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Code Issues Packages Projects Releases Wiki Activity

feat: server multi models support (#799)

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takatost
2023-08-12 00:57:00 +08:00
committed by GitHub
parent d8b712b325
commit 5fa2161b05
213 changed files with 10556 additions and 2579 deletions
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36
api/core/agent/agent_executor.py
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@@ -3,7 +3,6 @@ import logging
from typing import Union, Optional
from langchain.agents import BaseSingleActionAgent, BaseMultiActionAgent
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.manager import Callbacks
from langchain.memory.chat_memory import BaseChatMemory
from langchain.tools import BaseTool
@@ -13,14 +12,17 @@ from core.agent.agent.multi_dataset_router_agent import MultiDatasetRouterAgent
from core.agent.agent.openai_function_call import AutoSummarizingOpenAIFunctionCallAgent
from core.agent.agent.openai_multi_function_call import AutoSummarizingOpenMultiAIFunctionCallAgent
from core.agent.agent.output_parser.structured_chat import StructuredChatOutputParser
from core.agent.agent.structed_multi_dataset_router_agent import StructuredMultiDatasetRouterAgent
from core.agent.agent.structured_chat import AutoSummarizingStructuredChatAgent
from langchain.agents import AgentExecutor as LCAgentExecutor
from core.model_providers.models.llm.base import BaseLLM
from core.tool.dataset_retriever_tool import DatasetRetrieverTool
class PlanningStrategy(str, enum.Enum):
ROUTER = 'router'
REACT_ROUTER = 'react_router'
REACT = 'react'
FUNCTION_CALL = 'function_call'
MULTI_FUNCTION_CALL = 'multi_function_call'
@@ -28,10 +30,9 @@ class PlanningStrategy(str, enum.Enum):
class AgentConfiguration(BaseModel):
strategy: PlanningStrategy
llm: BaseLanguageModel
model_instance: BaseLLM
tools: list[BaseTool]
summary_llm: BaseLanguageModel
dataset_llm: BaseLanguageModel
summary_model_instance: BaseLLM
memory: Optional[BaseChatMemory] = None
callbacks: Callbacks = None
max_iterations: int = 6
@@ -60,36 +61,49 @@ class AgentExecutor:
def _init_agent(self) -> Union[BaseSingleActionAgent | BaseMultiActionAgent]:
if self.configuration.strategy == PlanningStrategy.REACT:
agent = AutoSummarizingStructuredChatAgent.from_llm_and_tools(
llm=self.configuration.llm,
model_instance=self.configuration.model_instance,
llm=self.configuration.model_instance.client,
tools=self.configuration.tools,
output_parser=StructuredChatOutputParser(),
summary_llm=self.configuration.summary_llm,
summary_llm=self.configuration.summary_model_instance.client,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.FUNCTION_CALL:
agent = AutoSummarizingOpenAIFunctionCallAgent.from_llm_and_tools(
llm=self.configuration.llm,
model_instance=self.configuration.model_instance,
llm=self.configuration.model_instance.client,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None, # used for read chat histories memory
summary_llm=self.configuration.summary_llm,
summary_llm=self.configuration.summary_model_instance.client,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.MULTI_FUNCTION_CALL:
agent = AutoSummarizingOpenMultiAIFunctionCallAgent.from_llm_and_tools(
llm=self.configuration.llm,
model_instance=self.configuration.model_instance,
llm=self.configuration.model_instance.client,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None, # used for read chat histories memory
summary_llm=self.configuration.summary_llm,
summary_llm=self.configuration.summary_model_instance.client,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.ROUTER:
self.configuration.tools = [t for t in self.configuration.tools if isinstance(t, DatasetRetrieverTool)]
agent = MultiDatasetRouterAgent.from_llm_and_tools(
llm=self.configuration.dataset_llm,
model_instance=self.configuration.model_instance,
llm=self.configuration.model_instance.client,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.REACT_ROUTER:
self.configuration.tools = [t for t in self.configuration.tools if isinstance(t, DatasetRetrieverTool)]
agent = StructuredMultiDatasetRouterAgent.from_llm_and_tools(
model_instance=self.configuration.model_instance,
llm=self.configuration.model_instance.client,
tools=self.configuration.tools,
output_parser=StructuredChatOutputParser(),
verbose=True
)
else:
raise NotImplementedError(f"Unknown Agent Strategy: {self.configuration.strategy}")