) @@ -391,7 +392,7 @@ def test_ensure_form_active_errors(sample_form_record, mock_session_factory): service = HumanInputService(session_factory) # Submitted - submitted_record = dataclasses.replace(sample_form_record, submitted_at=datetime.utcnow()) + submitted_record = dataclasses.replace(sample_form_record, submitted_at=naive_utc_now()) with pytest.raises(human_input_service_module.FormSubmittedError): service.ensure_form_active(Form(submitted_record)) @@ -402,7 +403,7 @@ def test_ensure_form_active_errors(sample_form_record, mock_session_factory): # Expired time expired_time_record = dataclasses.replace( - sample_form_record, expiration_time=datetime.utcnow() - timedelta(minutes=1) + sample_form_record, expiration_time=naive_utc_now() - timedelta(minutes=1) ) with pytest.raises(FormExpiredError): service.ensure_form_active(Form(expired_time_record)) @@ -411,7 +412,7 @@ def test_ensure_form_active_errors(sample_form_record, mock_session_factory): def test_ensure_not_submitted_raises(sample_form_record, mock_session_factory): session_factory, _ = mock_session_factory service = HumanInputService(session_factory) - submitted_record = dataclasses.replace(sample_form_record, submitted_at=datetime.utcnow()) + submitted_record = dataclasses.replace(sample_form_record, submitted_at=naive_utc_now()) with pytest.raises(human_input_service_module.FormSubmittedError): service._ensure_not_submitted(Form(submitted_record)) diff --git a/api/tests/unit_tests/services/test_knowledge_service.py b/api/tests/unit_tests/services/test_knowledge_service.py index bc0caee0717..53c243ad716 100644 --- a/api/tests/unit_tests/services/test_knowledge_service.py +++ b/api/tests/unit_tests/services/test_knowledge_service.py @@ -3,7 +3,7 @@ from unittest.mock import MagicMock, patch import pytest -from services.knowledge_service import ExternalDatasetTestService +from services.knowledge_service import BedrockRetrievalSetting, ExternalDatasetTestService class TestKnowledgeService: @@ -24,7 +24,7 @@ class TestKnowledgeService: mock_client = MagicMock() mock_boto_client.return_value = mock_client - retrieval_setting = {"top_k": 4, "score_threshold": 0.5} + retrieval_setting = BedrockRetrievalSetting(top_k=4, score_threshold=0.5) query = "test query" knowledge_id = "kb-123" @@ -87,7 +87,10 @@ class TestKnowledgeService: mock_client.retrieve.return_value = {"ResponseMetadata": {"HTTPStatusCode": 200}, "retrievalResults": []} # Act - result = cast(dict[str, Any], ExternalDatasetTestService.knowledge_retrieval({"top_k": 1}, "query", "kb")) + result = cast( + dict[str, Any], + ExternalDatasetTestService.knowledge_retrieval(BedrockRetrievalSetting(top_k=1), "query", "kb"), + ) # Assert assert result["records"] == [] @@ -104,7 +107,10 @@ class TestKnowledgeService: mock_client.retrieve.return_value = {"ResponseMetadata": {"HTTPStatusCode": 500}} # Act - result = cast(dict[str, Any], ExternalDatasetTestService.knowledge_retrieval({"top_k": 1}, "query", "kb")) + result = cast( + dict[str, Any], + ExternalDatasetTestService.knowledge_retrieval(BedrockRetrievalSetting(top_k=1), "query", "kb"), + ) # Assert assert result["records"] == [] @@ -114,7 +120,7 @@ class TestKnowledgeService: with patch("services.knowledge_service.boto3.client") as mock_boto: mock_boto.side_effect = Exception("client init failed") with pytest.raises(Exception) as exc_info: - ExternalDatasetTestService.knowledge_retrieval({"top_k": 1}, "query", "kb") + ExternalDatasetTestService.knowledge_retrieval(BedrockRetrievalSetting(top_k=1), "query", "kb") assert "client init failed" in str(exc_info.value) # ===== Edge Cases ===== @@ -139,7 +145,10 @@ class TestKnowledgeService: # Act # retrieval_setting missing "score_threshold" - result = cast(dict[str, Any], ExternalDatasetTestService.knowledge_retrieval({"top_k": 1}, "query", "kb")) + result = cast( + dict[str, Any], + ExternalDatasetTestService.knowledge_retrieval(BedrockRetrievalSetting(top_k=1), "query", "kb"), + ) # Assert assert len(result["records"]) == 1 diff --git a/api/tests/unit_tests/services/test_message_service.py b/api/tests/unit_tests/services/test_message_service.py index e7740ef93a4..101b9bff24d 100644 --- a/api/tests/unit_tests/services/test_message_service.py +++ b/api/tests/unit_tests/services/test_message_service.py @@ -933,7 +933,7 @@ class TestMessageServiceSuggestedQuestions: ) # Test 28: get_suggested_questions_after_answer - Advanced Chat success - @patch("services.message_service.ModelManager") + @patch("services.message_service.ModelManager.for_tenant") @patch("services.message_service.WorkflowService") @patch("services.message_service.AdvancedChatAppConfigManager") @patch("services.message_service.TokenBufferMemory") @@ -983,7 +983,7 @@ class TestMessageServiceSuggestedQuestions: # Test 29: get_suggested_questions_after_answer - Chat app success (no override) @patch("services.message_service.db") - @patch("services.message_service.ModelManager") + @patch("services.message_service.ModelManager.for_tenant") @patch("services.message_service.TokenBufferMemory") @patch("services.message_service.LLMGenerator") @patch("services.message_service.TraceQueueManager") diff --git a/api/tests/unit_tests/services/test_metadata_partial_update.py b/api/tests/unit_tests/services/test_metadata_partial_update.py deleted file mode 100644 index 60252784bc5..00000000000 --- a/api/tests/unit_tests/services/test_metadata_partial_update.py +++ /dev/null @@ -1,187 +0,0 @@ -import unittest -from unittest.mock import MagicMock, patch - -import pytest - -from models.dataset import Dataset, Document -from services.entities.knowledge_entities.knowledge_entities import ( - DocumentMetadataOperation, - MetadataDetail, - MetadataOperationData, -) -from services.metadata_service import MetadataService - - -class TestMetadataPartialUpdate(unittest.TestCase): - def setUp(self): - self.dataset = MagicMock(spec=Dataset) - self.dataset.id = "dataset_id" - self.dataset.built_in_field_enabled = False - - self.document = MagicMock(spec=Document) - self.document.id = "doc_id" - self.document.doc_metadata = {"existing_key": "existing_value"} - self.document.data_source_type = "upload_file" - - @patch("services.metadata_service.db") - @patch("services.metadata_service.DocumentService") - @patch("services.metadata_service.current_account_with_tenant") - @patch("services.metadata_service.redis_client") - def test_partial_update_merges_metadata(self, mock_redis, mock_current_account, mock_document_service, mock_db): - # Setup mocks - mock_redis.get.return_value = None - mock_document_service.get_document.return_value = self.document - mock_current_account.return_value = (MagicMock(id="user_id"), "tenant_id") - - # Mock DB query for existing bindings - - # No existing binding for new key - mock_db.session.query.return_value.filter_by.return_value.first.return_value = None - - # Input data - operation = DocumentMetadataOperation( - document_id="doc_id", - metadata_list=[MetadataDetail(id="new_meta_id", name="new_key", value="new_value")], - partial_update=True, - ) - metadata_args = MetadataOperationData(operation_data=[operation]) - - # Execute - MetadataService.update_documents_metadata(self.dataset, metadata_args) - - # Verify - # 1. Check that doc_metadata contains BOTH existing and new keys - expected_metadata = {"existing_key": "existing_value", "new_key": "new_value"} - assert self.document.doc_metadata == expected_metadata - - # 2. Check that existing bindings were NOT deleted - # The delete call in the original code: db.session.query(...).filter_by(...).delete() - # In partial update, this should NOT be called. - mock_db.session.query.return_value.filter_by.return_value.delete.assert_not_called() - - @patch("services.metadata_service.db") - @patch("services.metadata_service.DocumentService") - @patch("services.metadata_service.current_account_with_tenant") - @patch("services.metadata_service.redis_client") - def test_full_update_replaces_metadata(self, mock_redis, mock_current_account, mock_document_service, mock_db): - # Setup mocks - mock_redis.get.return_value = None - mock_document_service.get_document.return_value = self.document - mock_current_account.return_value = (MagicMock(id="user_id"), "tenant_id") - - # Input data (partial_update=False by default) - operation = DocumentMetadataOperation( - document_id="doc_id", - metadata_list=[MetadataDetail(id="new_meta_id", name="new_key", value="new_value")], - partial_update=False, - ) - metadata_args = MetadataOperationData(operation_data=[operation]) - - # Execute - MetadataService.update_documents_metadata(self.dataset, metadata_args) - - # Verify - # 1. Check that doc_metadata contains ONLY the new key - expected_metadata = {"new_key": "new_value"} - assert self.document.doc_metadata == expected_metadata - - # 2. Check that existing bindings WERE deleted - # In full update (default), we expect the existing bindings to be cleared. - mock_db.session.query.return_value.filter_by.return_value.delete.assert_called() - - @patch("services.metadata_service.db") - @patch("services.metadata_service.DocumentService") - @patch("services.metadata_service.current_account_with_tenant") - @patch("services.metadata_service.redis_client") - def test_partial_update_skips_existing_binding( - self, mock_redis, mock_current_account, mock_document_service, mock_db - ): - # Setup mocks - mock_redis.get.return_value = None - mock_document_service.get_document.return_value = self.document - mock_current_account.return_value = (MagicMock(id="user_id"), "tenant_id") - - # Mock DB query to return an existing binding - # This simulates that the document ALREADY has the metadata we are trying to add - mock_existing_binding = MagicMock() - mock_db.session.query.return_value.filter_by.return_value.first.return_value = mock_existing_binding - - # Input data - operation = DocumentMetadataOperation( - document_id="doc_id", - metadata_list=[MetadataDetail(id="existing_meta_id", name="existing_key", value="existing_value")], - partial_update=True, - ) - metadata_args = MetadataOperationData(operation_data=[operation]) - - # Execute - MetadataService.update_documents_metadata(self.dataset, metadata_args) - - # Verify - # We verify that db.session.add was NOT called for DatasetMetadataBinding - # Since we can't easily check "not called with specific type" on the generic add method without complex logic, - # we can check if the number of add calls is 1 (only for the document update) instead of 2 (document + binding) - - # Expected calls: - # 1. db.session.add(document) - # 2. NO db.session.add(binding) because it exists - - # Note: In the code, db.session.add is called for document. - # Then loop over metadata_list. - # If existing_binding found, continue. - # So binding add should be skipped. - - # Let's filter the calls to add to see what was added - add_calls = mock_db.session.add.call_args_list - added_objects = [call.args[0] for call in add_calls] - - # Check that no DatasetMetadataBinding was added - from models.dataset import DatasetMetadataBinding - - has_binding_add = any( - isinstance(obj, DatasetMetadataBinding) - or (isinstance(obj, MagicMock) and getattr(obj, "__class__", None) == DatasetMetadataBinding) - for obj in added_objects - ) - - # Since we mock everything, checking isinstance might be tricky if DatasetMetadataBinding - # is not the exact class used in the service (imports match). - # But we can check the count. - # If it were added, there would be 2 calls. If skipped, 1 call. - assert mock_db.session.add.call_count == 1 - - @patch("services.metadata_service.db") - @patch("services.metadata_service.DocumentService") - @patch("services.metadata_service.current_account_with_tenant") - @patch("services.metadata_service.redis_client") - def test_rollback_called_on_commit_failure(self, mock_redis, mock_current_account, mock_document_service, mock_db): - """When db.session.commit() raises, rollback must be called and the exception must propagate.""" - # Setup mocks - mock_redis.get.return_value = None - mock_document_service.get_document.return_value = self.document - mock_current_account.return_value = (MagicMock(id="user_id"), "tenant_id") - mock_db.session.query.return_value.filter_by.return_value.first.return_value = None - - # Make commit raise an exception - mock_db.session.commit.side_effect = RuntimeError("database connection lost") - - operation = DocumentMetadataOperation( - document_id="doc_id", - metadata_list=[MetadataDetail(id="meta_id", name="key", value="value")], - partial_update=True, - ) - metadata_args = MetadataOperationData(operation_data=[operation]) - - # Act & Assert: the exception must propagate - with pytest.raises(RuntimeError, match="database connection lost"): - MetadataService.update_documents_metadata(self.dataset, metadata_args) - - # Verify rollback was called - mock_db.session.rollback.assert_called_once() - - # Verify the lock key was cleaned up despite the failure - mock_redis.delete.assert_called_with("document_metadata_lock_doc_id") - - -if __name__ == "__main__": - unittest.main() diff --git a/api/tests/unit_tests/services/test_model_load_balancing_service.py b/api/tests/unit_tests/services/test_model_load_balancing_service.py new file mode 100644 index 00000000000..b43e79dff50 --- /dev/null +++ b/api/tests/unit_tests/services/test_model_load_balancing_service.py @@ -0,0 +1,815 @@ +from __future__ import annotations + +import json +from types import SimpleNamespace +from typing import Any, cast +from unittest.mock import MagicMock + +import pytest +from graphon.model_runtime.entities.common_entities import I18nObject +from graphon.model_runtime.entities.model_entities import ModelType +from graphon.model_runtime.entities.provider_entities import ( + CredentialFormSchema, + FieldModelSchema, + FormType, + ModelCredentialSchema, + ProviderCredentialSchema, +) +from pytest_mock import MockerFixture + +from constants import HIDDEN_VALUE +from models.provider import LoadBalancingModelConfig +from services.model_load_balancing_service import ModelLoadBalancingService + + +def _build_provider_credential_schema() -> ProviderCredentialSchema: + return ProviderCredentialSchema( + credential_form_schemas=[ + CredentialFormSchema(variable="api_key", label=I18nObject(en_US="API Key"), type=FormType.SECRET_INPUT) + ] + ) + + +def _build_model_credential_schema() -> ModelCredentialSchema: + return ModelCredentialSchema( + model=FieldModelSchema(label=I18nObject(en_US="Model")), + credential_form_schemas=[ + CredentialFormSchema(variable="api_key", label=I18nObject(en_US="API Key"), type=FormType.SECRET_INPUT) + ], + ) + + +def _build_provider_configuration( + *, + custom_provider: bool = False, + load_balancing_enabled: bool | None = None, + model_schema: ModelCredentialSchema | None = None, + provider_schema: ProviderCredentialSchema | None = None, +) -> MagicMock: + provider_configuration = MagicMock() + provider_configuration.provider = SimpleNamespace( + provider="openai", + model_credential_schema=model_schema, + provider_credential_schema=provider_schema, + ) + provider_configuration.custom_configuration = SimpleNamespace(provider=custom_provider) + provider_configuration.extract_secret_variables.return_value = ["api_key"] + provider_configuration.obfuscated_credentials.side_effect = lambda credentials, credential_form_schemas: credentials + provider_configuration.get_provider_model_setting.return_value = ( + None if load_balancing_enabled is None else SimpleNamespace(load_balancing_enabled=load_balancing_enabled) + ) + return provider_configuration + + +def _load_balancing_model_config(**kwargs: Any) -> LoadBalancingModelConfig: + return cast(LoadBalancingModelConfig, SimpleNamespace(**kwargs)) + + +@pytest.fixture +def service(mocker: MockerFixture) -> ModelLoadBalancingService: + # Arrange + provider_manager = MagicMock() + mocker.patch("services.model_load_balancing_service.create_plugin_provider_manager", return_value=provider_manager) + model_assembly = SimpleNamespace(provider_manager=provider_manager, model_provider_factory=MagicMock()) + mocker.patch("services.model_load_balancing_service.create_plugin_model_assembly", return_value=model_assembly) + svc = ModelLoadBalancingService() + svc.provider_manager = provider_manager + svc.model_assembly = model_assembly + svc._get_provider_manager = lambda _tenant_id: provider_manager # type: ignore[method-assign] + return svc + + +@pytest.fixture +def mock_db(mocker: MockerFixture) -> MagicMock: + # Arrange + mocked_db = mocker.patch("services.model_load_balancing_service.db") + mocked_db.session = MagicMock() + return mocked_db + + +@pytest.mark.parametrize( + ("method_name", "expected_provider_method"), + [ + ("enable_model_load_balancing", "enable_model_load_balancing"), + ("disable_model_load_balancing", "disable_model_load_balancing"), + ], +) +def test_enable_disable_model_load_balancing_should_call_provider_configuration_method_when_provider_exists( + method_name: str, + expected_provider_method: str, + service: ModelLoadBalancingService, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + + # Act + getattr(service, method_name)("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value) + + # Assert + getattr(provider_configuration, expected_provider_method).assert_called_once_with( + model="gpt-4o-mini", model_type=ModelType.LLM + ) + + +@pytest.mark.parametrize( + "method_name", + ["enable_model_load_balancing", "disable_model_load_balancing"], +) +def test_enable_disable_model_load_balancing_should_raise_value_error_when_provider_missing( + method_name: str, + service: ModelLoadBalancingService, +) -> None: + # Arrange + service.provider_manager.get_configurations.return_value = {} + + # Act + Assert + with pytest.raises(ValueError, match="Provider openai does not exist"): + getattr(service, method_name)("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value) + + +def test_get_load_balancing_configs_should_raise_value_error_when_provider_missing( + service: ModelLoadBalancingService, +) -> None: + # Arrange + service.provider_manager.get_configurations.return_value = {} + + # Act + Assert + with pytest.raises(ValueError, match="Provider openai does not exist"): + service.get_load_balancing_configs("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value) + + +def test_get_load_balancing_configs_should_insert_inherit_config_when_missing_for_custom_provider( + service: ModelLoadBalancingService, + mock_db: MagicMock, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration( + custom_provider=True, + load_balancing_enabled=True, + provider_schema=_build_provider_credential_schema(), + ) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + config = SimpleNamespace( + id="cfg-1", + name="primary", + encrypted_config=json.dumps({"api_key": "encrypted-key"}), + credential_id="cred-1", + enabled=True, + ) + mock_db.session.query.return_value.where.return_value.order_by.return_value.all.return_value = [config] + mocker.patch( + "services.model_load_balancing_service.encrypter.get_decrypt_decoding", + return_value=("rsa", "cipher"), + ) + mocker.patch( + "services.model_load_balancing_service.encrypter.decrypt_token_with_decoding", + return_value="plain-key", + ) + mocker.patch( + "services.model_load_balancing_service.LBModelManager.get_config_in_cooldown_and_ttl", + return_value=(False, 0), + ) + + # Act + is_enabled, configs = service.get_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + ) + + # Assert + assert is_enabled is True + assert len(configs) == 2 + assert configs[0]["name"] == "__inherit__" + assert configs[1]["name"] == "primary" + assert configs[1]["credentials"] == {"api_key": "plain-key"} + assert mock_db.session.add.call_count == 1 + assert mock_db.session.commit.call_count == 1 + + +def test_get_load_balancing_configs_should_reorder_existing_inherit_and_tolerate_json_or_decrypt_errors( + service: ModelLoadBalancingService, + mock_db: MagicMock, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration( + custom_provider=True, + load_balancing_enabled=None, + provider_schema=_build_provider_credential_schema(), + ) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + normal_config = SimpleNamespace( + id="cfg-1", + name="normal", + encrypted_config=json.dumps({"api_key": "bad-encrypted"}), + credential_id="cred-1", + enabled=True, + ) + inherit_config = SimpleNamespace( + id="cfg-2", + name="__inherit__", + encrypted_config="not-json", + credential_id=None, + enabled=False, + ) + mock_db.session.query.return_value.where.return_value.order_by.return_value.all.return_value = [ + normal_config, + inherit_config, + ] + mocker.patch( + "services.model_load_balancing_service.encrypter.get_decrypt_decoding", + return_value=("rsa", "cipher"), + ) + mocker.patch( + "services.model_load_balancing_service.encrypter.decrypt_token_with_decoding", + side_effect=ValueError("cannot decrypt"), + ) + mocker.patch( + "services.model_load_balancing_service.LBModelManager.get_config_in_cooldown_and_ttl", + return_value=(True, 15), + ) + + # Act + is_enabled, configs = service.get_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + config_from="predefined-model", + ) + + # Assert + assert is_enabled is False + assert configs[0]["name"] == "__inherit__" + assert configs[0]["credentials"] == {} + assert configs[1]["credentials"] == {"api_key": "bad-encrypted"} + assert configs[1]["in_cooldown"] is True + assert configs[1]["ttl"] == 15 + + +def test_get_load_balancing_config_should_raise_value_error_when_provider_missing( + service: ModelLoadBalancingService, +) -> None: + # Arrange + service.provider_manager.get_configurations.return_value = {} + + # Act + Assert + with pytest.raises(ValueError, match="Provider openai does not exist"): + service.get_load_balancing_config("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value, "cfg-1") + + +def test_get_load_balancing_config_should_return_none_when_config_not_found( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.query.return_value.where.return_value.first.return_value = None + + # Act + result = service.get_load_balancing_config("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value, "cfg-1") + + # Assert + assert result is None + + +def test_get_load_balancing_config_should_return_obfuscated_payload_when_config_exists( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + provider_configuration.obfuscated_credentials.side_effect = lambda credentials, credential_form_schemas: { + "masked": credentials.get("api_key", "") + } + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + config = SimpleNamespace(id="cfg-1", name="primary", encrypted_config="not-json", enabled=True) + mock_db.session.query.return_value.where.return_value.first.return_value = config + + # Act + result = service.get_load_balancing_config("tenant-1", "openai", "gpt-4o-mini", ModelType.LLM.value, "cfg-1") + + # Assert + assert result == { + "id": "cfg-1", + "name": "primary", + "credentials": {"masked": ""}, + "enabled": True, + } + + +def test_init_inherit_config_should_create_and_persist_inherit_configuration( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + model_type = ModelType.LLM + + # Act + inherit_config = service._init_inherit_config("tenant-1", "openai", "gpt-4o-mini", model_type) + + # Assert + assert inherit_config.tenant_id == "tenant-1" + assert inherit_config.provider_name == "openai" + assert inherit_config.model_name == "gpt-4o-mini" + assert inherit_config.model_type == "text-generation" + assert inherit_config.name == "__inherit__" + mock_db.session.add.assert_called_once_with(inherit_config) + mock_db.session.commit.assert_called_once() + + +def test_update_load_balancing_configs_should_raise_value_error_when_provider_missing( + service: ModelLoadBalancingService, +) -> None: + # Arrange + service.provider_manager.get_configurations.return_value = {} + + # Act + Assert + with pytest.raises(ValueError, match="Provider openai does not exist"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [], + "custom-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_configs_is_not_list( + service: ModelLoadBalancingService, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing configs"): + service.update_load_balancing_configs( # type: ignore[arg-type] + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + cast(list[dict[str, object]], "invalid-configs"), + "custom-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_config_item_is_not_dict( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.scalars.return_value.all.return_value = [] + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing config"): + service.update_load_balancing_configs( # type: ignore[list-item] + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + cast(list[dict[str, object]], ["bad-item"]), + "custom-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_credential_id_not_found( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.scalars.return_value.all.return_value = [] + mock_db.session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + Assert + with pytest.raises(ValueError, match="Provider credential with id cred-1 not found"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"credential_id": "cred-1", "enabled": True}], + "predefined-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_name_or_enabled_is_invalid( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.scalars.return_value.all.return_value = [] + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing config name"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"enabled": True}], + "custom-model", + ) + + with pytest.raises(ValueError, match="Invalid load balancing config enabled"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"name": "cfg-without-enabled"}], + "custom-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_existing_config_id_is_invalid( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + current_config = SimpleNamespace(id="cfg-1") + mock_db.session.scalars.return_value.all.return_value = [current_config] + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing config id: cfg-2"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"id": "cfg-2", "name": "invalid", "enabled": True}], + "custom-model", + ) + + +def test_update_load_balancing_configs_should_raise_value_error_when_credentials_are_invalid_for_update_or_create( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + existing_config = SimpleNamespace(id="cfg-1", name="old", enabled=True, encrypted_config=None, updated_at=None) + mock_db.session.scalars.return_value.all.return_value = [existing_config] + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing config credentials"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"id": "cfg-1", "name": "new", "enabled": True, "credentials": "bad"}], + "custom-model", + ) + + with pytest.raises(ValueError, match="Invalid load balancing config credentials"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"name": "new-config", "enabled": True, "credentials": "bad"}], + "custom-model", + ) + + +def test_update_load_balancing_configs_should_update_existing_create_new_and_delete_removed_configs( + service: ModelLoadBalancingService, + mock_db: MagicMock, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + existing_config_1 = SimpleNamespace( + id="cfg-1", + name="existing-one", + enabled=True, + encrypted_config=json.dumps({"api_key": "old"}), + updated_at=None, + ) + existing_config_2 = SimpleNamespace( + id="cfg-2", + name="existing-two", + enabled=True, + encrypted_config=None, + updated_at=None, + ) + mock_db.session.scalars.return_value.all.return_value = [existing_config_1, existing_config_2] + mocker.patch.object(service, "_custom_credentials_validate", return_value={"api_key": "encrypted"}) + mock_clear_cache = mocker.patch.object(service, "_clear_credentials_cache") + + # Act + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [ + {"id": "cfg-1", "name": "updated-name", "enabled": False, "credentials": {"api_key": "plain"}}, + {"name": "new-config", "enabled": True, "credentials": {"api_key": "plain"}}, + ], + "custom-model", + ) + + # Assert + assert existing_config_1.name == "updated-name" + assert existing_config_1.enabled is False + assert json.loads(existing_config_1.encrypted_config) == {"api_key": "encrypted"} + assert mock_db.session.add.call_count == 1 + mock_db.session.delete.assert_called_once_with(existing_config_2) + assert mock_db.session.commit.call_count >= 3 + mock_clear_cache.assert_any_call("tenant-1", "cfg-1") + mock_clear_cache.assert_any_call("tenant-1", "cfg-2") + + +def test_update_load_balancing_configs_should_raise_value_error_for_invalid_new_config_name_or_missing_credentials( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.scalars.return_value.all.return_value = [] + + # Act + Assert + with pytest.raises(ValueError, match="Invalid load balancing config name"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"name": "__inherit__", "enabled": True, "credentials": {"api_key": "x"}}], + "custom-model", + ) + + with pytest.raises(ValueError, match="Invalid load balancing config credentials"): + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"name": "new", "enabled": True}], + "custom-model", + ) + + +def test_update_load_balancing_configs_should_create_from_existing_provider_credential_when_credential_id_provided( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.scalars.return_value.all.return_value = [] + credential_record = SimpleNamespace(credential_name="Main Credential", encrypted_config='{"api_key":"enc"}') + mock_db.session.query.return_value.filter_by.return_value.first.return_value = credential_record + + # Act + service.update_load_balancing_configs( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + [{"credential_id": "cred-1", "enabled": True}], + "predefined-model", + ) + + # Assert + created_config = mock_db.session.add.call_args.args[0] + assert created_config.name == "Main Credential" + assert created_config.credential_id == "cred-1" + assert created_config.credential_source_type == "provider" + assert created_config.encrypted_config == '{"api_key":"enc"}' + mock_db.session.commit.assert_called() + + +def test_validate_load_balancing_credentials_should_raise_value_error_when_provider_missing( + service: ModelLoadBalancingService, +) -> None: + # Arrange + service.provider_manager.get_configurations.return_value = {} + + # Act + Assert + with pytest.raises(ValueError, match="Provider openai does not exist"): + service.validate_load_balancing_credentials( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + {"api_key": "plain"}, + ) + + +def test_validate_load_balancing_credentials_should_raise_value_error_when_config_id_is_invalid( + service: ModelLoadBalancingService, + mock_db: MagicMock, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + mock_db.session.query.return_value.where.return_value.first.return_value = None + + # Act + Assert + with pytest.raises(ValueError, match="Load balancing config cfg-1 does not exist"): + service.validate_load_balancing_credentials( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + {"api_key": "plain"}, + config_id="cfg-1", + ) + + +def test_validate_load_balancing_credentials_should_delegate_to_custom_validate_with_or_without_config( + service: ModelLoadBalancingService, + mock_db: MagicMock, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + service.provider_manager.get_configurations.return_value = {"openai": provider_configuration} + existing_config = SimpleNamespace(id="cfg-1") + mock_db.session.query.return_value.where.return_value.first.return_value = existing_config + mock_validate = mocker.patch.object(service, "_custom_credentials_validate") + + # Act + service.validate_load_balancing_credentials( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + {"api_key": "plain"}, + config_id="cfg-1", + ) + service.validate_load_balancing_credentials( + "tenant-1", + "openai", + "gpt-4o-mini", + ModelType.LLM.value, + {"api_key": "plain"}, + ) + + # Assert + assert mock_validate.call_count == 2 + assert mock_validate.call_args_list[0].kwargs["load_balancing_model_config"] is existing_config + assert mock_validate.call_args_list[1].kwargs["load_balancing_model_config"] is None + shared_model_provider_factory = service.model_assembly.model_provider_factory + assert mock_validate.call_args_list[0].kwargs["model_provider_factory"] is shared_model_provider_factory + assert mock_validate.call_args_list[1].kwargs["model_provider_factory"] is shared_model_provider_factory + + +def test_custom_credentials_validate_should_replace_hidden_secret_with_original_value_and_encrypt( + service: ModelLoadBalancingService, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + load_balancing_model_config = _load_balancing_model_config( + encrypted_config=json.dumps({"api_key": "old-encrypted-token"}) + ) + mocker.patch("services.model_load_balancing_service.encrypter.decrypt_token", return_value="old-plain-value") + mock_encrypt = mocker.patch( + "services.model_load_balancing_service.encrypter.encrypt_token", + side_effect=lambda tenant_id, value: f"enc:{value}", + ) + + # Act + result = service._custom_credentials_validate( + tenant_id="tenant-1", + provider_configuration=provider_configuration, + model_type=ModelType.LLM, + model="gpt-4o-mini", + credentials={"api_key": HIDDEN_VALUE, "region": "us"}, + load_balancing_model_config=load_balancing_model_config, + validate=False, + ) + + # Assert + assert result == {"api_key": "enc:old-plain-value", "region": "us"} + mock_encrypt.assert_called_once_with("tenant-1", "old-plain-value") + + +def test_custom_credentials_validate_should_handle_invalid_original_json_and_validate_with_model_schema( + service: ModelLoadBalancingService, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(model_schema=_build_model_credential_schema()) + load_balancing_model_config = _load_balancing_model_config(encrypted_config="not-json") + mock_factory = MagicMock() + mock_factory.model_credentials_validate.return_value = {"api_key": "validated"} + mock_encrypt = mocker.patch( + "services.model_load_balancing_service.encrypter.encrypt_token", + side_effect=lambda tenant_id, value: f"enc:{value}", + ) + + # Act + result = service._custom_credentials_validate( + tenant_id="tenant-1", + provider_configuration=provider_configuration, + model_type=ModelType.LLM, + model="gpt-4o-mini", + credentials={"api_key": "plain"}, + load_balancing_model_config=load_balancing_model_config, + model_provider_factory=mock_factory, + validate=True, + ) + + # Assert + assert result == {"api_key": "enc:validated"} + mock_factory.model_credentials_validate.assert_called_once() + mock_factory.provider_credentials_validate.assert_not_called() + mock_encrypt.assert_called_once_with("tenant-1", "validated") + + +def test_custom_credentials_validate_should_validate_with_provider_schema_when_model_schema_absent( + service: ModelLoadBalancingService, + mocker: MockerFixture, +) -> None: + # Arrange + provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema()) + mock_factory = MagicMock() + mock_factory.provider_credentials_validate.return_value = {"api_key": "provider-validated"} + mocker.patch( + "services.model_load_balancing_service.encrypter.encrypt_token", + side_effect=lambda tenant_id, value: f"enc:{value}", + ) + + # Act + result = service._custom_credentials_validate( + tenant_id="tenant-1", + provider_configuration=provider_configuration, + model_type=ModelType.LLM, + model="gpt-4o-mini", + credentials={"api_key": "plain"}, + model_provider_factory=mock_factory, + validate=True, + ) + + # Assert + assert result == {"api_key": "enc:provider-validated"} + mock_factory.provider_credentials_validate.assert_called_once() + mock_factory.model_credentials_validate.assert_not_called() + + +def test_get_credential_schema_should_return_model_schema_or_provider_schema_or_raise( + service: ModelLoadBalancingService, +) -> None: + # Arrange + model_schema = _build_model_credential_schema() + provider_schema = _build_provider_credential_schema() + provider_configuration_with_model = _build_provider_configuration(model_schema=model_schema) + provider_configuration_with_provider = _build_provider_configuration(provider_schema=provider_schema) + provider_configuration_without_schema = _build_provider_configuration() + + # Act + schema_from_model = service._get_credential_schema(provider_configuration_with_model) + schema_from_provider = service._get_credential_schema(provider_configuration_with_provider) + + # Assert + assert schema_from_model is model_schema + assert schema_from_provider is provider_schema + with pytest.raises(ValueError, match="No credential schema found"): + service._get_credential_schema(provider_configuration_without_schema) + + +def test_clear_credentials_cache_should_delete_load_balancing_cache_entry( + service: ModelLoadBalancingService, + mocker: MockerFixture, +) -> None: + # Arrange + mock_cache_instance = MagicMock() + mock_cache_cls = mocker.patch( + "services.model_load_balancing_service.ProviderCredentialsCache", + return_value=mock_cache_instance, + ) + + # Act + service._clear_credentials_cache("tenant-1", "cfg-1") + + # Assert + mock_cache_cls.assert_called_once() + assert mock_cache_cls.call_args.kwargs == { + "tenant_id": "tenant-1", + "identity_id": "cfg-1", + "cache_type": mocker.ANY, + } + assert mock_cache_cls.call_args.kwargs["cache_type"].name == "LOAD_BALANCING_MODEL" + mock_cache_instance.delete.assert_called_once() diff --git a/api/tests/unit_tests/services/test_model_provider_service_sanitization.py b/api/tests/unit_tests/services/test_model_provider_service_sanitization.py index 6a6b63f0037..1bd979b9ec2 100644 --- a/api/tests/unit_tests/services/test_model_provider_service_sanitization.py +++ b/api/tests/unit_tests/services/test_model_provider_service_sanitization.py @@ -1,11 +1,11 @@ import types import pytest +from graphon.model_runtime.entities.common_entities import I18nObject +from graphon.model_runtime.entities.model_entities import ModelType +from graphon.model_runtime.entities.provider_entities import ConfigurateMethod from core.entities.provider_entities import CredentialConfiguration, CustomModelConfiguration -from dify_graph.model_runtime.entities.common_entities import I18nObject -from dify_graph.model_runtime.entities.model_entities import ModelType -from dify_graph.model_runtime.entities.provider_entities import ConfigurateMethod from models.provider import ProviderType from services.model_provider_service import ModelProviderService @@ -71,7 +71,7 @@ def service_with_fake_configurations(): return _FakeConfigurations(fake_provider_configuration) svc = ModelProviderService() - svc.provider_manager = _FakeProviderManager() + svc._get_provider_manager = lambda tenant_id: _FakeProviderManager() return svc diff --git a/api/tests/unit_tests/services/test_restore_archived_workflow_run.py b/api/tests/unit_tests/services/test_restore_archived_workflow_run.py deleted file mode 100644 index a214ecf7284..00000000000 --- a/api/tests/unit_tests/services/test_restore_archived_workflow_run.py +++ /dev/null @@ -1,37 +0,0 @@ -""" -Unit tests for workflow run restore functionality. -""" - -from datetime import datetime - - -class TestWorkflowRunRestore: - """Tests for the WorkflowRunRestore class.""" - - def test_restore_initialization(self): - """Restore service should respect dry_run flag.""" - from services.retention.workflow_run.restore_archived_workflow_run import WorkflowRunRestore - - restore = WorkflowRunRestore(dry_run=True) - - assert restore.dry_run is True - - def test_convert_datetime_fields(self): - """ISO datetime strings should be converted to datetime objects.""" - from models.workflow import WorkflowRun - from services.retention.workflow_run.restore_archived_workflow_run import WorkflowRunRestore - - record = { - "id": "test-id", - "created_at": "2024-01-01T12:00:00", - "finished_at": "2024-01-01T12:05:00", - "name": "test", - } - - restore = WorkflowRunRestore() - result = restore._convert_datetime_fields(record, WorkflowRun) - - assert isinstance(result["created_at"], datetime) - assert result["created_at"].year == 2024 - assert result["created_at"].month == 1 - assert result["name"] == "test" diff --git a/api/tests/unit_tests/services/test_saved_message_service.py b/api/tests/unit_tests/services/test_saved_message_service.py deleted file mode 100644 index 87b946fe461..00000000000 --- a/api/tests/unit_tests/services/test_saved_message_service.py +++ /dev/null @@ -1,626 +0,0 @@ -""" -Comprehensive unit tests for SavedMessageService. - -This test suite provides complete coverage of saved message operations in Dify, -following TDD principles with the Arrange-Act-Assert pattern. - -## Test Coverage - -### 1. Pagination (TestSavedMessageServicePagination) -Tests saved message listing and pagination: -- Pagination with valid user (Account and EndUser) -- Pagination without user raises ValueError -- Pagination with last_id parameter -- Empty results when no saved messages exist -- Integration with MessageService pagination - -### 2. Save Operations (TestSavedMessageServiceSave) -Tests saving messages: -- Save message for Account user -- Save message for EndUser -- Save without user (no-op) -- Prevent duplicate saves (idempotent) -- Message validation through MessageService - -### 3. Delete Operations (TestSavedMessageServiceDelete) -Tests deleting saved messages: -- Delete saved message for Account user -- Delete saved message for EndUser -- Delete without user (no-op) -- Delete non-existent saved message (no-op) -- Proper database cleanup - -## Testing Approach - -- **Mocking Strategy**: All external dependencies (database, MessageService) are mocked - for fast, isolated unit tests -- **Factory Pattern**: SavedMessageServiceTestDataFactory provides consistent test data -- **Fixtures**: Mock objects are configured per test method -- **Assertions**: Each test verifies return values and side effects - (database operations, method calls) - -## Key Concepts - -**User Types:** -- Account: Workspace members (console users) -- EndUser: API users (end users) - -**Saved Messages:** -- Users can save messages for later reference -- Each user has their own saved message list -- Saving is idempotent (duplicate saves ignored) -- Deletion is safe (non-existent deletes ignored) -""" - -from datetime import UTC, datetime -from unittest.mock import MagicMock, Mock, create_autospec, patch - -import pytest - -from libs.infinite_scroll_pagination import InfiniteScrollPagination -from models import Account -from models.model import App, EndUser, Message -from models.web import SavedMessage -from services.saved_message_service import SavedMessageService - - -class SavedMessageServiceTestDataFactory: - """ - Factory for creating test data and mock objects. - - Provides reusable methods to create consistent mock objects for testing - saved message operations. - """ - - @staticmethod - def create_account_mock(account_id: str = "account-123", **kwargs) -> Mock: - """ - Create a mock Account object. - - Args: - account_id: Unique identifier for the account - **kwargs: Additional attributes to set on the mock - - Returns: - Mock Account object with specified attributes - """ - account = create_autospec(Account, instance=True) - account.id = account_id - for key, value in kwargs.items(): - setattr(account, key, value) - return account - - @staticmethod - def create_end_user_mock(user_id: str = "user-123", **kwargs) -> Mock: - """ - Create a mock EndUser object. - - Args: - user_id: Unique identifier for the end user - **kwargs: Additional attributes to set on the mock - - Returns: - Mock EndUser object with specified attributes - """ - user = create_autospec(EndUser, instance=True) - user.id = user_id - for key, value in kwargs.items(): - setattr(user, key, value) - return user - - @staticmethod - def create_app_mock(app_id: str = "app-123", tenant_id: str = "tenant-123", **kwargs) -> Mock: - """ - Create a mock App object. - - Args: - app_id: Unique identifier for the app - tenant_id: Tenant/workspace identifier - **kwargs: Additional attributes to set on the mock - - Returns: - Mock App object with specified attributes - """ - app = create_autospec(App, instance=True) - app.id = app_id - app.tenant_id = tenant_id - app.name = kwargs.get("name", "Test App") - app.mode = kwargs.get("mode", "chat") - for key, value in kwargs.items(): - setattr(app, key, value) - return app - - @staticmethod - def create_message_mock( - message_id: str = "msg-123", - app_id: str = "app-123", - **kwargs, - ) -> Mock: - """ - Create a mock Message object. - - Args: - message_id: Unique identifier for the message - app_id: Associated app identifier - **kwargs: Additional attributes to set on the mock - - Returns: - Mock Message object with specified attributes - """ - message = create_autospec(Message, instance=True) - message.id = message_id - message.app_id = app_id - message.query = kwargs.get("query", "Test query") - message.answer = kwargs.get("answer", "Test answer") - message.created_at = kwargs.get("created_at", datetime.now(UTC)) - for key, value in kwargs.items(): - setattr(message, key, value) - return message - - @staticmethod - def create_saved_message_mock( - saved_message_id: str = "saved-123", - app_id: str = "app-123", - message_id: str = "msg-123", - created_by: str = "user-123", - created_by_role: str = "account", - **kwargs, - ) -> Mock: - """ - Create a mock SavedMessage object. - - Args: - saved_message_id: Unique identifier for the saved message - app_id: Associated app identifier - message_id: Associated message identifier - created_by: User who saved the message - created_by_role: Role of the user ('account' or 'end_user') - **kwargs: Additional attributes to set on the mock - - Returns: - Mock SavedMessage object with specified attributes - """ - saved_message = create_autospec(SavedMessage, instance=True) - saved_message.id = saved_message_id - saved_message.app_id = app_id - saved_message.message_id = message_id - saved_message.created_by = created_by - saved_message.created_by_role = created_by_role - saved_message.created_at = kwargs.get("created_at", datetime.now(UTC)) - for key, value in kwargs.items(): - setattr(saved_message, key, value) - return saved_message - - -@pytest.fixture -def factory(): - """Provide the test data factory to all tests.""" - return SavedMessageServiceTestDataFactory - - -class TestSavedMessageServicePagination: - """Test saved message pagination operations.""" - - @patch("services.saved_message_service.MessageService.pagination_by_last_id", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_pagination_with_account_user(self, mock_db_session, mock_message_pagination, factory): - """Test pagination with an Account user.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - - # Create saved messages for this user - saved_messages = [ - factory.create_saved_message_mock( - saved_message_id=f"saved-{i}", - app_id=app.id, - message_id=f"msg-{i}", - created_by=user.id, - created_by_role="account", - ) - for i in range(3) - ] - - # Mock database query - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.order_by.return_value = mock_query - mock_query.all.return_value = saved_messages - - # Mock MessageService pagination response - expected_pagination = InfiniteScrollPagination(data=[], limit=20, has_more=False) - mock_message_pagination.return_value = expected_pagination - - # Act - result = SavedMessageService.pagination_by_last_id(app_model=app, user=user, last_id=None, limit=20) - - # Assert - assert result == expected_pagination - mock_db_session.query.assert_called_once_with(SavedMessage) - # Verify MessageService was called with correct message IDs - mock_message_pagination.assert_called_once_with( - app_model=app, - user=user, - last_id=None, - limit=20, - include_ids=["msg-0", "msg-1", "msg-2"], - ) - - @patch("services.saved_message_service.MessageService.pagination_by_last_id", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_pagination_with_end_user(self, mock_db_session, mock_message_pagination, factory): - """Test pagination with an EndUser.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_end_user_mock() - - # Create saved messages for this end user - saved_messages = [ - factory.create_saved_message_mock( - saved_message_id=f"saved-{i}", - app_id=app.id, - message_id=f"msg-{i}", - created_by=user.id, - created_by_role="end_user", - ) - for i in range(2) - ] - - # Mock database query - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.order_by.return_value = mock_query - mock_query.all.return_value = saved_messages - - # Mock MessageService pagination response - expected_pagination = InfiniteScrollPagination(data=[], limit=10, has_more=False) - mock_message_pagination.return_value = expected_pagination - - # Act - result = SavedMessageService.pagination_by_last_id(app_model=app, user=user, last_id=None, limit=10) - - # Assert - assert result == expected_pagination - # Verify correct role was used in query - mock_message_pagination.assert_called_once_with( - app_model=app, - user=user, - last_id=None, - limit=10, - include_ids=["msg-0", "msg-1"], - ) - - def test_pagination_without_user_raises_error(self, factory): - """Test that pagination without user raises ValueError.""" - # Arrange - app = factory.create_app_mock() - - # Act & Assert - with pytest.raises(ValueError, match="User is required"): - SavedMessageService.pagination_by_last_id(app_model=app, user=None, last_id=None, limit=20) - - @patch("services.saved_message_service.MessageService.pagination_by_last_id", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_pagination_with_last_id(self, mock_db_session, mock_message_pagination, factory): - """Test pagination with last_id parameter.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - last_id = "msg-last" - - saved_messages = [ - factory.create_saved_message_mock( - message_id=f"msg-{i}", - app_id=app.id, - created_by=user.id, - ) - for i in range(5) - ] - - # Mock database query - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.order_by.return_value = mock_query - mock_query.all.return_value = saved_messages - - # Mock MessageService pagination response - expected_pagination = InfiniteScrollPagination(data=[], limit=10, has_more=True) - mock_message_pagination.return_value = expected_pagination - - # Act - result = SavedMessageService.pagination_by_last_id(app_model=app, user=user, last_id=last_id, limit=10) - - # Assert - assert result == expected_pagination - # Verify last_id was passed to MessageService - mock_message_pagination.assert_called_once() - call_args = mock_message_pagination.call_args - assert call_args.kwargs["last_id"] == last_id - - @patch("services.saved_message_service.MessageService.pagination_by_last_id", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_pagination_with_empty_saved_messages(self, mock_db_session, mock_message_pagination, factory): - """Test pagination when user has no saved messages.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - - # Mock database query returning empty list - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.order_by.return_value = mock_query - mock_query.all.return_value = [] - - # Mock MessageService pagination response - expected_pagination = InfiniteScrollPagination(data=[], limit=20, has_more=False) - mock_message_pagination.return_value = expected_pagination - - # Act - result = SavedMessageService.pagination_by_last_id(app_model=app, user=user, last_id=None, limit=20) - - # Assert - assert result == expected_pagination - # Verify MessageService was called with empty include_ids - mock_message_pagination.assert_called_once_with( - app_model=app, - user=user, - last_id=None, - limit=20, - include_ids=[], - ) - - -class TestSavedMessageServiceSave: - """Test save message operations.""" - - @patch("services.saved_message_service.MessageService.get_message", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_save_message_for_account(self, mock_db_session, mock_get_message, factory): - """Test saving a message for an Account user.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - message = factory.create_message_mock(message_id="msg-123", app_id=app.id) - - # Mock database query - no existing saved message - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Mock MessageService.get_message - mock_get_message.return_value = message - - # Act - SavedMessageService.save(app_model=app, user=user, message_id=message.id) - - # Assert - mock_db_session.add.assert_called_once() - saved_message = mock_db_session.add.call_args[0][0] - assert saved_message.app_id == app.id - assert saved_message.message_id == message.id - assert saved_message.created_by == user.id - assert saved_message.created_by_role == "account" - mock_db_session.commit.assert_called_once() - - @patch("services.saved_message_service.MessageService.get_message", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_save_message_for_end_user(self, mock_db_session, mock_get_message, factory): - """Test saving a message for an EndUser.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_end_user_mock() - message = factory.create_message_mock(message_id="msg-456", app_id=app.id) - - # Mock database query - no existing saved message - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Mock MessageService.get_message - mock_get_message.return_value = message - - # Act - SavedMessageService.save(app_model=app, user=user, message_id=message.id) - - # Assert - mock_db_session.add.assert_called_once() - saved_message = mock_db_session.add.call_args[0][0] - assert saved_message.app_id == app.id - assert saved_message.message_id == message.id - assert saved_message.created_by == user.id - assert saved_message.created_by_role == "end_user" - mock_db_session.commit.assert_called_once() - - @patch("services.saved_message_service.db.session", autospec=True) - def test_save_without_user_does_nothing(self, mock_db_session, factory): - """Test that saving without user is a no-op.""" - # Arrange - app = factory.create_app_mock() - - # Act - SavedMessageService.save(app_model=app, user=None, message_id="msg-123") - - # Assert - mock_db_session.query.assert_not_called() - mock_db_session.add.assert_not_called() - mock_db_session.commit.assert_not_called() - - @patch("services.saved_message_service.MessageService.get_message", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_save_duplicate_message_is_idempotent(self, mock_db_session, mock_get_message, factory): - """Test that saving an already saved message is idempotent.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - message_id = "msg-789" - - # Mock database query - existing saved message found - existing_saved = factory.create_saved_message_mock( - app_id=app.id, - message_id=message_id, - created_by=user.id, - created_by_role="account", - ) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = existing_saved - - # Act - SavedMessageService.save(app_model=app, user=user, message_id=message_id) - - # Assert - no new saved message created - mock_db_session.add.assert_not_called() - mock_db_session.commit.assert_not_called() - mock_get_message.assert_not_called() - - @patch("services.saved_message_service.MessageService.get_message", autospec=True) - @patch("services.saved_message_service.db.session", autospec=True) - def test_save_validates_message_exists(self, mock_db_session, mock_get_message, factory): - """Test that save validates message exists through MessageService.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - message = factory.create_message_mock() - - # Mock database query - no existing saved message - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Mock MessageService.get_message - mock_get_message.return_value = message - - # Act - SavedMessageService.save(app_model=app, user=user, message_id=message.id) - - # Assert - MessageService.get_message was called for validation - mock_get_message.assert_called_once_with(app_model=app, user=user, message_id=message.id) - - -class TestSavedMessageServiceDelete: - """Test delete saved message operations.""" - - @patch("services.saved_message_service.db.session", autospec=True) - def test_delete_saved_message_for_account(self, mock_db_session, factory): - """Test deleting a saved message for an Account user.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - message_id = "msg-123" - - # Mock database query - existing saved message found - saved_message = factory.create_saved_message_mock( - app_id=app.id, - message_id=message_id, - created_by=user.id, - created_by_role="account", - ) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = saved_message - - # Act - SavedMessageService.delete(app_model=app, user=user, message_id=message_id) - - # Assert - mock_db_session.delete.assert_called_once_with(saved_message) - mock_db_session.commit.assert_called_once() - - @patch("services.saved_message_service.db.session", autospec=True) - def test_delete_saved_message_for_end_user(self, mock_db_session, factory): - """Test deleting a saved message for an EndUser.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_end_user_mock() - message_id = "msg-456" - - # Mock database query - existing saved message found - saved_message = factory.create_saved_message_mock( - app_id=app.id, - message_id=message_id, - created_by=user.id, - created_by_role="end_user", - ) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = saved_message - - # Act - SavedMessageService.delete(app_model=app, user=user, message_id=message_id) - - # Assert - mock_db_session.delete.assert_called_once_with(saved_message) - mock_db_session.commit.assert_called_once() - - @patch("services.saved_message_service.db.session", autospec=True) - def test_delete_without_user_does_nothing(self, mock_db_session, factory): - """Test that deleting without user is a no-op.""" - # Arrange - app = factory.create_app_mock() - - # Act - SavedMessageService.delete(app_model=app, user=None, message_id="msg-123") - - # Assert - mock_db_session.query.assert_not_called() - mock_db_session.delete.assert_not_called() - mock_db_session.commit.assert_not_called() - - @patch("services.saved_message_service.db.session", autospec=True) - def test_delete_non_existent_saved_message_does_nothing(self, mock_db_session, factory): - """Test that deleting a non-existent saved message is a no-op.""" - # Arrange - app = factory.create_app_mock() - user = factory.create_account_mock() - message_id = "msg-nonexistent" - - # Mock database query - no saved message found - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Act - SavedMessageService.delete(app_model=app, user=user, message_id=message_id) - - # Assert - no deletion occurred - mock_db_session.delete.assert_not_called() - mock_db_session.commit.assert_not_called() - - @patch("services.saved_message_service.db.session", autospec=True) - def test_delete_only_affects_user_own_saved_messages(self, mock_db_session, factory): - """Test that delete only removes the user's own saved message.""" - # Arrange - app = factory.create_app_mock() - user1 = factory.create_account_mock(account_id="user-1") - message_id = "msg-shared" - - # Mock database query - finds user1's saved message - saved_message = factory.create_saved_message_mock( - app_id=app.id, - message_id=message_id, - created_by=user1.id, - created_by_role="account", - ) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = saved_message - - # Act - SavedMessageService.delete(app_model=app, user=user1, message_id=message_id) - - # Assert - only user1's saved message is deleted - mock_db_session.delete.assert_called_once_with(saved_message) - # Verify the query filters by user - assert mock_query.where.called diff --git a/api/tests/unit_tests/services/test_summary_index_service.py b/api/tests/unit_tests/services/test_summary_index_service.py index be64e431ba7..cbf3e121d8c 100644 --- a/api/tests/unit_tests/services/test_summary_index_service.py +++ b/api/tests/unit_tests/services/test_summary_index_service.py @@ -11,6 +11,7 @@ from unittest.mock import MagicMock import pytest import services.summary_index_service as summary_module +from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType from models.enums import SegmentStatus, SummaryStatus from services.summary_index_service import SummaryIndexService @@ -26,7 +27,7 @@ class _SessionContext: return None -def _dataset(*, indexing_technique: str = "high_quality") -> MagicMock: +def _dataset(*, indexing_technique: str = IndexTechniqueType.HIGH_QUALITY) -> MagicMock: dataset = MagicMock(name="dataset") dataset.id = "dataset-1" dataset.tenant_id = "tenant-1" @@ -48,7 +49,7 @@ def _segment(*, has_document: bool = True) -> MagicMock: if has_document: doc = MagicMock(name="document") doc.doc_language = "en" - doc.doc_form = "text_model" + doc.doc_form = IndexStructureType.PARAGRAPH_INDEX segment.document = doc else: segment.document = None @@ -168,7 +169,8 @@ def test_create_summary_record_creates_new(monkeypatch: pytest.MonkeyPatch) -> N def test_vectorize_summary_skips_non_high_quality(monkeypatch: pytest.MonkeyPatch) -> None: vector_cls = MagicMock() monkeypatch.setattr(summary_module, "Vector", vector_cls) - SummaryIndexService.vectorize_summary(_summary_record(), _segment(), _dataset(indexing_technique="economy")) + dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY) + SummaryIndexService.vectorize_summary(_summary_record(), _segment(), dataset) vector_cls.assert_not_called() @@ -189,7 +191,7 @@ def test_vectorize_summary_retries_connection_errors_then_succeeds(monkeypatch: embedding_model.get_text_embedding_num_tokens.return_value = [5] model_manager = MagicMock() model_manager.get_model_instance.return_value = embedding_model - monkeypatch.setattr(summary_module, "ModelManager", MagicMock(return_value=model_manager)) + monkeypatch.setattr(summary_module.ModelManager, "for_tenant", MagicMock(return_value=model_manager)) vector_instance = MagicMock() vector_instance.add_texts.side_effect = [RuntimeError("connection timeout"), None] @@ -228,7 +230,7 @@ def test_vectorize_summary_without_session_creates_record_when_missing(monkeypat model_manager = MagicMock() model_manager.get_model_instance.side_effect = RuntimeError("no model") - monkeypatch.setattr(summary_module, "ModelManager", MagicMock(return_value=model_manager)) + monkeypatch.setattr(summary_module.ModelManager, "for_tenant", MagicMock(return_value=model_manager)) # New session used after vectorization succeeds (record not found by id nor chunk_id). session = MagicMock(name="session") @@ -405,8 +407,8 @@ def test_vectorize_summary_updates_existing_record_found_by_chunk_id(monkeypatch vector_instance.add_texts.return_value = None monkeypatch.setattr(summary_module, "Vector", MagicMock(return_value=vector_instance)) monkeypatch.setattr( - summary_module, - "ModelManager", + summary_module.ModelManager, + "for_tenant", MagicMock(return_value=MagicMock(get_model_instance=MagicMock(return_value=None))), ) @@ -439,8 +441,8 @@ def test_vectorize_summary_updates_existing_record_found_by_id(monkeypatch: pyte summary_module, "Vector", MagicMock(return_value=MagicMock(add_texts=MagicMock(return_value=None))) ) monkeypatch.setattr( - summary_module, - "ModelManager", + summary_module.ModelManager, + "for_tenant", MagicMock(return_value=MagicMock(get_model_instance=MagicMock(return_value=None))), ) @@ -472,8 +474,8 @@ def test_vectorize_summary_session_enter_returns_none_triggers_runtime_error(mon summary_module, "Vector", MagicMock(return_value=MagicMock(add_texts=MagicMock(return_value=None))) ) monkeypatch.setattr( - summary_module, - "ModelManager", + summary_module.ModelManager, + "for_tenant", MagicMock(return_value=MagicMock(get_model_instance=MagicMock(return_value=None))), ) @@ -508,8 +510,8 @@ def test_vectorize_summary_created_record_becomes_none_triggers_guard(monkeypatc summary_module, "Vector", MagicMock(return_value=MagicMock(add_texts=MagicMock(return_value=None))) ) monkeypatch.setattr( - summary_module, - "ModelManager", + summary_module.ModelManager, + "for_tenant", MagicMock(return_value=MagicMock(get_model_instance=MagicMock(return_value=None))), ) @@ -620,16 +622,16 @@ def test_generate_and_vectorize_summary_creates_missing_record_and_logs_usage(mo def test_generate_summaries_for_document_skip_conditions(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _dataset(indexing_technique="economy") + dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY) document = MagicMock(spec=summary_module.DatasetDocument) document.id = "doc-1" - document.doc_form = "text_model" + document.doc_form = IndexStructureType.PARAGRAPH_INDEX assert SummaryIndexService.generate_summaries_for_document(dataset, document, {"enable": True}) == [] dataset = _dataset() assert SummaryIndexService.generate_summaries_for_document(dataset, document, {"enable": False}) == [] - document.doc_form = "qa_model" + document.doc_form = IndexStructureType.QA_INDEX assert SummaryIndexService.generate_summaries_for_document(dataset, document, {"enable": True}) == [] @@ -637,7 +639,7 @@ def test_generate_summaries_for_document_runs_and_handles_errors(monkeypatch: py dataset = _dataset() document = MagicMock(spec=summary_module.DatasetDocument) document.id = "doc-1" - document.doc_form = "text_model" + document.doc_form = IndexStructureType.PARAGRAPH_INDEX seg1 = _segment() seg2 = _segment() @@ -673,7 +675,7 @@ def test_generate_summaries_for_document_no_segments_returns_empty(monkeypatch: dataset = _dataset() document = MagicMock(spec=summary_module.DatasetDocument) document.id = "doc-1" - document.doc_form = "text_model" + document.doc_form = IndexStructureType.PARAGRAPH_INDEX session = MagicMock() query = MagicMock() @@ -696,7 +698,7 @@ def test_generate_summaries_for_document_applies_segment_ids_and_only_parent_chu dataset = _dataset() document = MagicMock(spec=summary_module.DatasetDocument) document.id = "doc-1" - document.doc_form = "text_model" + document.doc_form = IndexStructureType.PARAGRAPH_INDEX seg = _segment() session = MagicMock() @@ -777,7 +779,7 @@ def test_disable_summaries_for_segments_no_summaries_noop(monkeypatch: pytest.Mo def test_enable_summaries_for_segments_skips_non_high_quality() -> None: - SummaryIndexService.enable_summaries_for_segments(_dataset(indexing_technique="economy")) + SummaryIndexService.enable_summaries_for_segments(_dataset(indexing_technique=IndexTechniqueType.ECONOMY)) def test_enable_summaries_for_segments_revectorizes_and_enables(monkeypatch: pytest.MonkeyPatch) -> None: @@ -931,11 +933,10 @@ def test_delete_summaries_for_segments_no_summaries_noop(monkeypatch: pytest.Mon def test_update_summary_for_segment_skip_conditions() -> None: - assert ( - SummaryIndexService.update_summary_for_segment(_segment(), _dataset(indexing_technique="economy"), "x") is None - ) + economy_dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY) + assert SummaryIndexService.update_summary_for_segment(_segment(), economy_dataset, "x") is None seg = _segment(has_document=True) - seg.document.doc_form = "qa_model" + seg.document.doc_form = IndexStructureType.QA_INDEX assert SummaryIndexService.update_summary_for_segment(seg, _dataset(), "x") is None diff --git a/api/tests/unit_tests/services/test_tag_service.py b/api/tests/unit_tests/services/test_tag_service.py deleted file mode 100644 index 264eac4d77f..00000000000 --- a/api/tests/unit_tests/services/test_tag_service.py +++ /dev/null @@ -1,1335 +0,0 @@ -""" -Comprehensive unit tests for TagService. - -This test suite provides complete coverage of tag management operations in Dify, -following TDD principles with the Arrange-Act-Assert pattern. - -The TagService is responsible for managing tags that can be associated with -datasets (knowledge bases) and applications. Tags enable users to organize, -categorize, and filter their content effectively. - -## Test Coverage - -### 1. Tag Retrieval (TestTagServiceRetrieval) -Tests tag listing and filtering: -- Get tags with binding counts -- Filter tags by keyword (case-insensitive) -- Get tags by target ID (apps/datasets) -- Get tags by tag name -- Get target IDs by tag IDs -- Empty results handling - -### 2. Tag CRUD Operations (TestTagServiceCRUD) -Tests tag creation, update, and deletion: -- Create new tags -- Prevent duplicate tag names -- Update tag names -- Update with duplicate name validation -- Delete tags and cascade delete bindings -- Get tag binding counts -- NotFound error handling - -### 3. Tag Binding Operations (TestTagServiceBindings) -Tests tag-to-resource associations: -- Save tag bindings (apps/datasets) -- Prevent duplicate bindings (idempotent) -- Delete tag bindings -- Check target exists validation -- Batch binding operations - -## Testing Approach - -- **Mocking Strategy**: All external dependencies (database, current_user) are mocked - for fast, isolated unit tests -- **Factory Pattern**: TagServiceTestDataFactory provides consistent test data -- **Fixtures**: Mock objects are configured per test method -- **Assertions**: Each test verifies return values and side effects - (database operations, method calls) - -## Key Concepts - -**Tag Types:** -- knowledge: Tags for datasets/knowledge bases -- app: Tags for applications - -**Tag Bindings:** -- Many-to-many relationship between tags and resources -- Each binding links a tag to a specific app or dataset -- Bindings are tenant-scoped for multi-tenancy - -**Validation:** -- Tag names must be unique within tenant and type -- Target resources must exist before binding -- Cascade deletion of bindings when tag is deleted -""" - - -# ============================================================================ -# IMPORTS -# ============================================================================ - -from datetime import UTC, datetime -from unittest.mock import MagicMock, Mock, create_autospec, patch - -import pytest -from werkzeug.exceptions import NotFound - -from models.dataset import Dataset -from models.model import App, Tag, TagBinding -from services.tag_service import TagService - -# ============================================================================ -# TEST DATA FACTORY -# ============================================================================ - - -class TagServiceTestDataFactory: - """ - Factory for creating test data and mock objects. - - Provides reusable methods to create consistent mock objects for testing - tag-related operations. This factory ensures all test data follows the - same structure and reduces code duplication across tests. - - The factory pattern is used here to: - - Ensure consistent test data creation - - Reduce boilerplate code in individual tests - - Make tests more maintainable and readable - - Centralize mock object configuration - """ - - @staticmethod - def create_tag_mock( - tag_id: str = "tag-123", - name: str = "Test Tag", - tag_type: str = "app", - tenant_id: str = "tenant-123", - **kwargs, - ) -> Mock: - """ - Create a mock Tag object. - - This method creates a mock Tag instance with all required attributes - set to sensible defaults. Additional attributes can be passed via - kwargs to customize the mock for specific test scenarios. - - Args: - tag_id: Unique identifier for the tag - name: Tag name (e.g., "Frontend", "Backend", "Data Science") - tag_type: Type of tag ('app' or 'knowledge') - tenant_id: Tenant identifier for multi-tenancy isolation - **kwargs: Additional attributes to set on the mock - (e.g., created_by, created_at, etc.) - - Returns: - Mock Tag object with specified attributes - - Example: - >>> tag = factory.create_tag_mock( - ... tag_id="tag-456", - ... name="Machine Learning", - ... tag_type="knowledge" - ... ) - """ - # Create a mock that matches the Tag model interface - tag = create_autospec(Tag, instance=True) - - # Set core attributes - tag.id = tag_id - tag.name = name - tag.type = tag_type - tag.tenant_id = tenant_id - - # Set default optional attributes - tag.created_by = kwargs.pop("created_by", "user-123") - tag.created_at = kwargs.pop("created_at", datetime(2023, 1, 1, 0, 0, 0, tzinfo=UTC)) - - # Apply any additional attributes from kwargs - for key, value in kwargs.items(): - setattr(tag, key, value) - - return tag - - @staticmethod - def create_tag_binding_mock( - binding_id: str = "binding-123", - tag_id: str = "tag-123", - target_id: str = "target-123", - tenant_id: str = "tenant-123", - **kwargs, - ) -> Mock: - """ - Create a mock TagBinding object. - - TagBindings represent the many-to-many relationship between tags - and resources (datasets or apps). This method creates a mock - binding with the necessary attributes. - - Args: - binding_id: Unique identifier for the binding - tag_id: Associated tag identifier - target_id: Associated target (app/dataset) identifier - tenant_id: Tenant identifier for multi-tenancy isolation - **kwargs: Additional attributes to set on the mock - (e.g., created_by, etc.) - - Returns: - Mock TagBinding object with specified attributes - - Example: - >>> binding = factory.create_tag_binding_mock( - ... tag_id="tag-456", - ... target_id="dataset-789", - ... tenant_id="tenant-123" - ... ) - """ - # Create a mock that matches the TagBinding model interface - binding = create_autospec(TagBinding, instance=True) - - # Set core attributes - binding.id = binding_id - binding.tag_id = tag_id - binding.target_id = target_id - binding.tenant_id = tenant_id - - # Set default optional attributes - binding.created_by = kwargs.pop("created_by", "user-123") - - # Apply any additional attributes from kwargs - for key, value in kwargs.items(): - setattr(binding, key, value) - - return binding - - @staticmethod - def create_app_mock(app_id: str = "app-123", tenant_id: str = "tenant-123", **kwargs) -> Mock: - """ - Create a mock App object. - - This method creates a mock App instance for testing tag bindings - to applications. Apps are one of the two target types that tags - can be bound to (the other being datasets/knowledge bases). - - Args: - app_id: Unique identifier for the app - tenant_id: Tenant identifier for multi-tenancy isolation - **kwargs: Additional attributes to set on the mock - - Returns: - Mock App object with specified attributes - - Example: - >>> app = factory.create_app_mock( - ... app_id="app-456", - ... name="My Chat App" - ... ) - """ - # Create a mock that matches the App model interface - app = create_autospec(App, instance=True) - - # Set core attributes - app.id = app_id - app.tenant_id = tenant_id - app.name = kwargs.get("name", "Test App") - - # Apply any additional attributes from kwargs - for key, value in kwargs.items(): - setattr(app, key, value) - - return app - - @staticmethod - def create_dataset_mock(dataset_id: str = "dataset-123", tenant_id: str = "tenant-123", **kwargs) -> Mock: - """ - Create a mock Dataset object. - - This method creates a mock Dataset instance for testing tag bindings - to knowledge bases. Datasets (knowledge bases) are one of the two - target types that tags can be bound to (the other being apps). - - Args: - dataset_id: Unique identifier for the dataset - tenant_id: Tenant identifier for multi-tenancy isolation - **kwargs: Additional attributes to set on the mock - - Returns: - Mock Dataset object with specified attributes - - Example: - >>> dataset = factory.create_dataset_mock( - ... dataset_id="dataset-456", - ... name="My Knowledge Base" - ... ) - """ - # Create a mock that matches the Dataset model interface - dataset = create_autospec(Dataset, instance=True) - - # Set core attributes - dataset.id = dataset_id - dataset.tenant_id = tenant_id - dataset.name = kwargs.pop("name", "Test Dataset") - - # Apply any additional attributes from kwargs - for key, value in kwargs.items(): - setattr(dataset, key, value) - - return dataset - - -# ============================================================================ -# PYTEST FIXTURES -# ============================================================================ - - -@pytest.fixture -def factory(): - """ - Provide the test data factory to all tests. - - This fixture makes the TagServiceTestDataFactory available to all test - methods, allowing them to create consistent mock objects easily. - - Returns: - TagServiceTestDataFactory class - """ - return TagServiceTestDataFactory - - -# ============================================================================ -# TAG RETRIEVAL TESTS -# ============================================================================ - - -class TestTagServiceRetrieval: - """ - Test tag retrieval operations. - - This test class covers all methods related to retrieving and querying - tags from the system. These operations are read-only and do not modify - the database state. - - Methods tested: - - get_tags: Retrieve tags with optional keyword filtering - - get_target_ids_by_tag_ids: Get target IDs (datasets/apps) by tag IDs - - get_tag_by_tag_name: Find tags by exact name match - - get_tags_by_target_id: Get all tags bound to a specific target - """ - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tags_with_binding_counts(self, mock_db_session, factory): - """ - Test retrieving tags with their binding counts. - - This test verifies that the get_tags method correctly retrieves - a list of tags along with the count of how many resources - (datasets/apps) are bound to each tag. - - The method should: - - Query tags filtered by type and tenant - - Include binding counts via a LEFT OUTER JOIN - - Return results ordered by creation date (newest first) - - Expected behavior: - - Returns a list of tuples containing (id, type, name, binding_count) - - Each tag includes its binding count - - Results are ordered by creation date descending - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - tag_type = "app" - - # Mock query results: tuples of (tag_id, type, name, binding_count) - # This simulates the SQL query result with aggregated binding counts - mock_results = [ - ("tag-1", "app", "Frontend", 5), # Frontend tag with 5 bindings - ("tag-2", "app", "Backend", 3), # Backend tag with 3 bindings - ("tag-3", "app", "API", 0), # API tag with no bindings - ] - - # Configure mock database session and query chain - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.outerjoin.return_value = mock_query # LEFT OUTER JOIN with TagBinding - mock_query.where.return_value = mock_query # WHERE clause for filtering - mock_query.group_by.return_value = mock_query # GROUP BY for aggregation - mock_query.order_by.return_value = mock_query # ORDER BY for sorting - mock_query.all.return_value = mock_results # Final result - - # Act - # Execute the method under test - results = TagService.get_tags(tag_type=tag_type, current_tenant_id=tenant_id) - - # Assert - # Verify the results match expectations - assert len(results) == 3, "Should return 3 tags" - - # Verify each tag's data structure - assert results[0] == ("tag-1", "app", "Frontend", 5), "First tag should match" - assert results[1] == ("tag-2", "app", "Backend", 3), "Second tag should match" - assert results[2] == ("tag-3", "app", "API", 0), "Third tag should match" - - # Verify database query was called - mock_db_session.query.assert_called_once() - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tags_with_keyword_filter(self, mock_db_session, factory): - """ - Test retrieving tags filtered by keyword (case-insensitive). - - This test verifies that the get_tags method correctly filters tags - by keyword when a keyword parameter is provided. The filtering - should be case-insensitive and support partial matches. - - The method should: - - Apply an additional WHERE clause when keyword is provided - - Use ILIKE for case-insensitive pattern matching - - Support partial matches (e.g., "data" matches "Database" and "Data Science") - - Expected behavior: - - Returns only tags whose names contain the keyword - - Matching is case-insensitive - - Partial matches are supported - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - tag_type = "knowledge" - keyword = "data" - - # Mock query results filtered by keyword - mock_results = [ - ("tag-1", "knowledge", "Database", 2), - ("tag-2", "knowledge", "Data Science", 4), - ] - - # Configure mock database session and query chain - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.outerjoin.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.group_by.return_value = mock_query - mock_query.order_by.return_value = mock_query - mock_query.all.return_value = mock_results - - # Act - # Execute the method with keyword filter - results = TagService.get_tags(tag_type=tag_type, current_tenant_id=tenant_id, keyword=keyword) - - # Assert - # Verify filtered results - assert len(results) == 2, "Should return 2 matching tags" - - # Verify keyword filter was applied - # The where() method should be called at least twice: - # 1. Initial WHERE clause for type and tenant - # 2. Additional WHERE clause for keyword filtering - assert mock_query.where.call_count >= 2, "Keyword filter should add WHERE clause" - - @patch("services.tag_service.db.session", autospec=True) - def test_get_target_ids_by_tag_ids(self, mock_db_session, factory): - """ - Test retrieving target IDs by tag IDs. - - This test verifies that the get_target_ids_by_tag_ids method correctly - retrieves all target IDs (dataset/app IDs) that are bound to the - specified tags. This is useful for filtering datasets or apps by tags. - - The method should: - - First validate and filter tags by type and tenant - - Then find all bindings for those tags - - Return the target IDs from those bindings - - Expected behavior: - - Returns a list of target IDs (strings) - - Only includes targets bound to valid tags - - Respects tenant and type filtering - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - tag_type = "app" - tag_ids = ["tag-1", "tag-2"] - - # Create mock tag objects - tags = [ - factory.create_tag_mock(tag_id="tag-1", tenant_id=tenant_id, tag_type=tag_type), - factory.create_tag_mock(tag_id="tag-2", tenant_id=tenant_id, tag_type=tag_type), - ] - - # Mock target IDs that are bound to these tags - target_ids = ["app-1", "app-2", "app-3"] - - # Mock tag query (first scalars call) - mock_scalars_tags = MagicMock() - mock_scalars_tags.all.return_value = tags - - # Mock binding query (second scalars call) - mock_scalars_bindings = MagicMock() - mock_scalars_bindings.all.return_value = target_ids - - # Configure side_effect to return different mocks for each scalars() call - mock_db_session.scalars.side_effect = [mock_scalars_tags, mock_scalars_bindings] - - # Act - # Execute the method under test - results = TagService.get_target_ids_by_tag_ids(tag_type=tag_type, current_tenant_id=tenant_id, tag_ids=tag_ids) - - # Assert - # Verify results match expected target IDs - assert results == target_ids, "Should return all target IDs bound to tags" - - # Verify both queries were executed - assert mock_db_session.scalars.call_count == 2, "Should execute tag query and binding query" - - @patch("services.tag_service.db.session", autospec=True) - def test_get_target_ids_with_empty_tag_ids(self, mock_db_session, factory): - """ - Test that empty tag_ids returns empty list. - - This test verifies the edge case handling when an empty list of - tag IDs is provided. The method should return early without - executing any database queries. - - Expected behavior: - - Returns empty list immediately - - Does not execute any database queries - - Handles empty input gracefully - """ - # Arrange - # Set up test parameters with empty tag IDs - tenant_id = "tenant-123" - tag_type = "app" - - # Act - # Execute the method with empty tag IDs list - results = TagService.get_target_ids_by_tag_ids(tag_type=tag_type, current_tenant_id=tenant_id, tag_ids=[]) - - # Assert - # Verify empty result and no database queries - assert results == [], "Should return empty list for empty input" - mock_db_session.scalars.assert_not_called(), "Should not query database for empty input" - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tag_by_tag_name(self, mock_db_session, factory): - """ - Test retrieving tags by name. - - This test verifies that the get_tag_by_tag_name method correctly - finds tags by their exact name. This is used for duplicate name - checking and tag lookup operations. - - The method should: - - Perform exact name matching (case-sensitive) - - Filter by type and tenant - - Return a list of matching tags (usually 0 or 1) - - Expected behavior: - - Returns list of tags with matching name - - Respects type and tenant filtering - - Returns empty list if no matches found - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - tag_type = "app" - tag_name = "Production" - - # Create mock tag with matching name - tags = [factory.create_tag_mock(name=tag_name, tag_type=tag_type, tenant_id=tenant_id)] - - # Configure mock database session - mock_scalars = MagicMock() - mock_scalars.all.return_value = tags - mock_db_session.scalars.return_value = mock_scalars - - # Act - # Execute the method under test - results = TagService.get_tag_by_tag_name(tag_type=tag_type, current_tenant_id=tenant_id, tag_name=tag_name) - - # Assert - # Verify tag was found - assert len(results) == 1, "Should find exactly one tag" - assert results[0].name == tag_name, "Tag name should match" - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tag_by_tag_name_returns_empty_for_missing_params(self, mock_db_session, factory): - """ - Test that missing tag_type or tag_name returns empty list. - - This test verifies the input validation for the get_tag_by_tag_name - method. When either tag_type or tag_name is empty or missing, - the method should return early without querying the database. - - Expected behavior: - - Returns empty list for empty tag_type - - Returns empty list for empty tag_name - - Does not execute database queries for invalid input - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - - # Act & Assert - # Test with empty tag_type - assert TagService.get_tag_by_tag_name("", tenant_id, "name") == [], "Should return empty for empty type" - - # Test with empty tag_name - assert TagService.get_tag_by_tag_name("app", tenant_id, "") == [], "Should return empty for empty name" - - # Verify no database queries were executed - mock_db_session.scalars.assert_not_called(), "Should not query database for invalid input" - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tags_by_target_id(self, mock_db_session, factory): - """ - Test retrieving tags associated with a specific target. - - This test verifies that the get_tags_by_target_id method correctly - retrieves all tags that are bound to a specific target (dataset or app). - This is useful for displaying tags associated with a resource. - - The method should: - - Join Tag and TagBinding tables - - Filter by target_id, tenant, and type - - Return all tags bound to the target - - Expected behavior: - - Returns list of Tag objects bound to the target - - Respects tenant and type filtering - - Returns empty list if no tags are bound - """ - # Arrange - # Set up test parameters - tenant_id = "tenant-123" - tag_type = "app" - target_id = "app-123" - - # Create mock tags that are bound to the target - tags = [ - factory.create_tag_mock(tag_id="tag-1", name="Frontend"), - factory.create_tag_mock(tag_id="tag-2", name="Production"), - ] - - # Configure mock database session and query chain - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.join.return_value = mock_query # JOIN with TagBinding - mock_query.where.return_value = mock_query # WHERE clause for filtering - mock_query.all.return_value = tags # Final result - - # Act - # Execute the method under test - results = TagService.get_tags_by_target_id(tag_type=tag_type, current_tenant_id=tenant_id, target_id=target_id) - - # Assert - # Verify tags were retrieved - assert len(results) == 2, "Should return 2 tags bound to target" - - # Verify tag names - assert results[0].name == "Frontend", "First tag name should match" - assert results[1].name == "Production", "Second tag name should match" - - -# ============================================================================ -# TAG CRUD OPERATIONS TESTS -# ============================================================================ - - -class TestTagServiceCRUD: - """ - Test tag CRUD operations. - - This test class covers all Create, Read, Update, and Delete operations - for tags. These operations modify the database state and require proper - transaction handling and validation. - - Methods tested: - - save_tags: Create new tags - - update_tags: Update existing tag names - - delete_tag: Delete tags and cascade delete bindings - - get_tag_binding_count: Get count of bindings for a tag - """ - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.get_tag_by_tag_name", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - @patch("services.tag_service.uuid.uuid4", autospec=True) - def test_save_tags(self, mock_uuid, mock_db_session, mock_get_tag_by_name, mock_current_user, factory): - """ - Test creating a new tag. - - This test verifies that the save_tags method correctly creates a new - tag in the database with all required attributes. The method should - validate uniqueness, generate a UUID, and persist the tag. - - The method should: - - Check for duplicate tag names (via get_tag_by_tag_name) - - Generate a unique UUID for the tag ID - - Set user and tenant information from current_user - - Persist the tag to the database - - Commit the transaction - - Expected behavior: - - Creates tag with correct attributes - - Assigns UUID to tag ID - - Sets created_by from current_user - - Sets tenant_id from current_user - - Commits to database - """ - # Arrange - # Configure mock current_user - mock_current_user.id = "user-123" - mock_current_user.current_tenant_id = "tenant-123" - - # Mock UUID generation - mock_uuid.return_value = "new-tag-id" - - # Mock no existing tag (duplicate check passes) - mock_get_tag_by_name.return_value = [] - - # Prepare tag creation arguments - args = {"name": "New Tag", "type": "app"} - - # Act - # Execute the method under test - result = TagService.save_tags(args) - - # Assert - # Verify tag was added to database session - mock_db_session.add.assert_called_once(), "Should add tag to session" - - # Verify transaction was committed - mock_db_session.commit.assert_called_once(), "Should commit transaction" - - # Verify tag attributes - added_tag = mock_db_session.add.call_args[0][0] - assert added_tag.name == "New Tag", "Tag name should match" - assert added_tag.type == "app", "Tag type should match" - assert added_tag.created_by == "user-123", "Created by should match current user" - assert added_tag.tenant_id == "tenant-123", "Tenant ID should match current tenant" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.get_tag_by_tag_name", autospec=True) - def test_save_tags_raises_error_for_duplicate_name(self, mock_get_tag_by_name, mock_current_user, factory): - """ - Test that creating a tag with duplicate name raises ValueError. - - This test verifies that the save_tags method correctly prevents - duplicate tag names within the same tenant and type. Tag names - must be unique per tenant and type combination. - - Expected behavior: - - Raises ValueError when duplicate name is detected - - Error message indicates "Tag name already exists" - - Does not create the tag - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Mock existing tag with same name (duplicate detected) - existing_tag = factory.create_tag_mock(name="Existing Tag") - mock_get_tag_by_name.return_value = [existing_tag] - - # Prepare tag creation arguments with duplicate name - args = {"name": "Existing Tag", "type": "app"} - - # Act & Assert - # Verify ValueError is raised for duplicate name - with pytest.raises(ValueError, match="Tag name already exists"): - TagService.save_tags(args) - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.get_tag_by_tag_name", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_update_tags(self, mock_db_session, mock_get_tag_by_name, mock_current_user, factory): - """ - Test updating a tag name. - - This test verifies that the update_tags method correctly updates - an existing tag's name while preserving other attributes. The method - should validate uniqueness of the new name and ensure the tag exists. - - The method should: - - Check for duplicate tag names (excluding the current tag) - - Find the tag by ID - - Update the tag name - - Commit the transaction - - Expected behavior: - - Updates tag name successfully - - Preserves other tag attributes - - Commits to database - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Mock no duplicate name (update check passes) - mock_get_tag_by_name.return_value = [] - - # Create mock tag to be updated - tag = factory.create_tag_mock(tag_id="tag-123", name="Old Name") - - # Configure mock database session to return the tag - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = tag - - # Prepare update arguments - args = {"name": "New Name", "type": "app"} - - # Act - # Execute the method under test - result = TagService.update_tags(args, tag_id="tag-123") - - # Assert - # Verify tag name was updated - assert tag.name == "New Name", "Tag name should be updated" - - # Verify transaction was committed - mock_db_session.commit.assert_called_once(), "Should commit transaction" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.get_tag_by_tag_name", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_update_tags_raises_error_for_duplicate_name( - self, mock_db_session, mock_get_tag_by_name, mock_current_user, factory - ): - """ - Test that updating to a duplicate name raises ValueError. - - This test verifies that the update_tags method correctly prevents - updating a tag to a name that already exists for another tag - within the same tenant and type. - - Expected behavior: - - Raises ValueError when duplicate name is detected - - Error message indicates "Tag name already exists" - - Does not update the tag - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Mock existing tag with the duplicate name - existing_tag = factory.create_tag_mock(name="Duplicate Name") - mock_get_tag_by_name.return_value = [existing_tag] - - # Prepare update arguments with duplicate name - args = {"name": "Duplicate Name", "type": "app"} - - # Act & Assert - # Verify ValueError is raised for duplicate name - with pytest.raises(ValueError, match="Tag name already exists"): - TagService.update_tags(args, tag_id="tag-123") - - @patch("services.tag_service.db.session", autospec=True) - def test_update_tags_raises_not_found_for_missing_tag(self, mock_db_session, factory): - """ - Test that updating a non-existent tag raises NotFound. - - This test verifies that the update_tags method correctly handles - the case when attempting to update a tag that does not exist. - This prevents silent failures and provides clear error feedback. - - Expected behavior: - - Raises NotFound exception - - Error message indicates "Tag not found" - - Does not attempt to update or commit - """ - # Arrange - # Configure mock database session to return None (tag not found) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Mock duplicate check and current_user - with patch("services.tag_service.TagService.get_tag_by_tag_name", return_value=[], autospec=True): - with patch("services.tag_service.current_user", autospec=True) as mock_user: - mock_user.current_tenant_id = "tenant-123" - args = {"name": "New Name", "type": "app"} - - # Act & Assert - # Verify NotFound is raised for non-existent tag - with pytest.raises(NotFound, match="Tag not found"): - TagService.update_tags(args, tag_id="nonexistent") - - @patch("services.tag_service.db.session", autospec=True) - def test_get_tag_binding_count(self, mock_db_session, factory): - """ - Test getting the count of bindings for a tag. - - This test verifies that the get_tag_binding_count method correctly - counts how many resources (datasets/apps) are bound to a specific tag. - This is useful for displaying tag usage statistics. - - The method should: - - Query TagBinding table filtered by tag_id - - Return the count of matching bindings - - Expected behavior: - - Returns integer count of bindings - - Returns 0 for tags with no bindings - """ - # Arrange - # Set up test parameters - tag_id = "tag-123" - expected_count = 5 - - # Configure mock database session - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.count.return_value = expected_count - - # Act - # Execute the method under test - result = TagService.get_tag_binding_count(tag_id) - - # Assert - # Verify count matches expectation - assert result == expected_count, "Binding count should match" - - @patch("services.tag_service.db.session", autospec=True) - def test_delete_tag(self, mock_db_session, factory): - """ - Test deleting a tag and its bindings. - - This test verifies that the delete_tag method correctly deletes - a tag along with all its associated bindings (cascade delete). - This ensures data integrity and prevents orphaned bindings. - - The method should: - - Find the tag by ID - - Delete the tag - - Find all bindings for the tag - - Delete all bindings (cascade delete) - - Commit the transaction - - Expected behavior: - - Deletes tag from database - - Deletes all associated bindings - - Commits transaction - """ - # Arrange - # Set up test parameters - tag_id = "tag-123" - - # Create mock tag to be deleted - tag = factory.create_tag_mock(tag_id=tag_id) - - # Create mock bindings that will be cascade deleted - bindings = [factory.create_tag_binding_mock(binding_id=f"binding-{i}", tag_id=tag_id) for i in range(3)] - - # Configure mock database session for tag query - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = tag - - # Configure mock database session for bindings query - mock_scalars = MagicMock() - mock_scalars.all.return_value = bindings - mock_db_session.scalars.return_value = mock_scalars - - # Act - # Execute the method under test - TagService.delete_tag(tag_id) - - # Assert - # Verify tag and bindings were deleted - mock_db_session.delete.assert_called(), "Should call delete method" - - # Verify delete was called 4 times (1 tag + 3 bindings) - assert mock_db_session.delete.call_count == 4, "Should delete tag and all bindings" - - # Verify transaction was committed - mock_db_session.commit.assert_called_once(), "Should commit transaction" - - @patch("services.tag_service.db.session", autospec=True) - def test_delete_tag_raises_not_found(self, mock_db_session, factory): - """ - Test that deleting a non-existent tag raises NotFound. - - This test verifies that the delete_tag method correctly handles - the case when attempting to delete a tag that does not exist. - This prevents silent failures and provides clear error feedback. - - Expected behavior: - - Raises NotFound exception - - Error message indicates "Tag not found" - - Does not attempt to delete or commit - """ - # Arrange - # Configure mock database session to return None (tag not found) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None - - # Act & Assert - # Verify NotFound is raised for non-existent tag - with pytest.raises(NotFound, match="Tag not found"): - TagService.delete_tag("nonexistent") - - -# ============================================================================ -# TAG BINDING OPERATIONS TESTS -# ============================================================================ - - -class TestTagServiceBindings: - """ - Test tag binding operations. - - This test class covers all operations related to binding tags to - resources (datasets and apps). Tag bindings create the many-to-many - relationship between tags and resources. - - Methods tested: - - save_tag_binding: Create bindings between tags and targets - - delete_tag_binding: Remove bindings between tags and targets - - check_target_exists: Validate target (dataset/app) existence - """ - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.check_target_exists", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_save_tag_binding(self, mock_db_session, mock_check_target, mock_current_user, factory): - """ - Test creating tag bindings. - - This test verifies that the save_tag_binding method correctly - creates bindings between tags and a target resource (dataset or app). - The method supports batch binding of multiple tags to a single target. - - The method should: - - Validate target exists (via check_target_exists) - - Check for existing bindings to avoid duplicates - - Create new bindings for tags that aren't already bound - - Commit the transaction - - Expected behavior: - - Validates target exists - - Creates bindings for each tag in tag_ids - - Skips tags that are already bound (idempotent) - - Commits transaction - """ - # Arrange - # Configure mock current_user - mock_current_user.id = "user-123" - mock_current_user.current_tenant_id = "tenant-123" - - # Configure mock database session (no existing bindings) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None # No existing bindings - - # Prepare binding arguments (batch binding) - args = {"type": "app", "target_id": "app-123", "tag_ids": ["tag-1", "tag-2"]} - - # Act - # Execute the method under test - TagService.save_tag_binding(args) - - # Assert - # Verify target existence was checked - mock_check_target.assert_called_once_with("app", "app-123"), "Should validate target exists" - - # Verify bindings were created (2 bindings for 2 tags) - assert mock_db_session.add.call_count == 2, "Should create 2 bindings" - - # Verify transaction was committed - mock_db_session.commit.assert_called_once(), "Should commit transaction" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.TagService.check_target_exists", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_save_tag_binding_is_idempotent(self, mock_db_session, mock_check_target, mock_current_user, factory): - """ - Test that saving duplicate bindings is idempotent. - - This test verifies that the save_tag_binding method correctly handles - the case when attempting to create a binding that already exists. - The method should skip existing bindings and not create duplicates, - making the operation idempotent. - - Expected behavior: - - Checks for existing bindings - - Skips tags that are already bound - - Does not create duplicate bindings - - Still commits transaction - """ - # Arrange - # Configure mock current_user - mock_current_user.id = "user-123" - mock_current_user.current_tenant_id = "tenant-123" - - # Mock existing binding (duplicate detected) - existing_binding = factory.create_tag_binding_mock() - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = existing_binding # Binding already exists - - # Prepare binding arguments - args = {"type": "app", "target_id": "app-123", "tag_ids": ["tag-1"]} - - # Act - # Execute the method under test - TagService.save_tag_binding(args) - - # Assert - # Verify no new binding was added (idempotent) - mock_db_session.add.assert_not_called(), "Should not create duplicate binding" - - @patch("services.tag_service.TagService.check_target_exists", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_delete_tag_binding(self, mock_db_session, mock_check_target, factory): - """ - Test deleting a tag binding. - - This test verifies that the delete_tag_binding method correctly - removes a binding between a tag and a target resource. This - operation should be safe even if the binding doesn't exist. - - The method should: - - Validate target exists (via check_target_exists) - - Find the binding by tag_id and target_id - - Delete the binding if it exists - - Commit the transaction - - Expected behavior: - - Validates target exists - - Deletes the binding - - Commits transaction - """ - # Arrange - # Create mock binding to be deleted - binding = factory.create_tag_binding_mock() - - # Configure mock database session - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = binding - - # Prepare delete arguments - args = {"type": "app", "target_id": "app-123", "tag_id": "tag-1"} - - # Act - # Execute the method under test - TagService.delete_tag_binding(args) - - # Assert - # Verify target existence was checked - mock_check_target.assert_called_once_with("app", "app-123"), "Should validate target exists" - - # Verify binding was deleted - mock_db_session.delete.assert_called_once_with(binding), "Should delete the binding" - - # Verify transaction was committed - mock_db_session.commit.assert_called_once(), "Should commit transaction" - - @patch("services.tag_service.TagService.check_target_exists", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_delete_tag_binding_does_nothing_if_not_exists(self, mock_db_session, mock_check_target, factory): - """ - Test that deleting a non-existent binding is a no-op. - - This test verifies that the delete_tag_binding method correctly - handles the case when attempting to delete a binding that doesn't - exist. The method should not raise an error and should not commit - if there's nothing to delete. - - Expected behavior: - - Validates target exists - - Does not raise error for non-existent binding - - Does not call delete or commit if binding doesn't exist - """ - # Arrange - # Configure mock database session (binding not found) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None # Binding doesn't exist - - # Prepare delete arguments - args = {"type": "app", "target_id": "app-123", "tag_id": "tag-1"} - - # Act - # Execute the method under test - TagService.delete_tag_binding(args) - - # Assert - # Verify no delete operation was attempted - mock_db_session.delete.assert_not_called(), "Should not delete if binding doesn't exist" - - # Verify no commit was made (nothing changed) - mock_db_session.commit.assert_not_called(), "Should not commit if nothing to delete" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_check_target_exists_for_dataset(self, mock_db_session, mock_current_user, factory): - """ - Test validating that a dataset target exists. - - This test verifies that the check_target_exists method correctly - validates the existence of a dataset (knowledge base) when the - target type is "knowledge". This validation ensures bindings - are only created for valid resources. - - The method should: - - Query Dataset table filtered by tenant and ID - - Raise NotFound if dataset doesn't exist - - Return normally if dataset exists - - Expected behavior: - - No exception raised when dataset exists - - Database query is executed - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Create mock dataset - dataset = factory.create_dataset_mock() - - # Configure mock database session - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = dataset # Dataset exists - - # Act - # Execute the method under test - TagService.check_target_exists("knowledge", "dataset-123") - - # Assert - # Verify no exception was raised and query was executed - mock_db_session.query.assert_called_once(), "Should query database for dataset" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_check_target_exists_for_app(self, mock_db_session, mock_current_user, factory): - """ - Test validating that an app target exists. - - This test verifies that the check_target_exists method correctly - validates the existence of an application when the target type is - "app". This validation ensures bindings are only created for valid - resources. - - The method should: - - Query App table filtered by tenant and ID - - Raise NotFound if app doesn't exist - - Return normally if app exists - - Expected behavior: - - No exception raised when app exists - - Database query is executed - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Create mock app - app = factory.create_app_mock() - - # Configure mock database session - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = app # App exists - - # Act - # Execute the method under test - TagService.check_target_exists("app", "app-123") - - # Assert - # Verify no exception was raised and query was executed - mock_db_session.query.assert_called_once(), "Should query database for app" - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_check_target_exists_raises_not_found_for_missing_dataset( - self, mock_db_session, mock_current_user, factory - ): - """ - Test that missing dataset raises NotFound. - - This test verifies that the check_target_exists method correctly - raises a NotFound exception when attempting to validate a dataset - that doesn't exist. This prevents creating bindings for invalid - resources. - - Expected behavior: - - Raises NotFound exception - - Error message indicates "Dataset not found" - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Configure mock database session (dataset not found) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None # Dataset doesn't exist - - # Act & Assert - # Verify NotFound is raised for non-existent dataset - with pytest.raises(NotFound, match="Dataset not found"): - TagService.check_target_exists("knowledge", "nonexistent") - - @patch("services.tag_service.current_user", autospec=True) - @patch("services.tag_service.db.session", autospec=True) - def test_check_target_exists_raises_not_found_for_missing_app(self, mock_db_session, mock_current_user, factory): - """ - Test that missing app raises NotFound. - - This test verifies that the check_target_exists method correctly - raises a NotFound exception when attempting to validate an app - that doesn't exist. This prevents creating bindings for invalid - resources. - - Expected behavior: - - Raises NotFound exception - - Error message indicates "App not found" - """ - # Arrange - # Configure mock current_user - mock_current_user.current_tenant_id = "tenant-123" - - # Configure mock database session (app not found) - mock_query = MagicMock() - mock_db_session.query.return_value = mock_query - mock_query.where.return_value = mock_query - mock_query.first.return_value = None # App doesn't exist - - # Act & Assert - # Verify NotFound is raised for non-existent app - with pytest.raises(NotFound, match="App not found"): - TagService.check_target_exists("app", "nonexistent") - - def test_check_target_exists_raises_not_found_for_invalid_type(self, factory): - """ - Test that invalid binding type raises NotFound. - - This test verifies that the check_target_exists method correctly - raises a NotFound exception when an invalid target type is provided. - Only "knowledge" (for datasets) and "app" are valid target types. - - Expected behavior: - - Raises NotFound exception - - Error message indicates "Invalid binding type" - """ - # Act & Assert - # Verify NotFound is raised for invalid target type - with pytest.raises(NotFound, match="Invalid binding type"): - TagService.check_target_exists("invalid_type", "target-123") diff --git a/api/tests/unit_tests/services/test_trigger_provider_service.py b/api/tests/unit_tests/services/test_trigger_provider_service.py new file mode 100644 index 00000000000..81a3b181fdb --- /dev/null +++ b/api/tests/unit_tests/services/test_trigger_provider_service.py @@ -0,0 +1,1249 @@ +from __future__ import annotations + +import contextlib +import json +from types import SimpleNamespace +from unittest.mock import MagicMock + +import pytest +from pytest_mock import MockerFixture + +from constants import HIDDEN_VALUE +from core.plugin.entities.plugin_daemon import CredentialType +from models.provider_ids import TriggerProviderID +from services.trigger.trigger_provider_service import TriggerProviderService + + +def _patch_redis_lock(mocker: MockerFixture) -> None: + mock_redis = mocker.patch("services.trigger.trigger_provider_service.redis_client") + mock_redis.lock.return_value = contextlib.nullcontext() + + +def _mock_get_trigger_provider(mocker: MockerFixture, provider: object | None) -> None: + mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.get_trigger_provider", + return_value=provider, + ) + + +def _encrypter_mock( + *, + decrypted: dict | None = None, + encrypted: dict | None = None, + masked: dict | None = None, +) -> MagicMock: + enc = MagicMock() + enc.decrypt.return_value = decrypted or {} + enc.encrypt.return_value = encrypted or {} + enc.mask_credentials.return_value = masked or {} + enc.mask_plugin_credentials.return_value = masked or {} + return enc + + +@pytest.fixture +def provider_id() -> TriggerProviderID: + # Arrange + return TriggerProviderID("langgenius/github/github") + + +@pytest.fixture(autouse=True) +def mock_db_engine(mocker: MockerFixture) -> SimpleNamespace: + # Arrange + mocked_db = SimpleNamespace(engine=object()) + mocker.patch("services.trigger.trigger_provider_service.db", mocked_db) + return mocked_db + + +@pytest.fixture +def mock_session(mocker: MockerFixture) -> MagicMock: + """Mocks the database session context manager used by TriggerProviderService.""" + # Arrange + mock_session_instance = MagicMock() + mock_session_cm = MagicMock() + mock_session_cm.__enter__.return_value = mock_session_instance + mock_session_cm.__exit__.return_value = False + mocker.patch("services.trigger.trigger_provider_service.Session", return_value=mock_session_cm) + return mock_session_instance + + +@pytest.fixture +def provider_controller() -> MagicMock: + # Arrange + controller = MagicMock() + controller.get_credential_schema_config.return_value = [] + controller.get_properties_schema.return_value = [] + controller.get_oauth_client_schema.return_value = [] + controller.plugin_unique_identifier = "langgenius/github:0.0.1" + return controller + + +def test_get_trigger_provider_should_return_api_entity_from_manager( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + provider = MagicMock() + provider.to_api_entity.return_value = {"provider": "ok"} + _mock_get_trigger_provider(mocker, provider) + + # Act + result = TriggerProviderService.get_trigger_provider("tenant-1", provider_id) + + # Assert + assert result == {"provider": "ok"} + + +def test_list_trigger_providers_should_return_api_entities_from_manager(mocker: MockerFixture) -> None: + # Arrange + provider_a = MagicMock() + provider_b = MagicMock() + provider_a.to_api_entity.return_value = {"id": "a"} + provider_b.to_api_entity.return_value = {"id": "b"} + mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.list_all_trigger_providers", + return_value=[provider_a, provider_b], + ) + + # Act + result = TriggerProviderService.list_trigger_providers("tenant-1") + + # Assert + assert result == [{"id": "a"}, {"id": "b"}] + + +def test_list_trigger_provider_subscriptions_should_return_empty_list_when_no_subscriptions( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + query = MagicMock() + query.filter_by.return_value.order_by.return_value.all.return_value = [] + mock_session.query.return_value = query + + # Act + result = TriggerProviderService.list_trigger_provider_subscriptions("tenant-1", provider_id) + + # Assert + assert result == [] + + +def test_list_trigger_provider_subscriptions_should_mask_fields_and_attach_workflow_counts( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + api_sub = SimpleNamespace( + id="sub-1", + credentials={"token": "enc"}, + properties={"hook": "enc"}, + parameters={"event": "push"}, + workflows_in_use=0, + ) + db_sub = SimpleNamespace(to_api_entity=lambda: api_sub) + usage_row = SimpleNamespace(subscription_id="sub-1", app_count=2) + + query_subs = MagicMock() + query_subs.filter_by.return_value.order_by.return_value.all.return_value = [db_sub] + query_usage = MagicMock() + query_usage.filter.return_value.group_by.return_value.all.return_value = [usage_row] + mock_session.query.side_effect = [query_subs, query_usage] + + _mock_get_trigger_provider(mocker, provider_controller) + cred_enc = _encrypter_mock(decrypted={"token": "plain"}, masked={"token": "****"}) + prop_enc = _encrypter_mock(decrypted={"hook": "plain"}, masked={"hook": "****"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(cred_enc, MagicMock()), + ) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_properties", + return_value=(prop_enc, MagicMock()), + ) + + # Act + result = TriggerProviderService.list_trigger_provider_subscriptions("tenant-1", provider_id) + + # Assert + assert len(result) == 1 + assert result[0].credentials == {"token": "****"} + assert result[0].properties == {"hook": "****"} + assert result[0].workflows_in_use == 2 + + +def test_add_trigger_subscription_should_create_subscription_successfully_for_api_key( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + query_count = MagicMock() + query_count.filter_by.return_value.count.return_value = 0 + query_existing = MagicMock() + query_existing.filter_by.return_value.first.return_value = None + mock_session.query.side_effect = [query_count, query_existing] + + _mock_get_trigger_provider(mocker, provider_controller) + cred_enc = _encrypter_mock(encrypted={"api_key": "enc"}) + prop_enc = _encrypter_mock(encrypted={"project": "enc"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_provider_encrypter", + side_effect=[(cred_enc, MagicMock()), (prop_enc, MagicMock())], + ) + + # Act + result = TriggerProviderService.add_trigger_subscription( + tenant_id="tenant-1", + user_id="user-1", + name="main", + provider_id=provider_id, + endpoint_id="endpoint-1", + credential_type=CredentialType.API_KEY, + parameters={"event": "push"}, + properties={"project": "demo"}, + credentials={"api_key": "plain"}, + ) + + # Assert + assert result["result"] == "success" + mock_session.add.assert_called_once() + mock_session.commit.assert_called_once() + + +def test_add_trigger_subscription_should_store_empty_credentials_for_unauthorized_type( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + query_count = MagicMock() + query_count.filter_by.return_value.count.return_value = 0 + query_existing = MagicMock() + query_existing.filter_by.return_value.first.return_value = None + mock_session.query.side_effect = [query_count, query_existing] + + _mock_get_trigger_provider(mocker, provider_controller) + prop_enc = _encrypter_mock(encrypted={"p": "enc"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_provider_encrypter", + return_value=(prop_enc, MagicMock()), + ) + + # Act + result = TriggerProviderService.add_trigger_subscription( + tenant_id="tenant-1", + user_id="user-1", + name="main", + provider_id=provider_id, + endpoint_id="endpoint-1", + credential_type=CredentialType.UNAUTHORIZED, + parameters={}, + properties={"p": "v"}, + credentials={}, + subscription_id="sub-fixed", + ) + + # Assert + assert result == {"result": "success", "id": "sub-fixed"} + + +def test_add_trigger_subscription_should_raise_error_when_provider_limit_reached( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + query_count = MagicMock() + query_count.filter_by.return_value.count.return_value = TriggerProviderService.__MAX_TRIGGER_PROVIDER_COUNT__ + mock_session.query.return_value = query_count + _mock_get_trigger_provider(mocker, provider_controller) + mock_logger = mocker.patch("services.trigger.trigger_provider_service.logger") + + # Act + Assert + with pytest.raises(ValueError, match="Maximum number of providers"): + TriggerProviderService.add_trigger_subscription( + tenant_id="tenant-1", + user_id="user-1", + name="main", + provider_id=provider_id, + endpoint_id="endpoint-1", + credential_type=CredentialType.API_KEY, + parameters={}, + properties={}, + credentials={}, + ) + mock_logger.exception.assert_called_once() + + +def test_add_trigger_subscription_should_raise_error_when_name_exists( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + query_count = MagicMock() + query_count.filter_by.return_value.count.return_value = 0 + query_existing = MagicMock() + query_existing.filter_by.return_value.first.return_value = object() + mock_session.query.side_effect = [query_count, query_existing] + _mock_get_trigger_provider(mocker, provider_controller) + + # Act + Assert + with pytest.raises(ValueError, match="Credential name 'main' already exists"): + TriggerProviderService.add_trigger_subscription( + tenant_id="tenant-1", + user_id="user-1", + name="main", + provider_id=provider_id, + endpoint_id="endpoint-1", + credential_type=CredentialType.API_KEY, + parameters={}, + properties={}, + credentials={}, + ) + + +def test_update_trigger_subscription_should_raise_error_when_subscription_not_found( + mocker: MockerFixture, + mock_session: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + query_sub = MagicMock() + query_sub.filter_by.return_value.first.return_value = None + mock_session.query.return_value = query_sub + + # Act + Assert + with pytest.raises(ValueError, match="not found"): + TriggerProviderService.update_trigger_subscription("tenant-1", "sub-1") + + +def test_update_trigger_subscription_should_raise_error_when_name_conflicts( + mocker: MockerFixture, + mock_session: MagicMock, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + subscription = SimpleNamespace( + id="sub-1", + name="old", + provider_id="langgenius/github/github", + credential_type=CredentialType.API_KEY.value, + ) + query_sub = MagicMock() + query_sub.filter_by.return_value.first.return_value = subscription + query_existing = MagicMock() + query_existing.filter_by.return_value.first.return_value = object() + mock_session.query.side_effect = [query_sub, query_existing] + _mock_get_trigger_provider(mocker, provider_controller) + + # Act + Assert + with pytest.raises(ValueError, match="already exists"): + TriggerProviderService.update_trigger_subscription("tenant-1", "sub-1", name="new-name") + + +def test_update_trigger_subscription_should_update_fields_and_clear_cache( + mocker: MockerFixture, + mock_session: MagicMock, + provider_controller: MagicMock, +) -> None: + # Arrange + _patch_redis_lock(mocker) + subscription = SimpleNamespace( + id="sub-1", + name="old", + tenant_id="tenant-1", + provider_id="langgenius/github/github", + properties={"project": "enc-old"}, + parameters={"event": "old"}, + credentials={"api_key": "enc-old"}, + credential_type=CredentialType.API_KEY.value, + credential_expires_at=0, + expires_at=0, + ) + query_sub = MagicMock() + query_sub.filter_by.return_value.first.return_value = subscription + query_existing = MagicMock() + query_existing.filter_by.return_value.first.return_value = None + mock_session.query.side_effect = [query_sub, query_existing] + + _mock_get_trigger_provider(mocker, provider_controller) + prop_enc = _encrypter_mock(decrypted={"project": "old-value"}, encrypted={"project": "new-value"}) + cred_enc = _encrypter_mock(encrypted={"api_key": "new-key"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_provider_encrypter", + side_effect=[(prop_enc, MagicMock()), (cred_enc, MagicMock())], + ) + mock_delete_cache = mocker.patch("services.trigger.trigger_provider_service.delete_cache_for_subscription") + + # Act + TriggerProviderService.update_trigger_subscription( + tenant_id="tenant-1", + subscription_id="sub-1", + name="new", + properties={"project": HIDDEN_VALUE, "region": "us"}, + parameters={"event": "new"}, + credentials={"api_key": "plain-key"}, + credential_expires_at=100, + expires_at=200, + ) + + # Assert + assert subscription.name == "new" + assert subscription.parameters == {"event": "new"} + assert subscription.credentials == {"api_key": "new-key"} + assert subscription.credential_expires_at == 100 + assert subscription.expires_at == 200 + mock_session.commit.assert_called_once() + mock_delete_cache.assert_called_once() + + +def test_get_subscription_by_id_should_return_none_when_missing(mocker: MockerFixture, mock_session: MagicMock) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + result = TriggerProviderService.get_subscription_by_id("tenant-1", "sub-1") + + # Assert + assert result is None + + +def test_get_subscription_by_id_should_decrypt_credentials_and_properties( + mocker: MockerFixture, + mock_session: MagicMock, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-1", + tenant_id="tenant-1", + provider_id="langgenius/github/github", + credentials={"token": "enc"}, + properties={"project": "enc"}, + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + cred_enc = _encrypter_mock(decrypted={"token": "plain"}) + prop_enc = _encrypter_mock(decrypted={"project": "plain"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(cred_enc, MagicMock()), + ) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_properties", + return_value=(prop_enc, MagicMock()), + ) + + # Act + result = TriggerProviderService.get_subscription_by_id("tenant-1", "sub-1") + + # Assert + assert result is subscription + assert subscription.credentials == {"token": "plain"} + assert subscription.properties == {"project": "plain"} + + +def test_delete_trigger_provider_should_raise_error_when_subscription_missing( + mocker: MockerFixture, + mock_session: MagicMock, +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + Assert + with pytest.raises(ValueError, match="not found"): + TriggerProviderService.delete_trigger_provider(mock_session, "tenant-1", "sub-1") + + +def test_delete_trigger_provider_should_delete_and_clear_cache_even_if_unsubscribe_fails( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-1", + user_id="user-1", + provider_id=str(provider_id), + credential_type=CredentialType.OAUTH2.value, + credentials={"token": "enc"}, + to_entity=lambda: SimpleNamespace(id="sub-1"), + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + cred_enc = _encrypter_mock(decrypted={"token": "plain"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(cred_enc, MagicMock()), + ) + mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.unsubscribe_trigger", + side_effect=RuntimeError("remote fail"), + ) + mock_delete_cache = mocker.patch("services.trigger.trigger_provider_service.delete_cache_for_subscription") + + # Act + TriggerProviderService.delete_trigger_provider(mock_session, "tenant-1", "sub-1") + + # Assert + mock_session.delete.assert_called_once_with(subscription) + mock_delete_cache.assert_called_once() + + +def test_delete_trigger_provider_should_skip_unsubscribe_for_unauthorized( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-2", + user_id="user-1", + provider_id=str(provider_id), + credential_type=CredentialType.UNAUTHORIZED.value, + credentials={}, + to_entity=lambda: SimpleNamespace(id="sub-2"), + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + mock_unsubscribe = mocker.patch("services.trigger.trigger_provider_service.TriggerManager.unsubscribe_trigger") + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(_encrypter_mock(decrypted={}), MagicMock()), + ) + + # Act + TriggerProviderService.delete_trigger_provider(mock_session, "tenant-1", "sub-2") + + # Assert + mock_unsubscribe.assert_not_called() + mock_session.delete.assert_called_once_with(subscription) + + +def test_refresh_oauth_token_should_raise_error_when_subscription_missing( + mocker: MockerFixture, mock_session: MagicMock +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + Assert + with pytest.raises(ValueError, match="not found"): + TriggerProviderService.refresh_oauth_token("tenant-1", "sub-1") + + +def test_refresh_oauth_token_should_raise_error_for_non_oauth_credentials( + mocker: MockerFixture, mock_session: MagicMock +) -> None: + # Arrange + subscription = SimpleNamespace(credential_type=CredentialType.API_KEY.value) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + + # Act + Assert + with pytest.raises(ValueError, match="Only OAuth credentials can be refreshed"): + TriggerProviderService.refresh_oauth_token("tenant-1", "sub-1") + + +def test_refresh_oauth_token_should_refresh_and_persist_new_credentials( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + provider_id=str(provider_id), + user_id="user-1", + credential_type=CredentialType.OAUTH2.value, + credentials={"access_token": "enc"}, + credential_expires_at=0, + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + cache = MagicMock() + cred_enc = _encrypter_mock(decrypted={"access_token": "old"}, encrypted={"access_token": "new"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_provider_encrypter", + return_value=(cred_enc, cache), + ) + mocker.patch.object(TriggerProviderService, "get_oauth_client", return_value={"client_id": "id"}) + refreshed = SimpleNamespace(credentials={"access_token": "new"}, expires_at=12345) + oauth_handler = MagicMock() + oauth_handler.refresh_credentials.return_value = refreshed + mocker.patch("services.trigger.trigger_provider_service.OAuthHandler", return_value=oauth_handler) + + # Act + result = TriggerProviderService.refresh_oauth_token("tenant-1", "sub-1") + + # Assert + assert result == {"result": "success", "expires_at": 12345} + assert subscription.credentials == {"access_token": "new"} + assert subscription.credential_expires_at == 12345 + mock_session.commit.assert_called_once() + cache.delete.assert_called_once() + + +def test_refresh_subscription_should_raise_error_when_subscription_missing( + mocker: MockerFixture, mock_session: MagicMock +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + Assert + with pytest.raises(ValueError, match="not found"): + TriggerProviderService.refresh_subscription("tenant-1", "sub-1", now=100) + + +def test_refresh_subscription_should_skip_when_not_due(mocker: MockerFixture, mock_session: MagicMock) -> None: + # Arrange + subscription = SimpleNamespace(expires_at=200) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + + # Act + result = TriggerProviderService.refresh_subscription("tenant-1", "sub-1", now=100) + + # Assert + assert result == {"result": "skipped", "expires_at": 200} + + +def test_refresh_subscription_should_refresh_and_persist_properties( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-1", + tenant_id="tenant-1", + endpoint_id="endpoint-1", + expires_at=50, + provider_id=str(provider_id), + parameters={"event": "push"}, + properties={"p": "enc"}, + credentials={"c": "enc"}, + credential_type=CredentialType.API_KEY.value, + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + cred_enc = _encrypter_mock(decrypted={"c": "plain"}) + prop_cache = MagicMock() + prop_enc = _encrypter_mock(decrypted={"p": "plain"}, encrypted={"p": "new-enc"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(cred_enc, MagicMock()), + ) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_properties", + return_value=(prop_enc, prop_cache), + ) + mocker.patch( + "services.trigger.trigger_provider_service.generate_plugin_trigger_endpoint_url", + return_value="https://endpoint", + ) + provider_controller.refresh_trigger.return_value = SimpleNamespace(properties={"p": "new"}, expires_at=999) + + # Act + result = TriggerProviderService.refresh_subscription("tenant-1", "sub-1", now=100) + + # Assert + assert result == {"result": "success", "expires_at": 999} + assert subscription.properties == {"p": "new-enc"} + assert subscription.expires_at == 999 + mock_session.commit.assert_called_once() + prop_cache.delete.assert_called_once() + + +def test_get_oauth_client_should_return_tenant_client_when_available( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + tenant_client = SimpleNamespace(oauth_params={"client_id": "enc"}) + system_client = None + query_tenant = MagicMock() + query_tenant.filter_by.return_value.first.return_value = tenant_client + mock_session.query.return_value = query_tenant + _mock_get_trigger_provider(mocker, provider_controller) + enc = _encrypter_mock(decrypted={"client_id": "plain"}) + mocker.patch("services.trigger.trigger_provider_service.create_provider_encrypter", return_value=(enc, MagicMock())) + + # Act + result = TriggerProviderService.get_oauth_client("tenant-1", provider_id) + + # Assert + assert result == {"client_id": "plain"} + + +def test_get_oauth_client_should_return_none_when_plugin_not_verified( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + query_tenant = MagicMock() + query_tenant.filter_by.return_value.first.return_value = None + query_system = MagicMock() + query_system.filter_by.return_value.first.return_value = None + mock_session.query.side_effect = [query_tenant, query_system] + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch("services.trigger.trigger_provider_service.PluginService.is_plugin_verified", return_value=False) + + # Act + result = TriggerProviderService.get_oauth_client("tenant-1", provider_id) + + # Assert + assert result is None + + +def test_get_oauth_client_should_return_decrypted_system_client_when_verified( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + query_tenant = MagicMock() + query_tenant.filter_by.return_value.first.return_value = None + query_system = MagicMock() + query_system.filter_by.return_value.first.return_value = SimpleNamespace(encrypted_oauth_params="enc") + mock_session.query.side_effect = [query_tenant, query_system] + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch("services.trigger.trigger_provider_service.PluginService.is_plugin_verified", return_value=True) + mocker.patch( + "services.trigger.trigger_provider_service.decrypt_system_oauth_params", + return_value={"client_id": "system"}, + ) + + # Act + result = TriggerProviderService.get_oauth_client("tenant-1", provider_id) + + # Assert + assert result == {"client_id": "system"} + + +def test_get_oauth_client_should_raise_error_when_system_decryption_fails( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + query_tenant = MagicMock() + query_tenant.filter_by.return_value.first.return_value = None + query_system = MagicMock() + query_system.filter_by.return_value.first.return_value = SimpleNamespace(encrypted_oauth_params="enc") + mock_session.query.side_effect = [query_tenant, query_system] + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch("services.trigger.trigger_provider_service.PluginService.is_plugin_verified", return_value=True) + mocker.patch( + "services.trigger.trigger_provider_service.decrypt_system_oauth_params", + side_effect=RuntimeError("bad data"), + ) + + # Act + Assert + with pytest.raises(ValueError, match="Error decrypting system oauth params"): + TriggerProviderService.get_oauth_client("tenant-1", provider_id) + + +def test_is_oauth_system_client_exists_should_return_false_when_unverified( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch("services.trigger.trigger_provider_service.PluginService.is_plugin_verified", return_value=False) + + # Act + result = TriggerProviderService.is_oauth_system_client_exists("tenant-1", provider_id) + + # Assert + assert result is False + + +@pytest.mark.parametrize("has_client", [True, False]) +def test_is_oauth_system_client_exists_should_reflect_database_record( + has_client: bool, + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = object() if has_client else None + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch("services.trigger.trigger_provider_service.PluginService.is_plugin_verified", return_value=True) + + # Act + result = TriggerProviderService.is_oauth_system_client_exists("tenant-1", provider_id) + + # Assert + assert result is has_client + + +def test_save_custom_oauth_client_params_should_return_success_when_nothing_to_update( + provider_id: TriggerProviderID, +) -> None: + # Arrange + # Act + result = TriggerProviderService.save_custom_oauth_client_params("tenant-1", provider_id, None, None) + + # Assert + assert result == {"result": "success"} + + +def test_save_custom_oauth_client_params_should_create_record_and_clear_params_when_client_params_none( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + query = MagicMock() + query.filter_by.return_value.first.return_value = None + mock_session.query.return_value = query + _mock_get_trigger_provider(mocker, provider_controller) + fake_model = SimpleNamespace(encrypted_oauth_params="", enabled=False, oauth_params={}) + mocker.patch("services.trigger.trigger_provider_service.TriggerOAuthTenantClient", return_value=fake_model) + + # Act + result = TriggerProviderService.save_custom_oauth_client_params( + tenant_id="tenant-1", + provider_id=provider_id, + client_params=None, + enabled=True, + ) + + # Assert + assert result == {"result": "success"} + assert fake_model.encrypted_oauth_params == "{}" + assert fake_model.enabled is True + mock_session.add.assert_called_once_with(fake_model) + mock_session.commit.assert_called_once() + + +def test_save_custom_oauth_client_params_should_merge_hidden_values_and_delete_cache( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + custom_client = SimpleNamespace(oauth_params={"client_id": "enc-old"}, enabled=False) + mock_session.query.return_value.filter_by.return_value.first.return_value = custom_client + _mock_get_trigger_provider(mocker, provider_controller) + cache = MagicMock() + enc = _encrypter_mock(decrypted={"client_id": "old-id"}, encrypted={"client_id": "new-id"}) + mocker.patch( + "services.trigger.trigger_provider_service.create_provider_encrypter", + return_value=(enc, cache), + ) + + # Act + result = TriggerProviderService.save_custom_oauth_client_params( + tenant_id="tenant-1", + provider_id=provider_id, + client_params={"client_id": HIDDEN_VALUE, "client_secret": "new"}, + enabled=None, + ) + + # Assert + assert result == {"result": "success"} + assert json.loads(custom_client.encrypted_oauth_params) == {"client_id": "new-id"} + cache.delete.assert_called_once() + mock_session.commit.assert_called_once() + + +def test_get_custom_oauth_client_params_should_return_empty_when_record_missing( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + result = TriggerProviderService.get_custom_oauth_client_params("tenant-1", provider_id) + + # Assert + assert result == {} + + +def test_get_custom_oauth_client_params_should_return_masked_decrypted_values( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + custom_client = SimpleNamespace(oauth_params={"client_id": "enc"}) + mock_session.query.return_value.filter_by.return_value.first.return_value = custom_client + _mock_get_trigger_provider(mocker, provider_controller) + enc = _encrypter_mock(decrypted={"client_id": "plain"}, masked={"client_id": "pl***id"}) + mocker.patch("services.trigger.trigger_provider_service.create_provider_encrypter", return_value=(enc, MagicMock())) + + # Act + result = TriggerProviderService.get_custom_oauth_client_params("tenant-1", provider_id) + + # Assert + assert result == {"client_id": "pl***id"} + + +def test_delete_custom_oauth_client_params_should_delete_record_and_commit( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.delete.return_value = 1 + + # Act + result = TriggerProviderService.delete_custom_oauth_client_params("tenant-1", provider_id) + + # Assert + assert result == {"result": "success"} + mock_session.commit.assert_called_once() + + +@pytest.mark.parametrize("exists", [True, False]) +def test_is_oauth_custom_client_enabled_should_return_expected_boolean( + exists: bool, + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = object() if exists else None + + # Act + result = TriggerProviderService.is_oauth_custom_client_enabled("tenant-1", provider_id) + + # Assert + assert result is exists + + +def test_get_subscription_by_endpoint_should_return_none_when_not_found( + mocker: MockerFixture, mock_session: MagicMock +) -> None: + # Arrange + mock_session.query.return_value.filter_by.return_value.first.return_value = None + + # Act + result = TriggerProviderService.get_subscription_by_endpoint("endpoint-1") + + # Assert + assert result is None + + +def test_get_subscription_by_endpoint_should_decrypt_credentials_and_properties( + mocker: MockerFixture, + mock_session: MagicMock, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + tenant_id="tenant-1", + provider_id="langgenius/github/github", + credentials={"token": "enc"}, + properties={"hook": "enc"}, + ) + mock_session.query.return_value.filter_by.return_value.first.return_value = subscription + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_subscription", + return_value=(_encrypter_mock(decrypted={"token": "plain"}), MagicMock()), + ) + mocker.patch( + "services.trigger.trigger_provider_service.create_trigger_provider_encrypter_for_properties", + return_value=(_encrypter_mock(decrypted={"hook": "plain"}), MagicMock()), + ) + + # Act + result = TriggerProviderService.get_subscription_by_endpoint("endpoint-1") + + # Assert + assert result is subscription + assert subscription.credentials == {"token": "plain"} + assert subscription.properties == {"hook": "plain"} + + +def test_verify_subscription_credentials_should_raise_when_provider_not_found( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + _mock_get_trigger_provider(mocker, None) + + # Act + Assert + with pytest.raises(ValueError, match="Provider .* not found"): + TriggerProviderService.verify_subscription_credentials( + tenant_id="tenant-1", + user_id="user-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + ) + + +def test_verify_subscription_credentials_should_raise_when_subscription_not_found( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=None) + + # Act + Assert + with pytest.raises(ValueError, match="Subscription sub-1 not found"): + TriggerProviderService.verify_subscription_credentials( + tenant_id="tenant-1", + user_id="user-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + ) + + +def test_verify_subscription_credentials_should_raise_when_api_key_validation_fails( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace(credential_type=CredentialType.API_KEY.value, credentials={"api_key": "old"}) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + provider_controller.validate_credentials.side_effect = RuntimeError("bad credentials") + + # Act + Assert + with pytest.raises(ValueError, match="Invalid credentials: bad credentials"): + TriggerProviderService.verify_subscription_credentials( + tenant_id="tenant-1", + user_id="user-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={"api_key": HIDDEN_VALUE}, + ) + + +def test_verify_subscription_credentials_should_return_verified_when_api_key_validation_succeeds( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace(credential_type=CredentialType.API_KEY.value, credentials={"api_key": "old"}) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + + # Act + result = TriggerProviderService.verify_subscription_credentials( + tenant_id="tenant-1", + user_id="user-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={"api_key": HIDDEN_VALUE}, + ) + + # Assert + assert result == {"verified": True} + + +def test_verify_subscription_credentials_should_return_verified_for_non_api_key_credentials( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace(credential_type=CredentialType.OAUTH2.value, credentials={}) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + + # Act + result = TriggerProviderService.verify_subscription_credentials( + tenant_id="tenant-1", + user_id="user-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + ) + + # Assert + assert result == {"verified": True} + + +def test_rebuild_trigger_subscription_should_raise_when_provider_not_found( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, +) -> None: + # Arrange + _mock_get_trigger_provider(mocker, None) + + # Act + Assert + with pytest.raises(ValueError, match="Provider .* not found"): + TriggerProviderService.rebuild_trigger_subscription( + tenant_id="tenant-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + parameters={}, + ) + + +def test_rebuild_trigger_subscription_should_raise_when_subscription_not_found( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=None) + + # Act + Assert + with pytest.raises(ValueError, match="Subscription sub-1 not found"): + TriggerProviderService.rebuild_trigger_subscription( + tenant_id="tenant-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + parameters={}, + ) + + +def test_rebuild_trigger_subscription_should_raise_for_unsupported_credential_type( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace(credential_type=CredentialType.UNAUTHORIZED.value) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + + # Act + Assert + with pytest.raises(ValueError, match="not supported for auto creation"): + TriggerProviderService.rebuild_trigger_subscription( + tenant_id="tenant-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + parameters={}, + ) + + +def test_rebuild_trigger_subscription_should_raise_when_unsubscribe_fails( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-1", + user_id="user-1", + endpoint_id="endpoint-1", + credential_type=CredentialType.API_KEY.value, + credentials={"api_key": "old"}, + to_entity=lambda: SimpleNamespace(id="sub-1"), + ) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.unsubscribe_trigger", + return_value=SimpleNamespace(success=False, message="remote error"), + ) + + # Act + Assert + with pytest.raises(ValueError, match="Failed to delete previous subscription"): + TriggerProviderService.rebuild_trigger_subscription( + tenant_id="tenant-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={}, + parameters={}, + ) + + +def test_rebuild_trigger_subscription_should_resubscribe_and_update_existing_subscription( + mocker: MockerFixture, + mock_session: MagicMock, + provider_id: TriggerProviderID, + provider_controller: MagicMock, +) -> None: + # Arrange + subscription = SimpleNamespace( + id="sub-1", + user_id="user-1", + endpoint_id="endpoint-1", + credential_type=CredentialType.API_KEY.value, + credentials={"api_key": "old-key"}, + to_entity=lambda: SimpleNamespace(id="sub-1"), + ) + new_subscription = SimpleNamespace(properties={"project": "new"}, expires_at=888) + _mock_get_trigger_provider(mocker, provider_controller) + mocker.patch.object(TriggerProviderService, "get_subscription_by_id", return_value=subscription) + mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.unsubscribe_trigger", + return_value=SimpleNamespace(success=True, message="ok"), + ) + mock_subscribe = mocker.patch( + "services.trigger.trigger_provider_service.TriggerManager.subscribe_trigger", + return_value=new_subscription, + ) + mocker.patch( + "services.trigger.trigger_provider_service.generate_plugin_trigger_endpoint_url", + return_value="https://endpoint", + ) + mock_update = mocker.patch.object(TriggerProviderService, "update_trigger_subscription") + + # Act + TriggerProviderService.rebuild_trigger_subscription( + tenant_id="tenant-1", + provider_id=provider_id, + subscription_id="sub-1", + credentials={"api_key": HIDDEN_VALUE, "region": "us"}, + parameters={"event": "push"}, + name="updated", + ) + + # Assert + call_kwargs = mock_subscribe.call_args.kwargs + assert call_kwargs["credentials"]["api_key"] == "old-key" + assert call_kwargs["credentials"]["region"] == "us" + mock_update.assert_called_once_with( + tenant_id="tenant-1", + subscription_id="sub-1", + name="updated", + parameters={"event": "push"}, + credentials={"api_key": "old-key", "region": "us"}, + properties={"project": "new"}, + expires_at=888, + ) diff --git a/api/tests/unit_tests/services/test_variable_truncator.py b/api/tests/unit_tests/services/test_variable_truncator.py index c703ab64d06..9c231352256 100644 --- a/api/tests/unit_tests/services/test_variable_truncator.py +++ b/api/tests/unit_tests/services/test_variable_truncator.py @@ -16,10 +16,8 @@ from typing import Any from uuid import uuid4 import pytest - -from dify_graph.file.enums import FileTransferMethod, FileType -from dify_graph.file.models import File -from dify_graph.variables.segments import ( +from graphon.file import File, FileTransferMethod, FileType +from graphon.variables.segments import ( ArrayFileSegment, ArrayNumberSegment, ArraySegment, @@ -30,6 +28,7 @@ from dify_graph.variables.segments import ( ObjectSegment, StringSegment, ) + from services.variable_truncator import ( DummyVariableTruncator, MaxDepthExceededError, diff --git a/api/tests/unit_tests/services/test_vector_service.py b/api/tests/unit_tests/services/test_vector_service.py index 7b0103a2a14..598ff3fc3a4 100644 --- a/api/tests/unit_tests/services/test_vector_service.py +++ b/api/tests/unit_tests/services/test_vector_service.py @@ -9,6 +9,7 @@ from unittest.mock import MagicMock import pytest import services.vector_service as vector_service_module +from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType from services.vector_service import VectorService @@ -31,8 +32,8 @@ class _ParentDocStub: def _make_dataset( *, - indexing_technique: str = "high_quality", - doc_form: str = "text_model", + indexing_technique: str = IndexTechniqueType.HIGH_QUALITY, + doc_form: str = IndexStructureType.PARAGRAPH_INDEX, tenant_id: str = "tenant-1", dataset_id: str = "dataset-1", is_multimodal: bool = False, @@ -106,7 +107,7 @@ def test_create_segments_vector_regular_indexing_loads_documents_and_keywords(mo factory_instance.init_index_processor.return_value = index_processor monkeypatch.setattr(vector_service_module, "IndexProcessorFactory", MagicMock(return_value=factory_instance)) - VectorService.create_segments_vector([["k1"]], [segment], dataset, "text_model") + VectorService.create_segments_vector([["k1"]], [segment], dataset, IndexStructureType.PARAGRAPH_INDEX) index_processor.load.assert_called_once() args, kwargs = index_processor.load.call_args @@ -131,7 +132,7 @@ def test_create_segments_vector_regular_indexing_loads_multimodal_documents(monk factory_instance.init_index_processor.return_value = index_processor monkeypatch.setattr(vector_service_module, "IndexProcessorFactory", MagicMock(return_value=factory_instance)) - VectorService.create_segments_vector([["k1"]], [segment], dataset, "text_model") + VectorService.create_segments_vector([["k1"]], [segment], dataset, IndexStructureType.PARAGRAPH_INDEX) assert index_processor.load.call_count == 2 first_args, first_kwargs = index_processor.load.call_args_list[0] @@ -153,7 +154,7 @@ def test_create_segments_vector_with_no_segments_does_not_load(monkeypatch: pyte factory_instance.init_index_processor.return_value = index_processor monkeypatch.setattr(vector_service_module, "IndexProcessorFactory", MagicMock(return_value=factory_instance)) - VectorService.create_segments_vector(None, [], dataset, "text_model") + VectorService.create_segments_vector(None, [], dataset, IndexStructureType.PARAGRAPH_INDEX) index_processor.load.assert_not_called() @@ -191,7 +192,7 @@ def test_create_segments_vector_parent_child_calls_generate_child_chunks_with_ex dataset = _make_dataset( doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX, embedding_model_provider="openai", - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, ) segment = _make_segment() @@ -213,7 +214,9 @@ def test_create_segments_vector_parent_child_calls_generate_child_chunks_with_ex embedding_model_instance = MagicMock(name="embedding_model_instance") model_manager_instance = MagicMock(name="model_manager_instance") model_manager_instance.get_model_instance.return_value = embedding_model_instance - monkeypatch.setattr(vector_service_module, "ModelManager", MagicMock(return_value=model_manager_instance)) + monkeypatch.setattr( + vector_service_module.ModelManager, "for_tenant", MagicMock(return_value=model_manager_instance) + ) generate_child_chunks_mock = MagicMock() monkeypatch.setattr(VectorService, "generate_child_chunks", generate_child_chunks_mock) @@ -240,7 +243,7 @@ def test_create_segments_vector_parent_child_uses_default_embedding_model_when_p dataset = _make_dataset( doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX, embedding_model_provider=None, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, ) segment = _make_segment() @@ -261,7 +264,9 @@ def test_create_segments_vector_parent_child_uses_default_embedding_model_when_p embedding_model_instance = MagicMock() model_manager_instance = MagicMock() model_manager_instance.get_default_model_instance.return_value = embedding_model_instance - monkeypatch.setattr(vector_service_module, "ModelManager", MagicMock(return_value=model_manager_instance)) + monkeypatch.setattr( + vector_service_module.ModelManager, "for_tenant", MagicMock(return_value=model_manager_instance) + ) generate_child_chunks_mock = MagicMock() monkeypatch.setattr(VectorService, "generate_child_chunks", generate_child_chunks_mock) @@ -328,7 +333,7 @@ def test_create_segments_vector_parent_child_missing_processing_rule_raises(monk def test_create_segments_vector_parent_child_non_high_quality_raises(monkeypatch: pytest.MonkeyPatch) -> None: dataset = _make_dataset( doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX, - indexing_technique="economy", + indexing_technique=IndexTechniqueType.ECONOMY, ) segment = _make_segment() dataset_document = MagicMock() @@ -347,7 +352,7 @@ def test_create_segments_vector_parent_child_non_high_quality_raises(monkeypatch def test_update_segment_vector_high_quality_uses_vector(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY) segment = _make_segment() vector_instance = MagicMock() @@ -363,7 +368,7 @@ def test_update_segment_vector_high_quality_uses_vector(monkeypatch: pytest.Monk def test_update_segment_vector_economy_uses_keyword_with_keywords_list(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="economy") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY) segment = _make_segment() keyword_instance = MagicMock() @@ -379,7 +384,7 @@ def test_update_segment_vector_economy_uses_keyword_with_keywords_list(monkeypat def test_update_segment_vector_economy_uses_keyword_without_keywords_list(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="economy") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY) segment = _make_segment() keyword_instance = MagicMock() @@ -392,7 +397,7 @@ def test_update_segment_vector_economy_uses_keyword_without_keywords_list(monkey def test_generate_child_chunks_regenerate_cleans_then_saves_children(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(doc_form="text_model", tenant_id="tenant-1", dataset_id="dataset-1") + dataset = _make_dataset(doc_form=IndexStructureType.PARAGRAPH_INDEX, tenant_id="tenant-1", dataset_id="dataset-1") segment = _make_segment(segment_id="seg-1") dataset_document = MagicMock() @@ -439,7 +444,7 @@ def test_generate_child_chunks_regenerate_cleans_then_saves_children(monkeypatch def test_generate_child_chunks_commits_even_when_no_children(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(doc_form="text_model") + dataset = _make_dataset(doc_form=IndexStructureType.PARAGRAPH_INDEX) segment = _make_segment() dataset_document = MagicMock() dataset_document.doc_language = "en" @@ -472,7 +477,7 @@ def test_generate_child_chunks_commits_even_when_no_children(monkeypatch: pytest def test_create_child_chunk_vector_high_quality_adds_texts(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY) child_chunk = MagicMock() child_chunk.content = "child" child_chunk.index_node_id = "id" @@ -488,7 +493,7 @@ def test_create_child_chunk_vector_high_quality_adds_texts(monkeypatch: pytest.M def test_create_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="economy") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY) vector_cls = MagicMock() monkeypatch.setattr(vector_service_module, "Vector", vector_cls) @@ -504,7 +509,7 @@ def test_create_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch) def test_update_child_chunk_vector_high_quality_updates_vector(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY) new_chunk = MagicMock() new_chunk.content = "n" @@ -535,7 +540,7 @@ def test_update_child_chunk_vector_high_quality_updates_vector(monkeypatch: pyte def test_update_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="economy") + dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY) vector_cls = MagicMock() monkeypatch.setattr(vector_service_module, "Vector", vector_cls) VectorService.update_child_chunk_vector([], [], [], dataset) @@ -560,7 +565,7 @@ def test_delete_child_chunk_vector_deletes_by_id(monkeypatch: pytest.MonkeyPatch def test_update_multimodel_vector_returns_when_not_high_quality(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="economy", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY, is_multimodal=True) segment = _make_segment(tenant_id="t", attachments=[{"id": "a"}]) vector_cls = MagicMock() @@ -574,7 +579,7 @@ def test_update_multimodel_vector_returns_when_not_high_quality(monkeypatch: pyt def test_update_multimodel_vector_returns_when_no_actual_change(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True) segment = _make_segment(tenant_id="t", attachments=[{"id": "a"}, {"id": "b"}]) vector_cls = MagicMock() @@ -590,7 +595,7 @@ def test_update_multimodel_vector_returns_when_no_actual_change(monkeypatch: pyt def test_update_multimodel_vector_deletes_bindings_and_commits_on_empty_new_ids( monkeypatch: pytest.MonkeyPatch, ) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True) segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}, {"id": "old-2"}]) vector_instance = MagicMock(name="vector_instance") @@ -611,7 +616,7 @@ def test_update_multimodel_vector_deletes_bindings_and_commits_on_empty_new_ids( def test_update_multimodel_vector_commits_when_no_upload_files_found(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True) segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}]) vector_instance = MagicMock() @@ -629,7 +634,7 @@ def test_update_multimodel_vector_commits_when_no_upload_files_found(monkeypatch def test_update_multimodel_vector_adds_bindings_and_vectors_and_skips_missing_upload_files( monkeypatch: pytest.MonkeyPatch, ) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True) segment = _make_segment(segment_id="seg-1", tenant_id="tenant-1", attachments=[{"id": "old-1"}]) vector_instance = MagicMock() @@ -662,7 +667,7 @@ def test_update_multimodel_vector_adds_bindings_and_vectors_and_skips_missing_up def test_update_multimodel_vector_updates_bindings_without_multimodal_vector_ops( monkeypatch: pytest.MonkeyPatch, ) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=False) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=False) segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}]) vector_instance = MagicMock() @@ -682,7 +687,7 @@ def test_update_multimodel_vector_updates_bindings_without_multimodal_vector_ops def test_update_multimodel_vector_rolls_back_and_reraises_on_error(monkeypatch: pytest.MonkeyPatch) -> None: - dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True) + dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True) segment = _make_segment(segment_id="seg-1", tenant_id="tenant-1", attachments=[{"id": "old-1"}]) vector_instance = MagicMock() diff --git a/api/tests/unit_tests/services/test_workflow_run_service_pause.py b/api/tests/unit_tests/services/test_workflow_run_service_pause.py index 27664c7e294..a62c9f45556 100644 --- a/api/tests/unit_tests/services/test_workflow_run_service_pause.py +++ b/api/tests/unit_tests/services/test_workflow_run_service_pause.py @@ -13,10 +13,10 @@ from datetime import datetime from unittest.mock import MagicMock, create_autospec, patch import pytest +from graphon.enums import WorkflowExecutionStatus from sqlalchemy import Engine from sqlalchemy.orm import Session, sessionmaker -from dify_graph.enums import WorkflowExecutionStatus from models.workflow import WorkflowPause from repositories.api_workflow_run_repository import APIWorkflowRunRepository from repositories.sqlalchemy_api_workflow_run_repository import _PrivateWorkflowPauseEntity diff --git a/api/tests/unit_tests/services/test_workflow_service.py b/api/tests/unit_tests/services/test_workflow_service.py index 57c0464dc62..cd71981bcf1 100644 --- a/api/tests/unit_tests/services/test_workflow_service.py +++ b/api/tests/unit_tests/services/test_workflow_service.py @@ -10,18 +10,37 @@ This test suite covers: """ import json -from unittest.mock import MagicMock, patch +import uuid +from typing import Any, cast +from unittest.mock import ANY, MagicMock, patch import pytest +from graphon.entities import WorkflowNodeExecution +from graphon.enums import ( + BuiltinNodeTypes, + ErrorStrategy, + WorkflowNodeExecutionMetadataKey, + WorkflowNodeExecutionStatus, +) +from graphon.errors import WorkflowNodeRunFailedError +from graphon.graph_events import NodeRunFailedEvent, NodeRunSucceededEvent +from graphon.model_runtime.entities.model_entities import ModelType +from graphon.node_events import NodeRunResult +from graphon.nodes.http_request import HTTP_REQUEST_CONFIG_FILTER_KEY, HttpRequestNode, HttpRequestNodeConfig +from graphon.variables.input_entities import VariableEntityType -from dify_graph.enums import BuiltinNodeTypes -from dify_graph.nodes.http_request import HTTP_REQUEST_CONFIG_FILTER_KEY, HttpRequestNode, HttpRequestNodeConfig from libs.datetime_utils import naive_utc_now +from models.human_input import RecipientType from models.model import App, AppMode from models.workflow import Workflow, WorkflowType from services.errors.app import IsDraftWorkflowError, TriggerNodeLimitExceededError, WorkflowHashNotEqualError from services.errors.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError -from services.workflow_service import WorkflowService +from services.workflow_service import ( + WorkflowService, + _rebuild_file_for_user_inputs_in_start_node, + _rebuild_single_file, + _setup_variable_pool, +) class TestWorkflowAssociatedDataFactory: @@ -544,6 +563,89 @@ class TestWorkflowService: conversation_variables=[], ) + def test_restore_published_workflow_to_draft_keeps_source_features_unmodified( + self, workflow_service, mock_db_session + ): + app = TestWorkflowAssociatedDataFactory.create_app_mock() + account = TestWorkflowAssociatedDataFactory.create_account_mock() + legacy_features = { + "file_upload": { + "image": { + "enabled": True, + "number_limits": 6, + "transfer_methods": ["remote_url", "local_file"], + } + }, + "opening_statement": "", + "retriever_resource": {"enabled": True}, + "sensitive_word_avoidance": {"enabled": False}, + "speech_to_text": {"enabled": False}, + "suggested_questions": [], + "suggested_questions_after_answer": {"enabled": False}, + "text_to_speech": {"enabled": False, "language": "", "voice": ""}, + } + normalized_features = { + "file_upload": { + "enabled": True, + "allowed_file_types": ["image"], + "allowed_file_extensions": [], + "allowed_file_upload_methods": ["remote_url", "local_file"], + "number_limits": 6, + }, + "opening_statement": "", + "retriever_resource": {"enabled": True}, + "sensitive_word_avoidance": {"enabled": False}, + "speech_to_text": {"enabled": False}, + "suggested_questions": [], + "suggested_questions_after_answer": {"enabled": False}, + "text_to_speech": {"enabled": False, "language": "", "voice": ""}, + } + source_workflow = Workflow( + id="published-workflow-id", + tenant_id=app.tenant_id, + app_id=app.id, + type=WorkflowType.WORKFLOW.value, + version="2026-03-19T00:00:00", + graph=json.dumps(TestWorkflowAssociatedDataFactory.create_valid_workflow_graph()), + features=json.dumps(legacy_features), + created_by=account.id, + environment_variables=[], + conversation_variables=[], + rag_pipeline_variables=[], + ) + draft_workflow = Workflow( + id="draft-workflow-id", + tenant_id=app.tenant_id, + app_id=app.id, + type=WorkflowType.WORKFLOW.value, + version=Workflow.VERSION_DRAFT, + graph=json.dumps({"nodes": [], "edges": []}), + features=json.dumps({}), + created_by=account.id, + environment_variables=[], + conversation_variables=[], + rag_pipeline_variables=[], + ) + + with ( + patch.object(workflow_service, "get_published_workflow_by_id", return_value=source_workflow), + patch.object(workflow_service, "get_draft_workflow", return_value=draft_workflow), + patch.object(workflow_service, "validate_graph_structure"), + patch.object(workflow_service, "validate_features_structure") as mock_validate_features, + patch("services.workflow_service.app_draft_workflow_was_synced"), + ): + result = workflow_service.restore_published_workflow_to_draft( + app_model=app, + workflow_id=source_workflow.id, + account=account, + ) + + mock_validate_features.assert_called_once_with(app_model=app, features=normalized_features) + assert result is draft_workflow + assert source_workflow.serialized_features == json.dumps(legacy_features) + assert draft_workflow.serialized_features == json.dumps(legacy_features) + mock_db_session.session.commit.assert_called_once() + # ==================== Workflow Validation Tests ==================== # These tests verify graph structure and feature configuration validation @@ -1226,3 +1328,1460 @@ class TestWorkflowService: with pytest.raises(ValueError, match="not supported convert to workflow"): workflow_service.convert_to_workflow(app, account, args) + + +# =========================================================================== +# TestWorkflowServiceCredentialValidation +# Tests for _validate_workflow_credentials and related private helpers +# =========================================================================== + + +class TestWorkflowServiceCredentialValidation: + """ + Tests for the private credential-validation helpers on WorkflowService. + + These helpers gate `publish_workflow` when `PluginManager` is enabled. + Each test focuses on a distinct branch inside `_validate_workflow_credentials`, + `_validate_llm_model_config`, `_check_default_tool_credential`, and the + load-balancing path. + """ + + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + @staticmethod + def _make_workflow(nodes: list[dict]) -> MagicMock: + wf = MagicMock(spec=Workflow) + wf.tenant_id = "tenant-1" + wf.app_id = "app-1" + wf.graph_dict = {"nodes": nodes} + return wf + + # --- _validate_workflow_credentials: tool node (with credential_id) --- + + def test_validate_workflow_credentials_should_check_tool_credential_when_credential_id_present( + self, service: WorkflowService + ) -> None: + # Arrange + nodes = [ + { + "id": "tool-node", + "data": { + "type": "tool", + "provider_id": "my-provider", + "credential_id": "cred-123", + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + Assert + with patch("core.helper.credential_utils.check_credential_policy_compliance") as mock_check: + # Should not raise; mock allows the call + service._validate_workflow_credentials(workflow) + mock_check.assert_called_once() + + def test_validate_workflow_credentials_should_check_default_credential_when_no_credential_id( + self, service: WorkflowService + ) -> None: + # Arrange + nodes = [ + { + "id": "tool-node", + "data": { + "type": "tool", + "provider_id": "my-provider", + # No credential_id — should fall back to default + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + with patch.object(service, "_check_default_tool_credential") as mock_default: + service._validate_workflow_credentials(workflow) + + # Assert + mock_default.assert_called_once_with("tenant-1", "my-provider") + + def test_validate_workflow_credentials_should_skip_tool_node_without_provider( + self, service: WorkflowService + ) -> None: + """Tool nodes without a provider_id should be silently skipped.""" + # Arrange + nodes = [{"id": "tool-node", "data": {"type": "tool"}}] + workflow = self._make_workflow(nodes) + + # Act + Assert (no error raised) + with patch.object(service, "_check_default_tool_credential") as mock_default: + service._validate_workflow_credentials(workflow) + mock_default.assert_not_called() + + def test_validate_workflow_credentials_should_validate_llm_node_with_model_config( + self, service: WorkflowService + ) -> None: + # Arrange + nodes = [ + { + "id": "llm-node", + "data": { + "type": "llm", + "model": {"provider": "openai", "name": "gpt-4"}, + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + with ( + patch.object(service, "_validate_llm_model_config") as mock_llm, + patch.object(service, "_validate_load_balancing_credentials"), + ): + service._validate_workflow_credentials(workflow) + + # Assert + mock_llm.assert_called_once_with("tenant-1", "openai", "gpt-4") + + def test_validate_workflow_credentials_should_raise_for_llm_node_missing_model( + self, service: WorkflowService + ) -> None: + """LLM nodes without provider AND name should raise ValueError.""" + # Arrange + nodes = [ + { + "id": "llm-node", + "data": {"type": "llm", "model": {"provider": "openai"}}, # name missing + } + ] + workflow = self._make_workflow(nodes) + + # Act + Assert + with pytest.raises(ValueError, match="Missing provider or model configuration"): + service._validate_workflow_credentials(workflow) + + def test_validate_workflow_credentials_should_wrap_unexpected_exception_in_value_error( + self, service: WorkflowService + ) -> None: + """Non-ValueError exceptions from validation must be re-raised as ValueError.""" + # Arrange + nodes = [ + { + "id": "llm-node", + "data": { + "type": "llm", + "model": {"provider": "openai", "name": "gpt-4"}, + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + Assert + with patch.object(service, "_validate_llm_model_config", side_effect=RuntimeError("boom")): + with pytest.raises(ValueError, match="boom"): + service._validate_workflow_credentials(workflow) + + def test_validate_workflow_credentials_should_validate_agent_node_model(self, service: WorkflowService) -> None: + # Arrange + nodes = [ + { + "id": "agent-node", + "data": { + "type": "agent", + "agent_parameters": { + "model": {"value": {"provider": "openai", "model": "gpt-4"}}, + "tools": {"value": []}, + }, + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + with ( + patch.object(service, "_validate_llm_model_config") as mock_llm, + patch.object(service, "_validate_load_balancing_credentials"), + ): + service._validate_workflow_credentials(workflow) + + # Assert + mock_llm.assert_called_once_with("tenant-1", "openai", "gpt-4") + + def test_validate_workflow_credentials_should_validate_agent_tools(self, service: WorkflowService) -> None: + """Each agent tool with a provider should be checked for credential compliance.""" + # Arrange + nodes = [ + { + "id": "agent-node", + "data": { + "type": "agent", + "agent_parameters": { + "model": {"value": {}}, # no model config + "tools": { + "value": [ + {"provider_name": "provider-a", "credential_id": "cred-a"}, + {"provider_name": "provider-b"}, # uses default + ] + }, + }, + }, + } + ] + workflow = self._make_workflow(nodes) + + # Act + with ( + patch("core.helper.credential_utils.check_credential_policy_compliance") as mock_check, + patch.object(service, "_check_default_tool_credential") as mock_default, + ): + service._validate_workflow_credentials(workflow) + + # Assert + mock_check.assert_called_once() # provider-a has credential_id + mock_default.assert_called_once_with("tenant-1", "provider-b") + + # --- _validate_llm_model_config --- + + def test_validate_llm_model_config_should_raise_value_error_on_failure(self, service: WorkflowService) -> None: + """If ModelManager raises any exception it must be wrapped into ValueError.""" + # Arrange + assembly = MagicMock() + assembly.model_manager.get_model_instance.side_effect = RuntimeError("no key") + + with patch("services.workflow_service.create_plugin_model_assembly", return_value=assembly): + # Act + Assert + with pytest.raises(ValueError, match="Failed to validate LLM model configuration"): + service._validate_llm_model_config("tenant-1", "openai", "gpt-4") + + def test_validate_llm_model_config_success(self, service: WorkflowService) -> None: + """Test success path with ProviderManager and Model entities.""" + mock_model = MagicMock() + mock_model.model = "gpt-4" + mock_model.provider.provider = "openai" + + mock_configs = MagicMock() + mock_configs.get_models.return_value = [mock_model] + assembly = MagicMock() + assembly.provider_manager.get_configurations.return_value = mock_configs + + with patch("services.workflow_service.create_plugin_model_assembly", return_value=assembly): + # Act + service._validate_llm_model_config("tenant-1", "openai", "gpt-4") + + # Assert + mock_model.raise_for_status.assert_called_once() + assembly.model_manager.get_model_instance.assert_called_once_with( + tenant_id="tenant-1", + provider="openai", + model_type=ModelType.LLM, + model="gpt-4", + ) + + def test_validate_llm_model_config_model_not_found(self, service: WorkflowService) -> None: + """Test ValueError when model is not found in provider configurations.""" + mock_configs = MagicMock() + mock_configs.get_models.return_value = [] # No models + assembly = MagicMock() + assembly.provider_manager.get_configurations.return_value = mock_configs + + with patch("services.workflow_service.create_plugin_model_assembly", return_value=assembly): + # Act + Assert + with pytest.raises(ValueError, match="Model gpt-4 not found for provider openai"): + service._validate_llm_model_config("tenant-1", "openai", "gpt-4") + + # --- _check_default_tool_credential --- + + def test_check_default_tool_credential_should_silently_pass_when_no_provider_found( + self, service: WorkflowService + ) -> None: + """Missing BuiltinToolProvider → plugin requires no credentials → no error.""" + # Arrange + with patch("services.workflow_service.db") as mock_db: + mock_db.session.query.return_value.where.return_value.order_by.return_value.first.return_value = None + + # Act + Assert (should NOT raise) + service._check_default_tool_credential("tenant-1", "some-provider") + + def test_check_default_tool_credential_should_raise_when_compliance_fails(self, service: WorkflowService) -> None: + # Arrange + mock_provider = MagicMock() + mock_provider.id = "builtin-cred-id" + with ( + patch("services.workflow_service.db") as mock_db, + patch("core.helper.credential_utils.check_credential_policy_compliance", side_effect=Exception("denied")), + ): + mock_db.session.query.return_value.where.return_value.order_by.return_value.first.return_value = ( + mock_provider + ) + + # Act + Assert + with pytest.raises(ValueError, match="Failed to validate default credential"): + service._check_default_tool_credential("tenant-1", "some-provider") + + # --- _is_load_balancing_enabled --- + + def test_is_load_balancing_enabled_should_return_false_when_provider_not_found( + self, service: WorkflowService + ) -> None: + # Arrange + with patch("services.workflow_service.db"): + service_instance = WorkflowService() + + with patch("core.provider_manager.ProviderManager.get_configurations") as mock_get_configs: + mock_configs = MagicMock() + mock_configs.get.return_value = None # provider not found + mock_get_configs.return_value = mock_configs + + # Act + result = service_instance._is_load_balancing_enabled("tenant-1", "openai", "gpt-4") + + # Assert + assert result is False + + def test_is_load_balancing_enabled_should_return_true_when_setting_enabled(self, service: WorkflowService) -> None: + # Arrange + with patch("core.provider_manager.ProviderManager.get_configurations") as mock_get_configs: + mock_provider_config = MagicMock() + mock_provider_model_setting = MagicMock() + mock_provider_model_setting.load_balancing_enabled = True + mock_provider_config.get_provider_model_setting.return_value = mock_provider_model_setting + + mock_configs = MagicMock() + mock_configs.get.return_value = mock_provider_config + mock_get_configs.return_value = mock_configs + + # Act + result = service._is_load_balancing_enabled("tenant-1", "openai", "gpt-4") + + # Assert + assert result is True + + def test_is_load_balancing_enabled_should_return_false_on_exception(self, service: WorkflowService) -> None: + """Any exception should be swallowed and return False.""" + # Arrange + with patch("core.provider_manager.ProviderManager.get_configurations", side_effect=RuntimeError("db down")): + # Act + result = service._is_load_balancing_enabled("tenant-1", "openai", "gpt-4") + + # Assert + assert result is False + + # --- _get_load_balancing_configs --- + + def test_get_load_balancing_configs_should_return_empty_list_on_exception(self, service: WorkflowService) -> None: + """Any exception during LB config retrieval should return an empty list.""" + # Arrange + with patch( + "services.model_load_balancing_service.ModelLoadBalancingService.get_load_balancing_configs", + side_effect=RuntimeError("fail"), + ): + # Act + result = service._get_load_balancing_configs("tenant-1", "openai", "gpt-4") + + # Assert + assert result == [] + + def test_get_load_balancing_configs_should_merge_predefined_and_custom(self, service: WorkflowService) -> None: + # Arrange + predefined = [{"credential_id": "cred-a"}, {"credential_id": None}] + custom = [{"credential_id": "cred-b"}] + with patch( + "services.model_load_balancing_service.ModelLoadBalancingService.get_load_balancing_configs", + side_effect=[ + (None, predefined), # first call: predefined-model + (None, custom), # second call: custom-model + ], + ): + # Act + result = service._get_load_balancing_configs("tenant-1", "openai", "gpt-4") + + # Assert — only entries with a credential_id should be returned + assert len(result) == 2 + assert all(c["credential_id"] for c in result) + + # --- _validate_load_balancing_credentials --- + + def test_validate_load_balancing_credentials_should_skip_when_no_model_config( + self, service: WorkflowService + ) -> None: + """Missing provider or model in node_data should be a no-op.""" + # Arrange + workflow = self._make_workflow([]) + node_data: dict = {} # no model key + + # Act + Assert (no error expected) + service._validate_load_balancing_credentials(workflow, node_data, "node-1") + + def test_validate_load_balancing_credentials_should_skip_when_lb_not_enabled( + self, service: WorkflowService + ) -> None: + # Arrange + workflow = self._make_workflow([]) + node_data = {"model": {"provider": "openai", "name": "gpt-4"}} + + # Act + Assert (no error expected) + with patch.object(service, "_is_load_balancing_enabled", return_value=False): + service._validate_load_balancing_credentials(workflow, node_data, "node-1") + + def test_validate_load_balancing_credentials_should_raise_when_compliance_fails( + self, service: WorkflowService + ) -> None: + # Arrange + workflow = self._make_workflow([]) + node_data = {"model": {"provider": "openai", "name": "gpt-4"}} + lb_configs = [{"credential_id": "cred-lb-1"}] + + # Act + Assert + with ( + patch.object(service, "_is_load_balancing_enabled", return_value=True), + patch.object(service, "_get_load_balancing_configs", return_value=lb_configs), + patch( + "core.helper.credential_utils.check_credential_policy_compliance", + side_effect=Exception("policy violation"), + ), + ): + with pytest.raises(ValueError, match="Invalid load balancing credentials"): + service._validate_load_balancing_credentials(workflow, node_data, "node-1") + + +# =========================================================================== +# TestWorkflowServiceExecutionHelpers +# Tests for _apply_error_strategy, _populate_execution_result, _execute_node_safely +# =========================================================================== + + +class TestWorkflowServiceExecutionHelpers: + """ + Tests for the private execution-result handling methods: + _apply_error_strategy, _populate_execution_result, _execute_node_safely. + """ + + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + # --- _apply_error_strategy --- + + def test_apply_error_strategy_should_return_exception_status_noderunresult(self, service: WorkflowService) -> None: + # Arrange + node = MagicMock() + node.error_strategy = ErrorStrategy.FAIL_BRANCH + node.default_value_dict = {} + original = NodeRunResult( + status=WorkflowNodeExecutionStatus.FAILED, + error="something went wrong", + error_type="SomeError", + inputs={"x": 1}, + outputs={}, + ) + + # Act + result = service._apply_error_strategy(node, original) + + # Assert + assert result.status == WorkflowNodeExecutionStatus.EXCEPTION + assert result.error == "something went wrong" + assert result.metadata[WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY] == ErrorStrategy.FAIL_BRANCH + + def test_apply_error_strategy_should_include_default_values_for_default_value_strategy( + self, service: WorkflowService + ) -> None: + # Arrange + node = MagicMock() + node.error_strategy = ErrorStrategy.DEFAULT_VALUE + node.default_value_dict = {"output_key": "fallback"} + original = NodeRunResult( + status=WorkflowNodeExecutionStatus.FAILED, + error="err", + ) + + # Act + result = service._apply_error_strategy(node, original) + + # Assert + assert result.outputs.get("output_key") == "fallback" + assert result.status == WorkflowNodeExecutionStatus.EXCEPTION + + # --- _populate_execution_result --- + + def test_populate_execution_result_should_set_succeeded_fields_when_run_succeeded( + self, service: WorkflowService + ) -> None: + # Arrange + node_execution = MagicMock(error=None) + node_run_result = NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, + inputs={"q": "hello"}, + process_data={"steps": 3}, + outputs={"answer": "hi"}, + metadata={WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: 10}, + ) + + # Act + with patch("services.workflow_service.WorkflowEntry.handle_special_values", side_effect=lambda x: x): + service._populate_execution_result(node_execution, node_run_result, True, None) + + # Assert + assert node_execution.status == WorkflowNodeExecutionStatus.SUCCEEDED + assert node_execution.outputs == {"answer": "hi"} + assert node_execution.error is None # SUCCEEDED status doesn't set error + + def test_populate_execution_result_should_set_failed_status_and_error_when_not_succeeded( + self, service: WorkflowService + ) -> None: + # Arrange + node_execution = MagicMock(error=None) + + # Act + service._populate_execution_result(node_execution, None, False, "catastrophic failure") + + # Assert + assert node_execution.status == WorkflowNodeExecutionStatus.FAILED + assert node_execution.error == "catastrophic failure" + + def test_populate_execution_result_should_set_error_field_for_exception_status( + self, service: WorkflowService + ) -> None: + """A succeeded=True result with EXCEPTION status should still populate the error field.""" + # Arrange + node_execution = MagicMock() + node_run_result = NodeRunResult( + status=WorkflowNodeExecutionStatus.EXCEPTION, + error="constraint violated", + ) + + # Act + with patch("services.workflow_service.WorkflowEntry.handle_special_values", side_effect=lambda x: x): + service._populate_execution_result(node_execution, node_run_result, True, None) + + # Assert + assert node_execution.status == WorkflowNodeExecutionStatus.EXCEPTION + assert node_execution.error == "constraint violated" + + # --- _execute_node_safely --- + + def test_execute_node_safely_should_return_succeeded_result_on_happy_path(self, service: WorkflowService) -> None: + # Arrange + node = MagicMock() + node.error_strategy = None + node_run_result = MagicMock() + node_run_result.status = WorkflowNodeExecutionStatus.SUCCEEDED + node_run_result.error = None + + succeeded_event = MagicMock(spec=NodeRunSucceededEvent) + succeeded_event.node_run_result = node_run_result + + def invoke_fn(): + def _gen(): + yield succeeded_event + + return node, _gen() + + # Act + out_node, out_result, run_succeeded, error = service._execute_node_safely(invoke_fn) + + # Assert + assert out_node is node + assert run_succeeded is True + assert error is None + + def test_execute_node_safely_should_return_failed_result_on_failed_event(self, service: WorkflowService) -> None: + # Arrange + node = MagicMock() + node.error_strategy = None + node_run_result = MagicMock() + node_run_result.status = WorkflowNodeExecutionStatus.FAILED + node_run_result.error = "node exploded" + + failed_event = MagicMock(spec=NodeRunFailedEvent) + failed_event.node_run_result = node_run_result + + def invoke_fn(): + def _gen(): + yield failed_event + + return node, _gen() + + # Act + _, _, run_succeeded, error = service._execute_node_safely(invoke_fn) + + # Assert + assert run_succeeded is False + assert error == "node exploded" + + def test_execute_node_safely_should_handle_workflow_node_run_failed_error(self, service: WorkflowService) -> None: + # Arrange + node = MagicMock() + exc = WorkflowNodeRunFailedError(node, "runtime failure") + + def invoke_fn(): + raise exc + + # Act + out_node, out_result, run_succeeded, error = service._execute_node_safely(invoke_fn) + + # Assert + assert out_node is node + assert out_result is None + assert run_succeeded is False + assert error == "runtime failure" + + def test_execute_node_safely_should_raise_when_no_result_event(self, service: WorkflowService) -> None: + """If the generator produces no NodeRunSucceededEvent/NodeRunFailedEvent, ValueError is expected.""" + # Arrange + node = MagicMock() + node.error_strategy = None + + def invoke_fn(): + def _gen(): + yield from [] + + return node, _gen() + + # Act + Assert + with pytest.raises(ValueError, match="no result returned"): + service._execute_node_safely(invoke_fn) + + # --- _apply_error_strategy with FAIL_BRANCH strategy --- + + def test_execute_node_safely_should_apply_error_strategy_on_failed_status(self, service: WorkflowService) -> None: + # Arrange + node = MagicMock() + node.error_strategy = ErrorStrategy.FAIL_BRANCH + node.default_value_dict = {} + + original_result = MagicMock() + original_result.status = WorkflowNodeExecutionStatus.FAILED + original_result.error = "oops" + original_result.error_type = "ValueError" + original_result.inputs = {} + + failed_event = MagicMock(spec=NodeRunFailedEvent) + failed_event.node_run_result = original_result + + def invoke_fn(): + def _gen(): + yield failed_event + + return node, _gen() + + # Act + _, result, run_succeeded, _ = service._execute_node_safely(invoke_fn) + + # Assert — after applying error strategy status becomes EXCEPTION + assert result is not None + assert result.status == WorkflowNodeExecutionStatus.EXCEPTION + # run_succeeded should be True because EXCEPTION is in the succeeded set + assert run_succeeded is True + + +# =========================================================================== +# TestWorkflowServiceGetNodeLastRun +# Tests for get_node_last_run delegation to repository +# =========================================================================== + + +class TestWorkflowServiceGetNodeLastRun: + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + def test_get_node_last_run_should_delegate_to_repository(self, service: WorkflowService) -> None: + # Arrange + app = MagicMock(spec=App) + app.tenant_id = "tenant-1" + app.id = "app-1" + workflow = MagicMock(spec=Workflow) + workflow.id = "wf-1" + expected = MagicMock() + + service._node_execution_service_repo = MagicMock() + service._node_execution_service_repo.get_node_last_execution.return_value = expected + + # Act + result = service.get_node_last_run(app, workflow, "node-42") + + # Assert + assert result is expected + service._node_execution_service_repo.get_node_last_execution.assert_called_once_with( + tenant_id="tenant-1", + app_id="app-1", + workflow_id="wf-1", + node_id="node-42", + ) + + def test_get_node_last_run_should_return_none_when_repository_returns_none(self, service: WorkflowService) -> None: + # Arrange + app = MagicMock(spec=App) + app.tenant_id = "t" + app.id = "a" + workflow = MagicMock(spec=Workflow) + workflow.id = "w" + service._node_execution_service_repo = MagicMock() + service._node_execution_service_repo.get_node_last_execution.return_value = None + + # Act + result = service.get_node_last_run(app, workflow, "node-x") + + # Assert + assert result is None + + +# =========================================================================== +# TestWorkflowServiceModuleLevelHelpers +# Tests for module-level helper functions exported from workflow_service +# =========================================================================== + + +class TestSetupVariablePool: + """ + Tests for the module-level `_setup_variable_pool` function. + This helper initialises the VariablePool used for single-step workflow execution. + """ + + def _make_workflow(self, workflow_type: str = WorkflowType.WORKFLOW.value) -> MagicMock: + wf = MagicMock(spec=Workflow) + wf.app_id = "app-1" + wf.id = "wf-1" + wf.type = workflow_type + wf.environment_variables = [] + return wf + + def test_setup_variable_pool_should_use_full_system_variables_for_start_node( + self, + ) -> None: + # Arrange + workflow = self._make_workflow() + + # Act + with ( + patch("services.workflow_service.VariablePool") as MockPool, + patch("services.workflow_service.build_system_variables") as mock_build_system_variables, + patch("services.workflow_service.build_bootstrap_variables") as mock_build_bootstrap_variables, + patch("services.workflow_service.add_variables_to_pool") as mock_add_variables_to_pool, + patch("services.workflow_service.add_node_inputs_to_pool") as mock_add_node_inputs_to_pool, + ): + _setup_variable_pool( + query="hello", + files=[], + user_id="u-1", + user_inputs={"k": "v"}, + workflow=workflow, + node_id="start-node", + node_type=BuiltinNodeTypes.START, + conversation_id="conv-1", + conversation_variables=[], + ) + + # Assert — start nodes should build bootstrap variables and attach node inputs. + MockPool.assert_called_once_with() + mock_build_system_variables.assert_called_once() + mock_add_variables_to_pool.assert_called_once_with( + MockPool.return_value, + mock_build_bootstrap_variables.return_value, + ) + mock_add_node_inputs_to_pool.assert_called_once_with( + MockPool.return_value, + node_id="start-node", + inputs={"k": "v"}, + ) + + def test_setup_variable_pool_should_use_default_system_variables_for_non_start_node( + self, + ) -> None: + # Arrange + workflow = self._make_workflow() + + # Act + with ( + patch("services.workflow_service.VariablePool") as MockPool, + patch("services.workflow_service.default_system_variables") as mock_default_system_variables, + patch("services.workflow_service.build_bootstrap_variables") as mock_build_bootstrap_variables, + patch("services.workflow_service.add_variables_to_pool") as mock_add_variables_to_pool, + patch("services.workflow_service.add_node_inputs_to_pool") as mock_add_node_inputs_to_pool, + ): + _setup_variable_pool( + query="", + files=[], + user_id="u-1", + user_inputs={}, + workflow=workflow, + node_id="llm-node", + node_type=BuiltinNodeTypes.LLM, # not a start/trigger node + conversation_id="conv-1", + conversation_variables=[], + ) + + # Assert — default system variables should be used and node inputs should not be added. + mock_default_system_variables.assert_called_once() + MockPool.assert_called_once_with() + mock_add_variables_to_pool.assert_called_once_with( + MockPool.return_value, + mock_build_bootstrap_variables.return_value, + ) + mock_add_node_inputs_to_pool.assert_not_called() + + def test_setup_variable_pool_should_set_chatflow_specifics_for_non_workflow_type( + self, + ) -> None: + """For ADVANCED_CHAT workflows on a START node, query/conversation_id/dialogue_count should be set.""" + from models.workflow import WorkflowType + + # Arrange + workflow = self._make_workflow(workflow_type=WorkflowType.CHAT.value) + + # Act + with ( + patch("services.workflow_service.VariablePool") as MockPool, + patch("services.workflow_service.build_system_variables") as mock_build_system_variables, + patch("services.workflow_service.build_bootstrap_variables"), + patch("services.workflow_service.add_variables_to_pool"), + patch("services.workflow_service.add_node_inputs_to_pool"), + ): + _setup_variable_pool( + query="what is AI?", + files=[], + user_id="u-1", + user_inputs={}, + workflow=workflow, + node_id="start-node", + node_type=BuiltinNodeTypes.START, + conversation_id="conv-abc", + conversation_variables=[], + ) + + # Assert — chatflow system variables should include query, conversation_id and dialogue_count. + MockPool.assert_called_once_with() + system_variable_values = mock_build_system_variables.call_args.args[0] + assert system_variable_values["query"] == "what is AI?" + assert system_variable_values["conversation_id"] == "conv-abc" + assert system_variable_values["dialogue_count"] == 1 + + +class TestRebuildSingleFile: + """ + Tests for the module-level `_rebuild_single_file` function. + Ensures correct delegation to `build_from_mapping` / `build_from_mappings`. + """ + + def test_rebuild_single_file_should_call_build_from_mapping_for_file_type( + self, + ) -> None: + # Arrange + tenant_id = "tenant-1" + value = {"url": "https://example.com/file.pdf", "type": "document"} + mock_file = MagicMock() + + # Act + with patch("services.workflow_service.build_from_mapping", return_value=mock_file) as mock_build: + result = _rebuild_single_file(tenant_id, value, VariableEntityType.FILE) + + # Assert + assert result is mock_file + mock_build.assert_called_once_with(mapping=value, tenant_id=tenant_id, access_controller=ANY) + + def test_rebuild_single_file_should_raise_when_file_value_not_dict( + self, + ) -> None: + # Arrange + Act + Assert + with pytest.raises(ValueError, match="expected dict for file object"): + _rebuild_single_file("tenant-1", "not-a-dict", VariableEntityType.FILE) + + def test_rebuild_single_file_should_call_build_from_mappings_for_file_list( + self, + ) -> None: + # Arrange + tenant_id = "tenant-1" + value = [{"url": "https://example.com/a.pdf"}, {"url": "https://example.com/b.pdf"}] + mock_files = [MagicMock(), MagicMock()] + + # Act + with patch("services.workflow_service.build_from_mappings", return_value=mock_files) as mock_build: + result = _rebuild_single_file(tenant_id, value, VariableEntityType.FILE_LIST) + + # Assert + assert result is mock_files + mock_build.assert_called_once_with(mappings=value, tenant_id=tenant_id, access_controller=ANY) + + def test_rebuild_single_file_should_raise_when_file_list_value_not_list( + self, + ) -> None: + # Arrange + Act + Assert + with pytest.raises(ValueError, match="expected list for file list object"): + _rebuild_single_file("tenant-1", "not-a-list", VariableEntityType.FILE_LIST) + + def test_rebuild_single_file_should_return_empty_list_for_empty_file_list( + self, + ) -> None: + # Arrange + Act + result = _rebuild_single_file("tenant-1", [], VariableEntityType.FILE_LIST) + + # Assert + assert result == [] + + def test_rebuild_single_file_should_raise_when_first_element_not_dict( + self, + ) -> None: + # Arrange + Act + Assert + with pytest.raises(ValueError, match="expected dict for first element"): + _rebuild_single_file("tenant-1", ["not-a-dict"], VariableEntityType.FILE_LIST) + + +class TestRebuildFileForUserInputsInStartNode: + """ + Tests for the module-level `_rebuild_file_for_user_inputs_in_start_node` function. + """ + + def _make_start_node_data(self, variables: list) -> MagicMock: + start_data = MagicMock() + start_data.variables = variables + return start_data + + def _make_variable(self, name: str, var_type: VariableEntityType) -> MagicMock: + var = MagicMock() + var.variable = name + var.type = var_type + return var + + def test_rebuild_should_pass_through_non_file_variables( + self, + ) -> None: + # Arrange + text_var = self._make_variable("query", VariableEntityType.TEXT_INPUT) + start_data = self._make_start_node_data([text_var]) + user_inputs = {"query": "hello world"} + + # Act + result = _rebuild_file_for_user_inputs_in_start_node( + tenant_id="tenant-1", + start_node_data=start_data, + user_inputs=user_inputs, + ) + + # Assert — non-file inputs are untouched + assert result["query"] == "hello world" + + def test_rebuild_should_rebuild_file_variable( + self, + ) -> None: + # Arrange + file_var = self._make_variable("attachment", VariableEntityType.FILE) + start_data = self._make_start_node_data([file_var]) + file_value = {"url": "https://example.com/file.pdf"} + user_inputs = {"attachment": file_value} + mock_file = MagicMock() + + # Act + with patch("services.workflow_service.build_from_mapping", return_value=mock_file): + result = _rebuild_file_for_user_inputs_in_start_node( + tenant_id="tenant-1", + start_node_data=start_data, + user_inputs=user_inputs, + ) + + # Assert — the dict value should be replaced by the rebuilt File object + assert result["attachment"] is mock_file + + def test_rebuild_should_skip_variable_not_in_inputs( + self, + ) -> None: + # Arrange + file_var = self._make_variable("attachment", VariableEntityType.FILE) + start_data = self._make_start_node_data([file_var]) + user_inputs: dict = {} # attachment not provided + + # Act + result = _rebuild_file_for_user_inputs_in_start_node( + tenant_id="tenant-1", + start_node_data=start_data, + user_inputs=user_inputs, + ) + + # Assert — no key should be added for missing inputs + assert "attachment" not in result + + +class TestWorkflowServiceResolveDeliveryMethod: + """ + Tests for the static helper `_resolve_human_input_delivery_method`. + """ + + def _make_method(self, method_id) -> MagicMock: + m = MagicMock() + m.id = method_id + return m + + def test_resolve_delivery_method_should_return_method_when_id_matches(self) -> None: + # Arrange + method_a = self._make_method("method-1") + method_b = self._make_method("method-2") + + # Act + with patch("services.workflow_service.parse_human_input_delivery_methods", return_value=[method_a, method_b]): + result = WorkflowService._resolve_human_input_delivery_method( + node_data=MagicMock(), delivery_method_id="method-2" + ) + + # Assert + assert result is method_b + + def test_resolve_delivery_method_should_return_none_when_no_match(self) -> None: + # Arrange + method_a = self._make_method("method-1") + + # Act + with patch("services.workflow_service.parse_human_input_delivery_methods", return_value=[method_a]): + result = WorkflowService._resolve_human_input_delivery_method( + node_data=MagicMock(), delivery_method_id="does-not-exist" + ) + + # Assert + assert result is None + + def test_resolve_delivery_method_should_return_none_for_empty_methods(self) -> None: + # Act + with patch("services.workflow_service.parse_human_input_delivery_methods", return_value=[]): + result = WorkflowService._resolve_human_input_delivery_method( + node_data=MagicMock(), delivery_method_id="method-1" + ) + + # Assert + assert result is None + + +# =========================================================================== +# TestWorkflowServiceDraftExecution +# Tests for run_draft_workflow_node +# =========================================================================== + + +class TestWorkflowServiceDraftExecution: + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + def test_run_draft_workflow_node_should_execute_start_node_successfully(self, service: WorkflowService) -> None: + # Arrange + app = MagicMock(spec=App) + app.id = "app-1" + app.tenant_id = "tenant-1" + account = MagicMock() + account.id = "user-1" + + draft_workflow = MagicMock(spec=Workflow) + draft_workflow.id = "wf-1" + draft_workflow.tenant_id = "tenant-1" + draft_workflow.app_id = "app-1" + draft_workflow.graph_dict = {"nodes": []} + + node_id = "start-node" + node_config = {"id": node_id, "data": MagicMock(type=BuiltinNodeTypes.START)} + draft_workflow.get_node_config_by_id.return_value = node_config + draft_workflow.get_enclosing_node_type_and_id.return_value = None + + service.get_draft_workflow = MagicMock(return_value=draft_workflow) + + node_execution = MagicMock(spec=WorkflowNodeExecution) + node_execution.id = "exec-1" + node_execution.process_data = {} + + # Mocking complex dependencies + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.Session"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("services.workflow_service.StartNodeData") as mock_start_data, + patch( + "services.workflow_service._rebuild_file_for_user_inputs_in_start_node", + side_effect=lambda **kwargs: kwargs["user_inputs"], + ), + patch("services.workflow_service._setup_variable_pool"), + patch("services.workflow_service.DraftVarLoader"), + patch("services.workflow_service.WorkflowEntry.single_step_run") as mock_run, + patch("services.workflow_service.DifyCoreRepositoryFactory") as mock_repo_factory, + patch("services.workflow_service.DraftVariableSaver") as mock_saver_cls, + patch("services.workflow_service.storage"), + ): + mock_node = MagicMock() + mock_node.node_type = BuiltinNodeTypes.START + mock_node.title = "Start Node" + mock_run_result = NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={}, outputs={"result": "ok"} + ) + mock_event = NodeRunSucceededEvent( + id=str(uuid.uuid4()), + node_id="start-node", + node_type=BuiltinNodeTypes.START, + node_run_result=mock_run_result, + start_at=naive_utc_now(), + ) + mock_run.return_value = (mock_node, [mock_event]) + + mock_repo = MagicMock() + mock_repo_factory.create_workflow_node_execution_repository.return_value = mock_repo + + service._node_execution_service_repo = MagicMock() + mock_execution_record = MagicMock() + mock_execution_record.node_type = "start" + mock_execution_record.node_id = "start-node" + mock_execution_record.load_full_outputs.return_value = {} + service._node_execution_service_repo.get_execution_by_id.return_value = mock_execution_record + + # Act + result = service.run_draft_workflow_node( + app_model=app, + draft_workflow=draft_workflow, + account=account, + node_id=node_id, + user_inputs={"key": "val"}, + query="hi", + files=[], + ) + + # Assert + assert result is not None + mock_run.assert_called_once() + mock_repo.save.assert_called_once() + mock_saver_cls.return_value.save.assert_called_once() + + def test_run_draft_workflow_node_should_execute_non_start_node_successfully(self, service: WorkflowService) -> None: + # Arrange + app = MagicMock(spec=App) + account = MagicMock() + draft_workflow = MagicMock(spec=Workflow) + draft_workflow.graph_dict = {"nodes": []} + node_id = "llm-node" + node_config = {"id": node_id, "data": MagicMock(type=BuiltinNodeTypes.LLM)} + draft_workflow.get_node_config_by_id.return_value = node_config + draft_workflow.get_enclosing_node_type_and_id.return_value = None + service.get_draft_workflow = MagicMock(return_value=draft_workflow) + + node_execution = MagicMock(spec=WorkflowNodeExecution) + node_execution.id = "exec-1" + node_execution.process_data = {} + + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.Session"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("services.workflow_service.VariablePool") as mock_pool_cls, + patch("services.workflow_service.default_system_variables") as mock_default_system_variables, + patch("services.workflow_service.build_bootstrap_variables") as mock_build_bootstrap_variables, + patch("services.workflow_service.add_variables_to_pool") as mock_add_variables_to_pool, + patch("services.workflow_service.DraftVarLoader"), + patch("services.workflow_service.WorkflowEntry.single_step_run") as mock_run, + patch("services.workflow_service.DifyCoreRepositoryFactory"), + patch("services.workflow_service.DraftVariableSaver"), + patch("services.workflow_service.storage"), + ): + mock_node = MagicMock() + mock_node.node_type = BuiltinNodeTypes.LLM + mock_node.title = "LLM Node" + mock_run_result = NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={}, outputs={"result": "ok"} + ) + mock_event = NodeRunSucceededEvent( + id=str(uuid.uuid4()), + node_id="llm-node", + node_type=BuiltinNodeTypes.LLM, + node_run_result=mock_run_result, + start_at=naive_utc_now(), + ) + mock_run.return_value = (mock_node, [mock_event]) + + service._node_execution_service_repo = MagicMock() + mock_execution_record = MagicMock() + mock_execution_record.node_type = "llm" + mock_execution_record.node_id = "llm-node" + mock_execution_record.load_full_outputs.return_value = {"answer": "hello"} + service._node_execution_service_repo.get_execution_by_id.return_value = mock_execution_record + + # Act + service.run_draft_workflow_node( + app_model=app, + draft_workflow=draft_workflow, + account=account, + node_id=node_id, + user_inputs={}, + query="", + files=None, + ) + + # Assert + # For non-start nodes, bootstrap variables should be loaded into an empty pool. + mock_pool_cls.assert_called_once_with() + mock_default_system_variables.assert_called_once() + mock_build_bootstrap_variables.assert_called_once_with( + system_variables=mock_default_system_variables.return_value, + environment_variables=draft_workflow.environment_variables, + ) + mock_add_variables_to_pool.assert_called_once_with( + mock_pool_cls.return_value, mock_build_bootstrap_variables.return_value + ) + + +# =========================================================================== +# TestWorkflowServiceHumanInputOperations +# Tests for Human Input related methods +# =========================================================================== + + +class TestWorkflowServiceHumanInputOperations: + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + def test_get_human_input_form_preview_should_raise_if_workflow_not_init(self, service: WorkflowService) -> None: + service.get_draft_workflow = MagicMock(return_value=None) + with pytest.raises(ValueError, match="Workflow not initialized"): + service.get_human_input_form_preview(app_model=MagicMock(), account=MagicMock(), node_id="node-1") + + def test_get_human_input_form_preview_should_raise_if_wrong_node_type(self, service: WorkflowService) -> None: + draft = MagicMock() + draft.get_node_config_by_id.return_value = {"data": {"type": "llm"}} + service.get_draft_workflow = MagicMock(return_value=draft) + with patch("models.workflow.Workflow.get_node_type_from_node_config", return_value=BuiltinNodeTypes.LLM): + with pytest.raises(ValueError, match="Node type must be human-input"): + service.get_human_input_form_preview(app_model=MagicMock(), account=MagicMock(), node_id="node-1") + + def test_get_human_input_form_preview_success(self, service: WorkflowService) -> None: + app_model = MagicMock(spec=App) + app_model.id = "app-1" + app_model.tenant_id = "tenant-1" + + account = MagicMock() + account.id = "user-1" + + draft = MagicMock() + draft.id = "wf-1" + draft.tenant_id = "tenant-1" + draft.app_id = "app-1" + draft.graph_dict = {"nodes": []} + draft.get_node_config_by_id.return_value = { + "id": "node-1", + "data": MagicMock(type=BuiltinNodeTypes.HUMAN_INPUT), + } + service.get_draft_workflow = MagicMock(return_value=draft) + + mock_node = MagicMock() + mock_node.render_form_content_before_submission.return_value = "rendered" + mock_node.resolve_default_values.return_value = {"def": 1} + mock_node.title = "Form Title" + mock_node.node_data = MagicMock() + + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("models.workflow.Workflow.get_node_type_from_node_config", return_value=BuiltinNodeTypes.HUMAN_INPUT), + patch.object(service, "_build_human_input_variable_pool"), + patch("services.workflow_service.HumanInputNode", return_value=mock_node), + patch("services.workflow_service.HumanInputRequired") as mock_required_cls, + ): + service.get_human_input_form_preview(app_model=app_model, account=account, node_id="node-1") + mock_node.render_form_content_before_submission.assert_called_once() + mock_required_cls.return_value.model_dump.assert_called_once() + + def test_submit_human_input_form_preview_success(self, service: WorkflowService) -> None: + app_model = MagicMock(spec=App) + app_model.id = "app-1" + app_model.tenant_id = "tenant-1" + + account = MagicMock() + account.id = "user-1" + + draft = MagicMock() + draft.id = "wf-1" + draft.tenant_id = "tenant-1" + draft.app_id = "app-1" + draft.graph_dict = {"nodes": []} + draft.get_node_config_by_id.return_value = {"id": "node-1", "data": {"type": "human-input"}} + service.get_draft_workflow = MagicMock(return_value=draft) + + mock_node = MagicMock() + mock_node.node_data = MagicMock() + mock_node.node_data.outputs_field_names.return_value = ["field1"] + + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("models.workflow.Workflow.get_node_type_from_node_config", return_value=BuiltinNodeTypes.HUMAN_INPUT), + patch.object(service, "_build_human_input_variable_pool"), + patch("services.workflow_service.HumanInputNode", return_value=mock_node), + patch("services.workflow_service.validate_human_input_submission"), + patch("services.workflow_service.Session"), + patch("services.workflow_service.DraftVariableSaver") as mock_saver_cls, + ): + result = service.submit_human_input_form_preview( + app_model=app_model, account=account, node_id="node-1", form_inputs={"field1": "val1"}, action="submit" + ) + assert result["__action_id"] == "submit" + mock_saver_cls.return_value.save.assert_called_once() + + def test_test_human_input_delivery_success(self, service: WorkflowService) -> None: + draft = MagicMock() + draft.get_node_config_by_id.return_value = {"data": {"type": "human-input"}} + service.get_draft_workflow = MagicMock(return_value=draft) + + with ( + patch("models.workflow.Workflow.get_node_type_from_node_config", return_value=BuiltinNodeTypes.HUMAN_INPUT), + patch("services.workflow_service.HumanInputNodeData.model_validate"), + patch.object(service, "_resolve_human_input_delivery_method") as mock_resolve, + patch("services.workflow_service.apply_dify_debug_email_recipient"), + patch.object(service, "_build_human_input_variable_pool"), + patch.object(service, "_build_human_input_node"), + patch.object(service, "_create_human_input_delivery_test_form", return_value=("form-1", [])), + patch("services.workflow_service.HumanInputDeliveryTestService") as mock_test_srv, + ): + mock_resolve.return_value = MagicMock() + service.test_human_input_delivery( + app_model=MagicMock(), account=MagicMock(), node_id="node-1", delivery_method_id="method-1" + ) + mock_test_srv.return_value.send_test.assert_called_once() + + def test_test_human_input_delivery_failure_cases(self, service: WorkflowService) -> None: + draft = MagicMock() + draft.get_node_config_by_id.return_value = {"data": {"type": "human-input"}} + service.get_draft_workflow = MagicMock(return_value=draft) + + with ( + patch("models.workflow.Workflow.get_node_type_from_node_config", return_value=BuiltinNodeTypes.HUMAN_INPUT), + patch("services.workflow_service.HumanInputNodeData.model_validate"), + patch.object(service, "_resolve_human_input_delivery_method", return_value=None), + ): + with pytest.raises(ValueError, match="Delivery method not found"): + service.test_human_input_delivery( + app_model=MagicMock(), account=MagicMock(), node_id="node-1", delivery_method_id="none" + ) + + def test_load_email_recipients_parsing_failure(self, service: WorkflowService) -> None: + # Arrange + mock_recipient = MagicMock() + mock_recipient.recipient_payload = "invalid json" + mock_recipient.recipient_type = RecipientType.EMAIL_MEMBER + + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("services.workflow_service.Session") as mock_session_cls, + patch("services.workflow_service.select"), + patch("services.workflow_service.json.loads", side_effect=ValueError("bad json")), + ): + mock_session = mock_session_cls.return_value.__enter__.return_value + # sqlalchemy assertions check for .bind + mock_session.bind = MagicMock() # removed spec=Engine to avoid import issues for now + mock_session.scalars.return_value.all.return_value = [mock_recipient] + + # Act + # _load_email_recipients(form_id: str) is a static method + result = WorkflowService._load_email_recipients("form-1") + + # Assert + assert result == [] # Should fall back to empty list on parsing error + + def test_build_human_input_variable_pool(self, service: WorkflowService) -> None: + workflow = MagicMock() + workflow.environment_variables = [] + workflow.graph_dict = {} + + with ( + patch("services.workflow_service.db"), + patch("services.workflow_service.Session"), + patch("services.workflow_service.WorkflowDraftVariableService"), + patch("services.workflow_service.VariablePool") as mock_pool_cls, + patch("services.workflow_service.DraftVarLoader"), + patch("services.workflow_service.HumanInputNode.extract_variable_selector_to_variable_mapping"), + patch("services.workflow_service.load_into_variable_pool"), + patch("services.workflow_service.WorkflowEntry.mapping_user_inputs_to_variable_pool"), + ): + service._build_human_input_variable_pool( + app_model=MagicMock(), workflow=workflow, node_config={}, manual_inputs={}, user_id="user-1" + ) + mock_pool_cls.assert_called_once() + + +# =========================================================================== +# TestWorkflowServiceFreeNodeExecution +# Tests for run_free_workflow_node and handle_single_step_result +# =========================================================================== + + +class TestWorkflowServiceFreeNodeExecution: + @pytest.fixture + def service(self) -> WorkflowService: + with patch("services.workflow_service.db"): + return WorkflowService() + + def test_run_free_workflow_node_success(self, service: WorkflowService) -> None: + node_execution = MagicMock() + with ( + patch.object(service, "_handle_single_step_result", return_value=node_execution), + patch("services.workflow_service.WorkflowEntry.run_free_node"), + ): + result = service.run_free_workflow_node({}, "tenant-1", "user-1", "node-1", {}) + assert result == node_execution + + def test_validate_graph_structure_coexist_error(self, service: WorkflowService) -> None: + graph = { + "nodes": [ + {"data": {"type": "start"}}, + {"data": {"type": "trigger-webhook"}}, # is_trigger_node=True + ] + } + with pytest.raises(ValueError, match="Start node and trigger nodes cannot coexist"): + service.validate_graph_structure(graph) + + def test_validate_features_structure_success(self, service: WorkflowService) -> None: + app = MagicMock() + app.mode = "workflow" + features = {} + with patch("services.workflow_service.WorkflowAppConfigManager.config_validate") as mock_val: + service.validate_features_structure(app, features) + mock_val.assert_called_once() + + def test_validate_features_structure_invalid_mode(self, service: WorkflowService) -> None: + app = MagicMock() + app.mode = "invalid" + with pytest.raises(ValueError, match="Invalid app mode"): + service.validate_features_structure(app, {}) + + def test_validate_human_input_node_data_error(self, service: WorkflowService) -> None: + with patch( + "graphon.nodes.human_input.entities.HumanInputNodeData.model_validate", side_effect=Exception("error") + ): + with pytest.raises(ValueError, match="Invalid HumanInput node data"): + service._validate_human_input_node_data({}) + + def test_rebuild_single_file_unreachable(self) -> None: + # Test line 1523 (unreachable) + with pytest.raises(Exception, match="unreachable"): + _rebuild_single_file("tenant-1", {}, cast(Any, "invalid_type")) + + def test_build_human_input_node(self, service: WorkflowService) -> None: + """Cover _build_human_input_node (lines 1065-1088).""" + workflow = MagicMock() + workflow.id = "wf-1" + workflow.tenant_id = "t-1" + workflow.app_id = "app-1" + account = MagicMock() + account.id = "u-1" + node_config = {"id": "n-1"} + variable_pool = MagicMock() + + with ( + patch("services.workflow_service.GraphInitParams") as mock_graph_init_params, + patch("services.workflow_service.GraphRuntimeState"), + patch("services.workflow_service.build_dify_run_context"), + patch("services.workflow_service.DifyHumanInputNodeRuntime") as mock_runtime_cls, + patch("services.workflow_service.HumanInputNode") as mock_node_cls, + ): + node = service._build_human_input_node( + workflow=workflow, account=account, node_config=node_config, variable_pool=variable_pool + ) + assert node == mock_node_cls.return_value + mock_node_cls.assert_called_once() + mock_runtime_cls.assert_called_once_with(mock_graph_init_params.return_value.run_context) diff --git a/api/tests/unit_tests/services/tools/test_tools_transform_service.py b/api/tests/unit_tests/services/tools/test_tools_transform_service.py deleted file mode 100644 index 9616d2f1023..00000000000 --- a/api/tests/unit_tests/services/tools/test_tools_transform_service.py +++ /dev/null @@ -1,452 +0,0 @@ -from unittest.mock import Mock - -from core.tools.__base.tool import Tool -from core.tools.entities.api_entities import ToolApiEntity, ToolProviderApiEntity -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolParameter, ToolProviderType -from services.tools.tools_transform_service import ToolTransformService - - -class TestToolTransformService: - """Test cases for ToolTransformService.convert_tool_entity_to_api_entity method""" - - def test_convert_tool_with_parameter_override(self): - """Test that runtime parameters correctly override base parameters""" - # Create mock base parameters - base_param1 = Mock(spec=ToolParameter) - base_param1.name = "param1" - base_param1.form = ToolParameter.ToolParameterForm.FORM - base_param1.type = "string" - base_param1.label = "Base Param 1" - - base_param2 = Mock(spec=ToolParameter) - base_param2.name = "param2" - base_param2.form = ToolParameter.ToolParameterForm.FORM - base_param2.type = "string" - base_param2.label = "Base Param 2" - - # Create mock runtime parameters that override base parameters - runtime_param1 = Mock(spec=ToolParameter) - runtime_param1.name = "param1" - runtime_param1.form = ToolParameter.ToolParameterForm.FORM - runtime_param1.type = "string" - runtime_param1.label = "Runtime Param 1" # Different label to verify override - - # Create mock tool - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = [base_param1, base_param2] - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [runtime_param1] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.author == "test_author" - assert result.name == "test_tool" - assert result.parameters is not None - assert len(result.parameters) == 2 - - # Find the overridden parameter - overridden_param = next((p for p in result.parameters if p.name == "param1"), None) - assert overridden_param is not None - assert overridden_param.label == "Runtime Param 1" # Should be runtime version - - # Find the non-overridden parameter - original_param = next((p for p in result.parameters if p.name == "param2"), None) - assert original_param is not None - assert original_param.label == "Base Param 2" # Should be base version - - def test_convert_tool_with_additional_runtime_parameters(self): - """Test that additional runtime parameters are added to the final list""" - # Create mock base parameters - base_param1 = Mock(spec=ToolParameter) - base_param1.name = "param1" - base_param1.form = ToolParameter.ToolParameterForm.FORM - base_param1.type = "string" - base_param1.label = "Base Param 1" - - # Create mock runtime parameters - one that overrides and one that's new - runtime_param1 = Mock(spec=ToolParameter) - runtime_param1.name = "param1" - runtime_param1.form = ToolParameter.ToolParameterForm.FORM - runtime_param1.type = "string" - runtime_param1.label = "Runtime Param 1" - - runtime_param2 = Mock(spec=ToolParameter) - runtime_param2.name = "runtime_only" - runtime_param2.form = ToolParameter.ToolParameterForm.FORM - runtime_param2.type = "string" - runtime_param2.label = "Runtime Only Param" - - # Create mock tool - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = [base_param1] - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [runtime_param1, runtime_param2] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.parameters is not None - assert len(result.parameters) == 2 - - # Check that both parameters are present - param_names = [p.name for p in result.parameters] - assert "param1" in param_names - assert "runtime_only" in param_names - - # Verify the overridden parameter has runtime version - overridden_param = next((p for p in result.parameters if p.name == "param1"), None) - assert overridden_param is not None - assert overridden_param.label == "Runtime Param 1" - - # Verify the new runtime parameter is included - new_param = next((p for p in result.parameters if p.name == "runtime_only"), None) - assert new_param is not None - assert new_param.label == "Runtime Only Param" - - def test_convert_tool_with_non_form_runtime_parameters(self): - """Test that non-FORM runtime parameters are not added as new parameters""" - # Create mock base parameters - base_param1 = Mock(spec=ToolParameter) - base_param1.name = "param1" - base_param1.form = ToolParameter.ToolParameterForm.FORM - base_param1.type = "string" - base_param1.label = "Base Param 1" - - # Create mock runtime parameters with different forms - runtime_param1 = Mock(spec=ToolParameter) - runtime_param1.name = "param1" - runtime_param1.form = ToolParameter.ToolParameterForm.FORM - runtime_param1.type = "string" - runtime_param1.label = "Runtime Param 1" - - runtime_param2 = Mock(spec=ToolParameter) - runtime_param2.name = "llm_param" - runtime_param2.form = ToolParameter.ToolParameterForm.LLM - runtime_param2.type = "string" - runtime_param2.label = "LLM Param" - - # Create mock tool - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = [base_param1] - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [runtime_param1, runtime_param2] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.parameters is not None - assert len(result.parameters) == 1 # Only the FORM parameter should be present - - # Check that only the FORM parameter is present - param_names = [p.name for p in result.parameters] - assert "param1" in param_names - assert "llm_param" not in param_names - - def test_convert_tool_with_empty_parameters(self): - """Test conversion with empty base and runtime parameters""" - # Create mock tool with no parameters - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = [] - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.parameters is not None - assert len(result.parameters) == 0 - - def test_convert_tool_with_none_parameters(self): - """Test conversion when base parameters is None""" - # Create mock tool with None parameters - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = None - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.parameters is not None - assert len(result.parameters) == 0 - - def test_convert_tool_parameter_order_preserved(self): - """Test that parameter order is preserved correctly""" - # Create mock base parameters in specific order - base_param1 = Mock(spec=ToolParameter) - base_param1.name = "param1" - base_param1.form = ToolParameter.ToolParameterForm.FORM - base_param1.type = "string" - base_param1.label = "Base Param 1" - - base_param2 = Mock(spec=ToolParameter) - base_param2.name = "param2" - base_param2.form = ToolParameter.ToolParameterForm.FORM - base_param2.type = "string" - base_param2.label = "Base Param 2" - - base_param3 = Mock(spec=ToolParameter) - base_param3.name = "param3" - base_param3.form = ToolParameter.ToolParameterForm.FORM - base_param3.type = "string" - base_param3.label = "Base Param 3" - - # Create runtime parameter that overrides middle parameter - runtime_param2 = Mock(spec=ToolParameter) - runtime_param2.name = "param2" - runtime_param2.form = ToolParameter.ToolParameterForm.FORM - runtime_param2.type = "string" - runtime_param2.label = "Runtime Param 2" - - # Create new runtime parameter - runtime_param4 = Mock(spec=ToolParameter) - runtime_param4.name = "param4" - runtime_param4.form = ToolParameter.ToolParameterForm.FORM - runtime_param4.type = "string" - runtime_param4.label = "Runtime Param 4" - - # Create mock tool - mock_tool = Mock(spec=Tool) - mock_tool.entity = Mock() - mock_tool.entity.parameters = [base_param1, base_param2, base_param3] - mock_tool.entity.identity = Mock() - mock_tool.entity.identity.author = "test_author" - mock_tool.entity.identity.name = "test_tool" - mock_tool.entity.identity.label = I18nObject(en_US="Test Tool") - mock_tool.entity.description = Mock() - mock_tool.entity.description.human = I18nObject(en_US="Test description") - mock_tool.entity.output_schema = {} - mock_tool.get_runtime_parameters.return_value = [runtime_param2, runtime_param4] - - # Mock fork_tool_runtime to return the same tool - mock_tool.fork_tool_runtime.return_value = mock_tool - - # Call the method - result = ToolTransformService.convert_tool_entity_to_api_entity(mock_tool, "test_tenant", None) - - # Verify the result - assert isinstance(result, ToolApiEntity) - assert result.parameters is not None - assert len(result.parameters) == 4 - - # Check that order is maintained: base parameters first, then new runtime parameters - param_names = [p.name for p in result.parameters] - assert param_names == ["param1", "param2", "param3", "param4"] - - # Verify that param2 was overridden with runtime version - param2 = result.parameters[1] - assert param2.name == "param2" - assert param2.label == "Runtime Param 2" - - -class TestWorkflowProviderToUserProvider: - """Test cases for ToolTransformService.workflow_provider_to_user_provider method""" - - def test_workflow_provider_to_user_provider_with_workflow_app_id(self): - """Test that workflow_provider_to_user_provider correctly sets workflow_app_id.""" - from core.tools.workflow_as_tool.provider import WorkflowToolProviderController - - # Create mock workflow tool provider controller - workflow_app_id = "app_123" - provider_id = "provider_123" - mock_controller = Mock(spec=WorkflowToolProviderController) - mock_controller.provider_id = provider_id - mock_controller.entity = Mock() - mock_controller.entity.identity = Mock() - mock_controller.entity.identity.author = "test_author" - mock_controller.entity.identity.name = "test_workflow_tool" - mock_controller.entity.identity.description = I18nObject(en_US="Test description") - mock_controller.entity.identity.icon = {"type": "emoji", "content": "🔧"} - mock_controller.entity.identity.icon_dark = None - mock_controller.entity.identity.label = I18nObject(en_US="Test Workflow Tool") - - # Call the method - result = ToolTransformService.workflow_provider_to_user_provider( - provider_controller=mock_controller, - labels=["label1", "label2"], - workflow_app_id=workflow_app_id, - ) - - # Verify the result - assert isinstance(result, ToolProviderApiEntity) - assert result.id == provider_id - assert result.author == "test_author" - assert result.name == "test_workflow_tool" - assert result.type == ToolProviderType.WORKFLOW - assert result.workflow_app_id == workflow_app_id - assert result.labels == ["label1", "label2"] - assert result.is_team_authorization is True - assert result.plugin_id is None - assert result.plugin_unique_identifier is None - assert result.tools == [] - - def test_workflow_provider_to_user_provider_without_workflow_app_id(self): - """Test that workflow_provider_to_user_provider works when workflow_app_id is not provided.""" - from core.tools.workflow_as_tool.provider import WorkflowToolProviderController - - # Create mock workflow tool provider controller - provider_id = "provider_123" - mock_controller = Mock(spec=WorkflowToolProviderController) - mock_controller.provider_id = provider_id - mock_controller.entity = Mock() - mock_controller.entity.identity = Mock() - mock_controller.entity.identity.author = "test_author" - mock_controller.entity.identity.name = "test_workflow_tool" - mock_controller.entity.identity.description = I18nObject(en_US="Test description") - mock_controller.entity.identity.icon = {"type": "emoji", "content": "🔧"} - mock_controller.entity.identity.icon_dark = None - mock_controller.entity.identity.label = I18nObject(en_US="Test Workflow Tool") - - # Call the method without workflow_app_id - result = ToolTransformService.workflow_provider_to_user_provider( - provider_controller=mock_controller, - labels=["label1"], - ) - - # Verify the result - assert isinstance(result, ToolProviderApiEntity) - assert result.id == provider_id - assert result.workflow_app_id is None - assert result.labels == ["label1"] - - def test_workflow_provider_to_user_provider_workflow_app_id_none(self): - """Test that workflow_provider_to_user_provider handles None workflow_app_id explicitly.""" - from core.tools.workflow_as_tool.provider import WorkflowToolProviderController - - # Create mock workflow tool provider controller - provider_id = "provider_123" - mock_controller = Mock(spec=WorkflowToolProviderController) - mock_controller.provider_id = provider_id - mock_controller.entity = Mock() - mock_controller.entity.identity = Mock() - mock_controller.entity.identity.author = "test_author" - mock_controller.entity.identity.name = "test_workflow_tool" - mock_controller.entity.identity.description = I18nObject(en_US="Test description") - mock_controller.entity.identity.icon = {"type": "emoji", "content": "🔧"} - mock_controller.entity.identity.icon_dark = None - mock_controller.entity.identity.label = I18nObject(en_US="Test Workflow Tool") - - # Call the method with explicit None values - result = ToolTransformService.workflow_provider_to_user_provider( - provider_controller=mock_controller, - labels=None, - workflow_app_id=None, - ) - - # Verify the result - assert isinstance(result, ToolProviderApiEntity) - assert result.id == provider_id - assert result.workflow_app_id is None - assert result.labels == [] - - def test_workflow_provider_to_user_provider_preserves_other_fields(self): - """Test that workflow_provider_to_user_provider preserves all other entity fields.""" - from core.tools.workflow_as_tool.provider import WorkflowToolProviderController - - # Create mock workflow tool provider controller with various fields - workflow_app_id = "app_456" - provider_id = "provider_456" - mock_controller = Mock(spec=WorkflowToolProviderController) - mock_controller.provider_id = provider_id - mock_controller.entity = Mock() - mock_controller.entity.identity = Mock() - mock_controller.entity.identity.author = "another_author" - mock_controller.entity.identity.name = "another_workflow_tool" - mock_controller.entity.identity.description = I18nObject( - en_US="Another description", zh_Hans="Another description" - ) - mock_controller.entity.identity.icon = {"type": "emoji", "content": "⚙️"} - mock_controller.entity.identity.icon_dark = {"type": "emoji", "content": "🔧"} - mock_controller.entity.identity.label = I18nObject( - en_US="Another Workflow Tool", zh_Hans="Another Workflow Tool" - ) - - # Call the method - result = ToolTransformService.workflow_provider_to_user_provider( - provider_controller=mock_controller, - labels=["automation", "workflow"], - workflow_app_id=workflow_app_id, - ) - - # Verify all fields are preserved correctly - assert isinstance(result, ToolProviderApiEntity) - assert result.id == provider_id - assert result.author == "another_author" - assert result.name == "another_workflow_tool" - assert result.description.en_US == "Another description" - assert result.description.zh_Hans == "Another description" - assert result.icon == {"type": "emoji", "content": "⚙️"} - assert result.icon_dark == {"type": "emoji", "content": "🔧"} - assert result.label.en_US == "Another Workflow Tool" - assert result.label.zh_Hans == "Another Workflow Tool" - assert result.type == ToolProviderType.WORKFLOW - assert result.workflow_app_id == workflow_app_id - assert result.labels == ["automation", "workflow"] - assert result.masked_credentials == {} - assert result.is_team_authorization is True - assert result.allow_delete is True - assert result.plugin_id is None - assert result.plugin_unique_identifier is None - assert result.tools == [] diff --git a/api/tests/unit_tests/services/tools/test_workflow_tools_manage_service.py b/api/tests/unit_tests/services/tools/test_workflow_tools_manage_service.py deleted file mode 100644 index ae59da0a3da..00000000000 --- a/api/tests/unit_tests/services/tools/test_workflow_tools_manage_service.py +++ /dev/null @@ -1,162 +0,0 @@ -import json -from types import SimpleNamespace -from unittest.mock import MagicMock - -import pytest - -from core.tools.entities.tool_entities import ToolParameter, WorkflowToolParameterConfiguration -from core.tools.errors import WorkflowToolHumanInputNotSupportedError -from models.model import App -from models.tools import WorkflowToolProvider -from services.tools import workflow_tools_manage_service - - -class DummyWorkflow: - def __init__(self, graph_dict: dict, version: str = "1.0.0") -> None: - self._graph_dict = graph_dict - self.version = version - - @property - def graph_dict(self) -> dict: - return self._graph_dict - - -class FakeQuery: - def __init__(self, result): - self._result = result - - def where(self, *args, **kwargs): - return self - - def first(self): - return self._result - - -class DummySession: - def __init__(self) -> None: - self.added: list[object] = [] - - def __enter__(self) -> "DummySession": - return self - - def __exit__(self, exc_type, exc, tb) -> bool: - return False - - def add(self, obj) -> None: - self.added.append(obj) - - def begin(self): - return DummyBegin(self) - - -class DummyBegin: - def __init__(self, session: DummySession) -> None: - self._session = session - - def __enter__(self) -> DummySession: - return self._session - - def __exit__(self, exc_type, exc, tb) -> bool: - return False - - -class DummySessionContext: - def __init__(self, session: DummySession) -> None: - self._session = session - - def __enter__(self) -> DummySession: - return self._session - - def __exit__(self, exc_type, exc, tb) -> bool: - return False - - -class DummySessionFactory: - def __init__(self, session: DummySession) -> None: - self._session = session - - def create_session(self) -> DummySessionContext: - return DummySessionContext(self._session) - - -def _build_fake_session(app) -> SimpleNamespace: - def query(model): - if model is WorkflowToolProvider: - return FakeQuery(None) - if model is App: - return FakeQuery(app) - return FakeQuery(None) - - return SimpleNamespace(query=query) - - -def _build_parameters() -> list[WorkflowToolParameterConfiguration]: - return [ - WorkflowToolParameterConfiguration(name="input", description="input", form=ToolParameter.ToolParameterForm.LLM), - ] - - -def test_create_workflow_tool_rejects_human_input_nodes(monkeypatch): - workflow = DummyWorkflow(graph_dict={"nodes": [{"id": "node_1", "data": {"type": "human-input"}}]}) - app = SimpleNamespace(workflow=workflow) - - fake_session = _build_fake_session(app) - monkeypatch.setattr(workflow_tools_manage_service.db, "session", fake_session) - - mock_from_db = MagicMock() - monkeypatch.setattr(workflow_tools_manage_service.WorkflowToolProviderController, "from_db", mock_from_db) - mock_invalidate = MagicMock() - - with pytest.raises(WorkflowToolHumanInputNotSupportedError) as exc_info: - workflow_tools_manage_service.WorkflowToolManageService.create_workflow_tool( - user_id="user-id", - tenant_id="tenant-id", - workflow_app_id="app-id", - name="tool_name", - label="Tool", - icon={"type": "emoji", "emoji": "tool"}, - description="desc", - parameters=_build_parameters(), - ) - - assert exc_info.value.error_code == "workflow_tool_human_input_not_supported" - mock_from_db.assert_not_called() - mock_invalidate.assert_not_called() - - -def test_create_workflow_tool_success(monkeypatch): - workflow = DummyWorkflow(graph_dict={"nodes": [{"id": "node_1", "data": {"type": "start"}}]}) - app = SimpleNamespace(workflow=workflow) - - fake_db = MagicMock() - fake_session = _build_fake_session(app) - fake_db.session = fake_session - monkeypatch.setattr(workflow_tools_manage_service, "db", fake_db) - - dummy_session = DummySession() - monkeypatch.setattr(workflow_tools_manage_service, "Session", lambda *_, **__: dummy_session) - - mock_from_db = MagicMock() - monkeypatch.setattr(workflow_tools_manage_service.WorkflowToolProviderController, "from_db", mock_from_db) - - icon = {"type": "emoji", "emoji": "tool"} - - result = workflow_tools_manage_service.WorkflowToolManageService.create_workflow_tool( - user_id="user-id", - tenant_id="tenant-id", - workflow_app_id="app-id", - name="tool_name", - label="Tool", - icon=icon, - description="desc", - parameters=_build_parameters(), - ) - - assert result == {"result": "success"} - assert len(dummy_session.added) == 1 - created_provider = dummy_session.added[0] - assert created_provider.name == "tool_name" - assert created_provider.label == "Tool" - assert created_provider.icon == json.dumps(icon) - assert created_provider.version == workflow.version - mock_from_db.assert_called_once() diff --git a/api/tests/unit_tests/services/vector_service.py b/api/tests/unit_tests/services/vector_service.py index c99275c6b27..ee9ba1c6d68 100644 --- a/api/tests/unit_tests/services/vector_service.py +++ b/api/tests/unit_tests/services/vector_service.py @@ -121,6 +121,7 @@ import pytest from core.rag.datasource.vdb.vector_base import BaseVector from core.rag.datasource.vdb.vector_factory import Vector from core.rag.datasource.vdb.vector_type import VectorType +from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType from core.rag.models.document import Document from models.dataset import ChildChunk, Dataset, DatasetDocument, DatasetProcessRule, DocumentSegment from services.vector_service import VectorService @@ -151,8 +152,8 @@ class VectorServiceTestDataFactory: def create_dataset_mock( dataset_id: str = "dataset-123", tenant_id: str = "tenant-123", - doc_form: str = "text_model", - indexing_technique: str = "high_quality", + doc_form: str = IndexStructureType.PARAGRAPH_INDEX, + indexing_technique: str = IndexTechniqueType.HIGH_QUALITY, embedding_model_provider: str = "openai", embedding_model: str = "text-embedding-ada-002", index_struct_dict: dict | None = None, @@ -493,7 +494,7 @@ class TestVectorService: """ # Arrange dataset = VectorServiceTestDataFactory.create_dataset_mock( - doc_form="text_model", indexing_technique="high_quality" + doc_form=IndexStructureType.PARAGRAPH_INDEX, indexing_technique=IndexTechniqueType.HIGH_QUALITY ) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -505,7 +506,7 @@ class TestVectorService: mock_index_processor_factory.return_value.init_index_processor.return_value = mock_index_processor # Act - VectorService.create_segments_vector(keywords_list, [segment], dataset, "text_model") + VectorService.create_segments_vector(keywords_list, [segment], dataset, IndexStructureType.PARAGRAPH_INDEX) # Assert mock_index_processor.load.assert_called_once() @@ -521,7 +522,7 @@ class TestVectorService: assert call_args[1]["keywords_list"] == keywords_list @patch("services.vector_service.VectorService.generate_child_chunks") - @patch("services.vector_service.ModelManager") + @patch("services.vector_service.ModelManager.for_tenant") @patch("services.vector_service.db") def test_create_segments_vector_parent_child_indexing( self, mock_db, mock_model_manager, mock_generate_child_chunks @@ -534,7 +535,7 @@ class TestVectorService: """ # Arrange dataset = VectorServiceTestDataFactory.create_dataset_mock( - doc_form="parent_child_model", indexing_technique="high_quality" + doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY ) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -567,7 +568,7 @@ class TestVectorService: """ # Arrange dataset = VectorServiceTestDataFactory.create_dataset_mock( - doc_form="parent_child_model", indexing_technique="high_quality" + doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY ) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -590,7 +591,7 @@ class TestVectorService: """ # Arrange dataset = VectorServiceTestDataFactory.create_dataset_mock( - doc_form="parent_child_model", indexing_technique="high_quality" + doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY ) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -615,7 +616,7 @@ class TestVectorService: """ # Arrange dataset = VectorServiceTestDataFactory.create_dataset_mock( - doc_form="parent_child_model", indexing_technique="economy" + doc_form="parent_child_model", indexing_technique=IndexTechniqueType.ECONOMY ) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -649,7 +650,7 @@ class TestVectorService: mock_index_processor_factory.return_value.init_index_processor.return_value = mock_index_processor # Act - VectorService.create_segments_vector(None, [], dataset, "text_model") + VectorService.create_segments_vector(None, [], dataset, IndexStructureType.PARAGRAPH_INDEX) # Assert mock_index_processor.load.assert_not_called() @@ -668,7 +669,7 @@ class TestVectorService: store when using high_quality indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -694,7 +695,7 @@ class TestVectorService: index when using economy indexing with keywords. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -730,7 +731,7 @@ class TestVectorService: index when using economy indexing without keywords. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY) segment = VectorServiceTestDataFactory.create_document_segment_mock() @@ -894,7 +895,7 @@ class TestVectorService: when using high_quality indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -922,7 +923,7 @@ class TestVectorService: using economy indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY) child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -950,7 +951,7 @@ class TestVectorService: when there are new chunks, updated chunks, and deleted chunks. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock(chunk_id="new-chunk-1") @@ -992,7 +993,7 @@ class TestVectorService: add_texts is called, not delete_by_ids. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -1018,7 +1019,7 @@ class TestVectorService: delete_by_ids is called, not add_texts. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) delete_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -1044,7 +1045,7 @@ class TestVectorService: using economy indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY) new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -1074,7 +1075,7 @@ class TestVectorService: when using high_quality indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY) child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -1098,7 +1099,7 @@ class TestVectorService: using economy indexing. """ # Arrange - dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy") + dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY) child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock() @@ -1754,7 +1755,7 @@ class TestVector: # ======================================================================== @patch("core.rag.datasource.vdb.vector_factory.CacheEmbedding") - @patch("core.rag.datasource.vdb.vector_factory.ModelManager") + @patch("core.rag.datasource.vdb.vector_factory.ModelManager.for_tenant") @patch("core.rag.datasource.vdb.vector_factory.Vector._init_vector") def test_vector_get_embeddings(self, mock_init_vector, mock_model_manager, mock_cache_embedding): """ diff --git a/api/tests/unit_tests/services/workflow/test_draft_var_loader_simple.py b/api/tests/unit_tests/services/workflow/test_draft_var_loader_simple.py index f3391d6380c..8525672da8e 100644 --- a/api/tests/unit_tests/services/workflow/test_draft_var_loader_simple.py +++ b/api/tests/unit_tests/services/workflow/test_draft_var_loader_simple.py @@ -4,10 +4,12 @@ import json from unittest.mock import Mock, patch import pytest +from graphon.file import File, FileTransferMethod, FileType +from graphon.variables.segments import ObjectSegment, StringSegment +from graphon.variables.types import SegmentType from sqlalchemy import Engine -from dify_graph.variables.segments import ObjectSegment, StringSegment -from dify_graph.variables.types import SegmentType +from core.workflow.file_reference import build_file_reference from models.model import UploadFile from models.workflow import WorkflowDraftVariable, WorkflowDraftVariableFile from services.workflow_draft_variable_service import DraftVarLoader @@ -54,25 +56,18 @@ class TestDraftVarLoaderSimple: with patch("services.workflow_draft_variable_service.storage") as mock_storage: mock_storage.load.return_value = test_content.encode() - with patch("factories.variable_factory.segment_to_variable") as mock_segment_to_variable: - mock_variable = Mock() - mock_variable.id = "draft-var-id" - mock_variable.name = "test_variable" - mock_variable.value = StringSegment(value=test_content) - mock_segment_to_variable.return_value = mock_variable + # Execute the method + selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - # Execute the method - selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) + # Verify results + assert selector_tuple == ("test-node-id", "test_variable") + assert variable.id == "draft-var-id" + assert variable.name == "test_variable" + assert variable.description == "test description" + assert variable.value == test_content - # Verify results - assert selector_tuple == ("test-node-id", "test_variable") - assert variable.id == "draft-var-id" - assert variable.name == "test_variable" - assert variable.description == "test description" - assert variable.value == test_content - - # Verify storage was called correctly - mock_storage.load.assert_called_once_with("storage/key/test.txt") + # Verify storage was called correctly + mock_storage.load.assert_called_once_with("storage/key/test.txt") def test_load_offloaded_variable_object_type_unit(self, draft_var_loader): """Test _load_offloaded_variable with object type - isolated unit test.""" @@ -97,31 +92,22 @@ class TestDraftVarLoaderSimple: with patch("services.workflow_draft_variable_service.storage") as mock_storage: mock_storage.load.return_value = test_json_content.encode() + mock_segment = ObjectSegment(value=test_object) + draft_var.build_segment_from_serialized_value.return_value = mock_segment - with patch.object(WorkflowDraftVariable, "build_segment_with_type") as mock_build_segment: - mock_segment = ObjectSegment(value=test_object) - mock_build_segment.return_value = mock_segment + # Execute the method + selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - with patch("factories.variable_factory.segment_to_variable") as mock_segment_to_variable: - mock_variable = Mock() - mock_variable.id = "draft-var-id" - mock_variable.name = "test_object" - mock_variable.value = mock_segment - mock_segment_to_variable.return_value = mock_variable + # Verify results + assert selector_tuple == ("test-node-id", "test_object") + assert variable.id == "draft-var-id" + assert variable.name == "test_object" + assert variable.description == "test description" + assert variable.value == test_object - # Execute the method - selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - - # Verify results - assert selector_tuple == ("test-node-id", "test_object") - assert variable.id == "draft-var-id" - assert variable.name == "test_object" - assert variable.description == "test description" - assert variable.value == test_object - - # Verify method calls - mock_storage.load.assert_called_once_with("storage/key/test.json") - mock_build_segment.assert_called_once_with(SegmentType.OBJECT, test_object) + # Verify method calls + mock_storage.load.assert_called_once_with("storage/key/test.json") + draft_var.build_segment_from_serialized_value.assert_called_once_with(SegmentType.OBJECT, test_object) def test_load_offloaded_variable_missing_variable_file_unit(self, draft_var_loader): """Test that assertion error is raised when variable_file is None.""" @@ -176,32 +162,23 @@ class TestDraftVarLoaderSimple: with patch("services.workflow_draft_variable_service.storage") as mock_storage: mock_storage.load.return_value = test_json_content.encode() + from graphon.variables.segments import FloatSegment - with patch.object(WorkflowDraftVariable, "build_segment_with_type") as mock_build_segment: - from dify_graph.variables.segments import FloatSegment + mock_segment = FloatSegment(value=test_number) + draft_var.build_segment_from_serialized_value.return_value = mock_segment - mock_segment = FloatSegment(value=test_number) - mock_build_segment.return_value = mock_segment + # Execute the method + selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - with patch("factories.variable_factory.segment_to_variable") as mock_segment_to_variable: - mock_variable = Mock() - mock_variable.id = "draft-var-id" - mock_variable.name = "test_number" - mock_variable.value = mock_segment - mock_segment_to_variable.return_value = mock_variable + # Verify results + assert selector_tuple == ("test-node-id", "test_number") + assert variable.id == "draft-var-id" + assert variable.name == "test_number" + assert variable.description == "test number description" - # Execute the method - selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - - # Verify results - assert selector_tuple == ("test-node-id", "test_number") - assert variable.id == "draft-var-id" - assert variable.name == "test_number" - assert variable.description == "test number description" - - # Verify method calls - mock_storage.load.assert_called_once_with("storage/key/test_number.json") - mock_build_segment.assert_called_once_with(SegmentType.NUMBER, test_number) + # Verify method calls + mock_storage.load.assert_called_once_with("storage/key/test_number.json") + draft_var.build_segment_from_serialized_value.assert_called_once_with(SegmentType.NUMBER, test_number) def test_load_offloaded_variable_array_type_unit(self, draft_var_loader): """Test _load_offloaded_variable with array type - isolated unit test.""" @@ -226,32 +203,83 @@ class TestDraftVarLoaderSimple: with patch("services.workflow_draft_variable_service.storage") as mock_storage: mock_storage.load.return_value = test_json_content.encode() + from graphon.variables.segments import ArrayAnySegment - with patch.object(WorkflowDraftVariable, "build_segment_with_type") as mock_build_segment: - from dify_graph.variables.segments import ArrayAnySegment + mock_segment = ArrayAnySegment(value=test_array) + draft_var.build_segment_from_serialized_value.return_value = mock_segment - mock_segment = ArrayAnySegment(value=test_array) - mock_build_segment.return_value = mock_segment + # Execute the method + selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) - with patch("factories.variable_factory.segment_to_variable") as mock_segment_to_variable: - mock_variable = Mock() - mock_variable.id = "draft-var-id" - mock_variable.name = "test_array" - mock_variable.value = mock_segment - mock_segment_to_variable.return_value = mock_variable + # Verify results + assert selector_tuple == ("test-node-id", "test_array") + assert variable.id == "draft-var-id" + assert variable.name == "test_array" + assert variable.description == "test array description" - # Execute the method - selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) + # Verify method calls + mock_storage.load.assert_called_once_with("storage/key/test_array.json") + draft_var.build_segment_from_serialized_value.assert_called_once_with(SegmentType.ARRAY_ANY, test_array) - # Verify results - assert selector_tuple == ("test-node-id", "test_array") - assert variable.id == "draft-var-id" - assert variable.name == "test_array" - assert variable.description == "test array description" + def test_load_offloaded_variable_file_type_rebuilds_storage_backed_payload(self, draft_var_loader): + upload_file = Mock(spec=UploadFile) + upload_file.key = "storage/key/test_file.json" - # Verify method calls - mock_storage.load.assert_called_once_with("storage/key/test_array.json") - mock_build_segment.assert_called_once_with(SegmentType.ARRAY_ANY, test_array) + variable_file = Mock(spec=WorkflowDraftVariableFile) + variable_file.value_type = SegmentType.FILE + variable_file.upload_file = upload_file + + draft_var = WorkflowDraftVariable() + draft_var.id = "draft-var-id" + draft_var.app_id = "app-1" + draft_var.node_id = "test-node-id" + draft_var.name = "test_file" + draft_var.description = "test file description" + draft_var._set_selector(["test-node-id", "test_file"]) + draft_var.variable_file = variable_file + + persisted_file = File( + id="file-1", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.LOCAL_FILE, + reference=build_file_reference(record_id="upload-1", storage_key="legacy-storage-key"), + filename="test.txt", + extension=".txt", + mime_type="text/plain", + size=12, + ) + rebuilt_file = File( + id="file-1", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.LOCAL_FILE, + reference=build_file_reference(record_id="upload-1"), + filename="test.txt", + extension=".txt", + mime_type="text/plain", + size=12, + storage_key="canonical-storage-key", + ) + + raw_file = { + **persisted_file.model_dump(mode="json"), + "tenant_id": "legacy-tenant", + } + + with ( + patch("services.workflow_draft_variable_service.storage") as mock_storage, + patch("models.workflow._resolve_workflow_app_tenant_id", return_value="tenant-1"), + patch("models.workflow.build_file_from_stored_mapping", return_value=rebuilt_file) as rebuild_file, + ): + mock_storage.load.return_value = json.dumps(raw_file).encode() + + selector_tuple, variable = draft_var_loader._load_offloaded_variable(draft_var) + + assert selector_tuple == ("test-node-id", "test_file") + assert variable.id == "draft-var-id" + assert variable.name == "test_file" + assert variable.description == "test file description" + assert variable.value == rebuilt_file + rebuild_file.assert_called_once_with(file_mapping=raw_file, tenant_id="tenant-1") def test_load_variables_with_offloaded_variables_unit(self, draft_var_loader): """Test load_variables method with mix of regular and offloaded variables.""" diff --git a/api/tests/unit_tests/services/workflow/test_workflow_converter.py b/api/tests/unit_tests/services/workflow/test_workflow_converter.py deleted file mode 100644 index a847c2b4d1a..00000000000 --- a/api/tests/unit_tests/services/workflow/test_workflow_converter.py +++ /dev/null @@ -1,431 +0,0 @@ -# test for api/services/workflow/workflow_converter.py -import json -from unittest.mock import MagicMock - -import pytest - -from core.app.app_config.entities import ( - AdvancedChatMessageEntity, - AdvancedChatPromptTemplateEntity, - AdvancedCompletionPromptTemplateEntity, - DatasetEntity, - DatasetRetrieveConfigEntity, - ExternalDataVariableEntity, - ModelConfigEntity, - PromptTemplateEntity, -) -from core.helper import encrypter -from dify_graph.model_runtime.entities.llm_entities import LLMMode -from dify_graph.model_runtime.entities.message_entities import PromptMessageRole -from dify_graph.variables.input_entities import VariableEntity, VariableEntityType -from models.api_based_extension import APIBasedExtension, APIBasedExtensionPoint -from models.model import AppMode -from services.workflow.workflow_converter import WorkflowConverter - - -@pytest.fixture -def default_variables(): - value = [ - VariableEntity( - variable="text_input", - label="text-input", - type=VariableEntityType.TEXT_INPUT, - ), - VariableEntity( - variable="paragraph", - label="paragraph", - type=VariableEntityType.PARAGRAPH, - ), - VariableEntity( - variable="select", - label="select", - type=VariableEntityType.SELECT, - ), - ] - return value - - -def test__convert_to_start_node(default_variables): - # act - result = WorkflowConverter()._convert_to_start_node(default_variables) - - # assert - assert isinstance(result["data"]["variables"][0]["type"], str) - assert result["data"]["variables"][0]["type"] == "text-input" - assert result["data"]["variables"][0]["variable"] == "text_input" - assert result["data"]["variables"][1]["variable"] == "paragraph" - assert result["data"]["variables"][2]["variable"] == "select" - - -def test__convert_to_http_request_node_for_chatbot(default_variables): - """ - Test convert to http request nodes for chatbot - :return: - """ - app_model = MagicMock() - app_model.id = "app_id" - app_model.tenant_id = "tenant_id" - app_model.mode = AppMode.CHAT - - api_based_extension_id = "api_based_extension_id" - mock_api_based_extension = APIBasedExtension( - tenant_id="tenant_id", - name="api-1", - api_key="encrypted_api_key", - api_endpoint="https://dify.ai", - ) - - mock_api_based_extension.id = api_based_extension_id - workflow_converter = WorkflowConverter() - workflow_converter._get_api_based_extension = MagicMock(return_value=mock_api_based_extension) - - encrypter.decrypt_token = MagicMock(return_value="api_key") - - external_data_variables = [ - ExternalDataVariableEntity( - variable="external_variable", type="api", config={"api_based_extension_id": api_based_extension_id} - ) - ] - - nodes, _ = workflow_converter._convert_to_http_request_node( - app_model=app_model, variables=default_variables, external_data_variables=external_data_variables - ) - - assert len(nodes) == 2 - assert nodes[0]["data"]["type"] == "http-request" - - http_request_node = nodes[0] - - assert http_request_node["data"]["method"] == "post" - assert http_request_node["data"]["url"] == mock_api_based_extension.api_endpoint - assert http_request_node["data"]["authorization"]["type"] == "api-key" - assert http_request_node["data"]["authorization"]["config"] == {"type": "bearer", "api_key": "api_key"} - assert http_request_node["data"]["body"]["type"] == "json" - - body_data = http_request_node["data"]["body"]["data"] - - assert body_data - - body_data_json = json.loads(body_data) - assert body_data_json["point"] == APIBasedExtensionPoint.APP_EXTERNAL_DATA_TOOL_QUERY - - body_params = body_data_json["params"] - assert body_params["app_id"] == app_model.id - assert body_params["tool_variable"] == external_data_variables[0].variable - assert len(body_params["inputs"]) == 3 - assert body_params["query"] == "{{#sys.query#}}" # for chatbot - - code_node = nodes[1] - assert code_node["data"]["type"] == "code" - - -def test__convert_to_http_request_node_for_workflow_app(default_variables): - """ - Test convert to http request nodes for workflow app - :return: - """ - app_model = MagicMock() - app_model.id = "app_id" - app_model.tenant_id = "tenant_id" - app_model.mode = AppMode.WORKFLOW - - api_based_extension_id = "api_based_extension_id" - mock_api_based_extension = APIBasedExtension( - tenant_id="tenant_id", - name="api-1", - api_key="encrypted_api_key", - api_endpoint="https://dify.ai", - ) - mock_api_based_extension.id = api_based_extension_id - - workflow_converter = WorkflowConverter() - workflow_converter._get_api_based_extension = MagicMock(return_value=mock_api_based_extension) - - encrypter.decrypt_token = MagicMock(return_value="api_key") - - external_data_variables = [ - ExternalDataVariableEntity( - variable="external_variable", type="api", config={"api_based_extension_id": api_based_extension_id} - ) - ] - - nodes, _ = workflow_converter._convert_to_http_request_node( - app_model=app_model, variables=default_variables, external_data_variables=external_data_variables - ) - - assert len(nodes) == 2 - assert nodes[0]["data"]["type"] == "http-request" - - http_request_node = nodes[0] - - assert http_request_node["data"]["method"] == "post" - assert http_request_node["data"]["url"] == mock_api_based_extension.api_endpoint - assert http_request_node["data"]["authorization"]["type"] == "api-key" - assert http_request_node["data"]["authorization"]["config"] == {"type": "bearer", "api_key": "api_key"} - assert http_request_node["data"]["body"]["type"] == "json" - - body_data = http_request_node["data"]["body"]["data"] - - assert body_data - - body_data_json = json.loads(body_data) - assert body_data_json["point"] == APIBasedExtensionPoint.APP_EXTERNAL_DATA_TOOL_QUERY - - body_params = body_data_json["params"] - assert body_params["app_id"] == app_model.id - assert body_params["tool_variable"] == external_data_variables[0].variable - assert len(body_params["inputs"]) == 3 - assert body_params["query"] == "" - - code_node = nodes[1] - assert code_node["data"]["type"] == "code" - - -def test__convert_to_knowledge_retrieval_node_for_chatbot(): - new_app_mode = AppMode.ADVANCED_CHAT - - dataset_config = DatasetEntity( - dataset_ids=["dataset_id_1", "dataset_id_2"], - retrieve_config=DatasetRetrieveConfigEntity( - retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE, - top_k=5, - score_threshold=0.8, - reranking_model={"reranking_provider_name": "cohere", "reranking_model_name": "rerank-english-v2.0"}, - reranking_enabled=True, - ), - ) - - model_config = ModelConfigEntity(provider="openai", model="gpt-4", mode="chat", parameters={}, stop=[]) - - node = WorkflowConverter()._convert_to_knowledge_retrieval_node( - new_app_mode=new_app_mode, dataset_config=dataset_config, model_config=model_config - ) - assert node is not None - - assert node["data"]["type"] == "knowledge-retrieval" - assert node["data"]["query_variable_selector"] == ["sys", "query"] - assert node["data"]["dataset_ids"] == dataset_config.dataset_ids - assert node["data"]["retrieval_mode"] == dataset_config.retrieve_config.retrieve_strategy.value - assert node["data"]["multiple_retrieval_config"] == { - "top_k": dataset_config.retrieve_config.top_k, - "score_threshold": dataset_config.retrieve_config.score_threshold, - "reranking_model": dataset_config.retrieve_config.reranking_model, - } - - -def test__convert_to_knowledge_retrieval_node_for_workflow_app(): - new_app_mode = AppMode.WORKFLOW - - dataset_config = DatasetEntity( - dataset_ids=["dataset_id_1", "dataset_id_2"], - retrieve_config=DatasetRetrieveConfigEntity( - query_variable="query", - retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE, - top_k=5, - score_threshold=0.8, - reranking_model={"reranking_provider_name": "cohere", "reranking_model_name": "rerank-english-v2.0"}, - reranking_enabled=True, - ), - ) - - model_config = ModelConfigEntity(provider="openai", model="gpt-4", mode="chat", parameters={}, stop=[]) - - node = WorkflowConverter()._convert_to_knowledge_retrieval_node( - new_app_mode=new_app_mode, dataset_config=dataset_config, model_config=model_config - ) - assert node is not None - - assert node["data"]["type"] == "knowledge-retrieval" - assert node["data"]["query_variable_selector"] == ["start", dataset_config.retrieve_config.query_variable] - assert node["data"]["dataset_ids"] == dataset_config.dataset_ids - assert node["data"]["retrieval_mode"] == dataset_config.retrieve_config.retrieve_strategy.value - assert node["data"]["multiple_retrieval_config"] == { - "top_k": dataset_config.retrieve_config.top_k, - "score_threshold": dataset_config.retrieve_config.score_threshold, - "reranking_model": dataset_config.retrieve_config.reranking_model, - } - - -def test__convert_to_llm_node_for_chatbot_simple_chat_model(default_variables): - new_app_mode = AppMode.ADVANCED_CHAT - model = "gpt-4" - model_mode = LLMMode.CHAT - - workflow_converter = WorkflowConverter() - start_node = workflow_converter._convert_to_start_node(default_variables) - graph = { - "nodes": [start_node], - "edges": [], # no need - } - - model_config_mock = MagicMock(spec=ModelConfigEntity) - model_config_mock.provider = "openai" - model_config_mock.model = model - model_config_mock.mode = model_mode.value - model_config_mock.parameters = {} - model_config_mock.stop = [] - - prompt_template = PromptTemplateEntity( - prompt_type=PromptTemplateEntity.PromptType.SIMPLE, - simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}.", - ) - - llm_node = workflow_converter._convert_to_llm_node( - original_app_mode=AppMode.CHAT, - new_app_mode=new_app_mode, - model_config=model_config_mock, - graph=graph, - prompt_template=prompt_template, - ) - - assert llm_node["data"]["type"] == "llm" - assert llm_node["data"]["model"]["name"] == model - assert llm_node["data"]["model"]["mode"] == model_mode.value - template = prompt_template.simple_prompt_template - assert template is not None - for v in default_variables: - template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}") - assert llm_node["data"]["prompt_template"][0]["text"] == template + "\n" - assert llm_node["data"]["context"]["enabled"] is False - - -def test__convert_to_llm_node_for_chatbot_simple_completion_model(default_variables): - new_app_mode = AppMode.ADVANCED_CHAT - model = "gpt-3.5-turbo-instruct" - model_mode = LLMMode.COMPLETION - - workflow_converter = WorkflowConverter() - start_node = workflow_converter._convert_to_start_node(default_variables) - graph = { - "nodes": [start_node], - "edges": [], # no need - } - - model_config_mock = MagicMock(spec=ModelConfigEntity) - model_config_mock.provider = "openai" - model_config_mock.model = model - model_config_mock.mode = model_mode.value - model_config_mock.parameters = {} - model_config_mock.stop = [] - - prompt_template = PromptTemplateEntity( - prompt_type=PromptTemplateEntity.PromptType.SIMPLE, - simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}.", - ) - - llm_node = workflow_converter._convert_to_llm_node( - original_app_mode=AppMode.CHAT, - new_app_mode=new_app_mode, - model_config=model_config_mock, - graph=graph, - prompt_template=prompt_template, - ) - - assert llm_node["data"]["type"] == "llm" - assert llm_node["data"]["model"]["name"] == model - assert llm_node["data"]["model"]["mode"] == model_mode.value - template = prompt_template.simple_prompt_template - assert template is not None - for v in default_variables: - template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}") - assert llm_node["data"]["prompt_template"]["text"] == template + "\n" - assert llm_node["data"]["context"]["enabled"] is False - - -def test__convert_to_llm_node_for_chatbot_advanced_chat_model(default_variables): - new_app_mode = AppMode.ADVANCED_CHAT - model = "gpt-4" - model_mode = LLMMode.CHAT - - workflow_converter = WorkflowConverter() - start_node = workflow_converter._convert_to_start_node(default_variables) - graph = { - "nodes": [start_node], - "edges": [], # no need - } - - model_config_mock = MagicMock(spec=ModelConfigEntity) - model_config_mock.provider = "openai" - model_config_mock.model = model - model_config_mock.mode = model_mode.value - model_config_mock.parameters = {} - model_config_mock.stop = [] - - prompt_template = PromptTemplateEntity( - prompt_type=PromptTemplateEntity.PromptType.ADVANCED, - advanced_chat_prompt_template=AdvancedChatPromptTemplateEntity( - messages=[ - AdvancedChatMessageEntity( - text="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}", - role=PromptMessageRole.SYSTEM, - ), - AdvancedChatMessageEntity(text="Hi.", role=PromptMessageRole.USER), - AdvancedChatMessageEntity(text="Hello!", role=PromptMessageRole.ASSISTANT), - ] - ), - ) - - llm_node = workflow_converter._convert_to_llm_node( - original_app_mode=AppMode.CHAT, - new_app_mode=new_app_mode, - model_config=model_config_mock, - graph=graph, - prompt_template=prompt_template, - ) - - assert llm_node["data"]["type"] == "llm" - assert llm_node["data"]["model"]["name"] == model - assert llm_node["data"]["model"]["mode"] == model_mode.value - assert isinstance(llm_node["data"]["prompt_template"], list) - assert prompt_template.advanced_chat_prompt_template is not None - assert len(llm_node["data"]["prompt_template"]) == len(prompt_template.advanced_chat_prompt_template.messages) - template = prompt_template.advanced_chat_prompt_template.messages[0].text - for v in default_variables: - template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}") - assert llm_node["data"]["prompt_template"][0]["text"] == template - - -def test__convert_to_llm_node_for_workflow_advanced_completion_model(default_variables): - new_app_mode = AppMode.ADVANCED_CHAT - model = "gpt-3.5-turbo-instruct" - model_mode = LLMMode.COMPLETION - - workflow_converter = WorkflowConverter() - start_node = workflow_converter._convert_to_start_node(default_variables) - graph = { - "nodes": [start_node], - "edges": [], # no need - } - - model_config_mock = MagicMock(spec=ModelConfigEntity) - model_config_mock.provider = "openai" - model_config_mock.model = model - model_config_mock.mode = model_mode.value - model_config_mock.parameters = {} - model_config_mock.stop = [] - - prompt_template = PromptTemplateEntity( - prompt_type=PromptTemplateEntity.PromptType.ADVANCED, - advanced_completion_prompt_template=AdvancedCompletionPromptTemplateEntity( - prompt="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}\n\nHuman: hi\nAssistant: ", - role_prefix=AdvancedCompletionPromptTemplateEntity.RolePrefixEntity(user="Human", assistant="Assistant"), - ), - ) - - llm_node = workflow_converter._convert_to_llm_node( - original_app_mode=AppMode.CHAT, - new_app_mode=new_app_mode, - model_config=model_config_mock, - graph=graph, - prompt_template=prompt_template, - ) - - assert llm_node["data"]["type"] == "llm" - assert llm_node["data"]["model"]["name"] == model - assert llm_node["data"]["model"]["mode"] == model_mode.value - assert isinstance(llm_node["data"]["prompt_template"], dict) - assert prompt_template.advanced_completion_prompt_template is not None - template = prompt_template.advanced_completion_prompt_template.prompt - for v in default_variables: - template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}") - assert llm_node["data"]["prompt_template"]["text"] == template diff --git a/api/tests/unit_tests/services/workflow/test_workflow_deletion.py b/api/tests/unit_tests/services/workflow/test_workflow_deletion.py deleted file mode 100644 index dfe325648d2..00000000000 --- a/api/tests/unit_tests/services/workflow/test_workflow_deletion.py +++ /dev/null @@ -1,127 +0,0 @@ -from unittest.mock import MagicMock - -import pytest -from sqlalchemy.orm import Session - -from models.model import App -from models.workflow import Workflow -from services.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError, WorkflowService - - -@pytest.fixture -def workflow_setup(): - mock_session_maker = MagicMock() - workflow_service = WorkflowService(mock_session_maker) - session = MagicMock(spec=Session) - tenant_id = "test-tenant-id" - workflow_id = "test-workflow-id" - - # Mock workflow - workflow = MagicMock(spec=Workflow) - workflow.id = workflow_id - workflow.tenant_id = tenant_id - workflow.version = "1.0" # Not a draft - workflow.tool_published = False # Not published as a tool by default - - # Mock app - app = MagicMock(spec=App) - app.id = "test-app-id" - app.name = "Test App" - app.workflow_id = None # Not used by an app by default - - return { - "workflow_service": workflow_service, - "session": session, - "tenant_id": tenant_id, - "workflow_id": workflow_id, - "workflow": workflow, - "app": app, - } - - -def test_delete_workflow_success(workflow_setup): - # Setup mocks - - # Mock the tool provider query to return None (not published as a tool) - workflow_setup["session"].query.return_value.where.return_value.first.return_value = None - - workflow_setup["session"].scalar = MagicMock( - side_effect=[workflow_setup["workflow"], None] - ) # Return workflow first, then None for app - - # Call the method - result = workflow_setup["workflow_service"].delete_workflow( - session=workflow_setup["session"], - workflow_id=workflow_setup["workflow_id"], - tenant_id=workflow_setup["tenant_id"], - ) - - # Verify - assert result is True - workflow_setup["session"].delete.assert_called_once_with(workflow_setup["workflow"]) - - -def test_delete_workflow_draft_error(workflow_setup): - # Setup mocks - workflow_setup["workflow"].version = "draft" - workflow_setup["session"].scalar = MagicMock(return_value=workflow_setup["workflow"]) - - # Call the method and verify exception - with pytest.raises(DraftWorkflowDeletionError): - workflow_setup["workflow_service"].delete_workflow( - session=workflow_setup["session"], - workflow_id=workflow_setup["workflow_id"], - tenant_id=workflow_setup["tenant_id"], - ) - - # Verify - workflow_setup["session"].delete.assert_not_called() - - -def test_delete_workflow_in_use_by_app_error(workflow_setup): - # Setup mocks - workflow_setup["app"].workflow_id = workflow_setup["workflow_id"] - workflow_setup["session"].scalar = MagicMock( - side_effect=[workflow_setup["workflow"], workflow_setup["app"]] - ) # Return workflow first, then app - - # Call the method and verify exception - with pytest.raises(WorkflowInUseError) as excinfo: - workflow_setup["workflow_service"].delete_workflow( - session=workflow_setup["session"], - workflow_id=workflow_setup["workflow_id"], - tenant_id=workflow_setup["tenant_id"], - ) - - # Verify error message contains app name - assert "Cannot delete workflow that is currently in use by app" in str(excinfo.value) - - # Verify - workflow_setup["session"].delete.assert_not_called() - - -def test_delete_workflow_published_as_tool_error(workflow_setup): - # Setup mocks - from models.tools import WorkflowToolProvider - - # Mock the tool provider query - mock_tool_provider = MagicMock(spec=WorkflowToolProvider) - workflow_setup["session"].query.return_value.where.return_value.first.return_value = mock_tool_provider - - workflow_setup["session"].scalar = MagicMock( - side_effect=[workflow_setup["workflow"], None] - ) # Return workflow first, then None for app - - # Call the method and verify exception - with pytest.raises(WorkflowInUseError) as excinfo: - workflow_setup["workflow_service"].delete_workflow( - session=workflow_setup["session"], - workflow_id=workflow_setup["workflow_id"], - tenant_id=workflow_setup["tenant_id"], - ) - - # Verify error message - assert "Cannot delete workflow that is published as a tool" in str(excinfo.value) - - # Verify - workflow_setup["session"].delete.assert_not_called() diff --git a/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py b/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py index 0c2be9c79fd..e7e72793a32 100644 --- a/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py +++ b/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py @@ -4,13 +4,19 @@ import uuid from unittest.mock import MagicMock, Mock, patch import pytest +from graphon.enums import BuiltinNodeTypes +from graphon.file import File, FileTransferMethod, FileType +from graphon.variables.segments import StringSegment +from graphon.variables.types import SegmentType from sqlalchemy import Engine from sqlalchemy.orm import Session -from dify_graph.constants import SYSTEM_VARIABLE_NODE_ID -from dify_graph.enums import BuiltinNodeTypes, SystemVariableKey -from dify_graph.variables.segments import StringSegment -from dify_graph.variables.types import SegmentType +from core.workflow.system_variables import SystemVariableKey +from core.workflow.variable_prefixes import ( + CONVERSATION_VARIABLE_NODE_ID, + ENVIRONMENT_VARIABLE_NODE_ID, + SYSTEM_VARIABLE_NODE_ID, +) from libs.uuid_utils import uuidv7 from models.account import Account from models.enums import DraftVariableType @@ -86,6 +92,20 @@ class TestDraftVariableSaver: expected_node_id=_NODE_ID, expected_name="start_input", ), + TestCase( + name="name with `env.` prefix should return the environment node_id", + input_node_id=_NODE_ID, + input_name="env.API_KEY", + expected_node_id=ENVIRONMENT_VARIABLE_NODE_ID, + expected_name="API_KEY", + ), + TestCase( + name="name with `conversation.` prefix should return the conversation node_id", + input_node_id=_NODE_ID, + input_name="conversation.session_id", + expected_node_id=CONVERSATION_VARIABLE_NODE_ID, + expected_name="session_id", + ), TestCase( name="dummy_variable should return the original input node_id", input_node_id=_NODE_ID, @@ -112,6 +132,47 @@ class TestDraftVariableSaver: assert node_id == c.expected_node_id, fail_msg assert name == c.expected_name, fail_msg + def test_build_variables_from_start_mapping_rebuilds_system_files(self): + mock_session = MagicMock(spec=Session) + mock_user = MagicMock(spec=Account) + mock_user.id = str(uuid.uuid4()) + saver = DraftVariableSaver( + session=mock_session, + app_id=self._get_test_app_id(), + node_id="start", + node_type=BuiltinNodeTypes.START, + node_execution_id="exec-1", + user=mock_user, + ) + rebuilt_file = File( + id="file-1", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.LOCAL_FILE, + reference="upload-1", + filename="test.txt", + extension=".txt", + mime_type="text/plain", + size=12, + storage_key="canonical-storage-key", + ) + raw_file = { + **rebuilt_file.model_dump(mode="json"), + "tenant_id": "legacy-tenant", + } + + with ( + patch.object(saver, "_resolve_app_tenant_id", return_value="tenant-1"), + patch( + "services.workflow_draft_variable_service.build_file_from_stored_mapping", + return_value=rebuilt_file, + ) as rebuild_file, + ): + draft_vars = saver._build_variables_from_start_mapping({"sys.files": [raw_file]}) + + sys_var = draft_vars[0] + assert sys_var.get_value().value[0] == rebuilt_file + rebuild_file.assert_called_once_with(file_mapping=raw_file, tenant_id="tenant-1") + @pytest.fixture def mock_session(self): """Mock SQLAlchemy session.""" @@ -218,6 +279,46 @@ class TestDraftVariableSaver: str(SystemVariableKey.WORKFLOW_EXECUTION_ID), } + @patch("services.workflow_draft_variable_service._batch_upsert_draft_variable", autospec=True) + def test_start_node_save_normalizes_reserved_prefix_outputs(self, mock_batch_upsert): + mock_session = MagicMock(spec=Session) + mock_user = MagicMock(spec=Account) + mock_user.id = "test-user-id" + mock_user.tenant_id = "test-tenant-id" + + saver = DraftVariableSaver( + session=mock_session, + app_id="test-app-id", + node_id="start-node-id", + node_type=BuiltinNodeTypes.START, + node_execution_id="exec-id", + user=mock_user, + ) + + saver.save( + outputs={ + "env.API_KEY": "secret", + "conversation.session_id": "conversation-1", + "sys.workflow_run_id": "run-id-123", + } + ) + + mock_batch_upsert.assert_called_once() + draft_vars = mock_batch_upsert.call_args[0][1] + + assert len(draft_vars) == 3 + + env_var = next(v for v in draft_vars if v.node_id == ENVIRONMENT_VARIABLE_NODE_ID) + assert env_var.name == "API_KEY" + assert env_var.editable is False + + conversation_var = next(v for v in draft_vars if v.node_id == CONVERSATION_VARIABLE_NODE_ID) + assert conversation_var.name == "session_id" + assert conversation_var.node_execution_id is None + + sys_var = next(v for v in draft_vars if v.node_id == SYSTEM_VARIABLE_NODE_ID) + assert sys_var.name == str(SystemVariableKey.WORKFLOW_EXECUTION_ID) + class TestWorkflowDraftVariableService: def _get_test_app_id(self): diff --git a/api/tests/unit_tests/services/workflow/test_workflow_event_snapshot_service.py b/api/tests/unit_tests/services/workflow/test_workflow_event_snapshot_service.py index 6c1adba2b8b..077a7c27a2b 100644 --- a/api/tests/unit_tests/services/workflow/test_workflow_event_snapshot_service.py +++ b/api/tests/unit_tests/services/workflow/test_workflow_event_snapshot_service.py @@ -8,13 +8,13 @@ from datetime import UTC, datetime from threading import Event import pytest +from graphon.entities.pause_reason import HumanInputRequired +from graphon.enums import WorkflowExecutionStatus, WorkflowNodeExecutionStatus +from graphon.runtime import GraphRuntimeState, VariablePool from core.app.app_config.entities import WorkflowUIBasedAppConfig from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity from core.app.layers.pause_state_persist_layer import WorkflowResumptionContext, _WorkflowGenerateEntityWrapper -from dify_graph.entities.pause_reason import HumanInputRequired -from dify_graph.enums import WorkflowExecutionStatus, WorkflowNodeExecutionStatus -from dify_graph.runtime import GraphRuntimeState, VariablePool from models.enums import CreatorUserRole from models.model import AppMode from models.workflow import WorkflowRun diff --git a/api/tests/unit_tests/services/workflow/test_workflow_human_input_delivery.py b/api/tests/unit_tests/services/workflow/test_workflow_human_input_delivery.py index c890ab6a65b..98d057e41fe 100644 --- a/api/tests/unit_tests/services/workflow/test_workflow_human_input_delivery.py +++ b/api/tests/unit_tests/services/workflow/test_workflow_human_input_delivery.py @@ -3,16 +3,16 @@ from types import SimpleNamespace from unittest.mock import MagicMock import pytest +from graphon.entities.graph_config import NodeConfigDict, NodeConfigDictAdapter +from graphon.enums import BuiltinNodeTypes +from graphon.nodes.human_input.entities import HumanInputNodeData from sqlalchemy.orm import sessionmaker -from dify_graph.entities.graph_config import NodeConfigDict, NodeConfigDictAdapter -from dify_graph.enums import BuiltinNodeTypes -from dify_graph.nodes.human_input.entities import ( +from core.workflow.human_input_compat import ( EmailDeliveryConfig, EmailDeliveryMethod, EmailRecipients, ExternalRecipient, - HumanInputNodeData, MemberRecipient, ) from services import workflow_service as workflow_service_module @@ -23,7 +23,7 @@ def _make_service() -> WorkflowService: return WorkflowService(session_maker=sessionmaker()) -def _build_node_config(delivery_methods: list[EmailDeliveryMethod]) -> NodeConfigDict: +def _build_node_config(delivery_methods: list[EmailDeliveryMethod], *, legacy: bool = False) -> NodeConfigDict: node_data = HumanInputNodeData( title="Human Input", delivery_methods=delivery_methods, @@ -31,6 +31,14 @@ def _build_node_config(delivery_methods: list[EmailDeliveryMethod]) -> NodeConfi inputs=[], user_actions=[], ).model_dump(mode="json") + if legacy: + for delivery_method in node_data["delivery_methods"]: + recipients = delivery_method.get("config", {}).get("recipients", {}) + if "include_bound_group" in recipients: + recipients["whole_workspace"] = recipients.pop("include_bound_group") + for recipient in recipients.get("items", []): + if "reference_id" in recipient: + recipient["user_id"] = recipient.pop("reference_id") node_data["type"] = BuiltinNodeTypes.HUMAN_INPUT return NodeConfigDictAdapter.validate_python({"id": "node-1", "data": node_data}) @@ -41,7 +49,7 @@ def _make_email_method(enabled: bool = True, debug_mode: bool = False) -> EmailD enabled=enabled, config=EmailDeliveryConfig( recipients=EmailRecipients( - whole_workspace=False, + include_bound_group=False, items=[ExternalRecipient(email="tester@example.com")], ), subject="Test subject", @@ -69,7 +77,7 @@ def test_human_input_delivery_requires_draft_workflow(): def test_human_input_delivery_allows_disabled_method(monkeypatch: pytest.MonkeyPatch): service = _make_service() delivery_method = _make_email_method(enabled=False) - node_config = _build_node_config([delivery_method]) + node_config = _build_node_config([delivery_method], legacy=True) workflow = MagicMock() workflow.get_node_config_by_id.return_value = node_config service.get_draft_workflow = MagicMock(return_value=workflow) # type: ignore[method-assign] @@ -105,7 +113,7 @@ def test_human_input_delivery_allows_disabled_method(monkeypatch: pytest.MonkeyP def test_human_input_delivery_dispatches_to_test_service(monkeypatch: pytest.MonkeyPatch): service = _make_service() delivery_method = _make_email_method(enabled=True) - node_config = _build_node_config([delivery_method]) + node_config = _build_node_config([delivery_method], legacy=True) workflow = MagicMock() workflow.get_node_config_by_id.return_value = node_config service.get_draft_workflow = MagicMock(return_value=workflow) # type: ignore[method-assign] @@ -144,7 +152,7 @@ def test_human_input_delivery_dispatches_to_test_service(monkeypatch: pytest.Mon def test_human_input_delivery_debug_mode_overrides_recipients(monkeypatch: pytest.MonkeyPatch): service = _make_service() delivery_method = _make_email_method(enabled=True, debug_mode=True) - node_config = _build_node_config([delivery_method]) + node_config = _build_node_config([delivery_method], legacy=True) workflow = MagicMock() workflow.get_node_config_by_id.return_value = node_config service.get_draft_workflow = MagicMock(return_value=workflow) # type: ignore[method-assign] @@ -178,8 +186,8 @@ def test_human_input_delivery_debug_mode_overrides_recipients(monkeypatch: pytes sent_method = test_service_instance.send_test.call_args.kwargs["method"] assert isinstance(sent_method, EmailDeliveryMethod) assert sent_method.config.debug_mode is True - assert sent_method.config.recipients.whole_workspace is False + assert sent_method.config.recipients.include_bound_group is False assert len(sent_method.config.recipients.items) == 1 recipient = sent_method.config.recipients.items[0] assert isinstance(recipient, MemberRecipient) - assert recipient.user_id == account.id + assert recipient.reference_id == account.id diff --git a/api/tests/unit_tests/services/workflow/test_workflow_node_execution_service_repository.py b/api/tests/unit_tests/services/workflow/test_workflow_node_execution_service_repository.py deleted file mode 100644 index 79bf5e94c28..00000000000 --- a/api/tests/unit_tests/services/workflow/test_workflow_node_execution_service_repository.py +++ /dev/null @@ -1,30 +0,0 @@ -from unittest.mock import MagicMock - -import pytest - -from repositories.sqlalchemy_api_workflow_node_execution_repository import ( - DifyAPISQLAlchemyWorkflowNodeExecutionRepository, -) - - -class TestSQLAlchemyWorkflowNodeExecutionServiceRepository: - @pytest.fixture - def repository(self): - mock_session_maker = MagicMock() - return DifyAPISQLAlchemyWorkflowNodeExecutionRepository(session_maker=mock_session_maker) - - def test_repository_implements_protocol(self, repository): - """Test that the repository implements the required protocol methods.""" - # Verify all protocol methods are implemented - assert hasattr(repository, "get_node_last_execution") - assert hasattr(repository, "get_executions_by_workflow_run") - assert hasattr(repository, "get_execution_by_id") - - # Verify methods are callable - assert callable(repository.get_node_last_execution) - assert callable(repository.get_executions_by_workflow_run) - assert callable(repository.get_execution_by_id) - assert callable(repository.delete_expired_executions) - assert callable(repository.delete_executions_by_app) - assert callable(repository.get_expired_executions_batch) - assert callable(repository.delete_executions_by_ids) diff --git a/api/tests/unit_tests/services/workflow/test_workflow_restore.py b/api/tests/unit_tests/services/workflow/test_workflow_restore.py new file mode 100644 index 00000000000..179361de452 --- /dev/null +++ b/api/tests/unit_tests/services/workflow/test_workflow_restore.py @@ -0,0 +1,77 @@ +import json +from types import SimpleNamespace + +from models.workflow import Workflow +from services.workflow_restore import apply_published_workflow_snapshot_to_draft + +LEGACY_FEATURES = { + "file_upload": { + "image": { + "enabled": True, + "number_limits": 6, + "transfer_methods": ["remote_url", "local_file"], + } + }, + "opening_statement": "", + "retriever_resource": {"enabled": True}, + "sensitive_word_avoidance": {"enabled": False}, + "speech_to_text": {"enabled": False}, + "suggested_questions": [], + "suggested_questions_after_answer": {"enabled": False}, + "text_to_speech": {"enabled": False, "language": "", "voice": ""}, +} + +NORMALIZED_FEATURES = { + "file_upload": { + "enabled": True, + "allowed_file_types": ["image"], + "allowed_file_extensions": [], + "allowed_file_upload_methods": ["remote_url", "local_file"], + "number_limits": 6, + }, + "opening_statement": "", + "retriever_resource": {"enabled": True}, + "sensitive_word_avoidance": {"enabled": False}, + "speech_to_text": {"enabled": False}, + "suggested_questions": [], + "suggested_questions_after_answer": {"enabled": False}, + "text_to_speech": {"enabled": False, "language": "", "voice": ""}, +} + + +def _create_workflow(*, workflow_id: str, version: str, features: dict[str, object]) -> Workflow: + return Workflow( + id=workflow_id, + tenant_id="tenant-id", + app_id="app-id", + type="workflow", + version=version, + graph=json.dumps({"nodes": [], "edges": []}), + features=json.dumps(features), + created_by="account-id", + environment_variables=[], + conversation_variables=[], + rag_pipeline_variables=[], + ) + + +def test_apply_published_workflow_snapshot_to_draft_copies_serialized_features_without_mutating_source() -> None: + source_workflow = _create_workflow( + workflow_id="published-workflow-id", + version="2026-03-19T00:00:00", + features=LEGACY_FEATURES, + ) + + draft_workflow, is_new_draft = apply_published_workflow_snapshot_to_draft( + tenant_id="tenant-id", + app_id="app-id", + source_workflow=source_workflow, + draft_workflow=None, + account=SimpleNamespace(id="account-id"), + updated_at_factory=lambda: source_workflow.updated_at, + ) + + assert is_new_draft is True + assert source_workflow.serialized_features == json.dumps(LEGACY_FEATURES) + assert source_workflow.normalized_features_dict == NORMALIZED_FEATURES + assert draft_workflow.serialized_features == json.dumps(LEGACY_FEATURES) diff --git a/api/tests/unit_tests/services/workflow/test_workflow_service.py b/api/tests/unit_tests/services/workflow/test_workflow_service.py deleted file mode 100644 index 538c1b3595c..00000000000 --- a/api/tests/unit_tests/services/workflow/test_workflow_service.py +++ /dev/null @@ -1,415 +0,0 @@ -from contextlib import nullcontext -from types import SimpleNamespace -from unittest.mock import MagicMock - -import pytest - -from dify_graph.entities.graph_config import NodeConfigDictAdapter -from dify_graph.enums import BuiltinNodeTypes -from dify_graph.nodes.human_input.entities import FormInput, HumanInputNodeData, UserAction -from dify_graph.nodes.human_input.enums import FormInputType -from models.model import App -from models.workflow import Workflow -from services import workflow_service as workflow_service_module -from services.workflow_service import WorkflowService - - -class TestWorkflowService: - @pytest.fixture - def workflow_service(self): - mock_session_maker = MagicMock() - return WorkflowService(mock_session_maker) - - @pytest.fixture - def mock_app(self): - app = MagicMock(spec=App) - app.id = "app-id-1" - app.workflow_id = "workflow-id-1" - app.tenant_id = "tenant-id-1" - return app - - @pytest.fixture - def mock_workflows(self): - workflows = [] - for i in range(5): - workflow = MagicMock(spec=Workflow) - workflow.id = f"workflow-id-{i}" - workflow.app_id = "app-id-1" - workflow.created_at = f"2023-01-0{5 - i}" # Descending date order - workflow.created_by = "user-id-1" if i % 2 == 0 else "user-id-2" - workflow.marked_name = f"Workflow {i}" if i % 2 == 0 else "" - workflows.append(workflow) - return workflows - - @pytest.fixture - def dummy_session_cls(self): - class DummySession: - def __init__(self, *args, **kwargs): - self.commit = MagicMock() - - def __enter__(self): - return self - - def __exit__(self, exc_type, exc, tb): - return False - - def begin(self): - return nullcontext() - - return DummySession - - def test_get_all_published_workflow_no_workflow_id(self, workflow_service, mock_app): - mock_app.workflow_id = None - mock_session = MagicMock() - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=10, user_id=None - ) - - assert workflows == [] - assert has_more is False - mock_session.scalars.assert_not_called() - - def test_get_all_published_workflow_basic(self, workflow_service, mock_app, mock_workflows): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - mock_scalar_result.all.return_value = mock_workflows[:3] - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=3, user_id=None - ) - - assert workflows == mock_workflows[:3] - assert has_more is False - mock_session.scalars.assert_called_once() - - def test_get_all_published_workflow_pagination(self, workflow_service, mock_app, mock_workflows): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - # Return 4 items when limit is 3, which should indicate has_more=True - mock_scalar_result.all.return_value = mock_workflows[:4] - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=3, user_id=None - ) - - # Should return only the first 3 items - assert len(workflows) == 3 - assert workflows == mock_workflows[:3] - assert has_more is True - - # Test page 2 - mock_scalar_result.all.return_value = mock_workflows[3:] - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=2, limit=3, user_id=None - ) - - assert len(workflows) == 2 - assert has_more is False - - def test_get_all_published_workflow_user_filter(self, workflow_service, mock_app, mock_workflows): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - # Filter workflows for user-id-1 - filtered_workflows = [w for w in mock_workflows if w.created_by == "user-id-1"] - mock_scalar_result.all.return_value = filtered_workflows - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=10, user_id="user-id-1" - ) - - assert workflows == filtered_workflows - assert has_more is False - mock_session.scalars.assert_called_once() - - # Verify that the select contains a user filter clause - args = mock_session.scalars.call_args[0][0] - assert "created_by" in str(args) - - def test_get_all_published_workflow_named_only(self, workflow_service, mock_app, mock_workflows): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - # Filter workflows that have a marked_name - named_workflows = [w for w in mock_workflows if w.marked_name] - mock_scalar_result.all.return_value = named_workflows - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=10, user_id=None, named_only=True - ) - - assert workflows == named_workflows - assert has_more is False - mock_session.scalars.assert_called_once() - - # Verify that the select contains a named_only filter clause - args = mock_session.scalars.call_args[0][0] - assert "marked_name !=" in str(args) - - def test_get_all_published_workflow_combined_filters(self, workflow_service, mock_app, mock_workflows): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - # Combined filter: user-id-1 and has marked_name - filtered_workflows = [w for w in mock_workflows if w.created_by == "user-id-1" and w.marked_name] - mock_scalar_result.all.return_value = filtered_workflows - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=10, user_id="user-id-1", named_only=True - ) - - assert workflows == filtered_workflows - assert has_more is False - mock_session.scalars.assert_called_once() - - # Verify that both filters are applied - args = mock_session.scalars.call_args[0][0] - assert "created_by" in str(args) - assert "marked_name !=" in str(args) - - def test_get_all_published_workflow_empty_result(self, workflow_service, mock_app): - mock_session = MagicMock() - mock_scalar_result = MagicMock() - mock_scalar_result.all.return_value = [] - mock_session.scalars.return_value = mock_scalar_result - - workflows, has_more = workflow_service.get_all_published_workflow( - session=mock_session, app_model=mock_app, page=1, limit=10, user_id=None - ) - - assert workflows == [] - assert has_more is False - mock_session.scalars.assert_called_once() - - def test_submit_human_input_form_preview_uses_rendered_content( - self, - workflow_service: WorkflowService, - monkeypatch: pytest.MonkeyPatch, - dummy_session_cls, - ) -> None: - service = workflow_service - node_data = HumanInputNodeData( - title="Human Input", - form_content="{{#$output.name#}}
", - inputs=[FormInput(type=FormInputType.TEXT_INPUT, output_variable_name="name")], - user_actions=[UserAction(id="approve", title="Approve")], - ) - node = MagicMock() - node.node_data = node_data - node.render_form_content_before_submission.return_value = "preview
" - node.render_form_content_with_outputs.return_value = "rendered
" - - service._build_human_input_variable_pool = MagicMock(return_value=MagicMock()) # type: ignore[method-assign] - service._build_human_input_node = MagicMock(return_value=node) # type: ignore[method-assign] - - workflow = MagicMock() - node_config = NodeConfigDictAdapter.validate_python( - {"id": "node-1", "data": {"type": BuiltinNodeTypes.HUMAN_INPUT}} - ) - workflow.get_node_config_by_id.return_value = node_config - workflow.get_enclosing_node_type_and_id.return_value = None - service.get_draft_workflow = MagicMock(return_value=workflow) # type: ignore[method-assign] - - saved_outputs: dict[str, object] = {} - - class DummySaver: - def __init__(self, *args, **kwargs): - pass - - def save(self, outputs, process_data): - saved_outputs.update(outputs) - - monkeypatch.setattr(workflow_service_module, "Session", dummy_session_cls) - monkeypatch.setattr(workflow_service_module, "DraftVariableSaver", DummySaver) - monkeypatch.setattr(workflow_service_module, "db", SimpleNamespace(engine=MagicMock())) - - app_model = SimpleNamespace(id="app-1", tenant_id="tenant-1") - account = SimpleNamespace(id="account-1") - - result = service.submit_human_input_form_preview( - app_model=app_model, - account=account, - node_id="node-1", - form_inputs={"name": "Ada", "extra": "ignored"}, - inputs={"#node-0.result#": "LLM output"}, - action="approve", - ) - - service._build_human_input_variable_pool.assert_called_once_with( - app_model=app_model, - workflow=workflow, - node_config=node_config, - manual_inputs={"#node-0.result#": "LLM output"}, - user_id="account-1", - ) - - node.render_form_content_with_outputs.assert_called_once() - called_args = node.render_form_content_with_outputs.call_args.args - assert called_args[0] == "preview
" - assert called_args[2] == node_data.outputs_field_names() - rendered_outputs = called_args[1] - assert rendered_outputs["name"] == "Ada" - assert rendered_outputs["extra"] == "ignored" - assert "extra" in saved_outputs - assert "extra" in result - assert saved_outputs["name"] == "Ada" - assert result["name"] == "Ada" - assert result["__action_id"] == "approve" - assert "__rendered_content" in result - - def test_submit_human_input_form_preview_missing_inputs_message(self, workflow_service: WorkflowService) -> None: - service = workflow_service - node_data = HumanInputNodeData( - title="Human Input", - form_content="{{#$output.name#}}
", - inputs=[FormInput(type=FormInputType.TEXT_INPUT, output_variable_name="name")], - user_actions=[UserAction(id="approve", title="Approve")], - ) - node = MagicMock() - node.node_data = node_data - node._render_form_content_before_submission.return_value = "preview
" - node._render_form_content_with_outputs.return_value = "rendered
" - - service._build_human_input_variable_pool = MagicMock(return_value=MagicMock()) # type: ignore[method-assign] - service._build_human_input_node = MagicMock(return_value=node) # type: ignore[method-assign] - - workflow = MagicMock() - workflow.get_node_config_by_id.return_value = NodeConfigDictAdapter.validate_python( - {"id": "node-1", "data": {"type": BuiltinNodeTypes.HUMAN_INPUT}} - ) - service.get_draft_workflow = MagicMock(return_value=workflow) # type: ignore[method-assign] - - app_model = SimpleNamespace(id="app-1", tenant_id="tenant-1") - account = SimpleNamespace(id="account-1") - with pytest.raises(ValueError) as exc_info: - service.submit_human_input_form_preview( - app_model=app_model, - account=account, - node_id="node-1", - form_inputs={}, - inputs={}, - action="approve", - ) - - assert "Missing required inputs" in str(exc_info.value) - - def test_run_draft_workflow_node_successful_behavior( - self, workflow_service, mock_app, monkeypatch, dummy_session_cls - ): - """Behavior: When a basic workflow node runs, it correctly sets up context, - executes the node, and saves outputs.""" - service = workflow_service - account = SimpleNamespace(id="account-1") - mock_workflow = MagicMock() - mock_workflow.id = "wf-1" - mock_workflow.tenant_id = "tenant-1" - mock_workflow.environment_variables = [] - mock_workflow.conversation_variables = [] - - # Mock node config - mock_workflow.get_node_config_by_id.return_value = NodeConfigDictAdapter.validate_python( - {"id": "node-1", "data": {"type": BuiltinNodeTypes.LLM}} - ) - mock_workflow.get_enclosing_node_type_and_id.return_value = None - - # Mock class methods - monkeypatch.setattr(workflow_service_module, "WorkflowDraftVariableService", MagicMock()) - monkeypatch.setattr(workflow_service_module, "DraftVarLoader", MagicMock()) - - # Mock workflow entry execution - mock_node_exec = MagicMock() - mock_node_exec.id = "exec-1" - mock_node_exec.process_data = {} - mock_run = MagicMock() - monkeypatch.setattr(workflow_service_module.WorkflowEntry, "single_step_run", mock_run) - - # Mock execution handling - service._handle_single_step_result = MagicMock(return_value=mock_node_exec) - - # Mock repository - mock_repo = MagicMock() - mock_repo.get_execution_by_id.return_value = mock_node_exec - mock_repo_factory = MagicMock(return_value=mock_repo) - monkeypatch.setattr( - workflow_service_module.DifyCoreRepositoryFactory, - "create_workflow_node_execution_repository", - mock_repo_factory, - ) - service._node_execution_service_repo = mock_repo - - # Set up node execution service repo mock to return our exec node - mock_node_exec.load_full_outputs.return_value = {"output_var": "result_value"} - mock_node_exec.node_id = "node-1" - mock_node_exec.node_type = "llm" - - # Mock draft variable saver - mock_saver = MagicMock() - monkeypatch.setattr(workflow_service_module, "DraftVariableSaver", MagicMock(return_value=mock_saver)) - - # Mock DB - monkeypatch.setattr(workflow_service_module, "db", SimpleNamespace(engine=MagicMock())) - - monkeypatch.setattr(workflow_service_module, "Session", dummy_session_cls) - - # Act - result = service.run_draft_workflow_node( - app_model=mock_app, - draft_workflow=mock_workflow, - node_id="node-1", - user_inputs={"input_val": "test"}, - account=account, - ) - - # Assert - assert result == mock_node_exec - service._handle_single_step_result.assert_called_once() - mock_repo.save.assert_called_once_with(mock_node_exec) - mock_saver.save.assert_called_once_with(process_data={}, outputs={"output_var": "result_value"}) - - def test_run_draft_workflow_node_failure_behavior(self, workflow_service, mock_app, monkeypatch, dummy_session_cls): - """Behavior: If retrieving the saved execution fails, an appropriate error bubble matches expectations.""" - service = workflow_service - account = SimpleNamespace(id="account-1") - mock_workflow = MagicMock() - mock_workflow.tenant_id = "tenant-1" - mock_workflow.environment_variables = [] - mock_workflow.conversation_variables = [] - mock_workflow.get_node_config_by_id.return_value = NodeConfigDictAdapter.validate_python( - {"id": "node-1", "data": {"type": BuiltinNodeTypes.LLM}} - ) - mock_workflow.get_enclosing_node_type_and_id.return_value = None - - monkeypatch.setattr(workflow_service_module, "WorkflowDraftVariableService", MagicMock()) - monkeypatch.setattr(workflow_service_module, "DraftVarLoader", MagicMock()) - monkeypatch.setattr(workflow_service_module.WorkflowEntry, "single_step_run", MagicMock()) - - mock_node_exec = MagicMock() - mock_node_exec.id = "exec-invalid" - service._handle_single_step_result = MagicMock(return_value=mock_node_exec) - - mock_repo = MagicMock() - mock_repo_factory = MagicMock(return_value=mock_repo) - monkeypatch.setattr( - workflow_service_module.DifyCoreRepositoryFactory, - "create_workflow_node_execution_repository", - mock_repo_factory, - ) - service._node_execution_service_repo = mock_repo - - # Simulate failure to retrieve the saved execution - mock_repo.get_execution_by_id.return_value = None - - monkeypatch.setattr(workflow_service_module, "db", SimpleNamespace(engine=MagicMock())) - - monkeypatch.setattr(workflow_service_module, "Session", dummy_session_cls) - - # Act & Assert - with pytest.raises(ValueError, match="WorkflowNodeExecution with id exec-invalid not found after saving"): - service.run_draft_workflow_node( - app_model=mock_app, draft_workflow=mock_workflow, node_id="node-1", user_inputs={}, account=account - ) diff --git a/api/tests/unit_tests/tasks/test_clean_dataset_task.py b/api/tests/unit_tests/tasks/test_clean_dataset_task.py index 74ba7f9c340..936a10d6c5d 100644 --- a/api/tests/unit_tests/tasks/test_clean_dataset_task.py +++ b/api/tests/unit_tests/tasks/test_clean_dataset_task.py @@ -16,6 +16,7 @@ from unittest.mock import MagicMock, patch import pytest +from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType from models.enums import DataSourceType from tasks.clean_dataset_task import clean_dataset_task @@ -183,10 +184,10 @@ class TestErrorHandling: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, ) # Assert @@ -228,10 +229,10 @@ class TestPipelineAndWorkflowDeletion: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, pipeline_id=pipeline_id, ) @@ -264,10 +265,10 @@ class TestPipelineAndWorkflowDeletion: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, pipeline_id=None, ) @@ -320,10 +321,10 @@ class TestSegmentAttachmentCleanup: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, ) # Assert @@ -365,10 +366,10 @@ class TestSegmentAttachmentCleanup: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, ) # Assert - storage delete was attempted @@ -407,10 +408,10 @@ class TestEdgeCases: clean_dataset_task( dataset_id=dataset_id, tenant_id=tenant_id, - indexing_technique="high_quality", + indexing_technique=IndexTechniqueType.HIGH_QUALITY, index_struct='{"type": "paragraph"}', collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, ) # Assert @@ -444,7 +445,7 @@ class TestIndexProcessorParameters: - Dataset object with correct attributes is passed """ # Arrange - indexing_technique = "high_quality" + indexing_technique = IndexTechniqueType.HIGH_QUALITY index_struct = '{"type": "paragraph"}' # Act @@ -454,7 +455,7 @@ class TestIndexProcessorParameters: indexing_technique=indexing_technique, index_struct=index_struct, collection_binding_id=collection_binding_id, - doc_form="paragraph_index", + doc_form=IndexStructureType.PARAGRAPH_INDEX, ) # Assert diff --git a/api/tests/unit_tests/tasks/test_dataset_indexing_task.py b/api/tests/unit_tests/tasks/test_dataset_indexing_task.py index 8a721124d64..0b189ebae29 100644 --- a/api/tests/unit_tests/tasks/test_dataset_indexing_task.py +++ b/api/tests/unit_tests/tasks/test_dataset_indexing_task.py @@ -15,6 +15,7 @@ from unittest.mock import MagicMock, Mock, patch import pytest from core.indexing_runner import DocumentIsPausedError +from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType from core.rag.pipeline.queue import TenantIsolatedTaskQueue from enums.cloud_plan import CloudPlan from extensions.ext_redis import redis_client @@ -58,6 +59,11 @@ def mock_redis(): # Redis is already mocked globally in conftest.py # Reset it for each test redis_client.reset_mock() + redis_client.get.reset_mock() + redis_client.setex.reset_mock() + redis_client.delete.reset_mock() + redis_client.lpush.reset_mock() + redis_client.rpop.reset_mock() redis_client.get.return_value = None redis_client.setex.return_value = True redis_client.delete.return_value = True @@ -203,7 +209,7 @@ def mock_dataset(dataset_id, tenant_id): dataset = Mock(spec=Dataset) dataset.id = dataset_id dataset.tenant_id = tenant_id - dataset.indexing_technique = "high_quality" + dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY dataset.embedding_model_provider = "openai" dataset.embedding_model = "text-embedding-ada-002" return dataset @@ -222,7 +228,7 @@ def mock_documents(document_ids, dataset_id): doc.stopped_at = None doc.processing_started_at = None # optional attribute used in some code paths - doc.doc_form = "text_model" + doc.doc_form = IndexStructureType.PARAGRAPH_INDEX documents.append(doc) return documents diff --git a/api/tests/unit_tests/tasks/test_document_indexing_sync_task.py b/api/tests/unit_tests/tasks/test_document_indexing_sync_task.py index 3668416e36b..f49f4535af7 100644 --- a/api/tests/unit_tests/tasks/test_document_indexing_sync_task.py +++ b/api/tests/unit_tests/tasks/test_document_indexing_sync_task.py @@ -11,6 +11,7 @@ from unittest.mock import MagicMock, Mock, patch import pytest +from core.rag.index_processor.constant.index_type import IndexStructureType from models.dataset import Dataset, Document from tasks.document_indexing_sync_task import document_indexing_sync_task @@ -62,7 +63,7 @@ def mock_document(document_id, dataset_id, notion_workspace_id, notion_page_id, document.tenant_id = str(uuid.uuid4()) document.data_source_type = "notion_import" document.indexing_status = "completed" - document.doc_form = "text_model" + document.doc_form = IndexStructureType.PARAGRAPH_INDEX document.data_source_info_dict = { "notion_workspace_id": notion_workspace_id, "notion_page_id": notion_page_id, diff --git a/api/tests/unit_tests/tasks/test_enterprise_telemetry_task.py b/api/tests/unit_tests/tasks/test_enterprise_telemetry_task.py new file mode 100644 index 00000000000..b48c69a146b --- /dev/null +++ b/api/tests/unit_tests/tasks/test_enterprise_telemetry_task.py @@ -0,0 +1,69 @@ +"""Unit tests for enterprise telemetry Celery task.""" + +import json +from unittest.mock import MagicMock, patch + +import pytest + +from enterprise.telemetry.contracts import TelemetryCase, TelemetryEnvelope +from tasks.enterprise_telemetry_task import process_enterprise_telemetry + + +@pytest.fixture +def sample_envelope_json(): + envelope = TelemetryEnvelope( + case=TelemetryCase.APP_CREATED, + tenant_id="test-tenant", + event_id="test-event-123", + payload={"app_id": "app-123"}, + ) + return envelope.model_dump_json() + + +def test_process_enterprise_telemetry_success(sample_envelope_json): + with patch("tasks.enterprise_telemetry_task.EnterpriseMetricHandler") as mock_handler_class: + mock_handler = MagicMock() + mock_handler_class.return_value = mock_handler + + process_enterprise_telemetry(sample_envelope_json) + + mock_handler.handle.assert_called_once() + call_args = mock_handler.handle.call_args[0][0] + assert isinstance(call_args, TelemetryEnvelope) + assert call_args.case == TelemetryCase.APP_CREATED + assert call_args.tenant_id == "test-tenant" + assert call_args.event_id == "test-event-123" + + +def test_process_enterprise_telemetry_invalid_json(caplog): + invalid_json = "not valid json" + + process_enterprise_telemetry(invalid_json) + + assert "Failed to process enterprise telemetry envelope" in caplog.text + + +def test_process_enterprise_telemetry_handler_exception(sample_envelope_json, caplog): + with patch("tasks.enterprise_telemetry_task.EnterpriseMetricHandler") as mock_handler_class: + mock_handler = MagicMock() + mock_handler.handle.side_effect = Exception("Handler error") + mock_handler_class.return_value = mock_handler + + process_enterprise_telemetry(sample_envelope_json) + + assert "Failed to process enterprise telemetry envelope" in caplog.text + + +def test_process_enterprise_telemetry_validation_error(caplog): + invalid_envelope = json.dumps( + { + "case": "INVALID_CASE", + "tenant_id": "test-tenant", + "event_id": "test-event", + "payload": {}, + } + ) + + process_enterprise_telemetry(invalid_envelope) + + assert "Failed to process enterprise telemetry envelope" in caplog.text diff --git a/api/tests/unit_tests/tasks/test_human_input_timeout_tasks.py b/api/tests/unit_tests/tasks/test_human_input_timeout_tasks.py index bd0182a4029..7119217e94e 100644 --- a/api/tests/unit_tests/tasks/test_human_input_timeout_tasks.py +++ b/api/tests/unit_tests/tasks/test_human_input_timeout_tasks.py @@ -5,8 +5,8 @@ from types import SimpleNamespace from typing import Any import pytest +from graphon.nodes.human_input.enums import HumanInputFormKind, HumanInputFormStatus -from dify_graph.nodes.human_input.enums import HumanInputFormKind, HumanInputFormStatus from tasks import human_input_timeout_tasks as task_module diff --git a/api/tests/unit_tests/tasks/test_workflow_node_execution_tasks.py b/api/tests/unit_tests/tasks/test_workflow_node_execution_tasks.py index a223f0119e8..8cac696d98f 100644 --- a/api/tests/unit_tests/tasks/test_workflow_node_execution_tasks.py +++ b/api/tests/unit_tests/tasks/test_workflow_node_execution_tasks.py @@ -11,11 +11,11 @@ # import pytest -# from dify_graph.entities.workflow_node_execution import ( +# from graphon.entities.workflow_node_execution import ( # WorkflowNodeExecution, # WorkflowNodeExecutionStatus, # ) -# from dify_graph.enums import BuiltinNodeTypes +# from graphon.enums import BuiltinNodeTypes # from libs.datetime_utils import naive_utc_now # from models import WorkflowNodeExecutionModel # from models.enums import ExecutionOffLoadType diff --git a/api/tests/unit_tests/tools/test_mcp_tool.py b/api/tests/unit_tests/tools/test_mcp_tool.py index fa9c6af2874..68359ba078d 100644 --- a/api/tests/unit_tests/tools/test_mcp_tool.py +++ b/api/tests/unit_tests/tools/test_mcp_tool.py @@ -3,6 +3,7 @@ from decimal import Decimal from unittest.mock import Mock, patch import pytest +from graphon.model_runtime.entities.llm_entities import LLMUsage from core.mcp.types import ( AudioContent, @@ -17,7 +18,6 @@ from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ToolEntity, ToolIdentity, ToolInvokeMessage from core.tools.mcp_tool.tool import MCPTool -from dify_graph.model_runtime.entities.llm_entities import LLMUsage def _make_mcp_tool(output_schema: dict | None = None) -> MCPTool: diff --git a/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py b/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py index 7ec1343f980..ffa6833524d 100644 --- a/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py +++ b/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py @@ -2,10 +2,7 @@ from decimal import Decimal from unittest.mock import MagicMock, patch import pytest - -from core.llm_generator.output_parser.errors import OutputParserError -from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output -from dify_graph.model_runtime.entities.llm_entities import ( +from graphon.model_runtime.entities.llm_entities import ( LLMResult, LLMResultChunk, LLMResultChunkDelta, @@ -13,13 +10,16 @@ from dify_graph.model_runtime.entities.llm_entities import ( LLMResultWithStructuredOutput, LLMUsage, ) -from dify_graph.model_runtime.entities.message_entities import ( +from graphon.model_runtime.entities.message_entities import ( AssistantPromptMessage, SystemPromptMessage, TextPromptMessageContent, UserPromptMessage, ) -from dify_graph.model_runtime.entities.model_entities import AIModelEntity, ModelType +from graphon.model_runtime.entities.model_entities import AIModelEntity, ModelType + +from core.llm_generator.output_parser.errors import OutputParserError +from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output def create_mock_usage(prompt_tokens: int = 10, completion_tokens: int = 5) -> LLMUsage: @@ -336,7 +336,6 @@ def test_structured_output_parser(): json_schema=case["json_schema"], stream=case["stream"], model_parameters={"temperature": 0.7, "max_tokens": 100}, - user="test_user", ) if case["expected_result_type"] == "generator": @@ -367,7 +366,7 @@ def test_structured_output_parser(): call_args = model_instance.invoke_llm.call_args assert call_args.kwargs["stream"] == case["stream"] - assert call_args.kwargs["user"] == "test_user" + assert "user" not in call_args.kwargs assert "temperature" in call_args.kwargs["model_parameters"] assert "max_tokens" in call_args.kwargs["model_parameters"] diff --git a/api/tests/workflow_test_utils.py b/api/tests/workflow_test_utils.py index 1f0bf8ef376..d33ac2c7108 100644 --- a/api/tests/workflow_test_utils.py +++ b/api/tests/workflow_test_utils.py @@ -1,8 +1,12 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a034083304e..1d4ff4d86f5 100755 --- a/dev/pytest/pytest_unit_tests.sh +++ b/dev/pytest/pytest_unit_tests.sh @@ -13,4 +13,4 @@ PYTEST_XDIST_ARGS="${PYTEST_XDIST_ARGS:--n auto}" pytest --timeout "${PYTEST_TIMEOUT}" ${PYTEST_XDIST_ARGS} api/tests/unit_tests --ignore=api/tests/unit_tests/controllers # Run controller tests sequentially to avoid import race conditions -pytest --timeout "${PYTEST_TIMEOUT}" api/tests/unit_tests/controllers +pytest --timeout "${PYTEST_TIMEOUT}" --cov-append api/tests/unit_tests/controllers diff --git a/dev/setup b/dev/setup index 399c8f28a58..4236ff7fa74 100755 --- a/dev/setup +++ b/dev/setup @@ -24,5 +24,4 @@ cp "$MIDDLEWARE_ENV_EXAMPLE" "$MIDDLEWARE_ENV" cd "$ROOT/api" uv sync --group dev -cd "$ROOT/web" -pnpm install +pnpm --dir "$ROOT" install diff --git a/dev/start-web b/dev/start-web index f853f4a895b..baf008274b6 100755 --- a/dev/start-web +++ b/dev/start-web @@ -3,6 +3,6 @@ set -x SCRIPT_DIR="$(dirname "$(realpath "$0")")" -cd "$SCRIPT_DIR/../web" +ROOT_DIR="$(dirname "$SCRIPT_DIR")" -pnpm install && pnpm dev:inspect +pnpm --dir "$ROOT_DIR" install && pnpm --dir "$ROOT_DIR/web" dev:inspect diff --git a/docker/.env.example b/docker/.env.example index 9d6cd653187..9fbf9a9e72a 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -488,7 +488,8 @@ ALIYUN_OSS_REGION=ap-southeast-1 ALIYUN_OSS_AUTH_VERSION=v4 # Don't start with '/'. OSS doesn't support leading slash in object names. ALIYUN_OSS_PATH=your-path -ALIYUN_CLOUDBOX_ID=your-cloudbox-id +# Optional CloudBox ID for Aliyun OSS, DO NOT enable it if you are not using CloudBox. +#ALIYUN_CLOUDBOX_ID=your-cloudbox-id # Tencent COS Configuration # @@ -771,6 +772,9 @@ BAIDU_VECTOR_DB_SHARD=1 BAIDU_VECTOR_DB_REPLICAS=3 BAIDU_VECTOR_DB_INVERTED_INDEX_ANALYZER=DEFAULT_ANALYZER BAIDU_VECTOR_DB_INVERTED_INDEX_PARSER_MODE=COARSE_MODE +BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT=500 +BAIDU_VECTOR_DB_AUTO_BUILD_ROW_COUNT_INCREMENT_RATIO=0.05 +BAIDU_VECTOR_DB_REBUILD_INDEX_TIMEOUT_IN_SECONDS=300 # VikingDB configurations, only available when VECTOR_STORE is `vikingdb` VIKINGDB_ACCESS_KEY=your-ak diff --git a/docker/dify-env-sync.py b/docker/dify-env-sync.py new file mode 100755 index 00000000000..d7c762748c5 --- /dev/null +++ b/docker/dify-env-sync.py @@ -0,0 +1,440 @@ +#!/usr/bin/env python3 + +# ================================================================ +# Dify Environment Variables Synchronization Script +# +# Features: +# - Synchronize latest settings from .env.example to .env +# - Preserve custom settings in existing .env +# - Add new environment variables +# - Detect removed environment variables +# - Create backup files +# ================================================================ + +import argparse +import re +import shutil +import sys +from datetime import datetime +from pathlib import Path + +# ANSI color codes +RED = "\033[0;31m" +GREEN = "\033[0;32m" +YELLOW = "\033[1;33m" +BLUE = "\033[0;34m" +NC = "\033[0m" # No Color + + +def supports_color() -> bool: + """Return True if the terminal supports ANSI color codes.""" + return hasattr(sys.stdout, "isatty") and sys.stdout.isatty() + + +def log_info(message: str) -> None: + """Print an informational message in blue.""" + if supports_color(): + print(f"{BLUE}[INFO]{NC} {message}") + else: + print(f"[INFO] {message}") + + +def log_success(message: str) -> None: + """Print a success message in green.""" + if supports_color(): + print(f"{GREEN}[SUCCESS]{NC} {message}") + else: + print(f"[SUCCESS] {message}") + + +def log_warning(message: str) -> None: + """Print a warning message in yellow to stderr.""" + if supports_color(): + print(f"{YELLOW}[WARNING]{NC} {message}", file=sys.stderr) + else: + print(f"[WARNING] {message}", file=sys.stderr) + + +def log_error(message: str) -> None: + """Print an error message in red to stderr.""" + if supports_color(): + print(f"{RED}[ERROR]{NC} {message}", file=sys.stderr) + else: + print(f"[ERROR] {message}", file=sys.stderr) + + +def parse_env_file(path: Path) -> dict[str, str]: + """Parse an .env-style file and return a mapping of key to raw value. + + Lines that are blank or start with '#' (after optional whitespace) are + skipped. Only lines containing '=' are considered variable definitions. + + Args: + path: Path to the .env file to parse. + + Returns: + Ordered dict mapping variable name to its value string. + """ + variables: dict[str, str] = {} + with path.open(encoding="utf-8") as fh: + for line in fh: + line = line.rstrip("\n") + # Skip blank lines and comment lines + stripped = line.strip() + if not stripped or stripped.startswith("#"): + continue + if "=" not in line: + continue + key, _, value = line.partition("=") + key = key.strip() + if key: + variables[key] = value.strip() + return variables + + +def check_files(work_dir: Path) -> None: + """Verify required files exist; create .env from .env.example if absent. + + Args: + work_dir: Directory that must contain .env.example (and optionally .env). + + Raises: + SystemExit: If .env.example does not exist. + """ + log_info("Checking required files...") + + example_file = work_dir / ".env.example" + env_file = work_dir / ".env" + + if not example_file.exists(): + log_error(".env.example file not found") + sys.exit(1) + + if not env_file.exists(): + log_warning(".env file does not exist. Creating from .env.example.") + shutil.copy2(example_file, env_file) + log_success(".env file created") + + log_success("Required files verified") + + +def create_backup(work_dir: Path) -> None: + """Create a timestamped backup of the current .env file. + + Backups are placed in ``
+
+
+
+
diff --git a/docs/bn-BD/README.md b/docs/bn-BD/README.md
index f3fa68b4668..5dceacb1875 100644
--- a/docs/bn-BD/README.md
+++ b/docs/bn-BD/README.md
@@ -57,7 +57,11 @@
+
+
+
+
ডিফাই একটি ওপেন-সোর্স LLM অ্যাপ ডেভেলপমেন্ট প্ল্যাটফর্ম। এটি ইন্টুইটিভ ইন্টারফেস, এজেন্টিক AI ওয়ার্কফ্লো, RAG পাইপলাইন, এজেন্ট ক্যাপাবিলিটি, মডেল ম্যানেজমেন্ট, মনিটরিং সুবিধা এবং আরও অনেক কিছু একত্রিত করে, যা দ্রুত প্রোটোটাইপ থেকে প্রোডাকশন পর্যন্ত নিয়ে যেতে সহায়তা করে।
diff --git a/docs/de-DE/README.md b/docs/de-DE/README.md
index c71a0bfccfa..1eab517a6d9 100644
--- a/docs/de-DE/README.md
+++ b/docs/de-DE/README.md
@@ -57,7 +57,11 @@
+
+
+
+
Dify ist eine Open-Source-Plattform zur Entwicklung von LLM-Anwendungen. Ihre intuitive Benutzeroberfläche vereint agentenbasierte KI-Workflows, RAG-Pipelines, Agentenfunktionen, Modellverwaltung, Überwachungsfunktionen und mehr, sodass Sie schnell von einem Prototyp in die Produktion übergehen können.
diff --git a/docs/es-ES/README.md b/docs/es-ES/README.md
index da81b51d6a4..f4c60e3d8f9 100644
--- a/docs/es-ES/README.md
+++ b/docs/es-ES/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/eu-ai-act-compliance.md b/docs/eu-ai-act-compliance.md
new file mode 100644
index 00000000000..5fa29eed3f3
--- /dev/null
+++ b/docs/eu-ai-act-compliance.md
@@ -0,0 +1,186 @@
+# EU AI Act Compliance Guide for Dify Deployers
+
+Dify is an LLMOps platform for building RAG pipelines, agents, and AI workflows. If you deploy Dify in the EU — whether self-hosted or using a cloud provider — the EU AI Act applies to your deployment. This guide covers what the regulation requires and how Dify's architecture maps to those requirements.
+
+## Is your system in scope?
+
+The detailed obligations in Articles 12, 13, and 14 only apply to **high-risk AI systems** as defined in Annex III of the EU AI Act. A Dify application is high-risk if it is used for:
+
+- **Recruitment and HR** — screening candidates, evaluating employee performance, allocating tasks
+- **Credit scoring and insurance** — assessing creditworthiness or setting premiums
+- **Law enforcement** — profiling, criminal risk assessment, border control
+- **Critical infrastructure** — managing energy, water, transport, or telecommunications systems
+- **Education assessment** — grading students, determining admissions
+- **Essential public services** — evaluating eligibility for benefits, housing, or emergency services
+
+Most Dify deployments (customer-facing chatbots, internal knowledge bases, content generation workflows) are **not** high-risk. If your Dify application does not fall into one of the categories above:
+
+- **Article 50** (end-user transparency) still applies if users interact with your application directly. See the [Article 50 section](#article-50-end-user-transparency) below.
+- **GDPR** still applies if you process personal data. See the [GDPR section](#gdpr-considerations) below.
+- The high-risk obligations (Articles 9-15) are less likely to apply, but risk classification is context-dependent. **Do not self-classify without legal review.** Focus on Article 50 (transparency) and GDPR (data protection) as your baseline obligations.
+
+If you are unsure whether your use case qualifies as high-risk, consult a qualified legal professional before proceeding.
+
+## Self-hosted vs cloud: different compliance profiles
+
+| Deployment | Your role | Dify's role | Who handles compliance? |
+|-----------|----------|-------------|------------------------|
+| **Self-hosted** | Provider and deployer | Framework provider — obligations under Article 25 apply only if Dify is placed on the market or put into service as part of a complete AI system bearing its name or trademark | You |
+| **Dify Cloud** | Deployer | Provider and processor | Shared — Dify handles SOC 2 and GDPR for the platform; you handle AI Act obligations for your specific use case |
+
+Dify Cloud already has SOC 2 Type II and GDPR compliance for the platform itself. But the EU AI Act adds obligations specific to AI systems that SOC 2 does not cover: risk classification, technical documentation, transparency, and human oversight.
+
+## Supported providers and services
+
+Dify integrates with a broad range of AI providers and data stores. The following are the key ones relevant to compliance:
+
+- **AI providers:** HuggingFace (core), plus integrations with OpenAI, Anthropic, Google, and 100+ models via provider plugins
+- **Model identifiers include:** gpt-4o, gpt-3.5-turbo, claude-3-opus, gemini-2.5-flash, whisper-1, and others
+- **Vector database connections:** Extensive RAG infrastructure supporting numerous vector stores
+
+Dify's plugin architecture means actual provider usage depends on your configuration. Document which providers and models are active in your deployment.
+
+## Data flow diagram
+
+A typical Dify RAG deployment:
+
+```mermaid
+graph LR
+ USER((User)) -->|query| DIFY[Dify Platform]
+ DIFY -->|prompts| LLM([LLM Provider])
+ LLM -->|responses| DIFY
+ DIFY -->|documents| EMBED([Embedding Model])
+ EMBED -->|vectors| DIFY
+ DIFY -->|store/retrieve| VS[(Vector Store)]
+ DIFY -->|knowledge| KB[(Knowledge Base)]
+ DIFY -->|response| USER
+
+ classDef processor fill:#60a5fa,stroke:#1e40af,color:#000
+ classDef controller fill:#4ade80,stroke:#166534,color:#000
+ classDef app fill:#a78bfa,stroke:#5b21b6,color:#000
+ classDef user fill:#f472b6,stroke:#be185d,color:#000
+
+ class USER user
+ class DIFY app
+ class LLM processor
+ class EMBED processor
+ class VS controller
+ class KB controller
+```
+
+**GDPR roles** (providers are typically processors for customer-submitted data, but the exact role depends on each provider's terms of service and processing purpose; deployers should review each provider's DPA):
+- **Cloud LLM providers (OpenAI, Anthropic, Google)** typically act as processors — requires DPA.
+- **Cloud embedding services** typically act as processors — requires DPA.
+- **Self-hosted vector stores (Weaviate, Qdrant, pgvector):** Your organization remains the controller — no third-party transfer.
+- **Cloud vector stores (Pinecone, Zilliz Cloud)** typically act as processors — requires DPA.
+- **Knowledge base documents:** Your organization is the controller — stored in your infrastructure.
+
+## Article 11: Technical documentation
+
+High-risk systems need Annex IV documentation. For Dify deployments, key sections include:
+
+| Section | What Dify provides | What you must document |
+|---------|-------------------|----------------------|
+| General description | Platform capabilities, supported models | Your specific use case, intended users, deployment context |
+| Development process | Dify's architecture, plugin system | Your RAG pipeline design, prompt engineering, knowledge base curation |
+| Monitoring | Dify's built-in logging and analytics | Your monitoring plan, alert thresholds, incident response |
+| Performance metrics | Dify's evaluation features | Your accuracy benchmarks, quality thresholds, bias testing |
+| Risk management | — | Risk assessment for your specific use case |
+
+Some sections can be derived from Dify's architecture and your deployment configuration, as shown in the table above. The remaining sections require your input.
+
+## Article 12: Record-keeping
+
+Dify's built-in logging covers several Article 12 requirements:
+
+| Requirement | Dify Feature | Status |
+|------------|-------------|--------|
+| Conversation logs | Full conversation history with timestamps | **Covered** |
+| Model tracking | Model name recorded per interaction | **Covered** |
+| Token usage | Token counts per message | **Covered** |
+| Cost tracking | Cost per conversation (if provider reports it) | **Partial** |
+| Document retrieval | RAG source documents logged | **Covered** |
+| User identification | User session tracking | **Covered** |
+| Error logging | Failed generation logs | **Covered** |
+| Data retention | Configurable | **Your responsibility** |
+
+**Retention periods:** The required retention period depends on your role under the Act. Article 18 requires **providers** of high-risk systems to retain logs and technical documentation for **10 years** after market placement. Article 26(6) requires **deployers** to retain logs for at least **6 months**. If you self-host Dify and have substantially modified the system, you may be classified as a provider rather than a deployer. Confirm the applicable retention period with legal counsel.
+
+## Article 13: Transparency to deployers
+
+Article 13 requires providers of high-risk AI systems to supply deployers with the information needed to understand and operate the system correctly. This is a **documentation obligation**, not a logging obligation. For Dify deployments, this means the upstream LLM and embedding providers must give you:
+
+- Instructions for use, including intended purpose and known limitations
+- Accuracy metrics and performance benchmarks
+- Known or foreseeable risks and residual risks after mitigation
+- Technical specifications: input/output formats, training data characteristics, model architecture details
+
+As a deployer, collect model cards, system documentation, and accuracy reports from each AI provider your Dify application uses. Maintain these as part of your Annex IV technical documentation.
+
+Dify's platform features provide **supporting evidence** that can inform Article 13 documentation, but they do not satisfy Article 13 on their own:
+- **Source attribution** — Dify's RAG citation feature shows which documents informed the response, supporting deployer-side auditing
+- **Model identification** — Dify logs which LLM model generates responses, providing evidence for system documentation
+- **Conversation logs** — execution history helps compile performance and behavior evidence
+
+You must independently produce system documentation covering how your specific Dify deployment uses AI, its intended purpose, performance characteristics, and residual risks.
+
+## Article 50: End-user transparency
+
+Article 50 requires deployers to inform end users that they are interacting with an AI system. This is a separate obligation from Article 13 and applies even to limited-risk systems.
+
+For Dify applications serving end users:
+
+1. **Disclose AI involvement** — tell users they are interacting with an AI system
+2. **AI-generated content labeling** — identify AI-generated content as such (e.g., clear labeling in the UI)
+
+Dify's "citation" feature also supports end-user transparency by showing users which knowledge base documents informed the answer.
+
+> **Note:** Article 50 applies to chatbots and systems interacting directly with natural persons. It has a separate scope from the high-risk designation under Annex III — it applies even to limited-risk systems.
+
+## Article 14: Human oversight
+
+Article 14 requires that high-risk AI systems be designed so that natural persons can effectively oversee them. Dify provides **automated technical safeguards** that support human oversight, but they are not a substitute for it:
+
+| Dify Feature | What It Does | Oversight Role |
+|-------------|-------------|----------------|
+| Annotation/feedback system | Human review of AI outputs | **Direct oversight** — humans evaluate and correct AI responses |
+| Content moderation | Built-in filtering before responses reach users | **Automated safeguard** — reduces harmful outputs but does not replace human judgment on edge cases |
+| Rate limiting | Controls on API usage | **Automated safeguard** — bounds system behavior, supports overseer's ability to maintain control |
+| Workflow control | Insert human review steps between AI generation and output | **Oversight enabler** — allows building approval gates into the pipeline |
+
+These automated controls are necessary building blocks, but Article 14 compliance requires **human oversight procedures** on top of them:
+- **Escalation procedures** — define what happens when moderation triggers or edge cases arise (who is notified, what action is taken)
+- **Human review pipeline** — for high-stakes decisions, route AI outputs to a qualified person before they take effect
+- **Override mechanism** — a human must be able to halt AI responses or override the system's output
+- **Competence requirements** — the human overseer must understand the system's capabilities, limitations, and the context of its outputs
+
+### Recommended pattern
+
+For high-risk use cases (HR, legal, medical), configure your Dify workflow to require human approval before the AI response is delivered to the end user or acted upon.
+
+## Knowledge base compliance
+
+Dify's knowledge base feature has specific compliance implications:
+
+1. **Data provenance:** Document where your knowledge base documents come from. Article 10 requires data governance for training data; knowledge bases are analogous.
+2. **Update tracking:** When you add, remove, or update documents in the knowledge base, log the change. The AI system's behavior changes with its knowledge base.
+3. **PII in documents:** If knowledge base documents contain personal data, GDPR applies to the entire RAG pipeline. Implement access controls and consider PII redaction before indexing.
+4. **Copyright:** Ensure you have the right to use the documents in your knowledge base for AI-assisted generation.
+
+## GDPR considerations
+
+1. **Legal basis** (Article 6): Document why AI processing of user queries is necessary
+2. **Data Processing Agreements** (Article 28): Required for each cloud LLM and embedding provider
+3. **Data minimization:** Only include necessary context in prompts; avoid sending entire documents when a relevant excerpt suffices
+4. **Right to erasure:** If a user requests deletion, ensure their conversations are removed from Dify's logs AND any vector store entries derived from their data
+5. **Cross-border transfers:** Providers based outside the EEA — including US-based providers (OpenAI, Anthropic), and any other non-EEA providers you route to — require Standard Contractual Clauses (SCCs) or equivalent safeguards under Chapter V of the GDPR. Review each provider's transfer mechanism individually.
+
+## Resources
+
+- [EU AI Act full text](https://artificialintelligenceact.eu/)
+- [Dify documentation](https://docs.dify.ai/)
+- [Dify SOC 2 compliance](https://dify.ai/trust)
+
+---
+
+*This is not legal advice. Consult a qualified professional for compliance decisions.*
diff --git a/docs/fr-FR/README.md b/docs/fr-FR/README.md
index 291c8dab40c..db8730b36bd 100644
--- a/docs/fr-FR/README.md
+++ b/docs/fr-FR/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/hi-IN/README.md b/docs/hi-IN/README.md
index bedeaa6246d..ad712046b54 100644
--- a/docs/hi-IN/README.md
+++ b/docs/hi-IN/README.md
@@ -58,6 +58,8 @@
+
+
diff --git a/docs/it-IT/README.md b/docs/it-IT/README.md
index 2e96335d3e0..bca560b574c 100644
--- a/docs/it-IT/README.md
+++ b/docs/it-IT/README.md
@@ -58,7 +58,10 @@
+
+
+
Dify è una piattaforma open-source per lo sviluppo di applicazioni LLM. La sua interfaccia intuitiva combina flussi di lavoro AI basati su agenti, pipeline RAG, funzionalità di agenti, gestione dei modelli, funzionalità di monitoraggio e altro ancora, permettendovi di passare rapidamente da un prototipo alla produzione.
diff --git a/docs/ja-JP/README.md b/docs/ja-JP/README.md
index 659ffbda515..298dcb95aa6 100644
--- a/docs/ja-JP/README.md
+++ b/docs/ja-JP/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/ko-KR/README.md b/docs/ko-KR/README.md
index 2f6c526ef27..2dcacaae8b5 100644
--- a/docs/ko-KR/README.md
+++ b/docs/ko-KR/README.md
@@ -53,7 +53,11 @@
-
+
+
+
+
+
Dify는 오픈 소스 LLM 앱 개발 플랫폼입니다. 직관적인 인터페이스를 통해 AI 워크플로우, RAG 파이프라인, 에이전트 기능, 모델 관리, 관찰 기능 등을 결합하여 프로토타입에서 프로덕션까지 빠르게 전환할 수 있습니다. 주요 기능 목록은 다음과 같습니다:
diff --git a/docs/pt-BR/README.md b/docs/pt-BR/README.md
index ed29ec02945..f7cc37a20f4 100644
--- a/docs/pt-BR/README.md
+++ b/docs/pt-BR/README.md
@@ -58,7 +58,10 @@
+
+
+
Dify é uma plataforma de desenvolvimento de aplicativos LLM de código aberto. Sua interface intuitiva combina workflow de IA, pipeline RAG, capacidades de agente, gerenciamento de modelos, recursos de observabilidade e muito mais, permitindo que você vá rapidamente do protótipo à produção. Aqui está uma lista das principais funcionalidades:
diff --git a/docs/sl-SI/README.md b/docs/sl-SI/README.md
index caef2c303c1..7b3fe76b5d8 100644
--- a/docs/sl-SI/README.md
+++ b/docs/sl-SI/README.md
@@ -53,9 +53,12 @@
-
+
+
+
+
Dify je odprtokodna platforma za razvoj aplikacij LLM. Njegov intuitivni vmesnik združuje agentski potek dela z umetno inteligenco, cevovod RAG, zmogljivosti agentov, upravljanje modelov, funkcije opazovanja in več, kar vam omogoča hiter prehod od prototipa do proizvodnje.
diff --git a/docs/tlh/README.md b/docs/tlh/README.md
index e2acd7734cb..a8e63026c80 100644
--- a/docs/tlh/README.md
+++ b/docs/tlh/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/tr-TR/README.md b/docs/tr-TR/README.md
index 6361ca5dd93..cecc1b189c3 100644
--- a/docs/tr-TR/README.md
+++ b/docs/tr-TR/README.md
@@ -53,7 +53,11 @@
+
+
+
+
Dify, açık kaynaklı bir LLM uygulama geliştirme platformudur. Sezgisel arayüzü, AI iş akışı, RAG pipeline'ı, ajan yetenekleri, model yönetimi, gözlemlenebilirlik özellikleri ve daha fazlasını birleştirerek, prototipten üretime hızlıca geçmenizi sağlar. İşte temel özelliklerin bir listesi:
diff --git a/docs/vi-VN/README.md b/docs/vi-VN/README.md
index 3042a98d95a..5230d531101 100644
--- a/docs/vi-VN/README.md
+++ b/docs/vi-VN/README.md
@@ -53,7 +53,11 @@
+
+
+
+
Dify là một nền tảng phát triển ứng dụng LLM mã nguồn mở. Giao diện trực quan kết hợp quy trình làm việc AI, mô hình RAG, khả năng tác nhân, quản lý mô hình, tính năng quan sát và hơn thế nữa, cho phép bạn nhanh chóng chuyển từ nguyên mẫu sang sản phẩm. Đây là danh sách các tính năng cốt lõi:
diff --git a/docs/zh-CN/README.md b/docs/zh-CN/README.md
index 15bb447ad8a..8ba8009959e 100644
--- a/docs/zh-CN/README.md
+++ b/docs/zh-CN/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/zh-TW/README.md b/docs/zh-TW/README.md
index 14b343ba29d..de5bab8679c 100644
--- a/docs/zh-TW/README.md
+++ b/docs/zh-TW/README.md
@@ -57,6 +57,11 @@
+
+
+
+
ডিফাই একটি ওপেন-সোর্স LLM অ্যাপ ডেভেলপমেন্ট প্ল্যাটফর্ম। এটি ইন্টুইটিভ ইন্টারফেস, এজেন্টিক AI ওয়ার্কফ্লো, RAG পাইপলাইন, এজেন্ট ক্যাপাবিলিটি, মডেল ম্যানেজমেন্ট, মনিটরিং সুবিধা এবং আরও অনেক কিছু একত্রিত করে, যা দ্রুত প্রোটোটাইপ থেকে প্রোডাকশন পর্যন্ত নিয়ে যেতে সহায়তা করে।
diff --git a/docs/de-DE/README.md b/docs/de-DE/README.md
index c71a0bfccfa..1eab517a6d9 100644
--- a/docs/de-DE/README.md
+++ b/docs/de-DE/README.md
@@ -57,7 +57,11 @@
+
+
+
+
Dify ist eine Open-Source-Plattform zur Entwicklung von LLM-Anwendungen. Ihre intuitive Benutzeroberfläche vereint agentenbasierte KI-Workflows, RAG-Pipelines, Agentenfunktionen, Modellverwaltung, Überwachungsfunktionen und mehr, sodass Sie schnell von einem Prototyp in die Produktion übergehen können.
diff --git a/docs/es-ES/README.md b/docs/es-ES/README.md
index da81b51d6a4..f4c60e3d8f9 100644
--- a/docs/es-ES/README.md
+++ b/docs/es-ES/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/eu-ai-act-compliance.md b/docs/eu-ai-act-compliance.md
new file mode 100644
index 00000000000..5fa29eed3f3
--- /dev/null
+++ b/docs/eu-ai-act-compliance.md
@@ -0,0 +1,186 @@
+# EU AI Act Compliance Guide for Dify Deployers
+
+Dify is an LLMOps platform for building RAG pipelines, agents, and AI workflows. If you deploy Dify in the EU — whether self-hosted or using a cloud provider — the EU AI Act applies to your deployment. This guide covers what the regulation requires and how Dify's architecture maps to those requirements.
+
+## Is your system in scope?
+
+The detailed obligations in Articles 12, 13, and 14 only apply to **high-risk AI systems** as defined in Annex III of the EU AI Act. A Dify application is high-risk if it is used for:
+
+- **Recruitment and HR** — screening candidates, evaluating employee performance, allocating tasks
+- **Credit scoring and insurance** — assessing creditworthiness or setting premiums
+- **Law enforcement** — profiling, criminal risk assessment, border control
+- **Critical infrastructure** — managing energy, water, transport, or telecommunications systems
+- **Education assessment** — grading students, determining admissions
+- **Essential public services** — evaluating eligibility for benefits, housing, or emergency services
+
+Most Dify deployments (customer-facing chatbots, internal knowledge bases, content generation workflows) are **not** high-risk. If your Dify application does not fall into one of the categories above:
+
+- **Article 50** (end-user transparency) still applies if users interact with your application directly. See the [Article 50 section](#article-50-end-user-transparency) below.
+- **GDPR** still applies if you process personal data. See the [GDPR section](#gdpr-considerations) below.
+- The high-risk obligations (Articles 9-15) are less likely to apply, but risk classification is context-dependent. **Do not self-classify without legal review.** Focus on Article 50 (transparency) and GDPR (data protection) as your baseline obligations.
+
+If you are unsure whether your use case qualifies as high-risk, consult a qualified legal professional before proceeding.
+
+## Self-hosted vs cloud: different compliance profiles
+
+| Deployment | Your role | Dify's role | Who handles compliance? |
+|-----------|----------|-------------|------------------------|
+| **Self-hosted** | Provider and deployer | Framework provider — obligations under Article 25 apply only if Dify is placed on the market or put into service as part of a complete AI system bearing its name or trademark | You |
+| **Dify Cloud** | Deployer | Provider and processor | Shared — Dify handles SOC 2 and GDPR for the platform; you handle AI Act obligations for your specific use case |
+
+Dify Cloud already has SOC 2 Type II and GDPR compliance for the platform itself. But the EU AI Act adds obligations specific to AI systems that SOC 2 does not cover: risk classification, technical documentation, transparency, and human oversight.
+
+## Supported providers and services
+
+Dify integrates with a broad range of AI providers and data stores. The following are the key ones relevant to compliance:
+
+- **AI providers:** HuggingFace (core), plus integrations with OpenAI, Anthropic, Google, and 100+ models via provider plugins
+- **Model identifiers include:** gpt-4o, gpt-3.5-turbo, claude-3-opus, gemini-2.5-flash, whisper-1, and others
+- **Vector database connections:** Extensive RAG infrastructure supporting numerous vector stores
+
+Dify's plugin architecture means actual provider usage depends on your configuration. Document which providers and models are active in your deployment.
+
+## Data flow diagram
+
+A typical Dify RAG deployment:
+
+```mermaid
+graph LR
+ USER((User)) -->|query| DIFY[Dify Platform]
+ DIFY -->|prompts| LLM([LLM Provider])
+ LLM -->|responses| DIFY
+ DIFY -->|documents| EMBED([Embedding Model])
+ EMBED -->|vectors| DIFY
+ DIFY -->|store/retrieve| VS[(Vector Store)]
+ DIFY -->|knowledge| KB[(Knowledge Base)]
+ DIFY -->|response| USER
+
+ classDef processor fill:#60a5fa,stroke:#1e40af,color:#000
+ classDef controller fill:#4ade80,stroke:#166534,color:#000
+ classDef app fill:#a78bfa,stroke:#5b21b6,color:#000
+ classDef user fill:#f472b6,stroke:#be185d,color:#000
+
+ class USER user
+ class DIFY app
+ class LLM processor
+ class EMBED processor
+ class VS controller
+ class KB controller
+```
+
+**GDPR roles** (providers are typically processors for customer-submitted data, but the exact role depends on each provider's terms of service and processing purpose; deployers should review each provider's DPA):
+- **Cloud LLM providers (OpenAI, Anthropic, Google)** typically act as processors — requires DPA.
+- **Cloud embedding services** typically act as processors — requires DPA.
+- **Self-hosted vector stores (Weaviate, Qdrant, pgvector):** Your organization remains the controller — no third-party transfer.
+- **Cloud vector stores (Pinecone, Zilliz Cloud)** typically act as processors — requires DPA.
+- **Knowledge base documents:** Your organization is the controller — stored in your infrastructure.
+
+## Article 11: Technical documentation
+
+High-risk systems need Annex IV documentation. For Dify deployments, key sections include:
+
+| Section | What Dify provides | What you must document |
+|---------|-------------------|----------------------|
+| General description | Platform capabilities, supported models | Your specific use case, intended users, deployment context |
+| Development process | Dify's architecture, plugin system | Your RAG pipeline design, prompt engineering, knowledge base curation |
+| Monitoring | Dify's built-in logging and analytics | Your monitoring plan, alert thresholds, incident response |
+| Performance metrics | Dify's evaluation features | Your accuracy benchmarks, quality thresholds, bias testing |
+| Risk management | — | Risk assessment for your specific use case |
+
+Some sections can be derived from Dify's architecture and your deployment configuration, as shown in the table above. The remaining sections require your input.
+
+## Article 12: Record-keeping
+
+Dify's built-in logging covers several Article 12 requirements:
+
+| Requirement | Dify Feature | Status |
+|------------|-------------|--------|
+| Conversation logs | Full conversation history with timestamps | **Covered** |
+| Model tracking | Model name recorded per interaction | **Covered** |
+| Token usage | Token counts per message | **Covered** |
+| Cost tracking | Cost per conversation (if provider reports it) | **Partial** |
+| Document retrieval | RAG source documents logged | **Covered** |
+| User identification | User session tracking | **Covered** |
+| Error logging | Failed generation logs | **Covered** |
+| Data retention | Configurable | **Your responsibility** |
+
+**Retention periods:** The required retention period depends on your role under the Act. Article 18 requires **providers** of high-risk systems to retain logs and technical documentation for **10 years** after market placement. Article 26(6) requires **deployers** to retain logs for at least **6 months**. If you self-host Dify and have substantially modified the system, you may be classified as a provider rather than a deployer. Confirm the applicable retention period with legal counsel.
+
+## Article 13: Transparency to deployers
+
+Article 13 requires providers of high-risk AI systems to supply deployers with the information needed to understand and operate the system correctly. This is a **documentation obligation**, not a logging obligation. For Dify deployments, this means the upstream LLM and embedding providers must give you:
+
+- Instructions for use, including intended purpose and known limitations
+- Accuracy metrics and performance benchmarks
+- Known or foreseeable risks and residual risks after mitigation
+- Technical specifications: input/output formats, training data characteristics, model architecture details
+
+As a deployer, collect model cards, system documentation, and accuracy reports from each AI provider your Dify application uses. Maintain these as part of your Annex IV technical documentation.
+
+Dify's platform features provide **supporting evidence** that can inform Article 13 documentation, but they do not satisfy Article 13 on their own:
+- **Source attribution** — Dify's RAG citation feature shows which documents informed the response, supporting deployer-side auditing
+- **Model identification** — Dify logs which LLM model generates responses, providing evidence for system documentation
+- **Conversation logs** — execution history helps compile performance and behavior evidence
+
+You must independently produce system documentation covering how your specific Dify deployment uses AI, its intended purpose, performance characteristics, and residual risks.
+
+## Article 50: End-user transparency
+
+Article 50 requires deployers to inform end users that they are interacting with an AI system. This is a separate obligation from Article 13 and applies even to limited-risk systems.
+
+For Dify applications serving end users:
+
+1. **Disclose AI involvement** — tell users they are interacting with an AI system
+2. **AI-generated content labeling** — identify AI-generated content as such (e.g., clear labeling in the UI)
+
+Dify's "citation" feature also supports end-user transparency by showing users which knowledge base documents informed the answer.
+
+> **Note:** Article 50 applies to chatbots and systems interacting directly with natural persons. It has a separate scope from the high-risk designation under Annex III — it applies even to limited-risk systems.
+
+## Article 14: Human oversight
+
+Article 14 requires that high-risk AI systems be designed so that natural persons can effectively oversee them. Dify provides **automated technical safeguards** that support human oversight, but they are not a substitute for it:
+
+| Dify Feature | What It Does | Oversight Role |
+|-------------|-------------|----------------|
+| Annotation/feedback system | Human review of AI outputs | **Direct oversight** — humans evaluate and correct AI responses |
+| Content moderation | Built-in filtering before responses reach users | **Automated safeguard** — reduces harmful outputs but does not replace human judgment on edge cases |
+| Rate limiting | Controls on API usage | **Automated safeguard** — bounds system behavior, supports overseer's ability to maintain control |
+| Workflow control | Insert human review steps between AI generation and output | **Oversight enabler** — allows building approval gates into the pipeline |
+
+These automated controls are necessary building blocks, but Article 14 compliance requires **human oversight procedures** on top of them:
+- **Escalation procedures** — define what happens when moderation triggers or edge cases arise (who is notified, what action is taken)
+- **Human review pipeline** — for high-stakes decisions, route AI outputs to a qualified person before they take effect
+- **Override mechanism** — a human must be able to halt AI responses or override the system's output
+- **Competence requirements** — the human overseer must understand the system's capabilities, limitations, and the context of its outputs
+
+### Recommended pattern
+
+For high-risk use cases (HR, legal, medical), configure your Dify workflow to require human approval before the AI response is delivered to the end user or acted upon.
+
+## Knowledge base compliance
+
+Dify's knowledge base feature has specific compliance implications:
+
+1. **Data provenance:** Document where your knowledge base documents come from. Article 10 requires data governance for training data; knowledge bases are analogous.
+2. **Update tracking:** When you add, remove, or update documents in the knowledge base, log the change. The AI system's behavior changes with its knowledge base.
+3. **PII in documents:** If knowledge base documents contain personal data, GDPR applies to the entire RAG pipeline. Implement access controls and consider PII redaction before indexing.
+4. **Copyright:** Ensure you have the right to use the documents in your knowledge base for AI-assisted generation.
+
+## GDPR considerations
+
+1. **Legal basis** (Article 6): Document why AI processing of user queries is necessary
+2. **Data Processing Agreements** (Article 28): Required for each cloud LLM and embedding provider
+3. **Data minimization:** Only include necessary context in prompts; avoid sending entire documents when a relevant excerpt suffices
+4. **Right to erasure:** If a user requests deletion, ensure their conversations are removed from Dify's logs AND any vector store entries derived from their data
+5. **Cross-border transfers:** Providers based outside the EEA — including US-based providers (OpenAI, Anthropic), and any other non-EEA providers you route to — require Standard Contractual Clauses (SCCs) or equivalent safeguards under Chapter V of the GDPR. Review each provider's transfer mechanism individually.
+
+## Resources
+
+- [EU AI Act full text](https://artificialintelligenceact.eu/)
+- [Dify documentation](https://docs.dify.ai/)
+- [Dify SOC 2 compliance](https://dify.ai/trust)
+
+---
+
+*This is not legal advice. Consult a qualified professional for compliance decisions.*
diff --git a/docs/fr-FR/README.md b/docs/fr-FR/README.md
index 291c8dab40c..db8730b36bd 100644
--- a/docs/fr-FR/README.md
+++ b/docs/fr-FR/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/hi-IN/README.md b/docs/hi-IN/README.md
index bedeaa6246d..ad712046b54 100644
--- a/docs/hi-IN/README.md
+++ b/docs/hi-IN/README.md
@@ -58,6 +58,8 @@
+
+
diff --git a/docs/it-IT/README.md b/docs/it-IT/README.md
index 2e96335d3e0..bca560b574c 100644
--- a/docs/it-IT/README.md
+++ b/docs/it-IT/README.md
@@ -58,7 +58,10 @@
+
+
+
Dify è una piattaforma open-source per lo sviluppo di applicazioni LLM. La sua interfaccia intuitiva combina flussi di lavoro AI basati su agenti, pipeline RAG, funzionalità di agenti, gestione dei modelli, funzionalità di monitoraggio e altro ancora, permettendovi di passare rapidamente da un prototipo alla produzione.
diff --git a/docs/ja-JP/README.md b/docs/ja-JP/README.md
index 659ffbda515..298dcb95aa6 100644
--- a/docs/ja-JP/README.md
+++ b/docs/ja-JP/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/ko-KR/README.md b/docs/ko-KR/README.md
index 2f6c526ef27..2dcacaae8b5 100644
--- a/docs/ko-KR/README.md
+++ b/docs/ko-KR/README.md
@@ -53,7 +53,11 @@
-
+
+
+
+
+
Dify는 오픈 소스 LLM 앱 개발 플랫폼입니다. 직관적인 인터페이스를 통해 AI 워크플로우, RAG 파이프라인, 에이전트 기능, 모델 관리, 관찰 기능 등을 결합하여 프로토타입에서 프로덕션까지 빠르게 전환할 수 있습니다. 주요 기능 목록은 다음과 같습니다:
diff --git a/docs/pt-BR/README.md b/docs/pt-BR/README.md
index ed29ec02945..f7cc37a20f4 100644
--- a/docs/pt-BR/README.md
+++ b/docs/pt-BR/README.md
@@ -58,7 +58,10 @@
+
+
+
Dify é uma plataforma de desenvolvimento de aplicativos LLM de código aberto. Sua interface intuitiva combina workflow de IA, pipeline RAG, capacidades de agente, gerenciamento de modelos, recursos de observabilidade e muito mais, permitindo que você vá rapidamente do protótipo à produção. Aqui está uma lista das principais funcionalidades:
diff --git a/docs/sl-SI/README.md b/docs/sl-SI/README.md
index caef2c303c1..7b3fe76b5d8 100644
--- a/docs/sl-SI/README.md
+++ b/docs/sl-SI/README.md
@@ -53,9 +53,12 @@
-
+
+
+
+
Dify je odprtokodna platforma za razvoj aplikacij LLM. Njegov intuitivni vmesnik združuje agentski potek dela z umetno inteligenco, cevovod RAG, zmogljivosti agentov, upravljanje modelov, funkcije opazovanja in več, kar vam omogoča hiter prehod od prototipa do proizvodnje.
diff --git a/docs/tlh/README.md b/docs/tlh/README.md
index e2acd7734cb..a8e63026c80 100644
--- a/docs/tlh/README.md
+++ b/docs/tlh/README.md
@@ -53,7 +53,11 @@
+
+
+
+
#
diff --git a/docs/tr-TR/README.md b/docs/tr-TR/README.md
index 6361ca5dd93..cecc1b189c3 100644
--- a/docs/tr-TR/README.md
+++ b/docs/tr-TR/README.md
@@ -53,7 +53,11 @@
+
+
+
+
Dify, açık kaynaklı bir LLM uygulama geliştirme platformudur. Sezgisel arayüzü, AI iş akışı, RAG pipeline'ı, ajan yetenekleri, model yönetimi, gözlemlenebilirlik özellikleri ve daha fazlasını birleştirerek, prototipten üretime hızlıca geçmenizi sağlar. İşte temel özelliklerin bir listesi:
diff --git a/docs/vi-VN/README.md b/docs/vi-VN/README.md
index 3042a98d95a..5230d531101 100644
--- a/docs/vi-VN/README.md
+++ b/docs/vi-VN/README.md
@@ -53,7 +53,11 @@
+
+
+
+
Dify là một nền tảng phát triển ứng dụng LLM mã nguồn mở. Giao diện trực quan kết hợp quy trình làm việc AI, mô hình RAG, khả năng tác nhân, quản lý mô hình, tính năng quan sát và hơn thế nữa, cho phép bạn nhanh chóng chuyển từ nguyên mẫu sang sản phẩm. Đây là danh sách các tính năng cốt lõi:
diff --git a/docs/zh-CN/README.md b/docs/zh-CN/README.md
index 15bb447ad8a..8ba8009959e 100644
--- a/docs/zh-CN/README.md
+++ b/docs/zh-CN/README.md
@@ -53,7 +53,11 @@
+
+
+
+
+
+
+
+
+
Dify 是一個開源的 LLM 應用程式開發平台。其直觀的界面結合了智能代理工作流程、RAG 管道、代理功能、模型管理、可觀察性功能等，讓您能夠快速從原型進展到生產環境。
diff --git a/e2e/.gitignore b/e2e/.gitignore
new file mode 100644
index 00000000000..96c1e0f3a18
--- /dev/null
+++ b/e2e/.gitignore
@@ -0,0 +1,6 @@
+node_modules/
+.auth/
+playwright-report/
+test-results/
+cucumber-report/
+.logs/
diff --git a/e2e/AGENTS.md b/e2e/AGENTS.md
new file mode 100644
index 00000000000..ae642768f5f
--- /dev/null
+++ b/e2e/AGENTS.md
@@ -0,0 +1,167 @@
+# E2E
+
+This package contains the repository-level end-to-end tests for Dify.
+
+This file is the canonical package guide for `e2e/`. Keep detailed workflow, architecture, debugging, and reporting documentation here. Keep `README.md` as a minimal pointer to this file so the two documents do not drift.
+
+The suite uses Cucumber for scenario definitions and Playwright as the browser execution layer.
+
+It tests:
+
+- backend API started from source
+- frontend served from the production artifact
+- middleware services started from Docker
+
+## Prerequisites
+
+- Node.js `^22.22.1`
+- `pnpm`
+- `uv`
+- Docker
+
+Run the following commands from the repository root.
+
+Install Playwright browsers once:
+
+```bash
+pnpm install
+pnpm -C e2e e2e:install
+pnpm -C e2e check
+```
+
+`pnpm install` is resolved through the repository workspace and uses the shared root lockfile plus `pnpm-workspace.yaml`.
+
+Use `pnpm check` as the default local verification step after editing E2E TypeScript, Cucumber support code, or feature glue. It runs formatting, linting, and type checks for this package.
+
+Common commands:
+
+```bash
+# authenticated-only regression (default excludes @fresh)
+# expects backend API, frontend artifact, and middleware stack to already be running
+pnpm -C e2e e2e
+
+# full reset + fresh install + authenticated scenarios
+# starts required middleware/dependencies for you
+pnpm -C e2e e2e:full
+
+# run a tagged subset
+pnpm -C e2e e2e -- --tags @smoke
+
+# headed browser
+pnpm -C e2e e2e:headed -- --tags @smoke
+
+# slow down browser actions for local debugging
+E2E_SLOW_MO=500 pnpm -C e2e e2e:headed -- --tags @smoke
+```
+
+Frontend artifact behavior:
+
+- if `web/.next/BUILD_ID` exists, E2E reuses the existing build by default
+- if you set `E2E_FORCE_WEB_BUILD=1`, E2E rebuilds the frontend before starting it
+
+## Lifecycle
+
+```mermaid
+flowchart TD
+ A["Start E2E run"] --> B["run-cucumber.ts orchestrates setup/API/frontend"]
+ B --> C["support/web-server.ts starts or reuses frontend directly"]
+ C --> D["Cucumber loads config, steps, and support modules"]
+ D --> E["BeforeAll bootstraps shared auth state via /install"]
+ E --> F{"Which command is running?"}
+ F -->|`pnpm e2e`| G["Run config default tags: not @fresh and not @skip"]
+ F -->|`pnpm e2e:full*`| H["Override tags to not @skip"]
+ G --> I["Per-scenario BrowserContext from shared browser"]
+ H --> I
+ I --> J["Failure artifacts written to cucumber-report/artifacts"]
+```
+
+Ownership is split like this:
+
+- `scripts/setup.ts` is the single environment entrypoint for reset, middleware, backend, and frontend startup
+- `run-cucumber.ts` orchestrates the E2E run and Cucumber invocation
+- `support/web-server.ts` manages frontend reuse, startup, readiness, and shutdown
+- `features/support/hooks.ts` manages auth bootstrap, scenario lifecycle, and diagnostics
+- `features/support/world.ts` owns per-scenario typed context
+- `features/step-definitions/` holds domain-oriented glue so the official VS Code Cucumber plugin works with default conventions when `e2e/` is opened as the workspace root
+
+Package layout:
+
+- `features/`: Gherkin scenarios grouped by capability
+- `features/step-definitions/`: domain-oriented step definitions
+- `features/support/hooks.ts`: suite lifecycle, auth-state bootstrap, diagnostics
+- `features/support/world.ts`: shared scenario context
+- `support/web-server.ts`: typed frontend startup/reuse logic
+- `scripts/setup.ts`: reset and service lifecycle commands
+- `scripts/run-cucumber.ts`: Cucumber orchestration entrypoint
+
+Behavior depends on instance state:
+
+- uninitialized instance: completes install and stores authenticated state
+- initialized instance: signs in and reuses authenticated state
+
+Because of that, the `@fresh` install scenario only runs in the `pnpm e2e:full*` flows. The default `pnpm e2e*` flows exclude `@fresh` via Cucumber config tags so they can be re-run against an already initialized instance.
+
+Reset all persisted E2E state:
+
+```bash
+pnpm -C e2e e2e:reset
+```
+
+This removes:
+
+- `docker/volumes/db/data`
+- `docker/volumes/redis/data`
+- `docker/volumes/weaviate`
+- `docker/volumes/plugin_daemon`
+- `e2e/.auth`
+- `e2e/.logs`
+- `e2e/cucumber-report`
+
+Start the full middleware stack:
+
+```bash
+pnpm -C e2e e2e:middleware:up
+```
+
+Stop the full middleware stack:
+
+```bash
+pnpm e2e:middleware:down
+```
+
+The middleware stack includes:
+
+- PostgreSQL
+- Redis
+- Weaviate
+- Sandbox
+- SSRF proxy
+- Plugin daemon
+
+Fresh install verification:
+
+```bash
+pnpm e2e:full
+```
+
+Run the Cucumber suite against an already running middleware stack:
+
+```bash
+pnpm e2e:middleware:up
+pnpm e2e
+pnpm e2e:middleware:down
+```
+
+Artifacts and diagnostics:
+
+- `cucumber-report/report.html`: HTML report
+- `cucumber-report/report.json`: JSON report
+- `cucumber-report/artifacts/`: failure screenshots and HTML captures
+- `.logs/cucumber-api.log`: backend startup log
+- `.logs/cucumber-web.log`: frontend startup log
+
+Open the HTML report locally with:
+
+```bash
+open cucumber-report/report.html
+```
diff --git a/e2e/README.md b/e2e/README.md
new file mode 100644
index 00000000000..9b4046eaff7
--- /dev/null
+++ b/e2e/README.md
@@ -0,0 +1,3 @@
+# E2E
+
+Canonical documentation for this package lives in [AGENTS.md](./AGENTS.md).
diff --git a/e2e/cucumber.config.ts b/e2e/cucumber.config.ts
new file mode 100644
index 00000000000..c162a6562e9
--- /dev/null
+++ b/e2e/cucumber.config.ts
@@ -0,0 +1,19 @@
+import type { IConfiguration } from '@cucumber/cucumber'
+
+const config = {
+ format: [
+ 'progress-bar',
+ 'summary',
+ 'html:./cucumber-report/report.html',
+ 'json:./cucumber-report/report.json',
+ ],
+ import: ['features/**/*.ts'],
+ parallel: 1,
+ paths: ['features/**/*.feature'],
+ tags: process.env.E2E_CUCUMBER_TAGS || 'not @fresh and not @skip',
+ timeout: 60_000,
+} satisfies Partial
- !readonly && onChange({ value: [v, (10 - v * 10) / 10] })}
- trackClassName="weightedScoreSliderTrack"
- disabled={readonly}
- />
+
+ !readonly && onChange({ value: [v, (10 - v * 10) / 10] })}
+ disabled={readonly}
+ aria-label={t('weightedScore.semantic', { ns: 'dataset' })}
+ />
+
-
+
-
{t('weightedScore.semantic', { ns: 'dataset' })}
{formatNumber(value.value[0])}
+
{formatNumber(value.value[1])}
{t('weightedScore.keyword', { ns: 'dataset' })}
diff --git a/web/app/components/app/configuration/debug/debug-with-multiple-model/index.spec.tsx b/web/app/components/app/configuration/debug/debug-with-multiple-model/index.spec.tsx
index 188086246a5..389ab189e9f 100644
--- a/web/app/components/app/configuration/debug/debug-with-multiple-model/index.spec.tsx
+++ b/web/app/components/app/configuration/debug/debug-with-multiple-model/index.spec.tsx
@@ -556,8 +556,8 @@ describe('DebugWithMultipleModel', () => {
)
const twoItems = screen.getAllByTestId('debug-item')
- expect(twoItems[0].style.width).toBe('calc(50% - 28px)')
- expect(twoItems[1].style.width).toBe('calc(50% - 28px)')
+ expect(twoItems[0].style.width).toBe('calc(50% - 4px - 24px)')
+ expect(twoItems[1].style.width).toBe('calc(50% - 4px - 24px)')
})
})
@@ -596,13 +596,13 @@ describe('DebugWithMultipleModel', () => {
// Assert
expect(items).toHaveLength(2)
expectItemLayout(items[0], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: '100%',
transform: 'translateX(0) translateY(0)',
classes: ['mr-2'],
})
expectItemLayout(items[1], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: '100%',
transform: 'translateX(calc(100% + 8px)) translateY(0)',
classes: [],
@@ -620,19 +620,19 @@ describe('DebugWithMultipleModel', () => {
// Assert
expect(items).toHaveLength(3)
expectItemLayout(items[0], {
- width: 'calc(33.3% - 21.33px)',
+ width: 'calc(33.3% - 5.33px - 16px)',
height: '100%',
transform: 'translateX(0) translateY(0)',
classes: ['mr-2'],
})
expectItemLayout(items[1], {
- width: 'calc(33.3% - 21.33px)',
+ width: 'calc(33.3% - 5.33px - 16px)',
height: '100%',
transform: 'translateX(calc(100% + 8px)) translateY(0)',
classes: ['mr-2'],
})
expectItemLayout(items[2], {
- width: 'calc(33.3% - 21.33px)',
+ width: 'calc(33.3% - 5.33px - 16px)',
height: '100%',
transform: 'translateX(calc(200% + 16px)) translateY(0)',
classes: [],
@@ -655,25 +655,25 @@ describe('DebugWithMultipleModel', () => {
// Assert
expect(items).toHaveLength(4)
expectItemLayout(items[0], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: 'calc(50% - 4px)',
transform: 'translateX(0) translateY(0)',
classes: ['mr-2', 'mb-2'],
})
expectItemLayout(items[1], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: 'calc(50% - 4px)',
transform: 'translateX(calc(100% + 8px)) translateY(0)',
classes: ['mb-2'],
})
expectItemLayout(items[2], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: 'calc(50% - 4px)',
transform: 'translateX(0) translateY(calc(100% + 8px))',
classes: ['mr-2'],
})
expectItemLayout(items[3], {
- width: 'calc(50% - 28px)',
+ width: 'calc(50% - 4px - 24px)',
height: 'calc(50% - 4px)',
transform: 'translateX(calc(100% + 8px)) translateY(calc(100% + 8px))',
classes: [],
diff --git a/web/app/components/app/create-app-dialog/app-list/index.tsx b/web/app/components/app/create-app-dialog/app-list/index.tsx
index 8b1876be043..1aa40d2014e 100644
--- a/web/app/components/app/create-app-dialog/app-list/index.tsx
+++ b/web/app/components/app/create-app-dialog/app-list/index.tsx
@@ -137,10 +137,7 @@ const Apps = ({
})
setIsShowCreateModal(false)
- toast.add({
- type: 'success',
- title: t('newApp.appCreated', { ns: 'app' }),
- })
+ toast.success(t('newApp.appCreated', { ns: 'app' }))
if (onSuccess)
onSuccess()
if (app.app_id)
@@ -149,7 +146,7 @@ const Apps = ({
getRedirection(isCurrentWorkspaceEditor, { id: app.app_id!, mode }, push)
}
catch {
- toast.add({ type: 'error', title: t('newApp.appCreateFailed', { ns: 'app' }) })
+ toast.error(t('newApp.appCreateFailed', { ns: 'app' }))
}
}
diff --git a/web/app/components/app/overview/settings/index.spec.tsx b/web/app/components/app/overview/settings/index.spec.tsx
index b849b4f0156..e933855ca8d 100644
--- a/web/app/components/app/overview/settings/index.spec.tsx
+++ b/web/app/components/app/overview/settings/index.spec.tsx
@@ -1,6 +1,3 @@
-/**
- * @vitest-environment jsdom
- */
import type { ReactNode } from 'react'
import type { ModalContextState } from '@/context/modal-context'
import type { ProviderContextState } from '@/context/provider-context'
diff --git a/web/app/components/app/type-selector/index.spec.tsx b/web/app/components/app/type-selector/index.spec.tsx
index e24d9633054..711678f0a8c 100644
--- a/web/app/components/app/type-selector/index.spec.tsx
+++ b/web/app/components/app/type-selector/index.spec.tsx
@@ -1,4 +1,4 @@
-import { fireEvent, render, screen, within } from '@testing-library/react'
+import { fireEvent, render, screen, waitFor, within } from '@testing-library/react'
import * as React from 'react'
import { AppModeEnum } from '@/types/app'
import AppTypeSelector, { AppTypeIcon, AppTypeLabel } from './index'
@@ -14,7 +14,7 @@ describe('AppTypeSelector', () => {
render(
@@ -22,43 +21,43 @@ const allTypes: AppModeEnum[] = [AppModeEnum.WORKFLOW, AppModeEnum.ADVANCED_CHAT
const AppTypeSelector = ({ value, onChange }: AppSelectorProps) => {
const [open, setOpen] = useState(false)
const { t } = useTranslation()
+ const triggerLabel = value.length === 0
+ ? t('typeSelector.all', { ns: 'app' })
+ : value.map(type => getAppTypeLabel(type, t)).join(', ')
return (
-
+
)
}
@@ -173,33 +172,54 @@ type AppTypeSelectorItemProps = {
}
function AppTypeSelectorItem({ checked, type, onClick }: AppTypeSelectorItemProps) {
return (
-
-
+
)
}
+function getAppTypeLabel(type: AppModeEnum, t: ReturnType['t']) {
+ if (type === AppModeEnum.CHAT)
+ return t('typeSelector.chatbot', { ns: 'app' })
+ if (type === AppModeEnum.AGENT_CHAT)
+ return t('typeSelector.agent', { ns: 'app' })
+ if (type === AppModeEnum.COMPLETION)
+ return t('typeSelector.completion', { ns: 'app' })
+ if (type === AppModeEnum.ADVANCED_CHAT)
+ return t('typeSelector.advanced', { ns: 'app' })
+ if (type === AppModeEnum.WORKFLOW)
+ return t('typeSelector.workflow', { ns: 'app' })
+
+ return ''
+}
+
type AppTypeLabelProps = {
type: AppModeEnum
className?: string
}
export function AppTypeLabel({ type, className }: AppTypeLabelProps) {
const { t } = useTranslation()
- let label = ''
- if (type === AppModeEnum.CHAT)
- label = t('typeSelector.chatbot', { ns: 'app' })
- if (type === AppModeEnum.AGENT_CHAT)
- label = t('typeSelector.agent', { ns: 'app' })
- if (type === AppModeEnum.COMPLETION)
- label = t('typeSelector.completion', { ns: 'app' })
- if (type === AppModeEnum.ADVANCED_CHAT)
- label = t('typeSelector.advanced', { ns: 'app' })
- if (type === AppModeEnum.WORKFLOW)
- label = t('typeSelector.workflow', { ns: 'app' })
- return {label}
+ return {getAppTypeLabel(type, t)}
}
diff --git a/web/app/components/apps/hooks/__tests__/use-dsl-drag-drop.spec.ts b/web/app/components/apps/hooks/__tests__/use-dsl-drag-drop.spec.ts
index 58fed4caa8a..00e2d69ab24 100644
--- a/web/app/components/apps/hooks/__tests__/use-dsl-drag-drop.spec.ts
+++ b/web/app/components/apps/hooks/__tests__/use-dsl-drag-drop.spec.ts
@@ -1,16 +1,15 @@
-import type { Mock } from 'vitest'
import { act, renderHook } from '@testing-library/react'
import { useDSLDragDrop } from '../use-dsl-drag-drop'
describe('useDSLDragDrop', () => {
let container: HTMLDivElement
- let mockOnDSLFileDropped: Mock
+ let mockOnDSLFileDropped = vi.fn<(file: File) => void>()
beforeEach(() => {
vi.clearAllMocks()
container = document.createElement('div')
document.body.appendChild(container)
- mockOnDSLFileDropped = vi.fn()
+ mockOnDSLFileDropped = vi.fn<(file: File) => void>()
})
afterEach(() => {
diff --git a/web/app/components/apps/index.tsx b/web/app/components/apps/index.tsx
index dce9de190d2..b6ca60bd7bd 100644
--- a/web/app/components/apps/index.tsx
+++ b/web/app/components/apps/index.tsx
@@ -8,12 +8,14 @@ import AppListContext from '@/context/app-list-context'
import useDocumentTitle from '@/hooks/use-document-title'
import { useImportDSL } from '@/hooks/use-import-dsl'
import { DSLImportMode } from '@/models/app'
+import dynamic from '@/next/dynamic'
import { fetchAppDetail } from '@/service/explore'
-import DSLConfirmModal from '../app/create-from-dsl-modal/dsl-confirm-modal'
-import CreateAppModal from '../explore/create-app-modal'
-import TryApp from '../explore/try-app'
import List from './list'
+const DSLConfirmModal = dynamic(() => import('../app/create-from-dsl-modal/dsl-confirm-modal'), { ssr: false })
+const CreateAppModal = dynamic(() => import('../explore/create-app-modal'), { ssr: false })
+const TryApp = dynamic(() => import('../explore/try-app'), { ssr: false })
+
const Apps = () => {
const { t } = useTranslation()
diff --git a/web/app/components/apps/list.tsx b/web/app/components/apps/list.tsx
index 0d52bd468cf..2ef344f816a 100644
--- a/web/app/components/apps/list.tsx
+++ b/web/app/components/apps/list.tsx
@@ -5,11 +5,11 @@ import { useDebounceFn } from 'ahooks'
import { parseAsStringLiteral, useQueryState } from 'nuqs'
import { useCallback, useEffect, useRef, useState } from 'react'
import { useTranslation } from 'react-i18next'
+import Checkbox from '@/app/components/base/checkbox'
import Input from '@/app/components/base/input'
import TabSliderNew from '@/app/components/base/tab-slider-new'
import TagFilter from '@/app/components/base/tag-management/filter'
import { useStore as useTagStore } from '@/app/components/base/tag-management/store'
-import CheckboxWithLabel from '@/app/components/datasets/create/website/base/checkbox-with-label'
import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
import { useAppContext } from '@/context/app-context'
import { useGlobalPublicStore } from '@/context/global-public-context'
@@ -205,12 +205,12 @@ const List: FC = ({
options={options}
/>
- setOpen(v => !v)}
- className="block"
- >
-
-
-
+
- 0 && 'pr-7',
)}
+ >
+
- -
+
-
{allTypes.map(mode => (
-
+
- = ({
}) => {
useEffect(() => {
// Only enable in Saas edition with valid API key
- if (!isAmplitudeEnabled())
+ if (!isAmplitudeEnabled)
return
// Initialize Amplitude
diff --git a/web/app/components/base/amplitude/__tests__/AmplitudeProvider.spec.tsx b/web/app/components/base/amplitude/__tests__/AmplitudeProvider.spec.tsx
index b30da72091c..5835634eb72 100644
--- a/web/app/components/base/amplitude/__tests__/AmplitudeProvider.spec.tsx
+++ b/web/app/components/base/amplitude/__tests__/AmplitudeProvider.spec.tsx
@@ -2,14 +2,24 @@ import * as amplitude from '@amplitude/analytics-browser'
import { sessionReplayPlugin } from '@amplitude/plugin-session-replay-browser'
import { render } from '@testing-library/react'
import { beforeEach, describe, expect, it, vi } from 'vitest'
-import AmplitudeProvider, { isAmplitudeEnabled } from '../AmplitudeProvider'
+import AmplitudeProvider from '../AmplitudeProvider'
const mockConfig = vi.hoisted(() => ({
AMPLITUDE_API_KEY: 'test-api-key',
IS_CLOUD_EDITION: true,
}))
-vi.mock('@/config', () => mockConfig)
+vi.mock('@/config', () => ({
+ get AMPLITUDE_API_KEY() {
+ return mockConfig.AMPLITUDE_API_KEY
+ },
+ get IS_CLOUD_EDITION() {
+ return mockConfig.IS_CLOUD_EDITION
+ },
+ get isAmplitudeEnabled() {
+ return mockConfig.IS_CLOUD_EDITION && !!mockConfig.AMPLITUDE_API_KEY
+ },
+}))
vi.mock('@amplitude/analytics-browser', () => ({
init: vi.fn(),
@@ -27,22 +37,6 @@ describe('AmplitudeProvider', () => {
mockConfig.IS_CLOUD_EDITION = true
})
- describe('isAmplitudeEnabled', () => {
- it('returns true when cloud edition and api key present', () => {
- expect(isAmplitudeEnabled()).toBe(true)
- })
-
- it('returns false when cloud edition but no api key', () => {
- mockConfig.AMPLITUDE_API_KEY = ''
- expect(isAmplitudeEnabled()).toBe(false)
- })
-
- it('returns false when not cloud edition', () => {
- mockConfig.IS_CLOUD_EDITION = false
- expect(isAmplitudeEnabled()).toBe(false)
- })
- })
-
describe('Component', () => {
it('initializes amplitude when enabled', () => {
render( = props => ) => {
- if (!isAmplitudeEnabled())
+ if (!isAmplitudeEnabled)
return
amplitude.track(eventName, eventProperties)
}
@@ -17,7 +17,7 @@ export const trackEvent = (eventName: string, eventProperties?: Record {
- if (!isAmplitudeEnabled())
+ if (!isAmplitudeEnabled)
return
amplitude.setUserId(userId)
}
@@ -27,7 +27,7 @@ export const setUserId = (userId: string) => {
* @param properties User properties
*/
export const setUserProperties = (properties: Record) => {
- if (!isAmplitudeEnabled())
+ if (!isAmplitudeEnabled)
return
const identifyEvent = new amplitude.Identify()
Object.entries(properties).forEach(([key, value]) => {
@@ -40,7 +40,7 @@ export const setUserProperties = (properties: Record) => {
* Reset user (e.g., when user logs out)
*/
export const resetUser = () => {
- if (!isAmplitudeEnabled())
+ if (!isAmplitudeEnabled)
return
amplitude.reset()
}
diff --git a/web/app/components/base/avatar/index.tsx b/web/app/components/base/avatar/index.tsx
index 2d55ec2720d..f53e1f8985c 100644
--- a/web/app/components/base/avatar/index.tsx
+++ b/web/app/components/base/avatar/index.tsx
@@ -1,8 +1,9 @@
import type { ImageLoadingStatus } from '@base-ui/react/avatar'
+import type * as React from 'react'
import { Avatar as BaseAvatar } from '@base-ui/react/avatar'
import { cn } from '@/utils/classnames'
-const SIZES = {
+const avatarSizeClasses = {
'xxs': { root: 'size-4', text: 'text-[7px]' },
'xs': { root: 'size-5', text: 'text-[8px]' },
'sm': { root: 'size-6', text: 'text-[10px]' },
@@ -13,7 +14,7 @@ const SIZES = {
'3xl': { root: 'size-16', text: 'text-2xl' },
} as const
-export type AvatarSize = keyof typeof SIZES
+export type AvatarSize = keyof typeof avatarSizeClasses
export type AvatarProps = {
name: string
@@ -23,7 +24,61 @@ export type AvatarProps = {
onLoadingStatusChange?: (status: ImageLoadingStatus) => void
}
-const BASE_CLASS = 'relative inline-flex shrink-0 select-none items-center justify-center overflow-hidden rounded-full bg-primary-600'
+export type AvatarRootProps = React.ComponentPropsWithRef & {
+ size?: AvatarSize
+}
+
+export function AvatarRoot({
+ size = 'md',
+ className,
+ ...props
+}: AvatarRootProps) {
+ return (
+
+
+export function AvatarImage({
+ className,
+ ...props
+}: AvatarImageProps) {
+ return (
+ & {
+ size?: AvatarSize
+}
+
+export function AvatarFallback({
+ size = 'md',
+ className,
+ ...props
+}: AvatarFallbackProps) {
+ return (
+
+
{avatar && (
-
+
{name?.[0]?.toLocaleUpperCase()}
-
-
+
+
)
}
diff --git a/web/app/components/base/carousel/__tests__/index.spec.tsx b/web/app/components/base/carousel/__tests__/index.spec.tsx
index cc452569374..e409b85757f 100644
--- a/web/app/components/base/carousel/__tests__/index.spec.tsx
+++ b/web/app/components/base/carousel/__tests__/index.spec.tsx
@@ -11,15 +11,15 @@ type EmblaEventName = 'reInit' | 'select'
type EmblaListener = (api: MockEmblaApi | undefined) => void
type MockEmblaApi = {
- scrollPrev: Mock
- scrollNext: Mock
- scrollTo: Mock
- selectedScrollSnap: Mock
- canScrollPrev: Mock
- canScrollNext: Mock
- slideNodes: Mock
- on: Mock
- off: Mock
+ scrollPrev: Mock<() => void>
+ scrollNext: Mock<() => void>
+ scrollTo: Mock<(index: number) => void>
+ selectedScrollSnap: Mock<() => number>
+ canScrollPrev: Mock<() => boolean>
+ canScrollNext: Mock<() => boolean>
+ slideNodes: Mock<() => HTMLDivElement[]>
+ on: Mock<(event: EmblaEventName, callback: EmblaListener) => void>
+ off: Mock<(event: EmblaEventName, callback: EmblaListener) => void>
}
let mockCanScrollPrev = false
@@ -33,19 +33,19 @@ const mockCarouselRef = vi.fn()
const mockedUseEmblaCarousel = vi.mocked(useEmblaCarousel)
const createMockEmblaApi = (): MockEmblaApi => ({
- scrollPrev: vi.fn(),
- scrollNext: vi.fn(),
- scrollTo: vi.fn(),
- selectedScrollSnap: vi.fn(() => mockSelectedIndex),
- canScrollPrev: vi.fn(() => mockCanScrollPrev),
- canScrollNext: vi.fn(() => mockCanScrollNext),
- slideNodes: vi.fn(() =>
- Array.from({ length: mockSlideCount }).fill(document.createElement('div')),
+ scrollPrev: vi.fn<() => void>(),
+ scrollNext: vi.fn<() => void>(),
+ scrollTo: vi.fn<(index: number) => void>(),
+ selectedScrollSnap: vi.fn<() => number>(() => mockSelectedIndex),
+ canScrollPrev: vi.fn<() => boolean>(() => mockCanScrollPrev),
+ canScrollNext: vi.fn<() => boolean>(() => mockCanScrollNext),
+ slideNodes: vi.fn<() => HTMLDivElement[]>(() =>
+ Array.from({ length: mockSlideCount }, () => document.createElement('div')),
),
- on: vi.fn((event: EmblaEventName, callback: EmblaListener) => {
+ on: vi.fn<(event: EmblaEventName, callback: EmblaListener) => void>((event, callback) => {
listeners[event].push(callback)
}),
- off: vi.fn((event: EmblaEventName, callback: EmblaListener) => {
+ off: vi.fn<(event: EmblaEventName, callback: EmblaListener) => void>((event, callback) => {
listeners[event] = listeners[event].filter(listener => listener !== callback)
}),
})
diff --git a/web/app/components/base/chat/chat/__tests__/hooks.spec.tsx b/web/app/components/base/chat/chat/__tests__/hooks.spec.tsx
index f5b261d5f31..92fa9ea42ee 100644
--- a/web/app/components/base/chat/chat/__tests__/hooks.spec.tsx
+++ b/web/app/components/base/chat/chat/__tests__/hooks.spec.tsx
@@ -141,6 +141,145 @@ describe('useChat', () => {
expect(result.current.chatList[0].suggestedQuestions).toEqual(['Ask Bob'])
})
+ describe('opening statement referential stability', () => {
+ it('should keep the same item reference across multiple streaming chatTree mutations', () => {
+ let callbacks: HookCallbacks
+
+ vi.mocked(ssePost).mockImplementation(async (_url, _params, options) => {
+ callbacks = options as HookCallbacks
+ })
+
+ const config = {
+ opening_statement: 'Welcome!',
+ suggested_questions: ['Q1', 'Q2'],
+ }
+ const { result } = renderHook(() => useChat(config as ChatConfig))
+
+ const openerInitial = result.current.chatList[0]
+ expect(openerInitial.isOpeningStatement).toBe(true)
+ expect(openerInitial.content).toBe('Welcome!')
+
+ act(() => {
+ result.current.handleSend('url', { query: 'hello' }, {})
+ })
+
+ act(() => {
+ callbacks.onWorkflowStarted({ workflow_run_id: 'wr-1', task_id: 't-1' })
+ })
+ expect(result.current.chatList[0]).toBe(openerInitial)
+
+ act(() => {
+ callbacks.onData('chunk-1 ', true, { messageId: 'm-1', conversationId: 'c-1', taskId: 't-1' })
+ })
+ expect(result.current.chatList.length).toBeGreaterThan(1)
+ expect(result.current.chatList[0]).toBe(openerInitial)
+
+ act(() => {
+ callbacks.onData('chunk-2 ', false, { messageId: 'm-1' })
+ })
+ expect(result.current.chatList[0]).toBe(openerInitial)
+
+ act(() => {
+ callbacks.onData('chunk-3', false, { messageId: 'm-1' })
+ callbacks.onMessageEnd({ metadata: { retriever_resources: [] } })
+ callbacks.onWorkflowFinished({ data: { status: 'succeeded' } })
+ callbacks.onCompleted()
+ })
+ expect(result.current.chatList[0]).toBe(openerInitial)
+ expect(result.current.chatList.at(-1)!.content).toBe('chunk-1 chunk-2 chunk-3')
+ })
+
+ it('should keep stable reference when getIntroduction identity changes but output is identical', () => {
+ const config = {
+ opening_statement: 'Hello {{name}}',
+ suggested_questions: ['Ask about {{name}}'],
+ }
+
+ const { result, rerender } = renderHook(
+ ({ fs }) => useChat(config as ChatConfig, fs as UseChatFormSettings),
+ { initialProps: { fs: { inputs: { name: 'Alice' }, inputsForm: [] } } },
+ )
+
+ const openerBefore = result.current.chatList[0]
+ expect(openerBefore.content).toBe('Hello Alice')
+ expect(openerBefore.suggestedQuestions).toEqual(['Ask about Alice'])
+
+ rerender({ fs: { inputs: { name: 'Alice' }, inputsForm: [] } })
+
+ expect(result.current.chatList[0]).toBe(openerBefore)
+ })
+
+ it('should produce a new item when the processed content actually changes', () => {
+ const config = {
+ opening_statement: 'Hello {{name}}',
+ suggested_questions: ['Ask {{name}}'],
+ }
+
+ const { result, rerender } = renderHook(
+ ({ fs }) => useChat(config as ChatConfig, fs as UseChatFormSettings),
+ { initialProps: { fs: { inputs: { name: 'Alice' }, inputsForm: [] } } },
+ )
+
+ const before = result.current.chatList[0]
+
+ rerender({ fs: { inputs: { name: 'Bob' }, inputsForm: [] } })
+
+ const after = result.current.chatList[0]
+ expect(after).not.toBe(before)
+ expect(after.content).toBe('Hello Bob')
+ expect(after.suggestedQuestions).toEqual(['Ask Bob'])
+ })
+
+ it('should keep content and suggestedQuestions stable for opener already in prevChatTree even when sibling metadata changes', () => {
+ let callbacks: HookCallbacks
+ vi.mocked(ssePost).mockImplementation(async (_url, _params, options) => {
+ callbacks = options as HookCallbacks
+ })
+
+ const config = {
+ opening_statement: 'Hello updated',
+ suggested_questions: ['S1'],
+ }
+ const prevChatTree = [{
+ id: 'opening-statement',
+ content: 'old',
+ isAnswer: true,
+ isOpeningStatement: true,
+ suggestedQuestions: [],
+ }]
+
+ const { result } = renderHook(() =>
+ useChat(config as ChatConfig, undefined, prevChatTree as ChatItemInTree[]),
+ )
+
+ const openerBefore = result.current.chatList[0]
+ expect(openerBefore.content).toBe('Hello updated')
+ expect(openerBefore.suggestedQuestions).toEqual(['S1'])
+
+ const contentBefore = openerBefore.content
+ const suggestionsBefore = openerBefore.suggestedQuestions
+
+ act(() => {
+ result.current.handleSend('url', { query: 'msg' }, {})
+ })
+ act(() => {
+ callbacks.onData('resp', true, { messageId: 'm-1', conversationId: 'c-1', taskId: 't-1' })
+ })
+
+ expect(result.current.chatList.length).toBeGreaterThan(1)
+ const openerAfter = result.current.chatList[0]
+ expect(openerAfter.content).toBe(contentBefore)
+ expect(openerAfter.suggestedQuestions).toBe(suggestionsBefore)
+ })
+
+ it('should use a stable id of "opening-statement"', () => {
+ const { result } = renderHook(() =>
+ useChat({ opening_statement: 'Hi' } as ChatConfig),
+ )
+ expect(result.current.chatList[0].id).toBe('opening-statement')
+ })
+ })
+
describe('handleSend', () => {
it('should block send if already responding', async () => {
const { result } = renderHook(() => useChat())
diff --git a/web/app/components/base/chat/chat/__tests__/index.spec.tsx b/web/app/components/base/chat/chat/__tests__/index.spec.tsx
index 781b5e86f31..0100b059f01 100644
--- a/web/app/components/base/chat/chat/__tests__/index.spec.tsx
+++ b/web/app/components/base/chat/chat/__tests__/index.spec.tsx
@@ -8,10 +8,10 @@ import Chat from '../index'
// ─── Why each mock exists ─────────────────────────────────────────────────────
//
// Answer – transitively pulls Markdown (rehype/remark/katex), AgentContent,
-// WorkflowProcessItem and Operation; none can resolve in jsdom.
+// WorkflowProcessItem and Operation; none can resolve in the test DOM runtime.
// Question – pulls Markdown, copy-to-clipboard, react-textarea-autosize.
// ChatInputArea – pulls js-audio-recorder (requires Web Audio API unavailable in
-// jsdom) and VoiceInput / FileContextProvider chains.
+// the test DOM runtime) and VoiceInput / FileContextProvider chains.
// PromptLogModal– pulls CopyFeedbackNew and deep modal dep chain.
// AgentLogModal – pulls @remixicon/react (causes lint push error), useClickAway
// from ahooks, and AgentLogDetail (workflow graph renderer).
diff --git a/web/app/components/base/chat/chat/hooks.ts b/web/app/components/base/chat/chat/hooks.ts
index 9c06f49b3d7..a0f335f567c 100644
--- a/web/app/components/base/chat/chat/hooks.ts
+++ b/web/app/components/base/chat/chat/hooks.ts
@@ -88,30 +88,54 @@ export const useChat = (
return processOpeningStatement(str, formSettings?.inputs || {}, formSettings?.inputsForm || [])
}, [formSettings?.inputs, formSettings?.inputsForm])
+ const processedOpeningContent = config?.opening_statement
+ ? getIntroduction(config.opening_statement)
+ : undefined
+ const processedSuggestionsKey = config?.suggested_questions
+ ? JSON.stringify(config.suggested_questions.map(q => getIntroduction(q)))
+ : undefined
+
+ const openingStatementItem = useMemo(() => {
+ if (!processedOpeningContent)
+ return null
+ return {
+ id: 'opening-statement',
+ content: processedOpeningContent,
+ isAnswer: true,
+ isOpeningStatement: true,
+ suggestedQuestions: processedSuggestionsKey
+ ? JSON.parse(processedSuggestionsKey) as string[]
+ : undefined,
+ }
+ }, [processedOpeningContent, processedSuggestionsKey])
+
+ const threadOpener = useMemo(
+ () => threadMessages.find(item => item.isOpeningStatement) ?? null,
+ [threadMessages],
+ )
+
+ const mergedOpeningItem = useMemo(() => {
+ if (!threadOpener || !openingStatementItem)
+ return null
+ return {
+ ...threadOpener,
+ content: openingStatementItem.content,
+ suggestedQuestions: openingStatementItem.suggestedQuestions,
+ }
+ }, [threadOpener, openingStatementItem])
+
/** Final chat list that will be rendered */
const chatList = useMemo(() => {
const ret = [...threadMessages]
- if (config?.opening_statement) {
+ if (openingStatementItem) {
const index = threadMessages.findIndex(item => item.isOpeningStatement)
- if (index > -1) {
- ret[index] = {
- ...ret[index],
- content: getIntroduction(config.opening_statement),
- suggestedQuestions: config.suggested_questions?.map(item => getIntroduction(item)),
- }
- }
- else {
- ret.unshift({
- id: 'opening-statement',
- content: getIntroduction(config.opening_statement),
- isAnswer: true,
- isOpeningStatement: true,
- suggestedQuestions: config.suggested_questions?.map(item => getIntroduction(item)),
- })
- }
+ if (index > -1 && mergedOpeningItem)
+ ret[index] = mergedOpeningItem
+ else if (index === -1)
+ ret.unshift(openingStatementItem)
}
return ret
- }, [threadMessages, config, getIntroduction])
+ }, [threadMessages, openingStatementItem, mergedOpeningItem])
useEffect(() => {
setAutoFreeze(false)
diff --git a/web/app/components/base/chat/utils.ts b/web/app/components/base/chat/utils.ts
index b47fec1d0ad..5881f565a49 100644
--- a/web/app/components/base/chat/utils.ts
+++ b/web/app/components/base/chat/utils.ts
@@ -158,7 +158,7 @@ function buildChatItemTree(allMessages: IChatItem[]): ChatItemInTree[] {
rootNodes.push(questionNode)
}
else {
- map[parentMessageId]?.children!.push(questionNode)
+ map[parentMessageId].children!.push(questionNode)
}
}
}
diff --git a/web/app/components/base/date-and-time-picker/calendar/__tests__/index.spec.tsx b/web/app/components/base/date-and-time-picker/calendar/__tests__/index.spec.tsx
index d8e00780b1e..8839798c15e 100644
--- a/web/app/components/base/date-and-time-picker/calendar/__tests__/index.spec.tsx
+++ b/web/app/components/base/date-and-time-picker/calendar/__tests__/index.spec.tsx
@@ -3,7 +3,7 @@ import { fireEvent, render, screen } from '@testing-library/react'
import dayjs from '../../utils/dayjs'
import Calendar from '../index'
-// Mock scrollIntoView since jsdom doesn't implement it
+// Mock scrollIntoView since the test DOM runtime doesn't implement it
beforeAll(() => {
Element.prototype.scrollIntoView = vi.fn()
})
diff --git a/web/app/components/base/date-and-time-picker/time-picker/__tests__/index.spec.tsx b/web/app/components/base/date-and-time-picker/time-picker/__tests__/index.spec.tsx
index 910faf9cd42..199ed4ee411 100644
--- a/web/app/components/base/date-and-time-picker/time-picker/__tests__/index.spec.tsx
+++ b/web/app/components/base/date-and-time-picker/time-picker/__tests__/index.spec.tsx
@@ -3,7 +3,7 @@ import { fireEvent, render, screen, within } from '@testing-library/react'
import dayjs, { isDayjsObject } from '../../utils/dayjs'
import TimePicker from '../index'
-// Mock scrollIntoView since jsdom doesn't implement it
+// Mock scrollIntoView since the test DOM runtime doesn't implement it
beforeAll(() => {
Element.prototype.scrollIntoView = vi.fn()
})
diff --git a/web/app/components/base/features/new-feature-panel/annotation-reply/config-param-modal.tsx b/web/app/components/base/features/new-feature-panel/annotation-reply/config-param-modal.tsx
index 332b87cb300..ac0b6d0f579 100644
--- a/web/app/components/base/features/new-feature-panel/annotation-reply/config-param-modal.tsx
+++ b/web/app/components/base/features/new-feature-panel/annotation-reply/config-param-modal.tsx
@@ -93,7 +93,6 @@ const ConfigParamModal: FC = ({
className="mt-1"
value={(annotationConfig.score_threshold || ANNOTATION_DEFAULT.score_threshold) * 100}
onChange={(val) => {
- /* v8 ignore next -- callback dispatch depends on react-slider drag mechanics that are flaky in jsdom. @preserve */
setAnnotationConfig({
...annotationConfig,
score_threshold: val / 100,
diff --git a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/__tests__/index.spec.tsx b/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/__tests__/index.spec.tsx
index 2bc30e4ead7..ffa9c330439 100644
--- a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/__tests__/index.spec.tsx
+++ b/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/__tests__/index.spec.tsx
@@ -1,20 +1,9 @@
import { render, screen } from '@testing-library/react'
import ScoreSlider from '../index'
-vi.mock('@/app/components/base/features/new-feature-panel/annotation-reply/score-slider/base-slider', () => ({
- default: ({ value, onChange, min, max }: { value: number, onChange: (v: number) => void, min: number, max: number }) => (
- onChange(Number(e.target.value))}
- />
- ),
-}))
-
describe('ScoreSlider', () => {
+ const getSliderInput = () => screen.getByLabelText('appDebug.feature.annotation.scoreThreshold.title')
+
beforeEach(() => {
vi.clearAllMocks()
})
@@ -22,7 +11,7 @@ describe('ScoreSlider', () => {
it('should render the slider', () => {
render( = ({ className, max, min, step, value, disabled, onChange }) => {
- return (
- (
- = ({
className,
value,
onChange,
}) => {
const { t } = useTranslation()
+ const safeValue = clamp(value, 80, 100)
return (
-
- )}
- />
- )
-}
-
-export default Slider
diff --git a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/base-slider/style.module.css b/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/base-slider/style.module.css
deleted file mode 100644
index 8ef23b54b5b..00000000000
--- a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/base-slider/style.module.css
+++ /dev/null
@@ -1,20 +0,0 @@
-.slider {
- position: relative;
-}
-
-.slider.disabled {
- opacity: 0.6;
-}
-
-.slider-thumb:focus {
- outline: none;
-}
-
-.slider-track {
- background-color: #528BFF;
- height: 2px;
-}
-
-.slider-track-1 {
- background-color: #E5E7EB;
-}
diff --git a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/index.tsx b/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/index.tsx
index c6fb1a0b4e8..0363eb28208 100644
--- a/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/index.tsx
+++ b/web/app/components/base/features/new-feature-panel/annotation-reply/score-slider/index.tsx
@@ -2,7 +2,7 @@
import type { FC } from 'react'
import * as React from 'react'
import { useTranslation } from 'react-i18next'
-import Slider from '@/app/components/base/features/new-feature-panel/annotation-reply/score-slider/base-slider'
+import { Slider } from '@/app/components/base/ui/slider'
type Props = {
className?: string
@@ -10,23 +10,42 @@ type Props = {
onChange: (value: number) => void
}
+const clamp = (value: number, min: number, max: number) => {
+ if (!Number.isFinite(value))
+ return min
+
+ return Math.min(Math.max(value, min), max)
+}
+
const ScoreSlider: FC
-
-
- {(state.valueNow / 100).toFixed(2)}
-
-
-
+
(null)
+ const [blurHidden, setBlurHidden] = useState(false)
+ const blurTimerRef = useRef | null>(null)
+
+ const clearBlurTimer = useCallback(() => {
+ if (blurTimerRef.current) {
+ clearTimeout(blurTimerRef.current)
+ blurTimerRef.current = null
+ }
+ }, [])
+
+ useEffect(() => {
+ const unregister = mergeRegister(
+ editor.registerCommand(
+ BLUR_COMMAND,
+ (event) => {
+ clearBlurTimer()
+ const target = event?.relatedTarget as HTMLElement
+ if (!target?.classList?.contains('var-search-input'))
+ blurTimerRef.current = setTimeout(() => setBlurHidden(true), 200)
+ return false
+ },
+ COMMAND_PRIORITY_EDITOR,
+ ),
+ editor.registerCommand(
+ FOCUS_COMMAND,
+ () => {
+ clearBlurTimer()
+ setBlurHidden(false)
+ return false
+ },
+ COMMAND_PRIORITY_EDITOR,
+ ),
+ )
+
+ return () => {
+ if (blurTimerRef.current)
+ clearTimeout(blurTimerRef.current)
+ unregister()
+ }
+ }, [editor, clearBlurTimer])
eventEmitter?.useSubscription((v: any) => {
if (v.type === INSERT_VARIABLE_VALUE_BLOCK_COMMAND)
@@ -159,6 +207,8 @@ const ComponentPicker = ({
anchorElementRef,
{ options, selectedIndex, selectOptionAndCleanUp, setHighlightedIndex },
) => {
+ if (blurHidden)
+ return null
if (!(anchorElementRef.current && (allFlattenOptions.length || workflowVariableBlock?.show)))
return null
@@ -240,7 +290,7 @@ const ComponentPicker = ({
}
)
- }, [allFlattenOptions.length, workflowVariableBlock?.show, floatingStyles, isPositioned, refs, workflowVariableOptions, isSupportFileVar, handleClose, currentBlock?.generatorType, handleSelectWorkflowVariable, queryString, workflowVariableBlock?.showManageInputField, workflowVariableBlock?.onManageInputField])
+ }, [blurHidden, allFlattenOptions.length, workflowVariableBlock?.show, floatingStyles, isPositioned, refs, workflowVariableOptions, isSupportFileVar, handleClose, currentBlock?.generatorType, handleSelectWorkflowVariable, queryString, workflowVariableBlock?.showManageInputField, workflowVariableBlock?.onManageInputField])
return (
void
@@ -20,35 +18,13 @@ const OnBlurBlock: FC = ({
}) => {
const [editor] = useLexicalComposerContext()
- const ref = useRef | null>(null)
-
useEffect(() => {
- const clearHideMenuTimeout = () => {
- if (ref.current) {
- clearTimeout(ref.current)
- ref.current = null
- }
- }
-
- const unregister = mergeRegister(
- editor.registerCommand(
- CLEAR_HIDE_MENU_TIMEOUT,
- () => {
- clearHideMenuTimeout()
- return true
- },
- COMMAND_PRIORITY_EDITOR,
- ),
+ return mergeRegister(
editor.registerCommand(
BLUR_COMMAND,
(event) => {
- // Check if the clicked target element is var-search-input
const target = event?.relatedTarget as HTMLElement
if (!target?.classList?.contains('var-search-input')) {
- clearHideMenuTimeout()
- ref.current = setTimeout(() => {
- editor.dispatchCommand(KEY_ESCAPE_COMMAND, new KeyboardEvent('keydown', { key: 'Escape' }))
- }, 200)
if (onBlur)
onBlur()
}
@@ -66,11 +42,6 @@ const OnBlurBlock: FC = ({
COMMAND_PRIORITY_EDITOR,
),
)
-
- return () => {
- clearHideMenuTimeout()
- unregister()
- }
}, [editor, onBlur, onFocus])
return null
diff --git a/web/app/components/base/prompt-editor/plugins/shortcuts-popup-plugin/index.tsx b/web/app/components/base/prompt-editor/plugins/shortcuts-popup-plugin/index.tsx
index abe6ea9a452..7dcda803f23 100644
--- a/web/app/components/base/prompt-editor/plugins/shortcuts-popup-plugin/index.tsx
+++ b/web/app/components/base/prompt-editor/plugins/shortcuts-popup-plugin/index.tsx
@@ -141,7 +141,7 @@ export default function ShortcutsPopupPlugin({
const portalRef = useRef(null)
const lastSelectionRef = useRef(null)
- /* v8 ignore next -- defensive non-browser fallback; this client-only plugin runs where document exists (browser/jsdom). @preserve */
+ /* v8 ignore next -- defensive non-browser fallback; this client-only plugin runs where document exists (browser/test DOM runtime). @preserve */
const containerEl = useMemo(() => container ?? (typeof document !== 'undefined' ? document.body : null), [container])
const useContainer = !!containerEl && containerEl !== document.body
@@ -210,7 +210,7 @@ export default function ShortcutsPopupPlugin({
if (rect.width === 0 && rect.height === 0) {
const root = editor.getRootElement()
- /* v8 ignore next 10 -- zero-size rect recovery depends on browser layout/selection geometry; deterministic reproduction in jsdom is unreliable. @preserve */
+ /* v8 ignore next 10 -- zero-size rect recovery depends on browser layout/selection geometry; deterministic reproduction in the test DOM runtime is unreliable. @preserve */
if (root) {
const sc = range.startContainer
const node = sc.nodeType === Node.ELEMENT_NODE
diff --git a/web/app/components/base/prompt-editor/plugins/update-block.tsx b/web/app/components/base/prompt-editor/plugins/update-block.tsx
index bf89a259af5..2d83573b1fe 100644
--- a/web/app/components/base/prompt-editor/plugins/update-block.tsx
+++ b/web/app/components/base/prompt-editor/plugins/update-block.tsx
@@ -3,7 +3,6 @@ import { $insertNodes } from 'lexical'
import { useEventEmitterContextContext } from '@/context/event-emitter'
import { textToEditorState } from '../utils'
import { CustomTextNode } from './custom-text/node'
-import { CLEAR_HIDE_MENU_TIMEOUT } from './workflow-variable-block'
export const PROMPT_EDITOR_UPDATE_VALUE_BY_EVENT_EMITTER = 'PROMPT_EDITOR_UPDATE_VALUE_BY_EVENT_EMITTER'
export const PROMPT_EDITOR_INSERT_QUICKLY = 'PROMPT_EDITOR_INSERT_QUICKLY'
@@ -30,8 +29,6 @@ const UpdateBlock = ({
editor.update(() => {
const textNode = new CustomTextNode('/')
$insertNodes([textNode])
-
- editor.dispatchCommand(CLEAR_HIDE_MENU_TIMEOUT, undefined)
})
}
})
diff --git a/web/app/components/base/prompt-editor/plugins/workflow-variable-block/__tests__/index.spec.tsx b/web/app/components/base/prompt-editor/plugins/workflow-variable-block/__tests__/index.spec.tsx
index ca4973b8300..1591dc44f9f 100644
--- a/web/app/components/base/prompt-editor/plugins/workflow-variable-block/__tests__/index.spec.tsx
+++ b/web/app/components/base/prompt-editor/plugins/workflow-variable-block/__tests__/index.spec.tsx
@@ -9,7 +9,6 @@ import { $insertNodes, COMMAND_PRIORITY_EDITOR } from 'lexical'
import { Type } from '@/app/components/workflow/nodes/llm/types'
import { BlockEnum } from '@/app/components/workflow/types'
import {
- CLEAR_HIDE_MENU_TIMEOUT,
DELETE_WORKFLOW_VARIABLE_BLOCK_COMMAND,
INSERT_WORKFLOW_VARIABLE_BLOCK_COMMAND,
UPDATE_WORKFLOW_NODES_MAP,
@@ -134,7 +133,6 @@ describe('WorkflowVariableBlock', () => {
const insertHandler = mockRegisterCommand.mock.calls[0][1] as (variables: string[]) => boolean
const result = insertHandler(['node-1', 'answer'])
- expect(mockDispatchCommand).toHaveBeenCalledWith(CLEAR_HIDE_MENU_TIMEOUT, undefined)
expect($createWorkflowVariableBlockNode).toHaveBeenCalledWith(
['node-1', 'answer'],
workflowNodesMap,
diff --git a/web/app/components/base/prompt-editor/plugins/workflow-variable-block/index.tsx b/web/app/components/base/prompt-editor/plugins/workflow-variable-block/index.tsx
index 76b27958031..c8cac64d19d 100644
--- a/web/app/components/base/prompt-editor/plugins/workflow-variable-block/index.tsx
+++ b/web/app/components/base/prompt-editor/plugins/workflow-variable-block/index.tsx
@@ -18,7 +18,6 @@ import {
export const INSERT_WORKFLOW_VARIABLE_BLOCK_COMMAND = createCommand('INSERT_WORKFLOW_VARIABLE_BLOCK_COMMAND')
export const DELETE_WORKFLOW_VARIABLE_BLOCK_COMMAND = createCommand('DELETE_WORKFLOW_VARIABLE_BLOCK_COMMAND')
-export const CLEAR_HIDE_MENU_TIMEOUT = createCommand('CLEAR_HIDE_MENU_TIMEOUT')
export const UPDATE_WORKFLOW_NODES_MAP = createCommand('UPDATE_WORKFLOW_NODES_MAP')
export type WorkflowVariableBlockProps = {
@@ -49,7 +48,6 @@ const WorkflowVariableBlock = memo(({
editor.registerCommand(
INSERT_WORKFLOW_VARIABLE_BLOCK_COMMAND,
(variables: string[]) => {
- editor.dispatchCommand(CLEAR_HIDE_MENU_TIMEOUT, undefined)
const workflowVariableBlockNode = $createWorkflowVariableBlockNode(variables, workflowNodesMap, getVarType)
$insertNodes([workflowVariableBlockNode])
diff --git a/web/app/components/base/slider/__tests__/index.spec.tsx b/web/app/components/base/slider/__tests__/index.spec.tsx
deleted file mode 100644
index bb1f030689a..00000000000
--- a/web/app/components/base/slider/__tests__/index.spec.tsx
+++ /dev/null
@@ -1,77 +0,0 @@
-import { act, render, screen } from '@testing-library/react'
-import userEvent from '@testing-library/user-event'
-import { describe, expect, it, vi } from 'vitest'
-import Slider from '../index'
-
-describe('Slider Component', () => {
- it('should render with correct default ARIA limits and current value', () => {
- render(
-
-export default meta
-type Story = StoryObj
-
-// Interactive demo wrapper
-const SliderDemo = (args: any) => {
- const [value, setValue] = useState(args.value || 50)
-
- return (
- = ({
- className,
- thumbClassName,
- trackClassName,
- max,
- min,
- step,
- value,
- disabled,
- onChange,
-}) => {
- return (
- = ({
const setShowTagManagementModal = useTagStore(s => s.setShowTagManagementModal)
const [keywords, setKeywords] = useState('')
- const [searchKeywords, setSearchKeywords] = useState('')
- const { run: handleSearch } = useDebounceFn(() => {
- setSearchKeywords(keywords)
- }, { wait: 500 })
- const handleKeywordsChange = (value: string) => {
- setKeywords(value)
- handleSearch()
- }
const filteredTagList = useMemo(() => {
- return tagList.filter(tag => tag.type === type && tag.name.includes(searchKeywords))
- }, [type, tagList, searchKeywords])
+ return tagList.filter(tag => tag.type === type && tag.name.includes(keywords))
+ }, [type, tagList, keywords])
const currentTag = useMemo(() => {
return tagList.find(tag => tag.id === value[0])
@@ -64,61 +56,61 @@ const TagFilter: FC = ({
})
return (
-
+ {(safeValue / 100).toFixed(2)}
+
diff --git a/web/app/components/base/file-uploader/file-from-link-or-local/index.tsx b/web/app/components/base/file-uploader/file-from-link-or-local/index.tsx
index 69496903a67..de9cc7ecd00 100644
--- a/web/app/components/base/file-uploader/file-from-link-or-local/index.tsx
+++ b/web/app/components/base/file-uploader/file-from-link-or-local/index.tsx
@@ -37,11 +37,11 @@ const FileFromLinkOrLocal = ({
const { handleLoadFileFromLink } = useFile(fileConfig)
const disabled = !!fileConfig.number_limits && files.length >= fileConfig.number_limits
const fileLinkPlaceholder = t('fileUploader.pasteFileLinkInputPlaceholder', { ns: 'common' })
- /* v8 ignore next -- fallback for missing i18n key is not reliably testable under current global translation mocks in jsdom @preserve */
+ /* v8 ignore next -- fallback for a missing i18n key is not reliably testable under the current global translation mocks in the test DOM runtime. @preserve */
const fileLinkPlaceholderText = fileLinkPlaceholder || ''
const handleSaveUrl = () => {
- /* v8 ignore next -- guarded by UI-level disabled state (`disabled={!url || disabled}`), not reachable in jsdom click flow @preserve */
+ /* v8 ignore next -- guarded by UI-level disabled state (`disabled={!url || disabled}`), not reachable in the current test click flow. @preserve */
if (!url)
return
diff --git a/web/app/components/base/icons/__tests__/utils.spec.ts b/web/app/components/base/icons/__tests__/utils.spec.ts
index a25f39111d9..f8534038bfa 100644
--- a/web/app/components/base/icons/__tests__/utils.spec.ts
+++ b/web/app/components/base/icons/__tests__/utils.spec.ts
@@ -62,7 +62,7 @@ describe('generate icon base utils', () => {
const { container } = render(generate(node, 'key'))
// to svg element
expect(container.firstChild).toHaveClass('container')
- expect(container.querySelector('span')).toHaveStyle({ color: 'rgb(0, 0, 255)' })
+ expect(container.querySelector('span')).toHaveStyle({ color: 'blue' })
})
// add not has children
diff --git a/web/app/components/base/input/__tests__/index.spec.tsx b/web/app/components/base/input/__tests__/index.spec.tsx
index 2c5b563a127..dfab8617c28 100644
--- a/web/app/components/base/input/__tests__/index.spec.tsx
+++ b/web/app/components/base/input/__tests__/index.spec.tsx
@@ -99,7 +99,7 @@ describe('Input component', () => {
render()
const input = screen.getByPlaceholderText(/input/i)
expect(input).toHaveClass(customClass)
- expect(input).toHaveStyle({ color: 'rgb(255, 0, 0)' })
+ expect(input).toHaveStyle({ color: 'red' })
})
it('applies large size variant correctly', () => {
diff --git a/web/app/components/base/markdown-blocks/__tests__/code-block.spec.tsx b/web/app/components/base/markdown-blocks/__tests__/code-block.spec.tsx
index 308232fd0f4..a16686801c6 100644
--- a/web/app/components/base/markdown-blocks/__tests__/code-block.spec.tsx
+++ b/web/app/components/base/markdown-blocks/__tests__/code-block.spec.tsx
@@ -1,6 +1,6 @@
-import { createRequire } from 'node:module'
import { act, render, screen, waitFor } from '@testing-library/react'
import userEvent from '@testing-library/user-event'
+import * as echarts from 'echarts'
import { Theme } from '@/types/app'
import CodeBlock from '../code-block'
@@ -10,17 +10,28 @@ type UseThemeReturn = {
}
const mockUseTheme = vi.fn<() => UseThemeReturn>(() => ({ theme: Theme.light }))
-const require = createRequire(import.meta.url)
-const echartsCjs = require('echarts') as {
- getInstanceByDom: (dom: HTMLDivElement | null) => {
- resize: (opts?: { width?: string, height?: string }) => void
- } | null
-}
+const mockEcharts = vi.hoisted(() => {
+ const state = {
+ finishedHandler: undefined as undefined | ((event?: unknown) => void),
+ echartsInstance: {
+ resize: vi.fn<(opts?: { width?: string, height?: string }) => void>(),
+ trigger: vi.fn((eventName: string, event?: unknown) => {
+ if (eventName === 'finished')
+ state.finishedHandler?.(event)
+ }),
+ },
+ getInstanceByDom: vi.fn(() => state.echartsInstance),
+ }
+
+ return state
+})
let clientWidthSpy: { mockRestore: () => void } | null = null
let clientHeightSpy: { mockRestore: () => void } | null = null
let offsetWidthSpy: { mockRestore: () => void } | null = null
let offsetHeightSpy: { mockRestore: () => void } | null = null
+let consoleErrorSpy: ReturnType | null = null
+let consoleWarnSpy: ReturnType | null = null
type AudioContextCtor = new () => unknown
type WindowWithLegacyAudio = Window & {
@@ -59,6 +70,42 @@ vi.mock('@/hooks/use-theme', () => ({
default: () => mockUseTheme(),
}))
+vi.mock('echarts', () => ({
+ getInstanceByDom: mockEcharts.getInstanceByDom,
+}))
+
+vi.mock('echarts-for-react', async () => {
+ const React = await vi.importActual('react')
+
+ const MockReactEcharts = React.forwardRef(({
+ onChartReady,
+ onEvents,
+ }: {
+ onChartReady?: (instance: typeof mockEcharts.echartsInstance) => void
+ onEvents?: { finished?: (event?: unknown) => void }
+ }, ref: React.ForwardedRef<{ getEchartsInstance: () => typeof mockEcharts.echartsInstance }>) => {
+ React.useImperativeHandle(ref, () => ({
+ getEchartsInstance: () => mockEcharts.echartsInstance,
+ }))
+
+ React.useEffect(() => {
+ mockEcharts.finishedHandler = onEvents?.finished
+ onChartReady?.(mockEcharts.echartsInstance)
+ onEvents?.finished?.({})
+ return () => {
+ mockEcharts.finishedHandler = undefined
+ }
+ }, [onChartReady, onEvents])
+
+ return
+ })
+
+ return {
+ __esModule: true,
+ default: MockReactEcharts,
+ }
+})
+
vi.mock('@/app/components/base/mermaid', () => ({
__esModule: true,
default: ({ PrimitiveCode }: { PrimitiveCode: string }) =>
,
)
- // Initial state should show "Thinking..."
- expect(screen.getByText(/Thinking\.\.\./)).toBeInTheDocument()
-
- // Advance timer
- act(() => {
- vi.advanceTimersByTime(2000)
- })
-
- // Timer should still be running (showing "Thinking..." not "Thought")
- expect(screen.getByText(/Thinking\.\.\./)).toBeInTheDocument()
- expect(screen.getByText(/\(2\.0s\)/)).toBeInTheDocument()
+ // Timer should be stopped immediately — isResponding undefined means not in active response
+ expect(screen.getByText(/Thought/)).toBeInTheDocument()
})
})
diff --git a/web/app/components/base/markdown-blocks/code-block.tsx b/web/app/components/base/markdown-blocks/code-block.tsx
index b36d8d77885..412c61d52d3 100644
--- a/web/app/components/base/markdown-blocks/code-block.tsx
+++ b/web/app/components/base/markdown-blocks/code-block.tsx
@@ -85,13 +85,30 @@ const CodeBlock: any = memo(({ inline, className, children = '', ...props }: any
const processedRef = useRef(false) // Track if content was successfully processed
const isInitialRenderRef = useRef(true) // Track if this is initial render
const chartInstanceRef = useRef(null) // Direct reference to ECharts instance
- const resizeTimerRef = useRef(null) // For debounce handling
+ const resizeTimerRef = useRef | null>(null) // For debounce handling
+ const chartReadyTimerRef = useRef | null>(null)
const finishedEventCountRef = useRef(0) // Track finished event trigger count
const match = /language-(\w+)/.exec(className || '')
const language = match?.[1]
const languageShowName = getCorrectCapitalizationLanguageName(language || '')
const isDarkMode = theme === Theme.dark
+ const clearResizeTimer = useCallback(() => {
+ if (!resizeTimerRef.current)
+ return
+
+ clearTimeout(resizeTimerRef.current)
+ resizeTimerRef.current = null
+ }, [])
+
+ const clearChartReadyTimer = useCallback(() => {
+ if (!chartReadyTimerRef.current)
+ return
+
+ clearTimeout(chartReadyTimerRef.current)
+ chartReadyTimerRef.current = null
+ }, [])
+
const echartsStyle = useMemo(() => ({
height: '350px',
width: '100%',
@@ -104,26 +121,27 @@ const CodeBlock: any = memo(({ inline, className, children = '', ...props }: any
// Debounce resize operations
const debouncedResize = useCallback(() => {
- if (resizeTimerRef.current)
- clearTimeout(resizeTimerRef.current)
+ clearResizeTimer()
resizeTimerRef.current = setTimeout(() => {
if (chartInstanceRef.current)
chartInstanceRef.current.resize()
resizeTimerRef.current = null
}, 200)
- }, [])
+ }, [clearResizeTimer])
// Handle ECharts instance initialization
const handleChartReady = useCallback((instance: any) => {
chartInstanceRef.current = instance
// Force resize to ensure timeline displays correctly
- setTimeout(() => {
+ clearChartReadyTimer()
+ chartReadyTimerRef.current = setTimeout(() => {
if (chartInstanceRef.current)
chartInstanceRef.current.resize()
+ chartReadyTimerRef.current = null
}, 200)
- }, [])
+ }, [clearChartReadyTimer])
// Store event handlers in useMemo to avoid recreating them
const echartsEvents = useMemo(() => ({
@@ -157,10 +175,20 @@ const CodeBlock: any = memo(({ inline, className, children = '', ...props }: any
return () => {
window.removeEventListener('resize', handleResize)
- if (resizeTimerRef.current)
- clearTimeout(resizeTimerRef.current)
+ clearResizeTimer()
+ clearChartReadyTimer()
+ chartInstanceRef.current = null
}
- }, [language, debouncedResize])
+ }, [language, debouncedResize, clearResizeTimer, clearChartReadyTimer])
+
+ useEffect(() => {
+ return () => {
+ clearResizeTimer()
+ clearChartReadyTimer()
+ chartInstanceRef.current = null
+ echartsRef.current = null
+ }
+ }, [clearResizeTimer, clearChartReadyTimer])
// Process chart data when content changes
useEffect(() => {
// Only process echarts content
diff --git a/web/app/components/base/markdown-blocks/think-block.tsx b/web/app/components/base/markdown-blocks/think-block.tsx
index f920218152e..184ed892745 100644
--- a/web/app/components/base/markdown-blocks/think-block.tsx
+++ b/web/app/components/base/markdown-blocks/think-block.tsx
@@ -39,9 +39,10 @@ const removeEndThink = (children: any): any => {
const useThinkTimer = (children: any) => {
const { isResponding } = useChatContext()
+ const endThinkDetected = hasEndThink(children)
const [startTime] = useState(() => Date.now())
const [elapsedTime, setElapsedTime] = useState(0)
- const [isComplete, setIsComplete] = useState(false)
+ const [isComplete, setIsComplete] = useState(() => endThinkDetected)
const timerRef = useRef(null)
useEffect(() => {
@@ -61,11 +62,10 @@ const useThinkTimer = (children: any) => {
useEffect(() => {
// Stop timer when:
// 1. Content has [ENDTHINKFLAG] marker (normal completion)
- // 2. isResponding is explicitly false (user clicked stop button)
- // Note: Don't stop when isResponding is undefined (component used outside ChatContextProvider)
- if (hasEndThink(children) || isResponding === false)
+ // 2. isResponding is not true (false = user clicked stop, undefined = historical conversation)
+ if (endThinkDetected || !isResponding)
setIsComplete(true)
- }, [children, isResponding])
+ }, [endThinkDetected, isResponding])
return { elapsedTime, isComplete }
}
diff --git a/web/app/components/base/node-status/__tests__/index.spec.tsx b/web/app/components/base/node-status/__tests__/index.spec.tsx
index f74af4965e7..37b12946c8e 100644
--- a/web/app/components/base/node-status/__tests__/index.spec.tsx
+++ b/web/app/components/base/node-status/__tests__/index.spec.tsx
@@ -41,7 +41,7 @@ describe('NodeStatus', () => {
it('applies styleCss correctly', () => {
const { container } = render(Prev ,
})
- fireEvent.keyPress(screen.getByText(/prev/i), { key: 'Enter', charCode: 13 })
+ fireEvent.keyDown(screen.getByText(/prev/i).closest('button')!, { key: 'Enter', code: 'Enter', keyCode: 13, which: 13 })
expect(setCurrentPage).toHaveBeenCalledWith(2)
})
@@ -142,7 +142,7 @@ describe('Pagination', () => {
setCurrentPage,
children: Prev ,
})
- fireEvent.keyPress(screen.getByText(/prev/i), { key: 'Enter', charCode: 13 })
+ fireEvent.keyDown(screen.getByText(/prev/i).closest('button')!, { key: 'Enter', code: 'Enter', keyCode: 13, which: 13 })
expect(setCurrentPage).not.toHaveBeenCalled()
})
@@ -213,7 +213,7 @@ describe('Pagination', () => {
setCurrentPage,
children: Next ,
})
- fireEvent.keyPress(screen.getByText(/next/i), { key: 'Enter', charCode: 13 })
+ fireEvent.keyDown(screen.getByText(/next/i).closest('button')!, { key: 'Enter', code: 'Enter', keyCode: 13, which: 13 })
expect(setCurrentPage).toHaveBeenCalledWith(1)
})
@@ -225,7 +225,7 @@ describe('Pagination', () => {
setCurrentPage,
children: Next ,
})
- fireEvent.keyPress(screen.getByText(/next/i), { key: 'Enter', charCode: 13 })
+ fireEvent.keyDown(screen.getByText(/next/i).closest('button')!, { key: 'Enter', code: 'Enter', keyCode: 13, which: 13 })
expect(setCurrentPage).not.toHaveBeenCalled()
})
@@ -318,7 +318,7 @@ describe('Pagination', () => {
/>
),
})
- fireEvent.keyPress(screen.getByText('4'), { key: 'Enter', charCode: 13 })
+ fireEvent.keyDown(screen.getByText('4').closest('a')!, { key: 'Enter', code: 'Enter', keyCode: 13, which: 13 })
expect(setCurrentPage).toHaveBeenCalledWith(3) // 0-indexed
})
diff --git a/web/app/components/base/pagination/pagination.tsx b/web/app/components/base/pagination/pagination.tsx
index 0eb06b594c7..b258090d80d 100644
--- a/web/app/components/base/pagination/pagination.tsx
+++ b/web/app/components/base/pagination/pagination.tsx
@@ -50,7 +50,7 @@ export const PrevButton = ({
tabIndex={disabled ? '-1' : 0}
disabled={disabled}
data-testid={dataTestId}
- onKeyPress={(event: React.KeyboardEvent) => {
+ onKeyDown={(event: React.KeyboardEvent) => {
event.preventDefault()
if (event.key === 'Enter' && !disabled)
previous()
@@ -85,7 +85,7 @@ export const NextButton = ({
tabIndex={disabled ? '-1' : 0}
disabled={disabled}
data-testid={dataTestId}
- onKeyPress={(event: React.KeyboardEvent) => {
+ onKeyDown={(event: React.KeyboardEvent) => {
event.preventDefault()
if (event.key === 'Enter' && !disabled)
next()
@@ -140,7 +140,7 @@ export const PageButton = ({
}) || undefined
}
tabIndex={0}
- onKeyPress={(event: React.KeyboardEvent) => {
+ onKeyDown={(event: React.KeyboardEvent) => {
if (event.key === 'Enter')
pagination.setCurrentPage(page - 1)
}}
diff --git a/web/app/components/base/param-item/__tests__/index-slider.spec.tsx b/web/app/components/base/param-item/__tests__/index-slider.spec.tsx
index 0048b896442..64488358449 100644
--- a/web/app/components/base/param-item/__tests__/index-slider.spec.tsx
+++ b/web/app/components/base/param-item/__tests__/index-slider.spec.tsx
@@ -14,12 +14,14 @@ describe('ParamItem Slider onChange', () => {
vi.clearAllMocks()
})
+ const getSlider = () => screen.getByLabelText('Test Param')
+
it('should divide slider value by 100 when max < 5', async () => {
const user = userEvent.setup()
render( = ({ className, id, name, noTooltip, tip, step = 0.1,
value={max < 5 ? value * 100 : value}
min={min < 1 ? min * 100 : min}
max={max < 5 ? max * 100 : max}
- onChange={value => onChange(id, value / (max < 5 ? 100 : 1))}
+ onValueChange={value => onChange(id, value / (max < 5 ? 100 : 1))}
+ aria-label={name}
/>
{PrimitiveCode}
,
@@ -74,15 +121,17 @@ const findEchartsHost = async () => {
const findEchartsInstance = async () => {
const host = await findEchartsHost()
await waitFor(() => {
- expect(echartsCjs.getInstanceByDom(host)).toBeTruthy()
+ expect(echarts.getInstanceByDom(host)).toBeTruthy()
})
- return echartsCjs.getInstanceByDom(host)!
+ return echarts.getInstanceByDom(host)!
}
describe('CodeBlock', () => {
beforeEach(() => {
vi.clearAllMocks()
mockUseTheme.mockReturnValue({ theme: Theme.light })
+ consoleErrorSpy = vi.spyOn(console, 'error').mockImplementation(() => {})
+ consoleWarnSpy = vi.spyOn(console, 'warn').mockImplementation(() => {})
clientWidthSpy = vi.spyOn(HTMLElement.prototype, 'clientWidth', 'get').mockReturnValue(900)
clientHeightSpy = vi.spyOn(HTMLElement.prototype, 'clientHeight', 'get').mockReturnValue(400)
offsetWidthSpy = vi.spyOn(HTMLElement.prototype, 'offsetWidth', 'get').mockReturnValue(900)
@@ -98,6 +147,10 @@ describe('CodeBlock', () => {
afterEach(() => {
vi.useRealTimers()
+ consoleErrorSpy?.mockRestore()
+ consoleWarnSpy?.mockRestore()
+ consoleErrorSpy = null
+ consoleWarnSpy = null
clientWidthSpy?.mockRestore()
clientHeightSpy?.mockRestore()
offsetWidthSpy?.mockRestore()
diff --git a/web/app/components/base/markdown-blocks/__tests__/think-block.spec.tsx b/web/app/components/base/markdown-blocks/__tests__/think-block.spec.tsx
index e8b956cbbfd..4f224681575 100644
--- a/web/app/components/base/markdown-blocks/__tests__/think-block.spec.tsx
+++ b/web/app/components/base/markdown-blocks/__tests__/think-block.spec.tsx
@@ -163,25 +163,16 @@ describe('ThinkBlock', () => {
expect(screen.getByText(/Thought/)).toBeInTheDocument()
})
- it('should NOT stop timer when isResponding is undefined (outside ChatContextProvider)', () => {
- // Render without ChatContextProvider
+ it('should stop timer when isResponding is undefined (historical conversation outside active response)', () => {
+ // Render without ChatContextProvider — simulates historical conversation
render(
Content without ENDTHINKFLAG
- {
- setValue(v)
- console.log('Slider value:', v)
- }}
- />
-
- )
-}
-
-// Default state
-export const Default: Story = {
- render: args =>
- Value:
- {' '}
- {value}
-
-
-
- )
-}
-
-export const VolumeControl: Story = {
- render: () =>
-
- Volume Control
- {getVolumeIcon(volume)} -
- Mute
-
- {volume}
- %
-
- Max
-
-
-
- )
-}
-
-export const BrightnessControl: Story = {
- render: () =>
-
- Screen Brightness
- ☀️ -
-
-
- Preview at
- {' '}
- {brightness}
- % brightness
-
-
-
- )
-}
-
-export const PriceRangeFilter: Story = {
- render: () => Filter by Price
-
-
-
- Maximum Price
-
- $
- {maxPrice}
-
-
-
-
-
- Showing
- {' '}
- {filteredProducts.length}
- {' '}
- of
- {' '}
- {products.length}
- {' '}
- products
-
-
- {filteredProducts.map(product => (
-
-
- {product.name}
-
- $
- {product.price}
-
-
- ))}
-
-
- )
-}
-
-export const TemperatureSelector: Story = {
- render: () => Thermostat Control
-
-
-
-
-
-
- Celsius
-
- {temperature}
- °C
-
-
-
- Fahrenheit
-
- {fahrenheit}
- °F
-
-
- {temperature < 18 && '🥶 Too cold'}
- {temperature >= 18 && temperature <= 24 && '😊 Comfortable'}
- {temperature > 24 && '🥵 Too warm'}
-
-
-
- )
-}
-
-export const ProgressSlider: Story = {
- render: () => Project Completion
-
-
-
- Progress
-
- {progress}
- %
-
-
-
-
-
- = 25 ? '✅' : '⏳'}>Planning
- 25%
-
-
- = 50 ? '✅' : '⏳'}>Development
- 50%
-
-
- = 75 ? '✅' : '⏳'}>Testing
- 75%
-
-
- = 100 ? '✅' : '⏳'}>Deployment
- 100%
-
-
-
- )
-}
-
-export const ZoomControl: Story = {
- render: () => Zoom Level
-
-
-
-
-
-
-
- 50%
-
- {zoom}
- %
-
- 200%
-
-
-
- Preview content
-
-
- )
-}
-
-export const AIModelParameters: Story = {
- render: () => Model Configuration
-
-
-
-
-
-
-
- {temperature}
-
- - Controls randomness. Lower is more focused, higher is more creative. -
-
-
-
-
-
- {maxTokens}
-
- - Maximum length of generated response. -
-
-
-
-
- {topP}
-
- - Nucleus sampling threshold. -
-
-
-
- Temperature:
- {' '}
- {temperature}
-
-
- Max Tokens:
- {' '}
- {maxTokens}
-
-
- Top P:
- {' '}
- {topP}
-
-
-
- )
-}
-
-export const ImageQualitySelector: Story = {
- render: () => Image Export Quality
-
-
-
-
- Quality
- {getQualityLabel(quality)}
-
- {quality}
- %
-
-
-
- File Size
-
- ~
- {estimatedSize}
- {' '}
- MB
-
- Estimated
-
-
- )
-}
-
-export const MultipleSliders: Story = {
- render: () => RGB Color Picker
-
-
-
-
-
-
- {red}
-
-
-
-
-
- {green}
-
-
-
-
-
- {blue}
-
-
-
-
-
-
- Color Value
- {rgbColor}
-
- #
- {red.toString(16).padStart(2, '0')}
- {green.toString(16).padStart(2, '0')}
- {blue.toString(16).padStart(2, '0')}
-
-
- setOpen(v => !v)}
- className="block"
- >
-
+
+export default meta
+
+type Story = StoryObj
+
+function SliderDemo({
+ value: initialValue = 50,
+ defaultValue: _defaultValue,
+ ...args
+}: React.ComponentProps) {
+ const [value, setValue] = useState(initialValue)
+
+ return (
+
+type SliderThumbProps = BaseSlider.Thumb.Props
+
+type SliderBaseProps = Pick<
+ SliderRootProps,
+ 'onValueChange' | 'min' | 'max' | 'step' | 'disabled' | 'name'
+> & Pick & {
+ className?: string
+}
+
+type ControlledSliderProps = SliderBaseProps & {
+ value: number
+ defaultValue?: never
+}
+
+type UncontrolledSliderProps = SliderBaseProps & {
+ value?: never
+ defaultValue?: number
+}
+
+export type SliderProps = ControlledSliderProps | UncontrolledSliderProps
+
+const sliderRootClassName = 'group/slider relative inline-flex w-full data-[disabled]:opacity-30'
+const sliderControlClassName = cn(
+ 'relative flex h-5 w-full touch-none select-none items-center',
+ 'data-[disabled]:cursor-not-allowed',
+)
+const sliderTrackClassName = cn(
+ 'relative h-1 w-full overflow-hidden rounded-full',
+ 'bg-[var(--slider-track,var(--color-components-slider-track))]',
+)
+const sliderIndicatorClassName = cn(
+ 'h-full rounded-full',
+ 'bg-[var(--slider-range,var(--color-components-slider-range))]',
+)
+const sliderThumbClassName = cn(
+ 'block h-5 w-2 shrink-0 rounded-[3px] border-[0.5px]',
+ 'border-[var(--slider-knob-border,var(--color-components-slider-knob-border))]',
+ 'bg-[var(--slider-knob,var(--color-components-slider-knob))] shadow-sm',
+ 'transition-[background-color,border-color,box-shadow,opacity] motion-reduce:transition-none',
+ 'hover:bg-[var(--slider-knob-hover,var(--color-components-slider-knob-hover))]',
+ 'focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-components-slider-knob-border-hover focus-visible:ring-offset-0',
+ 'active:shadow-md',
+ 'group-data-[disabled]/slider:bg-[var(--slider-knob-disabled,var(--color-components-slider-knob-disabled))]',
+ 'group-data-[disabled]/slider:border-[var(--slider-knob-border,var(--color-components-slider-knob-border))]',
+ 'group-data-[disabled]/slider:shadow-none',
+)
+
+const getSafeValue = (value: number | undefined, min: number) => {
+ if (value === undefined)
+ return undefined
+
+ return Number.isFinite(value) ? value : min
+}
+
+export function Slider({
+ value,
+ defaultValue,
+ onValueChange,
+ min = 0,
+ max = 100,
+ step = 1,
+ disabled = false,
+ name,
+ className,
+ 'aria-label': ariaLabel,
+ 'aria-labelledby': ariaLabelledby,
+}: SliderProps) {
+ return (
+
+
+
+
+
+
+ )
+}
diff --git a/web/app/components/base/ui/toast/__tests__/index.spec.tsx b/web/app/components/base/ui/toast/__tests__/index.spec.tsx
index 75364117c3f..db6d86719a3 100644
--- a/web/app/components/base/ui/toast/__tests__/index.spec.tsx
+++ b/web/app/components/base/ui/toast/__tests__/index.spec.tsx
@@ -7,27 +7,25 @@ describe('base/ui/toast', () => {
vi.clearAllMocks()
vi.useFakeTimers({ shouldAdvanceTime: true })
act(() => {
- toast.close()
+ toast.dismiss()
})
})
afterEach(() => {
act(() => {
- toast.close()
+ toast.dismiss()
vi.runOnlyPendingTimers()
})
vi.useRealTimers()
})
// Core host and manager integration.
- it('should render a toast when add is called', async () => {
+ it('should render a success toast when called through the typed shortcut', async () => {
render(, 'dat
type?: ToastType
}
+export type ToastOptions = Omit
+export type TypedToastOptions = Omit
+
type ToastPromiseResultOption = string | ToastUpdateOptions | ((value: Value) => string | ToastUpdateOptions)
export type ToastPromiseOptions = {
@@ -57,6 +61,21 @@ export type ToastHostProps = {
limit?: number
}
+type ToastDismiss = (toastId?: string) => void
+type ToastCall = (title: ReactNode, options?: ToastOptions) => string
+type TypedToastCall = (title: ReactNode, options?: TypedToastOptions) => string
+
+export type ToastApi = {
+ (title: ReactNode, options?: ToastOptions): string
+ success: TypedToastCall
+ error: TypedToastCall
+ warning: TypedToastCall
+ info: TypedToastCall
+ dismiss: ToastDismiss
+ update: (toastId: string, options: ToastUpdateOptions) => void
+ promise: (promiseValue: Promise, options: ToastPromiseOptions) => Promise
+}
+
const toastManager = BaseToast.createToastManager()
function isToastType(type: string): type is ToastType {
@@ -67,21 +86,48 @@ function getToastType(type?: string): ToastType | undefined {
return type && isToastType(type) ? type : undefined
}
-export const toast = {
- add(options: ToastAddOptions) {
- return toastManager.add(options)
- },
- close(toastId?: string) {
- toastManager.close(toastId)
- },
- update(toastId: string, options: ToastUpdateOptions) {
- toastManager.update(toastId, options)
- },
- promise(promiseValue: Promise, options: ToastPromiseOptions) {
- return toastManager.promise(promiseValue, options)
- },
+function addToast(options: ToastAddOptions) {
+ return toastManager.add(options)
}
+const showToast: ToastCall = (title, options) => addToast({
+ ...options,
+ title,
+})
+
+const dismissToast: ToastDismiss = (toastId) => {
+ toastManager.close(toastId)
+}
+
+function createTypedToast(type: ToastType): TypedToastCall {
+ return (title, options) => addToast({
+ ...options,
+ title,
+ type,
+ })
+}
+
+function updateToast(toastId: string, options: ToastUpdateOptions) {
+ toastManager.update(toastId, options)
+}
+
+function promiseToast(promiseValue: Promise, options: ToastPromiseOptions) {
+ return toastManager.promise(promiseValue, options)
+}
+
+export const toast: ToastApi = Object.assign(
+ showToast,
+ {
+ success: createTypedToast('success'),
+ error: createTypedToast('error'),
+ warning: createTypedToast('warning'),
+ info: createTypedToast('info'),
+ dismiss: dismissToast,
+ update: updateToast,
+ promise: promiseToast,
+ },
+)
+
function ToastIcon({ type }: { type?: ToastType }) {
return type
?
diff --git a/web/app/components/billing/partner-stack/__tests__/cookie-recorder.spec.tsx b/web/app/components/billing/partner-stack/__tests__/cookie-recorder.spec.tsx
new file mode 100644
index 00000000000..1441653c9ce
--- /dev/null
+++ b/web/app/components/billing/partner-stack/__tests__/cookie-recorder.spec.tsx
@@ -0,0 +1,45 @@
+import { render } from '@testing-library/react'
+import PartnerStackCookieRecorder from '../cookie-recorder'
+
+let isCloudEdition = true
+
+const saveOrUpdate = vi.fn()
+
+vi.mock('@/config', () => ({
+ get IS_CLOUD_EDITION() {
+ return isCloudEdition
+ },
+}))
+
+vi.mock('../use-ps-info', () => ({
+ default: () => ({
+ saveOrUpdate,
+ }),
+}))
+
+describe('PartnerStackCookieRecorder', () => {
+ beforeEach(() => {
+ vi.clearAllMocks()
+ isCloudEdition = true
+ })
+
+ it('should call saveOrUpdate once on mount when running in cloud edition', () => {
+ render(
-
-
+
-
+
)
}
diff --git a/web/app/components/base/ui/slider/__tests__/index.spec.tsx b/web/app/components/base/ui/slider/__tests__/index.spec.tsx
new file mode 100644
index 00000000000..f34de5010d3
--- /dev/null
+++ b/web/app/components/base/ui/slider/__tests__/index.spec.tsx
@@ -0,0 +1,73 @@
+import { act, render, screen } from '@testing-library/react'
+import userEvent from '@testing-library/user-event'
+import { describe, expect, it, vi } from 'vitest'
+import { Slider } from '../index'
+
+describe('Slider', () => {
+ const getSliderInput = () => screen.getByLabelText('Value')
+
+ it('should render with correct default ARIA limits and current value', () => {
+ render(
-
-
- {!value.length && t('tag.placeholder', { ns: 'common' })}
- {!!value.length && currentTag?.name}
-
- {value.length > 1 && (
- {`+${value.length - 1}`}
- )}
- {!value.length && (
+
-
+
- )}
- {!!value.length && (
- {
- e.stopPropagation()
- onChange([])
- }}
- data-testid="tag-filter-clear-button"
- >
-
+
-
-
+ {!value.length && t('tag.placeholder', { ns: 'common' })}
+ {!!value.length && currentTag?.name}
- )}
-
+ {value.length > 1 && (
+
+
- {`+${value.length - 1}`}
+ )}
+ {!value.length && (
+
+
+
+ )}
+
+ )}
+ />
+ {!!value.length && (
+
+ )}
+
handleKeywordsChange(e.target.value)}
- onClear={() => handleKeywordsChange('')}
+ onChange={e => setKeywords(e.target.value)}
+ onClear={() => setKeywords('')}
/>
@@ -155,9 +147,9 @@ const TagFilter: FC = ({
+
+ )
+}
+
+export const Default: Story = {
+ render: args =>
+ {value}
+
+
-
+
-
{t('plansCommon.title.plans', { ns: 'billing' })}
-
+
-
+