upgrade Unstructured version

Co-authored-by: 刘江波 <jiangbo721@163.com>

.github/actions/setup-poetry/action.yml

@@ -8,7 +8,7 @@ inputs:
   poetry-version:
     description: Poetry version to set up
     required: true
-    default: '1.8.4'
+    default: '2.0.1'
   poetry-lockfile:
     description: Path to the Poetry lockfile to restore cache from
     required: true

.github/workflows/api-tests.yml

@@ -26,6 +26,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Setup Poetry and Python ${{ matrix.python-version }}
         uses: ./.github/actions/setup-poetry
@@ -42,25 +45,23 @@ jobs:
         run: poetry install -C api --with dev
 
       - name: Check dependencies in pyproject.toml
-        run: poetry run -C api bash dev/pytest/pytest_artifacts.sh
+        run: poetry run -P api bash dev/pytest/pytest_artifacts.sh
 
       - name: Run Unit tests
-        run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
+        run: poetry run -P api bash dev/pytest/pytest_unit_tests.sh
 
       - name: Run ModelRuntime
-        run: poetry run -C api bash dev/pytest/pytest_model_runtime.sh
+        run: poetry run -P api bash dev/pytest/pytest_model_runtime.sh
 
       - name: Run dify config tests
-        run: poetry run -C api python dev/pytest/pytest_config_tests.py
+        run: poetry run -P api python dev/pytest/pytest_config_tests.py
 
       - name: Run Tool
-        run: poetry run -C api bash dev/pytest/pytest_tools.sh
+        run: poetry run -P api bash dev/pytest/pytest_tools.sh
 
       - name: Run mypy
         run: |
-          pushd api
-          poetry run python -m mypy --install-types --non-interactive .
-          popd
+          poetry run -C api python -m mypy --install-types --non-interactive .
 
       - name: Set up dotenvs
         run: |
@@ -80,4 +81,4 @@ jobs:
             ssrf_proxy
 
       - name: Run Workflow
-        run: poetry run -C api bash dev/pytest/pytest_workflow.sh
+        run: poetry run -P api bash dev/pytest/pytest_workflow.sh

.github/workflows/build-push.yml

@@ -79,10 +79,12 @@ jobs:
           cache-to: type=gha,mode=max,scope=${{ matrix.service_name }}
 
       - name: Export digest
+        env:
+          DIGEST: ${{ steps.build.outputs.digest }}
         run: |
           mkdir -p /tmp/digests
-          digest="${{ steps.build.outputs.digest }}"
-          touch "/tmp/digests/${digest#sha256:}"
+          sanitized_digest=${DIGEST#sha256:}
+          touch "/tmp/digests/${sanitized_digest}"
 
       - name: Upload digest
         uses: actions/upload-artifact@v4
@@ -132,10 +134,15 @@ jobs:
 
       - name: Create manifest list and push
         working-directory: /tmp/digests
+        env:
+          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
         run: |
           docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
-            $(printf '${{ env[matrix.image_name_env] }}@sha256:%s ' *)
+            $(printf "$IMAGE_NAME@sha256:%s " *)
 
       - name: Inspect image
+        env:
+          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
+          IMAGE_VERSION: ${{ steps.meta.outputs.version }}
         run: |
-          docker buildx imagetools inspect ${{ env[matrix.image_name_env] }}:${{ steps.meta.outputs.version }}
+          docker buildx imagetools inspect "$IMAGE_NAME:$IMAGE_VERSION"

.github/workflows/db-migration-test.yml

@@ -19,6 +19,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Setup Poetry and Python
         uses: ./.github/actions/setup-poetry

.github/workflows/docker-build.yml

@@ -0,0 +1,47 @@
+name: Build docker image
+
+on:
+  pull_request:
+    branches:
+      - "main"
+    paths:
+      - api/Dockerfile
+      - web/Dockerfile
+
+concurrency:
+  group: docker-build-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  build-docker:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        include:
+          - service_name: "api-amd64"
+            platform: linux/amd64
+            context: "api"
+          - service_name: "api-arm64"
+            platform: linux/arm64
+            context: "api"
+          - service_name: "web-amd64"
+            platform: linux/amd64
+            context: "web"
+          - service_name: "web-arm64"
+            platform: linux/arm64
+            context: "web"
+    steps:
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Build Docker Image
+        uses: docker/build-push-action@v6
+        with:
+          push: false
+          context: "{{defaultContext}}:${{ matrix.context }}"
+          platforms: ${{ matrix.platform }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max

.github/workflows/expose_service_ports.sh

@@ -9,6 +9,6 @@ yq eval '.services["pgvecto-rs"].ports += ["5431:5432"]' -i docker/docker-compos
 yq eval '.services["elasticsearch"].ports += ["9200:9200"]' -i docker/docker-compose.yaml
 yq eval '.services.couchbase-server.ports += ["8091-8096:8091-8096"]' -i docker/docker-compose.yaml
 yq eval '.services.couchbase-server.ports += ["11210:11210"]' -i docker/docker-compose.yaml
-yq eval '.services.tidb.ports += ["4000:4000"]' -i docker/docker-compose.yaml
+yq eval '.services.tidb.ports += ["4000:4000"]' -i docker/tidb/docker-compose.yaml
 
 echo "Ports exposed for sandbox, weaviate, tidb, qdrant, chroma, milvus, pgvector, pgvecto-rs, elasticsearch, couchbase"

.github/workflows/style.yml

@@ -17,6 +17,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -38,12 +41,12 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         run: |
           poetry run -C api ruff --version
-          poetry run -C api ruff check ./api
-          poetry run -C api ruff format --check ./api
+          poetry run -C api ruff check ./
+          poetry run -C api ruff format --check ./
 
       - name: Dotenv check
         if: steps.changed-files.outputs.any_changed == 'true'
-        run: poetry run -C api dotenv-linter ./api/.env.example ./web/.env.example
+        run: poetry run -P api dotenv-linter ./api/.env.example ./web/.env.example
 
       - name: Lint hints
         if: failure()
@@ -59,6 +62,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -82,6 +88,36 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         run: yarn run lint
 
+  docker-compose-template:
+    name: Docker Compose Template
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
+
+      - name: Check changed files
+        id: changed-files
+        uses: tj-actions/changed-files@v45
+        with:
+          files: |
+            docker/generate_docker_compose
+            docker/.env.example
+            docker/docker-compose-template.yaml
+            docker/docker-compose.yaml
+
+      - name: Generate Docker Compose
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: |
+          cd docker
+          ./generate_docker_compose
+
+      - name: Check for changes
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: git diff --exit-code
 
   superlinter:
     name: SuperLinter
@@ -90,6 +126,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Check changed files
         id: changed-files

.github/workflows/tool-test-sdks.yaml

@@ -26,6 +26,9 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Use Node.js ${{ matrix.node-version }}
         uses: actions/setup-node@v4

.github/workflows/translate-i18n-base-on-english.yml

@@ -16,6 +16,7 @@ jobs:
       - uses: actions/checkout@v4
         with:
           fetch-depth: 2 # last 2 commits
+          persist-credentials: false
 
       - name: Check for file changes in i18n/en-US
         id: check_files

.github/workflows/vdb-tests.yml

@@ -28,6 +28,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Setup Poetry and Python ${{ matrix.python-version }}
         uses: ./.github/actions/setup-poetry
@@ -51,7 +54,15 @@ jobs:
       - name: Expose Service Ports
         run: sh .github/workflows/expose_service_ports.sh
 
-      - name: Set up Vector Stores (TiDB, Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale, ElasticSearch, Couchbase)
+      - name: Set up Vector Store (TiDB)
+        uses: hoverkraft-tech/compose-action@v2.0.2
+        with:
+          compose-file: docker/tidb/docker-compose.yaml
+          services: |
+            tidb
+            tiflash
+
+      - name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale, ElasticSearch, Couchbase)
         uses: hoverkraft-tech/compose-action@v2.0.2
         with:
           compose-file: |
@@ -67,7 +78,9 @@ jobs:
             pgvector
             chroma
             elasticsearch
-            tidb
+
+      - name: Check TiDB Ready
+        run: poetry run -P api python api/tests/integration_tests/vdb/tidb_vector/check_tiflash_ready.py
 
       - name: Test Vector Stores
-        run: poetry run -C api bash dev/pytest/pytest_vdb.sh
+        run: poetry run -P api bash dev/pytest/pytest_vdb.sh

.github/workflows/web-tests.yml

@@ -22,6 +22,9 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
 
       - name: Check changed files
         id: changed-files

.gitignore

@@ -163,6 +163,7 @@ docker/volumes/db/data/*
 docker/volumes/redis/data/*
 docker/volumes/weaviate/*
 docker/volumes/qdrant/*
+docker/tidb/volumes/*
 docker/volumes/etcd/*
 docker/volumes/minio/*
 docker/volumes/milvus/*

README.md

@@ -25,6 +25,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -105,6 +108,72 @@ Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-host
 **7. Backend-as-a-Service**: 
   All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.
 
+## Feature Comparison
+<table style="width: 100%;">
+  <tr>
+    <th align="center">Feature</th>
+    <th align="center">Dify.AI</th>
+    <th align="center">LangChain</th>
+    <th align="center">Flowise</th>
+    <th align="center">OpenAI Assistants API</th>
+  </tr>
+  <tr>
+    <td align="center">Programming Approach</td>
+    <td align="center">API + App-oriented</td>
+    <td align="center">Python Code</td>
+    <td align="center">App-oriented</td>
+    <td align="center">API-oriented</td>
+  </tr>
+  <tr>
+    <td align="center">Supported LLMs</td>
+    <td align="center">Rich Variety</td>
+    <td align="center">Rich Variety</td>
+    <td align="center">Rich Variety</td>
+    <td align="center">OpenAI-only</td>
+  </tr>
+  <tr>
+    <td align="center">RAG Engine</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Agent</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Workflow</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Observability</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Enterprise Feature (SSO/Access control)</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Local Deployment</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+</table>
 
 ## Using Dify
 

README_AR.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_CN.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_ES.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="seguir en X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="seguir en LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Descargas de Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_FR.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="suivre sur X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="suivre sur LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Tirages Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_JA.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="X(Twitter)でフォロー"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="LinkedInでフォロー"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_KL.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -84,9 +87,7 @@ Dify is an open-source LLM app development platform. Its intuitive interface com
 
 ## Feature Comparison
 <table style="width: 100%;">
-  <tr
-
->
+  <tr>
     <th align="center">Feature</th>
     <th align="center">Dify.AI</th>
     <th align="center">LangChain</th>

README_KR.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_PT.md

@@ -25,6 +25,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

README_SI.md

@@ -22,6 +22,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="follow on LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -103,6 +106,73 @@ Prosimo, glejte naša pogosta vprašanja [FAQ](https://docs.dify.ai/getting-star
 **7. Backend-as-a-Service**: 
   AVse ponudbe Difyja so opremljene z ustreznimi API-ji, tako da lahko Dify brez težav integrirate v svojo poslovno logiko.
 
+## Primerjava Funkcij
+
+<table style="width: 100%;">
+  <tr>
+    <th align="center">Funkcija</th>
+    <th align="center">Dify.AI</th>
+    <th align="center">LangChain</th>
+    <th align="center">Flowise</th>
+    <th align="center">OpenAI Assistants API</th>
+  </tr>
+  <tr>
+    <td align="center">Programski pristop</td>
+    <td align="center">API + usmerjeno v aplikacije</td>
+    <td align="center">Python koda</td>
+    <td align="center">Usmerjeno v aplikacije</td>
+    <td align="center">Usmerjeno v API</td>
+  </tr>
+  <tr>
+    <td align="center">Podprti LLM-ji</td>
+    <td align="center">Bogata izbira</td>
+    <td align="center">Bogata izbira</td>
+    <td align="center">Bogata izbira</td>
+    <td align="center">Samo OpenAI</td>
+  </tr>
+  <tr>
+    <td align="center">RAG pogon</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Agent</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Potek dela</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Spremljanje</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Funkcija za podjetja (SSO/nadzor dostopa)</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Lokalna namestitev</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+</table>
 
 ## Uporaba Dify
 
@@ -184,4 +254,4 @@ Zaradi zaščite vaše zasebnosti se izogibajte objavljanju varnostnih vprašanj
 
 ## Licenca
 
-To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.
+To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.

README_TR.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="X(Twitter)'da takip et"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="LinkedIn'da takip et"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Çekmeleri" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -62,8 +65,6 @@ Görsel bir arayüz üzerinde güçlü AI iş akışları oluşturun ve test edi
 ![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
 
 
-Özür dilerim, haklısınız. Daha anlamlı ve akıcı bir çeviri yapmaya çalışayım. İşte güncellenmiş çeviri:
-
 **3. Prompt IDE**: 
   Komut istemlerini oluşturmak, model performansını karşılaştırmak ve sohbet tabanlı uygulamalara metin-konuşma gibi ek özellikler eklemek için kullanıcı dostu bir arayüz.
 
@@ -150,8 +151,6 @@ Görsel bir arayüz üzerinde güçlü AI iş akışları oluşturun ve test edi
 ## Dify'ı Kullanma
 
 - **Cloud </br>**
-İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
-- 
 Herkesin sıfır kurulumla denemesi için bir [Dify Cloud](https://dify.ai) hizmeti sunuyoruz. Bu hizmet, kendi kendine dağıtılan versiyonun tüm yeteneklerini sağlar ve sandbox planında 200 ücretsiz GPT-4 çağrısı içerir.
 
 - **Dify Topluluk Sürümünü Kendi Sunucunuzda Barındırma</br>**
@@ -177,8 +176,6 @@ GitHub'da Dify'a yıldız verin ve yeni sürümlerden anında haberdar olun.
 >- RAM >= 4GB
 
 </br>
-İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
-
 Dify sunucusunu başlatmanın en kolay yolu, [docker-compose.yml](docker/docker-compose.yaml) dosyamızı çalıştırmaktır. Kurulum komutunu çalıştırmadan önce, makinenizde [Docker](https://docs.docker.com/get-docker/) ve [Docker Compose](https://docs.docker.com/compose/install/)'un kurulu olduğundan emin olun:
 
 ```bash

README_VI.md

@@ -21,6 +21,9 @@
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="theo dõi trên X(Twitter)"></a>
+    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
+        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
+            alt="theo dõi trên LinkedIn"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">

api/.env.example

@@ -23,6 +23,9 @@ FILES_ACCESS_TIMEOUT=300
 # Access token expiration time in minutes
 ACCESS_TOKEN_EXPIRE_MINUTES=60
 
+# Refresh token expiration time in days
+REFRESH_TOKEN_EXPIRE_DAYS=30
+
 # celery configuration
 CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1
 

api/.ruff.toml

@@ -53,10 +53,12 @@ ignore = [
     "FURB152", # math-constant
     "UP007", # non-pep604-annotation
     "UP032", # f-string
+    "UP045", # non-pep604-annotation-optional
     "B005", # strip-with-multi-characters
     "B006", # mutable-argument-default
     "B007", # unused-loop-control-variable
     "B026", # star-arg-unpacking-after-keyword-arg
+    "B903", # class-as-data-structure
     "B904", # raise-without-from-inside-except
     "B905", # zip-without-explicit-strict
     "N806", # non-lowercase-variable-in-function

api/Dockerfile

@@ -4,7 +4,7 @@ FROM python:3.12-slim-bookworm AS base
 WORKDIR /app/api
 
 # Install Poetry
-ENV POETRY_VERSION=1.8.4
+ENV POETRY_VERSION=2.0.1
 
 # if you located in China, you can use aliyun mirror to speed up
 # RUN pip install --no-cache-dir poetry==${POETRY_VERSION} -i https://mirrors.aliyun.com/pypi/simple/
@@ -48,16 +48,18 @@ ENV TZ=UTC
 
 WORKDIR /app/api
 
-RUN apt-get update \
-    && apt-get install -y --no-install-recommends curl nodejs libgmp-dev libmpfr-dev libmpc-dev \
-    # if you located in China, you can use aliyun mirror to speed up
-    # && echo "deb http://mirrors.aliyun.com/debian testing main" > /etc/apt/sources.list \
-    && echo "deb http://deb.debian.org/debian testing main" > /etc/apt/sources.list \
-    && apt-get update \
-    # For Security
-    && apt-get install -y --no-install-recommends expat=2.6.4-1 libldap-2.5-0=2.5.19+dfsg-1 perl=5.40.0-8 libsqlite3-0=3.46.1-1 zlib1g=1:1.3.dfsg+really1.3.1-1+b1 \
-    # install a chinese font to support the use of tools like matplotlib
-    && apt-get install -y fonts-noto-cjk \
+RUN \
+    apt-get update \
+    # Install dependencies
+    && apt-get install -y --no-install-recommends \
+        # basic environment
+        curl nodejs libgmp-dev libmpfr-dev libmpc-dev \
+        # For Security
+        expat libldap-2.5-0 perl libsqlite3-0 zlib1g \
+        # install a chinese font to support the use of tools like matplotlib
+        fonts-noto-cjk \
+        # install libmagic to support the use of python-magic guess MIMETYPE
+        libmagic1 \
     && apt-get autoremove -y \
     && rm -rf /var/lib/apt/lists/*
 
@@ -76,7 +78,6 @@ COPY . /app/api/
 COPY docker/entrypoint.sh /entrypoint.sh
 RUN chmod +x /entrypoint.sh
 
-
 ARG COMMIT_SHA
 ENV COMMIT_SHA=${COMMIT_SHA}
 

api/README.md

@@ -37,7 +37,13 @@
 
 4. Create environment.
 
-   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. You can execute `poetry shell` to activate the environment.
+   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. First, you need to add the poetry shell plugin, if you don't have it already, in order to run in a virtual environment. [Note: Poetry shell is no longer a native command so you need to install the poetry plugin beforehand]
+
+   ```bash
+   poetry self add poetry-plugin-shell
+   ```
+   
+   Then, You can execute `poetry shell` to activate the environment.
 
 5. Install dependencies
 
@@ -79,5 +85,5 @@
 2. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`
 
    ```bash
-   poetry run -C api bash dev/pytest/pytest_all_tests.sh
+   poetry run -P api bash dev/pytest/pytest_all_tests.sh
    ```

api/app.py

@@ -1,12 +1,8 @@
-from libs import version_utils
-
-# preparation before creating app
-version_utils.check_supported_python_version()
+import os
+import sys
 
 
 def is_db_command():
-    import sys
-
     if len(sys.argv) > 1 and sys.argv[0].endswith("flask") and sys.argv[1] == "db":
         return True
     return False
@@ -18,10 +14,25 @@ if is_db_command():
 
     app = create_migrations_app()
 else:
-    from app_factory import create_app
-    from libs import threadings_utils
+    # It seems that JetBrains Python debugger does not work well with gevent,
+    # so we need to disable gevent in debug mode.
+    # If you are using debugpy and set GEVENT_SUPPORT=True, you can debug with gevent.
+    if (flask_debug := os.environ.get("FLASK_DEBUG", "0")) and flask_debug.lower() in {"false", "0", "no"}:
+        from gevent import monkey  # type: ignore
 
-    threadings_utils.apply_gevent_threading_patch()
+        # gevent
+        monkey.patch_all()
+
+        from grpc.experimental import gevent as grpc_gevent  # type: ignore
+
+        # grpc gevent
+        grpc_gevent.init_gevent()
+
+        import psycogreen.gevent  # type: ignore
+
+        psycogreen.gevent.patch_psycopg()
+
+    from app_factory import create_app
 
     app = create_app()
     celery = app.extensions["celery"]

api/configs/feature/__init__.py

@@ -146,7 +146,7 @@ class EndpointConfig(BaseSettings):
     )
 
     CONSOLE_WEB_URL: str = Field(
-        description="Base URL for the console web interface," "used for frontend references and CORS configuration",
+        description="Base URL for the console web interface,used for frontend references and CORS configuration",
         default="",
     )
 
@@ -315,8 +315,8 @@ class HttpConfig(BaseSettings):
     )
 
     RESPECT_XFORWARD_HEADERS_ENABLED: bool = Field(
-        description="Enable or disable the X-Forwarded-For Proxy Fix middleware from Werkzeug"
-        " to respect X-* headers to redirect clients",
+        description="Enable handling of X-Forwarded-For, X-Forwarded-Proto, and X-Forwarded-Port headers"
+        " when the app is behind a single trusted reverse proxy.",
         default=False,
     )
 
@@ -488,11 +488,21 @@ class AuthConfig(BaseSettings):
         default=60,
     )
 
+    REFRESH_TOKEN_EXPIRE_DAYS: PositiveFloat = Field(
+        description="Expiration time for refresh tokens in days",
+        default=30,
+    )
+
     LOGIN_LOCKOUT_DURATION: PositiveInt = Field(
         description="Time (in seconds) a user must wait before retrying login after exceeding the rate limit.",
         default=86400,
     )
 
+    FORGOT_PASSWORD_LOCKOUT_DURATION: PositiveInt = Field(
+        description="Time (in seconds) a user must wait before retrying password reset after exceeding the rate limit.",
+        default=86400,
+    )
+
 
 class ModerationConfig(BaseSettings):
     """
@@ -667,6 +677,11 @@ class IndexingConfig(BaseSettings):
         default=4000,
     )
 
+    CHILD_CHUNKS_PREVIEW_NUMBER: PositiveInt = Field(
+        description="Maximum number of child chunks to preview",
+        default=50,
+    )
+
 
 class MultiModalTransferConfig(BaseSettings):
     MULTIMODAL_SEND_FORMAT: Literal["base64", "url"] = Field(

api/configs/feature/hosted_service/__init__.py

@@ -1,9 +1,40 @@
 from typing import Optional
 
-from pydantic import Field, NonNegativeInt
+from pydantic import Field, NonNegativeInt, computed_field
 from pydantic_settings import BaseSettings
 
 
+class HostedCreditConfig(BaseSettings):
+    HOSTED_MODEL_CREDIT_CONFIG: str = Field(
+        description="Model credit configuration in format 'model:credits,model:credits', e.g., 'gpt-4:20,gpt-4o:10'",
+        default="",
+    )
+
+    def get_model_credits(self, model_name: str) -> int:
+        """
+        Get credit value for a specific model name.
+        Returns 1 if model is not found in configuration (default credit).
+
+        :param model_name: The name of the model to search for
+        :return: The credit value for the model
+        """
+        if not self.HOSTED_MODEL_CREDIT_CONFIG:
+            return 1
+
+        try:
+            credit_map = dict(
+                item.strip().split(":", 1) for item in self.HOSTED_MODEL_CREDIT_CONFIG.split(",") if ":" in item
+            )
+
+            # Search for matching model pattern
+            for pattern, credit in credit_map.items():
+                if pattern.strip() == model_name:
+                    return int(credit)
+            return 1  # Default quota if no match found
+        except (ValueError, AttributeError):
+            return 1  # Return default quota if parsing fails
+
+
 class HostedOpenAiConfig(BaseSettings):
     """
     Configuration for hosted OpenAI service
@@ -181,7 +212,7 @@ class HostedFetchAppTemplateConfig(BaseSettings):
     """
 
     HOSTED_FETCH_APP_TEMPLATES_MODE: str = Field(
-        description="Mode for fetching app templates: remote, db, or builtin" " default to remote,",
+        description="Mode for fetching app templates: remote, db, or builtin default to remote,",
         default="remote",
     )
 
@@ -202,5 +233,7 @@ class HostedServiceConfig(
     HostedZhipuAIConfig,
     # moderation
     HostedModerationConfig,
+    # credit config
+    HostedCreditConfig,
 ):
     pass

api/configs/middleware/vdb/milvus_config.py

@@ -33,3 +33,9 @@ class MilvusConfig(BaseSettings):
         description="Name of the Milvus database to connect to (default is 'default')",
         default="default",
     )
+
+    MILVUS_ENABLE_HYBRID_SEARCH: bool = Field(
+        description="Enable hybrid search features (requires Milvus >= 2.5.0). Set to false for compatibility with "
+        "older versions",
+        default=True,
+    )

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.14.2",
+        default="0.15.3",
     )
 
     COMMIT_SHA: str = Field(

api/constants/__init__.py

@@ -15,7 +15,7 @@ AUDIO_EXTENSIONS.extend([ext.upper() for ext in AUDIO_EXTENSIONS])
 
 if dify_config.ETL_TYPE == "Unstructured":
     DOCUMENT_EXTENSIONS = ["txt", "markdown", "md", "mdx", "pdf", "html", "htm", "xlsx", "xls"]
-    DOCUMENT_EXTENSIONS.extend(("docx", "csv", "eml", "msg", "pptx", "xml", "epub"))
+    DOCUMENT_EXTENSIONS.extend(("doc", "docx", "csv", "eml", "msg", "pptx", "xml", "epub"))
     if dify_config.UNSTRUCTURED_API_URL:
         DOCUMENT_EXTENSIONS.append("ppt")
     DOCUMENT_EXTENSIONS.extend([ext.upper() for ext in DOCUMENT_EXTENSIONS])

api/controllers/common/helpers.py

@@ -1,12 +1,32 @@
 import mimetypes
 import os
+import platform
 import re
 import urllib.parse
+import warnings
 from collections.abc import Mapping
 from typing import Any
 from uuid import uuid4
 
 import httpx
+
+try:
+    import magic
+except ImportError:
+    if platform.system() == "Windows":
+        warnings.warn(
+            "To use python-magic guess MIMETYPE, you need to run `pip install python-magic-bin`", stacklevel=2
+        )
+    elif platform.system() == "Darwin":
+        warnings.warn("To use python-magic guess MIMETYPE, you need to run `brew install libmagic`", stacklevel=2)
+    elif platform.system() == "Linux":
+        warnings.warn(
+            "To use python-magic guess MIMETYPE, you need to run `sudo apt-get install libmagic1`", stacklevel=2
+        )
+    else:
+        warnings.warn("To use python-magic guess MIMETYPE, you need to install `libmagic`", stacklevel=2)
+    magic = None  # type: ignore
+
 from pydantic import BaseModel
 
 from configs import dify_config
@@ -47,6 +67,13 @@ def guess_file_info_from_response(response: httpx.Response):
         # If guessing fails, use Content-Type from response headers
         mimetype = response.headers.get("Content-Type", "application/octet-stream")
 
+    # Use python-magic to guess MIME type if still unknown or generic
+    if mimetype == "application/octet-stream" and magic is not None:
+        try:
+            mimetype = magic.from_buffer(response.content[:1024], mime=True)
+        except magic.MagicException:
+            pass
+
     extension = os.path.splitext(filename)[1]
 
     # Ensure filename has an extension

api/controllers/console/admin.py

@@ -56,7 +56,7 @@ class InsertExploreAppListApi(Resource):
 
         app = App.query.filter(App.id == args["app_id"]).first()
         if not app:
-            raise NotFound(f'App \'{args["app_id"]}\' is not found')
+            raise NotFound(f"App '{args['app_id']}' is not found")
 
         site = app.site
         if not site:

api/controllers/console/app/app.py

@@ -57,12 +57,13 @@ class AppListApi(Resource):
         )
         parser.add_argument("name", type=str, location="args", required=False)
         parser.add_argument("tag_ids", type=uuid_list, location="args", required=False)
+        parser.add_argument("is_created_by_me", type=inputs.boolean, location="args", required=False)
 
         args = parser.parse_args()
 
         # get app list
         app_service = AppService()
-        app_pagination = app_service.get_paginate_apps(current_user.current_tenant_id, args)
+        app_pagination = app_service.get_paginate_apps(current_user.id, current_user.current_tenant_id, args)
         if not app_pagination:
             return {"data": [], "total": 0, "page": 1, "limit": 20, "has_more": False}
 

api/controllers/console/app/audio.py

@@ -22,7 +22,7 @@ from controllers.console.wraps import account_initialization_required, setup_req
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from libs.login import login_required
-from models.model import AppMode
+from models import App, AppMode
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -79,7 +79,7 @@ class ChatMessageTextApi(Resource):
     @login_required
     @account_initialization_required
     @get_app_model
-    def post(self, app_model):
+    def post(self, app_model: App):
         from werkzeug.exceptions import InternalServerError
 
         try:
@@ -98,9 +98,13 @@ class ChatMessageTextApi(Resource):
                 and app_model.workflow.features_dict
             ):
                 text_to_speech = app_model.workflow.features_dict.get("text_to_speech")
+                if text_to_speech is None:
+                    raise ValueError("TTS is not enabled")
                 voice = args.get("voice") or text_to_speech.get("voice")
             else:
                 try:
+                    if app_model.app_model_config is None:
+                        raise ValueError("AppModelConfig not found")
                     voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
                 except Exception:
                     voice = None

api/controllers/console/app/completion.py

@@ -20,7 +20,6 @@ from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpErr
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import (
-    AppInvokeQuotaExceededError,
     ModelCurrentlyNotSupportError,
     ProviderTokenNotInitError,
     QuotaExceededError,
@@ -76,7 +75,7 @@ class CompletionMessageApi(Resource):
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
             raise CompletionRequestError(e.description)
-        except (ValueError, AppInvokeQuotaExceededError) as e:
+        except ValueError as e:
             raise e
         except Exception as e:
             logging.exception("internal server error.")
@@ -141,7 +140,7 @@ class ChatMessageApi(Resource):
             raise InvokeRateLimitHttpError(ex.description)
         except InvokeError as e:
             raise CompletionRequestError(e.description)
-        except (ValueError, AppInvokeQuotaExceededError) as e:
+        except ValueError as e:
             raise e
         except Exception as e:
             logging.exception("internal server error.")

api/controllers/console/app/statistic.py

@@ -273,8 +273,7 @@ FROM
             messages m
             ON c.id = m.conversation_id
         WHERE
-            c.override_model_configs IS NULL
-            AND c.app_id = :app_id"""
+            c.app_id = :app_id"""
         arg_dict = {"tz": account.timezone, "app_id": app_model.id}
 
         timezone = pytz.timezone(account.timezone)

api/controllers/console/auth/error.py

@@ -59,3 +59,9 @@ class EmailCodeAccountDeletionRateLimitExceededError(BaseHTTPException):
     error_code = "email_code_account_deletion_rate_limit_exceeded"
     description = "Too many account deletion emails have been sent. Please try again in 5 minutes."
     code = 429
+
+
+class EmailPasswordResetLimitError(BaseHTTPException):
+    error_code = "email_password_reset_limit"
+    description = "Too many failed password reset attempts. Please try again in 24 hours."
+    code = 429

api/controllers/console/auth/forgot_password.py

@@ -6,7 +6,13 @@ from flask_restful import Resource, reqparse  # type: ignore
 
 from constants.languages import languages
 from controllers.console import api
-from controllers.console.auth.error import EmailCodeError, InvalidEmailError, InvalidTokenError, PasswordMismatchError
+from controllers.console.auth.error import (
+    EmailCodeError,
+    EmailPasswordResetLimitError,
+    InvalidEmailError,
+    InvalidTokenError,
+    PasswordMismatchError,
+)
 from controllers.console.error import AccountInFreezeError, AccountNotFound, EmailSendIpLimitError
 from controllers.console.wraps import setup_required
 from events.tenant_event import tenant_was_created
@@ -62,6 +68,10 @@ class ForgotPasswordCheckApi(Resource):
 
         user_email = args["email"]
 
+        is_forgot_password_error_rate_limit = AccountService.is_forgot_password_error_rate_limit(args["email"])
+        if is_forgot_password_error_rate_limit:
+            raise EmailPasswordResetLimitError()
+
         token_data = AccountService.get_reset_password_data(args["token"])
         if token_data is None:
             raise InvalidTokenError()
@@ -70,8 +80,10 @@ class ForgotPasswordCheckApi(Resource):
             raise InvalidEmailError()
 
         if args["code"] != token_data.get("code"):
+            AccountService.add_forgot_password_error_rate_limit(args["email"])
             raise EmailCodeError()
 
+        AccountService.reset_forgot_password_error_rate_limit(args["email"])
         return {"is_valid": True, "email": token_data.get("email")}
 
 

api/controllers/console/datasets/datasets.py

@@ -52,12 +52,12 @@ class DatasetListApi(Resource):
         # provider = request.args.get("provider", default="vendor")
         search = request.args.get("keyword", default=None, type=str)
         tag_ids = request.args.getlist("tag_ids")
-
+        include_all = request.args.get("include_all", default="false").lower() == "true"
         if ids:
             datasets, total = DatasetService.get_datasets_by_ids(ids, current_user.current_tenant_id)
         else:
             datasets, total = DatasetService.get_datasets(
-                page, limit, current_user.current_tenant_id, current_user, search, tag_ids
+                page, limit, current_user.current_tenant_id, current_user, search, tag_ids, include_all
             )
 
         # check embedding setting
@@ -457,7 +457,7 @@ class DatasetIndexingEstimateApi(Resource):
             )
         except LLMBadRequestError:
             raise ProviderNotInitializeError(
-                "No Embedding Model available. Please configure a valid provider " "in the Settings -> Model Provider."
+                "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
             )
         except ProviderTokenNotInitError as ex:
             raise ProviderNotInitializeError(ex.description)
@@ -619,9 +619,7 @@ class DatasetRetrievalSettingApi(Resource):
         vector_type = dify_config.VECTOR_STORE
         match vector_type:
             case (
-                VectorType.MILVUS
-                | VectorType.RELYT
-                | VectorType.PGVECTOR
+                VectorType.RELYT
                 | VectorType.TIDB_VECTOR
                 | VectorType.CHROMA
                 | VectorType.TENCENT
@@ -640,10 +638,12 @@ class DatasetRetrievalSettingApi(Resource):
                 | VectorType.MYSCALE
                 | VectorType.ORACLE
                 | VectorType.ELASTICSEARCH
+                | VectorType.ELASTICSEARCH_JA
                 | VectorType.PGVECTOR
                 | VectorType.TIDB_ON_QDRANT
                 | VectorType.LINDORM
                 | VectorType.COUCHBASE
+                | VectorType.MILVUS
             ):
                 return {
                     "retrieval_method": [
@@ -683,6 +683,7 @@ class DatasetRetrievalSettingMockApi(Resource):
                 | VectorType.MYSCALE
                 | VectorType.ORACLE
                 | VectorType.ELASTICSEARCH
+                | VectorType.ELASTICSEARCH_JA
                 | VectorType.COUCHBASE
                 | VectorType.PGVECTOR
                 | VectorType.LINDORM

api/controllers/console/datasets/datasets_document.py

@@ -257,7 +257,8 @@ class DatasetDocumentListApi(Resource):
         parser.add_argument("original_document_id", type=str, required=False, location="json")
         parser.add_argument("doc_form", type=str, default="text_model", required=False, nullable=False, location="json")
         parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
-
+        parser.add_argument("embedding_model", type=str, required=False, nullable=True, location="json")
+        parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
         parser.add_argument(
             "doc_language", type=str, default="English", required=False, nullable=False, location="json"
         )
@@ -349,8 +350,7 @@ class DatasetInitApi(Resource):
                 )
             except InvokeAuthorizationError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -525,8 +525,7 @@ class DocumentBatchIndexingEstimateApi(DocumentResource):
                 return response.model_dump(), 200
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/console/datasets/datasets_segments.py

@@ -168,8 +168,7 @@ class DatasetDocumentSegmentApi(Resource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -217,8 +216,7 @@ class DatasetDocumentSegmentAddApi(Resource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -267,8 +265,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -368,9 +365,9 @@ class DatasetDocumentSegmentBatchImportApi(Resource):
             result = []
             for index, row in df.iterrows():
                 if document.doc_form == "qa_model":
-                    data = {"content": row[0], "answer": row[1]}
+                    data = {"content": row.iloc[0], "answer": row.iloc[1]}
                 else:
-                    data = {"content": row[0]}
+                    data = {"content": row.iloc[0]}
                 result.append(data)
             if len(result) == 0:
                 raise ValueError("The CSV file is empty.")
@@ -437,8 +434,7 @@ class ChildChunkAddApi(Resource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/console/explore/completion.py

@@ -18,7 +18,11 @@ from controllers.console.explore.error import NotChatAppError, NotCompletionAppE
 from controllers.console.explore.wraps import InstalledAppResource
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.errors.error import (
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
 from core.model_runtime.errors.invoke import InvokeError
 from extensions.ext_database import db
 from libs import helper

api/controllers/console/explore/conversation.py

@@ -32,7 +32,7 @@ class ConversationListApi(InstalledAppResource):
 
         pinned = None
         if "pinned" in args and args["pinned"] is not None:
-            pinned = True if args["pinned"] == "true" else False
+            pinned = args["pinned"] == "true"
 
         try:
             with Session(db.engine) as session:

api/controllers/console/explore/message.py

@@ -50,7 +50,7 @@ class MessageListApi(InstalledAppResource):
 
         try:
             return MessageService.pagination_by_first_id(
-                app_model, current_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
+                app_model, current_user, args["conversation_id"], args["first_id"], args["limit"]
             )
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")

api/controllers/console/explore/workflow.py

@@ -13,7 +13,11 @@ from controllers.console.explore.error import NotWorkflowAppError
 from controllers.console.explore.wraps import InstalledAppResource
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.errors.error import (
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
 from core.model_runtime.errors.invoke import InvokeError
 from libs import helper
 from libs.login import current_user

api/controllers/inner_api/workspace/workspace.py

@@ -1,3 +1,5 @@
+import json
+
 from flask_restful import Resource, reqparse  # type: ignore
 
 from controllers.console.wraps import setup_required
@@ -29,4 +31,34 @@ class EnterpriseWorkspace(Resource):
         return {"message": "enterprise workspace created."}
 
 
+class EnterpriseWorkspaceNoOwnerEmail(Resource):
+    @setup_required
+    @inner_api_only
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("name", type=str, required=True, location="json")
+        args = parser.parse_args()
+
+        tenant = TenantService.create_tenant(args["name"], is_from_dashboard=True)
+
+        tenant_was_created.send(tenant)
+
+        resp = {
+            "id": tenant.id,
+            "name": tenant.name,
+            "encrypt_public_key": tenant.encrypt_public_key,
+            "plan": tenant.plan,
+            "status": tenant.status,
+            "custom_config": json.loads(tenant.custom_config) if tenant.custom_config else {},
+            "created_at": tenant.created_at.isoformat() + "Z" if tenant.created_at else None,
+            "updated_at": tenant.updated_at.isoformat() + "Z" if tenant.updated_at else None,
+        }
+
+        return {
+            "message": "enterprise workspace created.",
+            "tenant": resp,
+        }
+
+
 api.add_resource(EnterpriseWorkspace, "/enterprise/workspace")
+api.add_resource(EnterpriseWorkspaceNoOwnerEmail, "/enterprise/workspace/ownerless")

api/controllers/service_api/__init__.py

@@ -7,4 +7,4 @@ api = ExternalApi(bp)
 
 from . import index
 from .app import app, audio, completion, conversation, file, message, workflow
-from .dataset import dataset, document, hit_testing, segment
+from .dataset import dataset, document, hit_testing, segment, upload_file

api/controllers/service_api/app/completion.py

@@ -18,7 +18,6 @@ from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import (
-    AppInvokeQuotaExceededError,
     ModelCurrentlyNotSupportError,
     ProviderTokenNotInitError,
     QuotaExceededError,
@@ -74,7 +73,7 @@ class CompletionApi(Resource):
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
             raise CompletionRequestError(e.description)
-        except (ValueError, AppInvokeQuotaExceededError) as e:
+        except ValueError as e:
             raise e
         except Exception as e:
             logging.exception("internal server error.")
@@ -133,7 +132,7 @@ class ChatApi(Resource):
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
             raise CompletionRequestError(e.description)
-        except (ValueError, AppInvokeQuotaExceededError) as e:
+        except ValueError as e:
             raise e
         except Exception as e:
             logging.exception("internal server error.")

api/controllers/service_api/app/workflow.py

@@ -16,7 +16,6 @@ from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import (
-    AppInvokeQuotaExceededError,
     ModelCurrentlyNotSupportError,
     ProviderTokenNotInitError,
     QuotaExceededError,
@@ -94,7 +93,7 @@ class WorkflowRunApi(Resource):
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
             raise CompletionRequestError(e.description)
-        except (ValueError, AppInvokeQuotaExceededError) as e:
+        except ValueError as e:
             raise e
         except Exception as e:
             logging.exception("internal server error.")

api/controllers/service_api/dataset/dataset.py

@@ -31,8 +31,11 @@ class DatasetListApi(DatasetApiResource):
         # provider = request.args.get("provider", default="vendor")
         search = request.args.get("keyword", default=None, type=str)
         tag_ids = request.args.getlist("tag_ids")
+        include_all = request.args.get("include_all", default="false").lower() == "true"
 
-        datasets, total = DatasetService.get_datasets(page, limit, tenant_id, current_user, search, tag_ids)
+        datasets, total = DatasetService.get_datasets(
+            page, limit, tenant_id, current_user, search, tag_ids, include_all
+        )
         # check embedding setting
         provider_manager = ProviderManager()
         configurations = provider_manager.get_configurations(tenant_id=current_user.current_tenant_id)

api/controllers/service_api/dataset/document.py

@@ -18,6 +18,7 @@ from controllers.service_api.app.error import (
 from controllers.service_api.dataset.error import (
     ArchivedDocumentImmutableError,
     DocumentIndexingError,
+    InvalidMetadataError,
 )
 from controllers.service_api.wraps import DatasetApiResource, cloud_edition_billing_resource_check
 from core.errors.error import ProviderTokenNotInitError
@@ -50,6 +51,9 @@ class DocumentAddByTextApi(DatasetApiResource):
             "indexing_technique", type=str, choices=Dataset.INDEXING_TECHNIQUE_LIST, nullable=False, location="json"
         )
         parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
+        parser.add_argument("doc_type", type=str, required=False, nullable=True, location="json")
+        parser.add_argument("doc_metadata", type=dict, required=False, nullable=True, location="json")
+
         args = parser.parse_args()
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
@@ -61,6 +65,28 @@ class DocumentAddByTextApi(DatasetApiResource):
         if not dataset.indexing_technique and not args["indexing_technique"]:
             raise ValueError("indexing_technique is required.")
 
+        # Validate metadata if provided
+        if args.get("doc_type") or args.get("doc_metadata"):
+            if not args.get("doc_type") or not args.get("doc_metadata"):
+                raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
+
+            if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
+                raise InvalidMetadataError(
+                    "Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
+                )
+
+            if not isinstance(args["doc_metadata"], dict):
+                raise InvalidMetadataError("doc_metadata must be a dictionary")
+
+            # Validate metadata schema based on doc_type
+            if args["doc_type"] != "others":
+                metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
+                for key, value in args["doc_metadata"].items():
+                    if key in metadata_schema and not isinstance(value, metadata_schema[key]):
+                        raise InvalidMetadataError(f"Invalid type for metadata field {key}")
+            # set to MetaDataConfig
+            args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
+
         text = args.get("text")
         name = args.get("name")
         if text is None or name is None:
@@ -107,6 +133,8 @@ class DocumentUpdateByTextApi(DatasetApiResource):
             "doc_language", type=str, default="English", required=False, nullable=False, location="json"
         )
         parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
+        parser.add_argument("doc_type", type=str, required=False, nullable=True, location="json")
+        parser.add_argument("doc_metadata", type=dict, required=False, nullable=True, location="json")
         args = parser.parse_args()
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
@@ -115,6 +143,32 @@ class DocumentUpdateByTextApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset is not exist.")
 
+        # indexing_technique is already set in dataset since this is an update
+        args["indexing_technique"] = dataset.indexing_technique
+
+        # Validate metadata if provided
+        if args.get("doc_type") or args.get("doc_metadata"):
+            if not args.get("doc_type") or not args.get("doc_metadata"):
+                raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
+
+            if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
+                raise InvalidMetadataError(
+                    "Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
+                )
+
+            if not isinstance(args["doc_metadata"], dict):
+                raise InvalidMetadataError("doc_metadata must be a dictionary")
+
+            # Validate metadata schema based on doc_type
+            if args["doc_type"] != "others":
+                metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
+                for key, value in args["doc_metadata"].items():
+                    if key in metadata_schema and not isinstance(value, metadata_schema[key]):
+                        raise InvalidMetadataError(f"Invalid type for metadata field {key}")
+
+            # set to MetaDataConfig
+            args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
+
         if args["text"]:
             text = args.get("text")
             name = args.get("name")
@@ -161,6 +215,30 @@ class DocumentAddByFileApi(DatasetApiResource):
             args["doc_form"] = "text_model"
         if "doc_language" not in args:
             args["doc_language"] = "English"
+
+        # Validate metadata if provided
+        if args.get("doc_type") or args.get("doc_metadata"):
+            if not args.get("doc_type") or not args.get("doc_metadata"):
+                raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
+
+            if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
+                raise InvalidMetadataError(
+                    "Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
+                )
+
+            if not isinstance(args["doc_metadata"], dict):
+                raise InvalidMetadataError("doc_metadata must be a dictionary")
+
+            # Validate metadata schema based on doc_type
+            if args["doc_type"] != "others":
+                metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
+                for key, value in args["doc_metadata"].items():
+                    if key in metadata_schema and not isinstance(value, metadata_schema[key]):
+                        raise InvalidMetadataError(f"Invalid type for metadata field {key}")
+
+            # set to MetaDataConfig
+            args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
+
         # get dataset info
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
@@ -190,7 +268,10 @@ class DocumentAddByFileApi(DatasetApiResource):
             user=current_user,
             source="datasets",
         )
-        data_source = {"type": "upload_file", "info_list": {"file_info_list": {"file_ids": [upload_file.id]}}}
+        data_source = {
+            "type": "upload_file",
+            "info_list": {"data_source_type": "upload_file", "file_info_list": {"file_ids": [upload_file.id]}},
+        }
         args["data_source"] = data_source
         # validate args
         knowledge_config = KnowledgeConfig(**args)
@@ -225,6 +306,29 @@ class DocumentUpdateByFileApi(DatasetApiResource):
         if "doc_language" not in args:
             args["doc_language"] = "English"
 
+        # Validate metadata if provided
+        if args.get("doc_type") or args.get("doc_metadata"):
+            if not args.get("doc_type") or not args.get("doc_metadata"):
+                raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
+
+            if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
+                raise InvalidMetadataError(
+                    "Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
+                )
+
+            if not isinstance(args["doc_metadata"], dict):
+                raise InvalidMetadataError("doc_metadata must be a dictionary")
+
+            # Validate metadata schema based on doc_type
+            if args["doc_type"] != "others":
+                metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
+                for key, value in args["doc_metadata"].items():
+                    if key in metadata_schema and not isinstance(value, metadata_schema[key]):
+                        raise InvalidMetadataError(f"Invalid type for metadata field {key}")
+
+            # set to MetaDataConfig
+            args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
+
         # get dataset info
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
@@ -254,7 +358,10 @@ class DocumentUpdateByFileApi(DatasetApiResource):
                 raise FileTooLargeError(file_too_large_error.description)
             except services.errors.file.UnsupportedFileTypeError:
                 raise UnsupportedFileTypeError()
-            data_source = {"type": "upload_file", "info_list": {"file_info_list": {"file_ids": [upload_file.id]}}}
+            data_source = {
+                "type": "upload_file",
+                "info_list": {"data_source_type": "upload_file", "file_info_list": {"file_ids": [upload_file.id]}},
+            }
             args["data_source"] = data_source
         # validate args
         args["original_document_id"] = str(document_id)

api/controllers/service_api/dataset/segment.py

@@ -53,8 +53,7 @@ class SegmentApi(DatasetApiResource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -95,8 +94,7 @@ class SegmentApi(DatasetApiResource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -175,8 +173,7 @@ class DatasetSegmentApi(DatasetApiResource):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/service_api/dataset/upload_file.py

@@ -0,0 +1,54 @@
+from werkzeug.exceptions import NotFound
+
+from controllers.service_api import api
+from controllers.service_api.wraps import (
+    DatasetApiResource,
+)
+from core.file import helpers as file_helpers
+from extensions.ext_database import db
+from models.dataset import Dataset
+from models.model import UploadFile
+from services.dataset_service import DocumentService
+
+
+class UploadFileApi(DatasetApiResource):
+    def get(self, tenant_id, dataset_id, document_id):
+        """Get upload file."""
+        # check dataset
+        dataset_id = str(dataset_id)
+        tenant_id = str(tenant_id)
+        dataset = db.session.query(Dataset).filter(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id).first()
+        if not dataset:
+            raise NotFound("Dataset not found.")
+        # check document
+        document_id = str(document_id)
+        document = DocumentService.get_document(dataset.id, document_id)
+        if not document:
+            raise NotFound("Document not found.")
+        # check upload file
+        if document.data_source_type != "upload_file":
+            raise ValueError(f"Document data source type ({document.data_source_type}) is not upload_file.")
+        data_source_info = document.data_source_info_dict
+        if data_source_info and "upload_file_id" in data_source_info:
+            file_id = data_source_info["upload_file_id"]
+            upload_file = db.session.query(UploadFile).filter(UploadFile.id == file_id).first()
+            if not upload_file:
+                raise NotFound("UploadFile not found.")
+        else:
+            raise ValueError("Upload file id not found in document data source info.")
+
+        url = file_helpers.get_signed_file_url(upload_file_id=upload_file.id)
+        return {
+            "id": upload_file.id,
+            "name": upload_file.name,
+            "size": upload_file.size,
+            "extension": upload_file.extension,
+            "url": url,
+            "download_url": f"{url}&as_attachment=true",
+            "mime_type": upload_file.mime_type,
+            "created_by": upload_file.created_by,
+            "created_at": upload_file.created_at.timestamp(),
+        }, 200
+
+
+api.add_resource(UploadFileApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/upload-file")

api/controllers/service_api/wraps.py

@@ -1,5 +1,5 @@
 from collections.abc import Callable
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timedelta
 from enum import Enum
 from functools import wraps
 from typing import Optional
@@ -8,6 +8,8 @@ from flask import current_app, request
 from flask_login import user_logged_in  # type: ignore
 from flask_restful import Resource  # type: ignore
 from pydantic import BaseModel
+from sqlalchemy import select, update
+from sqlalchemy.orm import Session
 from werkzeug.exceptions import Forbidden, Unauthorized
 
 from extensions.ext_database import db
@@ -174,7 +176,7 @@ def validate_dataset_token(view=None):
     return decorator
 
 
-def validate_and_get_api_token(scope=None):
+def validate_and_get_api_token(scope: str | None = None):
     """
     Validate and get API token.
     """
@@ -188,20 +190,29 @@ def validate_and_get_api_token(scope=None):
     if auth_scheme != "bearer":
         raise Unauthorized("Authorization scheme must be 'Bearer'")
 
-    api_token = (
-        db.session.query(ApiToken)
-        .filter(
-            ApiToken.token == auth_token,
-            ApiToken.type == scope,
+    current_time = datetime.now(UTC).replace(tzinfo=None)
+    cutoff_time = current_time - timedelta(minutes=1)
+    with Session(db.engine, expire_on_commit=False) as session:
+        update_stmt = (
+            update(ApiToken)
+            .where(
+                ApiToken.token == auth_token,
+                (ApiToken.last_used_at.is_(None) | (ApiToken.last_used_at < cutoff_time)),
+                ApiToken.type == scope,
+            )
+            .values(last_used_at=current_time)
+            .returning(ApiToken)
         )
-        .first()
-    )
+        result = session.execute(update_stmt)
+        api_token = result.scalar_one_or_none()
 
-    if not api_token:
-        raise Unauthorized("Access token is invalid")
-
-    api_token.last_used_at = datetime.now(UTC).replace(tzinfo=None)
-    db.session.commit()
+        if not api_token:
+            stmt = select(ApiToken).where(ApiToken.token == auth_token, ApiToken.type == scope)
+            api_token = session.scalar(stmt)
+            if not api_token:
+                raise Unauthorized("Access token is invalid")
+        else:
+            session.commit()
 
     return api_token
 
@@ -229,7 +240,7 @@ def create_or_update_end_user_for_user_id(app_model: App, user_id: Optional[str]
             tenant_id=app_model.tenant_id,
             app_id=app_model.id,
             type="service_api",
-            is_anonymous=True if user_id == "DEFAULT-USER" else False,
+            is_anonymous=user_id == "DEFAULT-USER",
             session_id=user_id,
         )
         db.session.add(end_user)

api/controllers/web/completion.py

@@ -19,7 +19,11 @@ from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpErr
 from controllers.web.wraps import WebApiResource
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.errors.error import (
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
 from core.model_runtime.errors.invoke import InvokeError
 from libs import helper
 from libs.helper import uuid_value

api/controllers/web/conversation.py

@@ -39,7 +39,7 @@ class ConversationListApi(WebApiResource):
 
         pinned = None
         if "pinned" in args and args["pinned"] is not None:
-            pinned = True if args["pinned"] == "true" else False
+            pinned = args["pinned"] == "true"
 
         try:
             with Session(db.engine) as session:

api/controllers/web/message.py

@@ -91,7 +91,7 @@ class MessageListApi(WebApiResource):
 
         try:
             return MessageService.pagination_by_first_id(
-                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
+                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"]
             )
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")

api/controllers/web/workflow.py

@@ -14,7 +14,11 @@ from controllers.web.error import (
 from controllers.web.wraps import WebApiResource
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.errors.error import (
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
 from core.model_runtime.errors.invoke import InvokeError
 from libs import helper
 from models.model import App, AppMode, EndUser

api/core/agent/cot_agent_runner.py

@@ -172,7 +172,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
 
             self.save_agent_thought(
                 agent_thought=agent_thought,
-                tool_name=scratchpad.action.action_name if scratchpad.action else "",
+                tool_name=(scratchpad.action.action_name if scratchpad.action and not scratchpad.is_final() else ""),
                 tool_input={scratchpad.action.action_name: scratchpad.action.action_input} if scratchpad.action else {},
                 tool_invoke_meta={},
                 thought=scratchpad.thought or "",

api/core/app/apps/advanced_chat/app_generator.py

@@ -21,7 +21,7 @@ from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
 from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
 from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, InvokeFrom
 from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotAppStreamResponse
-from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
+from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.prompt.utils.get_thread_messages_length import get_thread_messages_length
 from extensions.ext_database import db
@@ -140,9 +140,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             app_config=app_config,
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=conversation.inputs
-            if conversation
-            else self._prepare_user_inputs(
+            inputs=self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,
@@ -336,7 +334,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
-            except (ValueError, InvokeError) as e:
+            except ValueError as e:
                 if dify_config.DEBUG:
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -67,24 +67,17 @@ from models.account import Account
 from models.enums import CreatedByRole
 from models.workflow import (
     Workflow,
-    WorkflowNodeExecution,
     WorkflowRunStatus,
 )
 
 logger = logging.getLogger(__name__)
 
 
-class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleManage, MessageCycleManage):
+class AdvancedChatAppGenerateTaskPipeline:
     """
     AdvancedChatAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
 
-    _task_state: WorkflowTaskState
-    _application_generate_entity: AdvancedChatAppGenerateEntity
-    _workflow_system_variables: dict[SystemVariableKey, Any]
-    _wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
-    _conversation_name_generate_thread: Optional[Thread] = None
-
     def __init__(
         self,
         application_generate_entity: AdvancedChatAppGenerateEntity,
@@ -96,7 +89,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         stream: bool,
         dialogue_count: int,
     ) -> None:
-        super().__init__(
+        self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
             queue_manager=queue_manager,
             stream=stream,
@@ -113,32 +106,35 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         else:
             raise NotImplementedError(f"User type not supported: {type(user)}")
 
-        self._workflow_id = workflow.id
-        self._workflow_features_dict = workflow.features_dict
-
-        self._conversation_id = conversation.id
-        self._conversation_mode = conversation.mode
-
-        self._message_id = message.id
-        self._message_created_at = int(message.created_at.timestamp())
-
-        self._workflow_system_variables = {
-            SystemVariableKey.QUERY: message.query,
-            SystemVariableKey.FILES: application_generate_entity.files,
-            SystemVariableKey.CONVERSATION_ID: conversation.id,
-            SystemVariableKey.USER_ID: user_session_id,
-            SystemVariableKey.DIALOGUE_COUNT: dialogue_count,
-            SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
-            SystemVariableKey.WORKFLOW_ID: workflow.id,
-            SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
-        }
+        self._workflow_cycle_manager = WorkflowCycleManage(
+            application_generate_entity=application_generate_entity,
+            workflow_system_variables={
+                SystemVariableKey.QUERY: message.query,
+                SystemVariableKey.FILES: application_generate_entity.files,
+                SystemVariableKey.CONVERSATION_ID: conversation.id,
+                SystemVariableKey.USER_ID: user_session_id,
+                SystemVariableKey.DIALOGUE_COUNT: dialogue_count,
+                SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
+                SystemVariableKey.WORKFLOW_ID: workflow.id,
+                SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
+            },
+        )
 
         self._task_state = WorkflowTaskState()
-        self._wip_workflow_node_executions = {}
+        self._message_cycle_manager = MessageCycleManage(
+            application_generate_entity=application_generate_entity, task_state=self._task_state
+        )
 
-        self._conversation_name_generate_thread = None
+        self._application_generate_entity = application_generate_entity
+        self._workflow_id = workflow.id
+        self._workflow_features_dict = workflow.features_dict
+        self._conversation_id = conversation.id
+        self._conversation_mode = conversation.mode
+        self._message_id = message.id
+        self._message_created_at = int(message.created_at.timestamp())
+        self._conversation_name_generate_thread: Thread | None = None
         self._recorded_files: list[Mapping[str, Any]] = []
-        self._workflow_run_id = ""
+        self._workflow_run_id: str = ""
 
     def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -146,13 +142,13 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         :return:
         """
         # start generate conversation name thread
-        self._conversation_name_generate_thread = self._generate_conversation_name(
+        self._conversation_name_generate_thread = self._message_cycle_manager._generate_conversation_name(
             conversation_id=self._conversation_id, query=self._application_generate_entity.query
         )
 
         generator = self._wrapper_process_stream_response(trace_manager=self._application_generate_entity.trace_manager)
 
-        if self._stream:
+        if self._base_task_pipeline._stream:
             return self._to_stream_response(generator)
         else:
             return self._to_blocking_response(generator)
@@ -269,24 +265,26 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         # init fake graph runtime state
         graph_runtime_state: Optional[GraphRuntimeState] = None
 
-        for queue_message in self._queue_manager.listen():
+        for queue_message in self._base_task_pipeline._queue_manager.listen():
             event = queue_message.event
 
             if isinstance(event, QueuePingEvent):
-                yield self._ping_stream_response()
+                yield self._base_task_pipeline._ping_stream_response()
             elif isinstance(event, QueueErrorEvent):
-                with Session(db.engine) as session:
-                    err = self._handle_error(event=event, session=session, message_id=self._message_id)
+                with Session(db.engine, expire_on_commit=False) as session:
+                    err = self._base_task_pipeline._handle_error(
+                        event=event, session=session, message_id=self._message_id
+                    )
                     session.commit()
-                yield self._error_to_stream_response(err)
+                yield self._base_task_pipeline._error_to_stream_response(err)
                 break
             elif isinstance(event, QueueWorkflowStartedEvent):
                 # override graph runtime state
                 graph_runtime_state = event.graph_runtime_state
 
-                with Session(db.engine) as session:
+                with Session(db.engine, expire_on_commit=False) as session:
                     # init workflow run
-                    workflow_run = self._handle_workflow_run_start(
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
                         session=session,
                         workflow_id=self._workflow_id,
                         user_id=self._user_id,
@@ -297,7 +295,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                     if not message:
                         raise ValueError(f"Message not found: {self._message_id}")
                     message.workflow_run_id = workflow_run.id
-                    workflow_start_resp = self._workflow_start_to_stream_response(
+                    workflow_start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()
@@ -310,12 +308,14 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    workflow_node_execution = self._handle_workflow_node_execution_retried(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
                         session=session, workflow_run=workflow_run, event=event
                     )
-                    node_retry_resp = self._workflow_node_retry_to_stream_response(
+                    node_retry_resp = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -329,13 +329,15 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    workflow_node_execution = self._handle_node_execution_start(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
                         session=session, workflow_run=workflow_run, event=event
                     )
 
-                    node_start_resp = self._workflow_node_start_to_stream_response(
+                    node_start_resp = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -348,12 +350,16 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueNodeSucceededEvent):
                 # Record files if it's an answer node or end node
                 if event.node_type in [NodeType.ANSWER, NodeType.END]:
-                    self._recorded_files.extend(self._fetch_files_from_node_outputs(event.outputs or {}))
+                    self._recorded_files.extend(
+                        self._workflow_cycle_manager._fetch_files_from_node_outputs(event.outputs or {})
+                    )
 
-                with Session(db.engine) as session:
-                    workflow_node_execution = self._handle_workflow_node_execution_success(session=session, event=event)
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
+                        session=session, event=event
+                    )
 
-                    node_finish_resp = self._workflow_node_finish_to_stream_response(
+                    node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -364,10 +370,12 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if node_finish_resp:
                     yield node_finish_resp
             elif isinstance(event, QueueNodeFailedEvent | QueueNodeInIterationFailedEvent | QueueNodeExceptionEvent):
-                with Session(db.engine) as session:
-                    workflow_node_execution = self._handle_workflow_node_execution_failed(session=session, event=event)
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
+                        session=session, event=event
+                    )
 
-                    node_finish_resp = self._workflow_node_finish_to_stream_response(
+                    node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -381,13 +389,17 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    parallel_start_resp = self._workflow_parallel_branch_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    parallel_start_resp = (
+                        self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
+                            session=session,
+                            task_id=self._application_generate_entity.task_id,
+                            workflow_run=workflow_run,
+                            event=event,
+                        )
                     )
 
                 yield parallel_start_resp
@@ -395,13 +407,17 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    parallel_finish_resp = self._workflow_parallel_branch_finished_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    parallel_finish_resp = (
+                        self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
+                            session=session,
+                            task_id=self._application_generate_entity.task_id,
+                            workflow_run=workflow_run,
+                            event=event,
+                        )
                     )
 
                 yield parallel_finish_resp
@@ -409,9 +425,11 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_start_resp = self._workflow_iteration_start_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -423,9 +441,11 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_next_resp = self._workflow_iteration_next_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -437,9 +457,11 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_finish_resp = self._workflow_iteration_completed_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -454,8 +476,8 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 if not graph_runtime_state:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_success(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -466,21 +488,23 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                         trace_manager=trace_manager,
                     )
 
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()
 
                 yield workflow_finish_resp
-                self._queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
+                self._base_task_pipeline._queue_manager.publish(
+                    QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE
+                )
             elif isinstance(event, QueueWorkflowPartialSuccessEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_partial_success(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -491,21 +515,23 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                         conversation_id=None,
                         trace_manager=trace_manager,
                     )
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()
 
                 yield workflow_finish_resp
-                self._queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
+                self._base_task_pipeline._queue_manager.publish(
+                    QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE
+                )
             elif isinstance(event, QueueWorkflowFailedEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_failed(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -517,20 +543,22 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                         trace_manager=trace_manager,
                         exceptions_count=event.exceptions_count,
                     )
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     err_event = QueueErrorEvent(error=ValueError(f"Run failed: {workflow_run.error}"))
-                    err = self._handle_error(event=err_event, session=session, message_id=self._message_id)
+                    err = self._base_task_pipeline._handle_error(
+                        event=err_event, session=session, message_id=self._message_id
+                    )
                     session.commit()
 
                 yield workflow_finish_resp
-                yield self._error_to_stream_response(err)
+                yield self._base_task_pipeline._error_to_stream_response(err)
                 break
             elif isinstance(event, QueueStopEvent):
                 if self._workflow_run_id and graph_runtime_state:
-                    with Session(db.engine) as session:
-                        workflow_run = self._handle_workflow_run_failed(
+                    with Session(db.engine, expire_on_commit=False) as session:
+                        workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
                             session=session,
                             workflow_run_id=self._workflow_run_id,
                             start_at=graph_runtime_state.start_at,
@@ -541,7 +569,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                             conversation_id=self._conversation_id,
                             trace_manager=trace_manager,
                         )
-                        workflow_finish_resp = self._workflow_finish_to_stream_response(
+                        workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                             session=session,
                             task_id=self._application_generate_entity.task_id,
                             workflow_run=workflow_run,
@@ -555,18 +583,18 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 yield self._message_end_to_stream_response()
                 break
             elif isinstance(event, QueueRetrieverResourcesEvent):
-                self._handle_retriever_resources(event)
+                self._message_cycle_manager._handle_retriever_resources(event)
 
-                with Session(db.engine) as session:
+                with Session(db.engine, expire_on_commit=False) as session:
                     message = self._get_message(session=session)
                     message.message_metadata = (
                         json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
                     )
                     session.commit()
             elif isinstance(event, QueueAnnotationReplyEvent):
-                self._handle_annotation_reply(event)
+                self._message_cycle_manager._handle_annotation_reply(event)
 
-                with Session(db.engine) as session:
+                with Session(db.engine, expire_on_commit=False) as session:
                     message = self._get_message(session=session)
                     message.message_metadata = (
                         json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
@@ -587,23 +615,27 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                     tts_publisher.publish(queue_message)
 
                 self._task_state.answer += delta_text
-                yield self._message_to_stream_response(
+                yield self._message_cycle_manager._message_to_stream_response(
                     answer=delta_text, message_id=self._message_id, from_variable_selector=event.from_variable_selector
                 )
             elif isinstance(event, QueueMessageReplaceEvent):
                 # published by moderation
-                yield self._message_replace_to_stream_response(answer=event.text)
+                yield self._message_cycle_manager._message_replace_to_stream_response(answer=event.text)
             elif isinstance(event, QueueAdvancedChatMessageEndEvent):
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                output_moderation_answer = self._handle_output_moderation_when_task_finished(self._task_state.answer)
+                output_moderation_answer = self._base_task_pipeline._handle_output_moderation_when_task_finished(
+                    self._task_state.answer
+                )
                 if output_moderation_answer:
                     self._task_state.answer = output_moderation_answer
-                    yield self._message_replace_to_stream_response(answer=output_moderation_answer)
+                    yield self._message_cycle_manager._message_replace_to_stream_response(
+                        answer=output_moderation_answer
+                    )
 
                 # Save message
-                with Session(db.engine) as session:
+                with Session(db.engine, expire_on_commit=False) as session:
                     self._save_message(session=session, graph_runtime_state=graph_runtime_state)
                     session.commit()
 
@@ -621,7 +653,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
     def _save_message(self, *, session: Session, graph_runtime_state: Optional[GraphRuntimeState] = None) -> None:
         message = self._get_message(session=session)
         message.answer = self._task_state.answer
-        message.provider_response_latency = time.perf_counter() - self._start_at
+        message.provider_response_latency = time.perf_counter() - self._base_task_pipeline._start_at
         message.message_metadata = (
             json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
         )
@@ -685,20 +717,20 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         :param text: text
         :return: True if output moderation should direct output, otherwise False
         """
-        if self._output_moderation_handler:
-            if self._output_moderation_handler.should_direct_output():
+        if self._base_task_pipeline._output_moderation_handler:
+            if self._base_task_pipeline._output_moderation_handler.should_direct_output():
                 # stop subscribe new token when output moderation should direct output
-                self._task_state.answer = self._output_moderation_handler.get_final_output()
-                self._queue_manager.publish(
+                self._task_state.answer = self._base_task_pipeline._output_moderation_handler.get_final_output()
+                self._base_task_pipeline._queue_manager.publish(
                     QueueTextChunkEvent(text=self._task_state.answer), PublishFrom.TASK_PIPELINE
                 )
 
-                self._queue_manager.publish(
+                self._base_task_pipeline._queue_manager.publish(
                     QueueStopEvent(stopped_by=QueueStopEvent.StopBy.OUTPUT_MODERATION), PublishFrom.TASK_PIPELINE
                 )
                 return True
             else:
-                self._output_moderation_handler.append_new_token(text)
+                self._base_task_pipeline._output_moderation_handler.append_new_token(text)
 
         return False
 

api/core/app/apps/agent_chat/app_generator.py

@@ -18,7 +18,7 @@ from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskSt
 from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
 from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
 from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, InvokeFrom
-from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
+from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from extensions.ext_database import db
 from factories import file_factory
@@ -148,9 +148,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             model_conf=ModelConfigConverter.convert(app_config),
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=conversation.inputs
-            if conversation
-            else self._prepare_user_inputs(
+            inputs=self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,
@@ -245,7 +243,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
-            except (ValueError, InvokeError) as e:
+            except ValueError as e:
                 if dify_config.DEBUG:
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)

api/core/app/apps/agent_chat/app_runner.py

@@ -202,7 +202,7 @@ class AgentChatAppRunner(AppRunner):
         # change function call strategy based on LLM model
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
         model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
-        if not model_schema or not model_schema.features:
+        if not model_schema:
             raise ValueError("Model schema not found")
 
         if {ModelFeature.MULTI_TOOL_CALL, ModelFeature.TOOL_CALL}.intersection(model_schema.features or []):

api/core/app/apps/base_app_queue_manager.py

@@ -167,8 +167,7 @@ class AppQueueManager:
         else:
             if isinstance(data, DeclarativeMeta) or hasattr(data, "_sa_instance_state"):
                 raise TypeError(
-                    "Critical Error: Passing SQLAlchemy Model instances "
-                    "that cause thread safety issues is not allowed."
+                    "Critical Error: Passing SQLAlchemy Model instances that cause thread safety issues is not allowed."
                 )
 
 

api/core/app/apps/chat/app_generator.py

@@ -18,7 +18,7 @@ from core.app.apps.chat.generate_response_converter import ChatAppGenerateRespon
 from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
 from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
 from core.app.entities.app_invoke_entities import ChatAppGenerateEntity, InvokeFrom
-from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
+from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from extensions.ext_database import db
 from factories import file_factory
@@ -141,9 +141,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             model_conf=ModelConfigConverter.convert(app_config),
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=conversation.inputs
-            if conversation
-            else self._prepare_user_inputs(
+            inputs=self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,
@@ -237,7 +235,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
-            except (ValueError, InvokeError) as e:
+            except ValueError as e:
                 if dify_config.DEBUG:
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)

api/core/app/apps/completion/app_generator.py

@@ -17,7 +17,7 @@ from core.app.apps.completion.generate_response_converter import CompletionAppGe
 from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
 from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
 from core.app.entities.app_invoke_entities import CompletionAppGenerateEntity, InvokeFrom
-from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
+from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from extensions.ext_database import db
 from factories import file_factory
@@ -214,7 +214,7 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
-            except (ValueError, InvokeError) as e:
+            except ValueError as e:
                 if dify_config.DEBUG:
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)

api/core/app/apps/message_based_app_generator.py

@@ -89,6 +89,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
             Conversation.id == conversation_id,
             Conversation.app_id == app_model.id,
             Conversation.status == "normal",
+            Conversation.is_deleted.is_(False),
         ]
 
         if isinstance(user, Account):

api/core/app/apps/workflow/app_generator.py

@@ -20,7 +20,7 @@ from core.app.apps.workflow.generate_response_converter import WorkflowAppGenera
 from core.app.apps.workflow.generate_task_pipeline import WorkflowAppGenerateTaskPipeline
 from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
 from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse
-from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
+from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from extensions.ext_database import db
 from factories import file_factory
@@ -221,6 +221,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             single_iteration_run=WorkflowAppGenerateEntity.SingleIterationRunEntity(
                 node_id=node_id, inputs=args["inputs"]
             ),
+            workflow_run_id=str(uuid.uuid4()),
         )
         contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
 
@@ -270,7 +271,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
-            except (ValueError, InvokeError) as e:
+            except ValueError as e:
                 if dify_config.DEBUG:
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -1,7 +1,7 @@
 import logging
 import time
 from collections.abc import Generator
-from typing import Any, Optional, Union
+from typing import Optional, Union
 
 from sqlalchemy.orm import Session
 
@@ -58,7 +58,6 @@ from models.workflow import (
     Workflow,
     WorkflowAppLog,
     WorkflowAppLogCreatedFrom,
-    WorkflowNodeExecution,
     WorkflowRun,
     WorkflowRunStatus,
 )
@@ -66,16 +65,11 @@ from models.workflow import (
 logger = logging.getLogger(__name__)
 
 
-class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleManage):
+class WorkflowAppGenerateTaskPipeline:
     """
     WorkflowAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
 
-    _task_state: WorkflowTaskState
-    _application_generate_entity: WorkflowAppGenerateEntity
-    _workflow_system_variables: dict[SystemVariableKey, Any]
-    _wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
-
     def __init__(
         self,
         application_generate_entity: WorkflowAppGenerateEntity,
@@ -84,7 +78,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         user: Union[Account, EndUser],
         stream: bool,
     ) -> None:
-        super().__init__(
+        self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
             queue_manager=queue_manager,
             stream=stream,
@@ -101,19 +95,21 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         else:
             raise ValueError(f"Invalid user type: {type(user)}")
 
+        self._workflow_cycle_manager = WorkflowCycleManage(
+            application_generate_entity=application_generate_entity,
+            workflow_system_variables={
+                SystemVariableKey.FILES: application_generate_entity.files,
+                SystemVariableKey.USER_ID: user_session_id,
+                SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
+                SystemVariableKey.WORKFLOW_ID: workflow.id,
+                SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
+            },
+        )
+
+        self._application_generate_entity = application_generate_entity
         self._workflow_id = workflow.id
         self._workflow_features_dict = workflow.features_dict
-
-        self._workflow_system_variables = {
-            SystemVariableKey.FILES: application_generate_entity.files,
-            SystemVariableKey.USER_ID: user_session_id,
-            SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
-            SystemVariableKey.WORKFLOW_ID: workflow.id,
-            SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
-        }
-
         self._task_state = WorkflowTaskState()
-        self._wip_workflow_node_executions = {}
         self._workflow_run_id = ""
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
@@ -122,7 +118,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         :return:
         """
         generator = self._wrapper_process_stream_response(trace_manager=self._application_generate_entity.trace_manager)
-        if self._stream:
+        if self._base_task_pipeline._stream:
             return self._to_stream_response(generator)
         else:
             return self._to_blocking_response(generator)
@@ -237,29 +233,29 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         """
         graph_runtime_state = None
 
-        for queue_message in self._queue_manager.listen():
+        for queue_message in self._base_task_pipeline._queue_manager.listen():
             event = queue_message.event
 
             if isinstance(event, QueuePingEvent):
-                yield self._ping_stream_response()
+                yield self._base_task_pipeline._ping_stream_response()
             elif isinstance(event, QueueErrorEvent):
-                err = self._handle_error(event=event)
-                yield self._error_to_stream_response(err)
+                err = self._base_task_pipeline._handle_error(event=event)
+                yield self._base_task_pipeline._error_to_stream_response(err)
                 break
             elif isinstance(event, QueueWorkflowStartedEvent):
                 # override graph runtime state
                 graph_runtime_state = event.graph_runtime_state
 
-                with Session(db.engine) as session:
+                with Session(db.engine, expire_on_commit=False) as session:
                     # init workflow run
-                    workflow_run = self._handle_workflow_run_start(
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
                         session=session,
                         workflow_id=self._workflow_id,
                         user_id=self._user_id,
                         created_by_role=self._created_by_role,
                     )
                     self._workflow_run_id = workflow_run.id
-                    start_resp = self._workflow_start_to_stream_response(
+                    start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()
@@ -271,12 +267,14 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             ):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    workflow_node_execution = self._handle_workflow_node_execution_retried(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
                         session=session, workflow_run=workflow_run, event=event
                     )
-                    response = self._workflow_node_retry_to_stream_response(
+                    response = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -290,12 +288,14 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    workflow_node_execution = self._handle_node_execution_start(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
                         session=session, workflow_run=workflow_run, event=event
                     )
-                    node_start_response = self._workflow_node_start_to_stream_response(
+                    node_start_response = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -306,9 +306,11 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if node_start_response:
                     yield node_start_response
             elif isinstance(event, QueueNodeSucceededEvent):
-                with Session(db.engine) as session:
-                    workflow_node_execution = self._handle_workflow_node_execution_success(session=session, event=event)
-                    node_success_response = self._workflow_node_finish_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
+                        session=session, event=event
+                    )
+                    node_success_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -319,12 +321,12 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if node_success_response:
                     yield node_success_response
             elif isinstance(event, QueueNodeFailedEvent | QueueNodeInIterationFailedEvent | QueueNodeExceptionEvent):
-                with Session(db.engine) as session:
-                    workflow_node_execution = self._handle_workflow_node_execution_failed(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
                         session=session,
                         event=event,
                     )
-                    node_failed_response = self._workflow_node_finish_to_stream_response(
+                    node_failed_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
                         session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
@@ -339,13 +341,17 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    parallel_start_resp = self._workflow_parallel_branch_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    parallel_start_resp = (
+                        self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
+                            session=session,
+                            task_id=self._application_generate_entity.task_id,
+                            workflow_run=workflow_run,
+                            event=event,
+                        )
                     )
 
                 yield parallel_start_resp
@@ -354,13 +360,17 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    parallel_finish_resp = self._workflow_parallel_branch_finished_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    parallel_finish_resp = (
+                        self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
+                            session=session,
+                            task_id=self._application_generate_entity.task_id,
+                            workflow_run=workflow_run,
+                            event=event,
+                        )
                     )
 
                 yield parallel_finish_resp
@@ -369,9 +379,11 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_start_resp = self._workflow_iteration_start_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -384,9 +396,11 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_next_resp = self._workflow_iteration_next_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -399,9 +413,11 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
-                    iter_finish_resp = self._workflow_iteration_completed_to_stream_response(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
+                        session=session, workflow_run_id=self._workflow_run_id
+                    )
+                    iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -416,8 +432,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_success(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -431,7 +447,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                     # save workflow app log
                     self._save_workflow_app_log(session=session, workflow_run=workflow_run)
 
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run,
@@ -445,8 +461,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_partial_success(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -461,7 +477,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                     # save workflow app log
                     self._save_workflow_app_log(session=session, workflow_run=workflow_run)
 
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()
@@ -473,8 +489,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                 if not graph_runtime_state:
                     raise ValueError("graph runtime state not initialized.")
 
-                with Session(db.engine) as session:
-                    workflow_run = self._handle_workflow_run_failed(
+                with Session(db.engine, expire_on_commit=False) as session:
+                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
                         session=session,
                         workflow_run_id=self._workflow_run_id,
                         start_at=graph_runtime_state.start_at,
@@ -492,7 +508,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                     # save workflow app log
                     self._save_workflow_app_log(session=session, workflow_run=workflow_run)
 
-                    workflow_finish_resp = self._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
                         session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
                     )
                     session.commit()

api/core/app/entities/app_invoke_entities.py

@@ -195,7 +195,7 @@ class WorkflowAppGenerateEntity(AppGenerateEntity):
 
     # app config
     app_config: WorkflowUIBasedAppConfig
-    workflow_run_id: Optional[str] = None
+    workflow_run_id: str
 
     class SingleIterationRunEntity(BaseModel):
         """

api/core/app/task_pipeline/based_generate_task_pipeline.py

@@ -15,7 +15,6 @@ from core.app.entities.queue_entities import (
 from core.app.entities.task_entities import (
     ErrorStreamResponse,
     PingStreamResponse,
-    TaskState,
 )
 from core.errors.error import QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
@@ -30,22 +29,12 @@ class BasedGenerateTaskPipeline:
     BasedGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
 
-    _task_state: TaskState
-    _application_generate_entity: AppGenerateEntity
-
     def __init__(
         self,
         application_generate_entity: AppGenerateEntity,
         queue_manager: AppQueueManager,
         stream: bool,
     ) -> None:
-        """
-        Initialize GenerateTaskPipeline.
-        :param application_generate_entity: application generate entity
-        :param queue_manager: queue manager
-        :param user: user
-        :param stream: stream
-        """
         self._application_generate_entity = application_generate_entity
         self._queue_manager = queue_manager
         self._start_at = time.perf_counter()

api/core/app/task_pipeline/message_cycle_manage.py

@@ -31,10 +31,19 @@ from services.annotation_service import AppAnnotationService
 
 
 class MessageCycleManage:
-    _application_generate_entity: Union[
-        ChatAppGenerateEntity, CompletionAppGenerateEntity, AgentChatAppGenerateEntity, AdvancedChatAppGenerateEntity
-    ]
-    _task_state: Union[EasyUITaskState, WorkflowTaskState]
+    def __init__(
+        self,
+        *,
+        application_generate_entity: Union[
+            ChatAppGenerateEntity,
+            CompletionAppGenerateEntity,
+            AgentChatAppGenerateEntity,
+            AdvancedChatAppGenerateEntity,
+        ],
+        task_state: Union[EasyUITaskState, WorkflowTaskState],
+    ) -> None:
+        self._application_generate_entity = application_generate_entity
+        self._task_state = task_state
 
     def _generate_conversation_name(self, *, conversation_id: str, query: str) -> Optional[Thread]:
         """
@@ -136,7 +145,7 @@ class MessageCycleManage:
 
             # get extension
             if "." in message_file.url:
-                extension = f'.{message_file.url.split(".")[-1]}'
+                extension = f".{message_file.url.split('.')[-1]}"
                 if len(extension) > 10:
                     extension = ".bin"
             else:

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -34,7 +34,6 @@ from core.app.entities.task_entities import (
     ParallelBranchStartStreamResponse,
     WorkflowFinishStreamResponse,
     WorkflowStartStreamResponse,
-    WorkflowTaskState,
 )
 from core.file import FILE_MODEL_IDENTITY, File
 from core.model_runtime.utils.encoders import jsonable_encoder
@@ -58,13 +57,20 @@ from models.workflow import (
     WorkflowRunStatus,
 )
 
-from .exc import WorkflowNodeExecutionNotFoundError, WorkflowRunNotFoundError
+from .exc import WorkflowRunNotFoundError
 
 
 class WorkflowCycleManage:
-    _application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity]
-    _task_state: WorkflowTaskState
-    _workflow_system_variables: dict[SystemVariableKey, Any]
+    def __init__(
+        self,
+        *,
+        application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
+        workflow_system_variables: dict[SystemVariableKey, Any],
+    ) -> None:
+        self._workflow_run: WorkflowRun | None = None
+        self._workflow_node_executions: dict[str, WorkflowNodeExecution] = {}
+        self._application_generate_entity = application_generate_entity
+        self._workflow_system_variables = workflow_system_variables
 
     def _handle_workflow_run_start(
         self,
@@ -102,7 +108,8 @@ class WorkflowCycleManage:
         inputs = dict(WorkflowEntry.handle_special_values(inputs) or {})
 
         # init workflow run
-        workflow_run_id = str(self._workflow_system_variables.get(SystemVariableKey.WORKFLOW_RUN_ID, uuid4()))
+        # TODO: This workflow_run_id should always not be None, maybe we can use a more elegant way to handle this
+        workflow_run_id = str(self._workflow_system_variables.get(SystemVariableKey.WORKFLOW_RUN_ID) or uuid4())
 
         workflow_run = WorkflowRun()
         workflow_run.id = workflow_run_id
@@ -239,7 +246,7 @@ class WorkflowCycleManage:
         workflow_run.finished_at = datetime.now(UTC).replace(tzinfo=None)
         workflow_run.exceptions_count = exceptions_count
 
-        stmt = select(WorkflowNodeExecution).where(
+        stmt = select(WorkflowNodeExecution.node_execution_id).where(
             WorkflowNodeExecution.tenant_id == workflow_run.tenant_id,
             WorkflowNodeExecution.app_id == workflow_run.app_id,
             WorkflowNodeExecution.workflow_id == workflow_run.workflow_id,
@@ -247,16 +254,18 @@ class WorkflowCycleManage:
             WorkflowNodeExecution.workflow_run_id == workflow_run.id,
             WorkflowNodeExecution.status == WorkflowNodeExecutionStatus.RUNNING.value,
         )
-
-        running_workflow_node_executions = session.scalars(stmt).all()
+        ids = session.scalars(stmt).all()
+        # Use self._get_workflow_node_execution here to make sure the cache is updated
+        running_workflow_node_executions = [
+            self._get_workflow_node_execution(session=session, node_execution_id=id) for id in ids if id
+        ]
 
         for workflow_node_execution in running_workflow_node_executions:
+            now = datetime.now(UTC).replace(tzinfo=None)
             workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
             workflow_node_execution.error = error
-            workflow_node_execution.finished_at = datetime.now(UTC).replace(tzinfo=None)
-            workflow_node_execution.elapsed_time = (
-                workflow_node_execution.finished_at - workflow_node_execution.created_at
-            ).total_seconds()
+            workflow_node_execution.finished_at = now
+            workflow_node_execution.elapsed_time = (now - workflow_node_execution.created_at).total_seconds()
 
         if trace_manager:
             trace_manager.add_trace_task(
@@ -274,7 +283,7 @@ class WorkflowCycleManage:
         self, *, session: Session, workflow_run: WorkflowRun, event: QueueNodeStartedEvent
     ) -> WorkflowNodeExecution:
         workflow_node_execution = WorkflowNodeExecution()
-        workflow_node_execution.id = event.node_execution_id
+        workflow_node_execution.id = str(uuid4())
         workflow_node_execution.tenant_id = workflow_run.tenant_id
         workflow_node_execution.app_id = workflow_run.app_id
         workflow_node_execution.workflow_id = workflow_run.workflow_id
@@ -298,6 +307,8 @@ class WorkflowCycleManage:
         workflow_node_execution.created_at = datetime.now(UTC).replace(tzinfo=None)
 
         session.add(workflow_node_execution)
+
+        self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
         return workflow_node_execution
 
     def _handle_workflow_node_execution_success(
@@ -325,6 +336,7 @@ class WorkflowCycleManage:
         workflow_node_execution.finished_at = finished_at
         workflow_node_execution.elapsed_time = elapsed_time
 
+        workflow_node_execution = session.merge(workflow_node_execution)
         return workflow_node_execution
 
     def _handle_workflow_node_execution_failed(
@@ -364,6 +376,7 @@ class WorkflowCycleManage:
         workflow_node_execution.elapsed_time = elapsed_time
         workflow_node_execution.execution_metadata = execution_metadata
 
+        workflow_node_execution = session.merge(workflow_node_execution)
         return workflow_node_execution
 
     def _handle_workflow_node_execution_retried(
@@ -391,7 +404,7 @@ class WorkflowCycleManage:
         execution_metadata = json.dumps(merged_metadata)
 
         workflow_node_execution = WorkflowNodeExecution()
-        workflow_node_execution.id = event.node_execution_id
+        workflow_node_execution.id = str(uuid4())
         workflow_node_execution.tenant_id = workflow_run.tenant_id
         workflow_node_execution.app_id = workflow_run.app_id
         workflow_node_execution.workflow_id = workflow_run.workflow_id
@@ -415,6 +428,8 @@ class WorkflowCycleManage:
         workflow_node_execution.index = event.node_run_index
 
         session.add(workflow_node_execution)
+
+        self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
         return workflow_node_execution
 
     #################################################
@@ -811,22 +826,20 @@ class WorkflowCycleManage:
         return None
 
     def _get_workflow_run(self, *, session: Session, workflow_run_id: str) -> WorkflowRun:
-        """
-        Refetch workflow run
-        :param workflow_run_id: workflow run id
-        :return:
-        """
+        if self._workflow_run and self._workflow_run.id == workflow_run_id:
+            cached_workflow_run = self._workflow_run
+            cached_workflow_run = session.merge(cached_workflow_run)
+            return cached_workflow_run
         stmt = select(WorkflowRun).where(WorkflowRun.id == workflow_run_id)
         workflow_run = session.scalar(stmt)
         if not workflow_run:
             raise WorkflowRunNotFoundError(workflow_run_id)
+        self._workflow_run = workflow_run
 
         return workflow_run
 
     def _get_workflow_node_execution(self, session: Session, node_execution_id: str) -> WorkflowNodeExecution:
-        stmt = select(WorkflowNodeExecution).where(WorkflowNodeExecution.id == node_execution_id)
-        workflow_node_execution = session.scalar(stmt)
-        if not workflow_node_execution:
-            raise WorkflowNodeExecutionNotFoundError(node_execution_id)
-
-        return workflow_node_execution
+        if node_execution_id not in self._workflow_node_executions:
+            raise ValueError(f"Workflow node execution not found: {node_execution_id}")
+        cached_workflow_node_execution = self._workflow_node_executions[node_execution_id]
+        return session.merge(cached_workflow_node_execution)

api/core/external_data_tool/api/api.py

@@ -62,8 +62,9 @@ class ApiExternalDataTool(ExternalDataTool):
 
         if not api_based_extension:
             raise ValueError(
-                "[External data tool] API query failed, variable: {}, "
-                "error: api_based_extension_id is invalid".format(self.variable)
+                "[External data tool] API query failed, variable: {}, error: api_based_extension_id is invalid".format(
+                    self.variable
+                )
             )
 
         # decrypt api_key

api/core/file/models.py

@@ -90,7 +90,7 @@ class File(BaseModel):
     def markdown(self) -> str:
         url = self.generate_url()
         if self.type == FileType.IMAGE:
-            text = f'![{self.filename or ""}]({url})'
+            text = f"![{self.filename or ''}]({url})"
         else:
             text = f"[{self.filename or url}]({url})"
 

api/core/helper/ssrf_proxy.py

@@ -11,15 +11,6 @@ from configs import dify_config
 
 SSRF_DEFAULT_MAX_RETRIES = dify_config.SSRF_DEFAULT_MAX_RETRIES
 
-proxy_mounts = (
-    {
-        "http://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTP_URL),
-        "https://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTPS_URL),
-    }
-    if dify_config.SSRF_PROXY_HTTP_URL and dify_config.SSRF_PROXY_HTTPS_URL
-    else None
-)
-
 BACKOFF_FACTOR = 0.5
 STATUS_FORCELIST = [429, 500, 502, 503, 504]
 
@@ -51,7 +42,11 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs):
             if dify_config.SSRF_PROXY_ALL_URL:
                 with httpx.Client(proxy=dify_config.SSRF_PROXY_ALL_URL) as client:
                     response = client.request(method=method, url=url, **kwargs)
-            elif proxy_mounts:
+            elif dify_config.SSRF_PROXY_HTTP_URL and dify_config.SSRF_PROXY_HTTPS_URL:
+                proxy_mounts = {
+                    "http://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTP_URL),
+                    "https://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTPS_URL),
+                }
                 with httpx.Client(mounts=proxy_mounts) as client:
                     response = client.request(method=method, url=url, **kwargs)
             else:

api/core/indexing_runner.py

@@ -530,7 +530,6 @@ class IndexingRunner:
         # chunk nodes by chunk size
         indexing_start_at = time.perf_counter()
         tokens = 0
-        chunk_size = 10
         if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
             # create keyword index
             create_keyword_thread = threading.Thread(
@@ -539,11 +538,22 @@ class IndexingRunner:
             )
             create_keyword_thread.start()
 
+        max_workers = 10
         if dataset.indexing_technique == "high_quality":
-            with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
+            with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
                 futures = []
-                for i in range(0, len(documents), chunk_size):
-                    chunk_documents = documents[i : i + chunk_size]
+
+                # Distribute documents into multiple groups based on the hash values of page_content
+                # This is done to prevent multiple threads from processing the same document,
+                # Thereby avoiding potential database insertion deadlocks
+                document_groups: list[list[Document]] = [[] for _ in range(max_workers)]
+                for document in documents:
+                    hash = helper.generate_text_hash(document.page_content)
+                    group_index = int(hash, 16) % max_workers
+                    document_groups[group_index].append(document)
+                for chunk_documents in document_groups:
+                    if len(chunk_documents) == 0:
+                        continue
                     futures.append(
                         executor.submit(
                             self._process_chunk,

api/core/llm_generator/prompts.py

@@ -131,7 +131,7 @@ JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE = (
 SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
     "Please help me predict the three most likely questions that human would ask, "
     "and keeping each question under 20 characters.\n"
-    "MAKE SURE your output is the SAME language as the Assistant's latest response"
+    "MAKE SURE your output is the SAME language as the Assistant's latest response. "
     "The output must be an array in JSON format following the specified schema:\n"
     '["question1","question2","question3"]\n'
 )

api/core/model_runtime/entities/__init__.py

@@ -1,4 +1,4 @@
-from .llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
+from .llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from .message_entities import (
     AssistantPromptMessage,
     AudioPromptMessageContent,
@@ -23,6 +23,7 @@ __all__ = [
     "AudioPromptMessageContent",
     "DocumentPromptMessageContent",
     "ImagePromptMessageContent",
+    "LLMMode",
     "LLMResult",
     "LLMResultChunk",
     "LLMResultChunkDelta",

api/core/model_runtime/entities/llm_entities.py

@@ -1,5 +1,5 @@
 from decimal import Decimal
-from enum import Enum
+from enum import StrEnum
 from typing import Optional
 
 from pydantic import BaseModel
@@ -8,7 +8,7 @@ from core.model_runtime.entities.message_entities import AssistantPromptMessage,
 from core.model_runtime.entities.model_entities import ModelUsage, PriceInfo
 
 
-class LLMMode(Enum):
+class LLMMode(StrEnum):
     """
     Enum class for large language model mode.
     """

api/core/model_runtime/model_providers/__base/ai_model.py

@@ -221,13 +221,12 @@ class AIModel(ABC):
         :param credentials: model credentials
         :return: model schema
         """
-        # get predefined models (predefined_models)
-        models = self.predefined_models()
-
-        model_map = {model.model: model for model in models}
-        if model in model_map:
-            return model_map[model]
+        # Try to get model schema from predefined models
+        for predefined_model in self.predefined_models():
+            if model == predefined_model.model:
+                return predefined_model
 
+        # Try to get model schema from credentials
         if credentials:
             model_schema = self.get_customizable_model_schema_from_credentials(model, credentials)
             if model_schema:

api/core/model_runtime/model_providers/__base/large_language_model.py

@@ -400,6 +400,32 @@ if you are not sure about the structure.
                     ),
                 )
 
+    def _wrap_thinking_by_reasoning_content(self, delta: dict, is_reasoning: bool) -> tuple[str, bool]:
+        """
+        If the reasoning response is from delta.get("reasoning_content"), we wrap
+        it with HTML think tag.
+
+        :param delta: delta dictionary from LLM streaming response
+        :param is_reasoning: is reasoning
+        :return: tuple of (processed_content, is_reasoning)
+        """
+
+        content = delta.get("content") or ""
+        reasoning_content = delta.get("reasoning_content")
+
+        if reasoning_content:
+            if not is_reasoning:
+                content = "<think>\n" + reasoning_content
+                is_reasoning = True
+            else:
+                content = reasoning_content
+        elif is_reasoning and content:
+            # do not end reasoning when content is empty
+            # there may be more reasoning_content later that follows previous reasoning closely
+            content = "\n</think>" + content
+            is_reasoning = False
+        return content, is_reasoning
+
     def _invoke_result_generator(
         self,
         model: str,

api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenzier.py

@@ -1,8 +1,8 @@
-from os.path import abspath, dirname, join
+import logging
 from threading import Lock
 from typing import Any
 
-from transformers import GPT2Tokenizer as TransformerGPT2Tokenizer  # type: ignore
+logger = logging.getLogger(__name__)
 
 _tokenizer: Any = None
 _lock = Lock()
@@ -15,11 +15,16 @@ class GPT2Tokenizer:
         use gpt2 tokenizer to get num tokens
         """
         _tokenizer = GPT2Tokenizer.get_encoder()
-        tokens = _tokenizer.encode(text, verbose=False)
+        tokens = _tokenizer.encode(text)
         return len(tokens)
 
     @staticmethod
     def get_num_tokens(text: str) -> int:
+        # Because this process needs more cpu resource, we turn this back before we find a better way to handle it.
+        #
+        # future = _executor.submit(GPT2Tokenizer._get_num_tokens_by_gpt2, text)
+        # result = future.result()
+        # return cast(int, result)
         return GPT2Tokenizer._get_num_tokens_by_gpt2(text)
 
     @staticmethod
@@ -27,8 +32,20 @@ class GPT2Tokenizer:
         global _tokenizer, _lock
         with _lock:
             if _tokenizer is None:
-                base_path = abspath(__file__)
-                gpt2_tokenizer_path = join(dirname(base_path), "gpt2")
-                _tokenizer = TransformerGPT2Tokenizer.from_pretrained(gpt2_tokenizer_path)
+                # Try to use tiktoken to get the tokenizer because it is faster
+                #
+                try:
+                    import tiktoken
+
+                    _tokenizer = tiktoken.get_encoding("gpt2")
+                except Exception:
+                    from os.path import abspath, dirname, join
+
+                    from transformers import GPT2Tokenizer as TransformerGPT2Tokenizer  # type: ignore
+
+                    base_path = abspath(__file__)
+                    gpt2_tokenizer_path = join(dirname(base_path), "gpt2")
+                    _tokenizer = TransformerGPT2Tokenizer.from_pretrained(gpt2_tokenizer_path)
+                    logger.info("Fallback to Transformers' GPT-2 tokenizer from tiktoken")
 
             return _tokenizer

api/core/model_runtime/model_providers/_position.yaml

@@ -1,4 +1,5 @@
 - openai
+- deepseek
 - anthropic
 - azure_openai
 - google
@@ -32,7 +33,6 @@
 - localai
 - volcengine_maas
 - openai_api_compatible
-- deepseek
 - hunyuan
 - siliconflow
 - perfxcloud

api/core/model_runtime/model_providers/azure_ai_studio/azure_ai_studio.yaml

@@ -51,6 +51,40 @@ model_credential_schema:
       show_on:
         - variable: __model_type
           value: llm
+    - variable: mode
+      show_on:
+        - variable: __model_type
+          value: llm
+      label:
+        en_US: Completion mode
+      type: select
+      required: false
+      default: chat
+      placeholder:
+        zh_Hans: 选择对话类型
+        en_US: Select completion mode
+      options:
+        - value: completion
+          label:
+            en_US: Completion
+            zh_Hans: 补全
+        - value: chat
+          label:
+            en_US: Chat
+            zh_Hans: 对话
+    - variable: context_size
+      label:
+        zh_Hans: 模型上下文长度
+        en_US: Model context size
+      required: true
+      show_on:
+        - variable: __model_type
+          value: llm
+      type: text-input
+      default: "4096"
+      placeholder:
+        zh_Hans: 在此输入您的模型上下文长度
+        en_US: Enter your Model context size
     - variable: jwt_token
       required: true
       label:

api/core/model_runtime/model_providers/azure_ai_studio/llm/llm.py

@@ -1,9 +1,9 @@
 import logging
-from collections.abc import Generator
+from collections.abc import Generator, Sequence
 from typing import Any, Optional, Union
 
 from azure.ai.inference import ChatCompletionsClient
-from azure.ai.inference.models import StreamingChatCompletionsUpdate
+from azure.ai.inference.models import StreamingChatCompletionsUpdate, SystemMessage, UserMessage
 from azure.core.credentials import AzureKeyCredential
 from azure.core.exceptions import (
     ClientAuthenticationError,
@@ -20,7 +20,7 @@ from azure.core.exceptions import (
 )
 
 from core.model_runtime.callbacks.base_callback import Callback
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
     PromptMessage,
@@ -30,6 +30,7 @@ from core.model_runtime.entities.model_entities import (
     AIModelEntity,
     FetchFrom,
     I18nObject,
+    ModelPropertyKey,
     ModelType,
     ParameterRule,
     ParameterType,
@@ -60,10 +61,10 @@ class AzureAIStudioLargeLanguageModel(LargeLanguageModel):
         self,
         model: str,
         credentials: dict,
-        prompt_messages: list[PromptMessage],
+        prompt_messages: Sequence[PromptMessage],
         model_parameters: dict,
-        tools: Optional[list[PromptMessageTool]] = None,
-        stop: Optional[list[str]] = None,
+        tools: Optional[Sequence[PromptMessageTool]] = None,
+        stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
     ) -> Union[LLMResult, Generator]:
@@ -82,8 +83,8 @@ class AzureAIStudioLargeLanguageModel(LargeLanguageModel):
         """
 
         if not self.client:
-            endpoint = credentials.get("endpoint")
-            api_key = credentials.get("api_key")
+            endpoint = str(credentials.get("endpoint"))
+            api_key = str(credentials.get("api_key"))
             self.client = ChatCompletionsClient(endpoint=endpoint, credential=AzureKeyCredential(api_key))
 
         messages = [{"role": msg.role.value, "content": msg.content} for msg in prompt_messages]
@@ -94,6 +95,7 @@ class AzureAIStudioLargeLanguageModel(LargeLanguageModel):
             "temperature": model_parameters.get("temperature", 0),
             "top_p": model_parameters.get("top_p", 1),
             "stream": stream,
+            "model": model,
         }
 
         if stop:
@@ -255,10 +257,16 @@ class AzureAIStudioLargeLanguageModel(LargeLanguageModel):
         :return:
         """
         try:
-            endpoint = credentials.get("endpoint")
-            api_key = credentials.get("api_key")
+            endpoint = str(credentials.get("endpoint"))
+            api_key = str(credentials.get("api_key"))
             client = ChatCompletionsClient(endpoint=endpoint, credential=AzureKeyCredential(api_key))
-            client.get_model_info()
+            client.complete(
+                messages=[
+                    SystemMessage(content="I say 'ping', you say 'pong'"),
+                    UserMessage(content="ping"),
+                ],
+                model=model,
+            )
         except Exception as ex:
             raise CredentialsValidateFailedError(str(ex))
 
@@ -327,7 +335,10 @@ class AzureAIStudioLargeLanguageModel(LargeLanguageModel):
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_type=ModelType.LLM,
             features=[],
-            model_properties={},
+            model_properties={
+                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "4096")),
+                ModelPropertyKey.MODE: credentials.get("mode", LLMMode.CHAT),
+            },
             parameter_rules=rules,
         )
 

api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml

@@ -53,6 +53,9 @@ model_credential_schema:
       type: select
       required: true
       options:
+        - label:
+            en_US: 2024-12-01-preview
+          value: 2024-12-01-preview
         - label:
             en_US: 2024-10-01-preview
           value: 2024-10-01-preview
@@ -135,6 +138,18 @@ model_credential_schema:
           show_on:
             - variable: __model_type
               value: llm
+        - label:
+            en_US: o3-mini
+          value: o3-mini
+          show_on:
+            - variable: __model_type
+              value: llm
+        - label:
+            en_US: o3-mini-2025-01-31
+          value: o3-mini-2025-01-31
+          show_on:
+            - variable: __model_type
+              value: llm
         - label:
             en_US: o1-preview
           value: o1-preview

api/core/model_runtime/model_providers/azure_openai/llm/llm.py

@@ -108,7 +108,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
 
         if not ai_model_entity:
-            raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
+            raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
 
         try:
             client = AzureOpenAI(**self._to_credential_kwargs(credentials))

api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py

@@ -130,7 +130,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
             raise CredentialsValidateFailedError("Base Model Name is required")
 
         if not self._get_ai_model_entity(credentials["base_model_name"], model):
-            raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
+            raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
 
         try:
             credentials_kwargs = self._to_credential_kwargs(credentials)

api/core/model_runtime/model_providers/bedrock/bedrock.yaml

@@ -44,6 +44,7 @@ provider_credential_schema:
       label:
         en_US: AWS Region
         zh_Hans: AWS 地区
+        ja_JP: AWS リージョン
       type: select
       default: us-east-1
       options:
@@ -51,62 +52,86 @@ provider_credential_schema:
           label:
             en_US: US East (N. Virginia)
             zh_Hans: 美国东部 (弗吉尼亚北部)
+            ja_JP: 米国 (バージニア北部)
         - value: us-east-2
           label:
             en_US: US East (Ohio)
-            zh_Hans: 美国东部 (弗吉尼亚北部)
+            zh_Hans: 美国东部 (俄亥俄)
+            ja_JP: 米国 (オハイオ)
         - value: us-west-2
           label:
             en_US: US West (Oregon)
             zh_Hans: 美国西部 (俄勒冈州)
+            ja_JP: 米国 (オレゴン)
         - value: ap-south-1
           label:
             en_US: Asia Pacific (Mumbai)
             zh_Hans: 亚太地区（孟买）
+            ja_JP: アジアパシフィック (ムンバイ)
         - value: ap-southeast-1
           label:
             en_US: Asia Pacific (Singapore)
             zh_Hans: 亚太地区 (新加坡)
+            ja_JP: アジアパシフィック (シンガポール)
         - value: ap-southeast-2
           label:
             en_US: Asia Pacific (Sydney)
             zh_Hans: 亚太地区 (悉尼)
+            ja_JP: アジアパシフィック (シドニー)
         - value: ap-northeast-1
           label:
             en_US: Asia Pacific (Tokyo)
             zh_Hans: 亚太地区 (东京)
+            ja_JP: アジアパシフィック (東京)
         - value: ap-northeast-2
           label:
             en_US: Asia Pacific (Seoul)
             zh_Hans: 亚太地区（首尔）
+            ja_JP: アジアパシフィック (ソウル)
         - value: ca-central-1
           label:
             en_US: Canada (Central)
             zh_Hans: 加拿大（中部）
+            ja_JP: カナダ (中部)
         - value: eu-central-1
           label:
             en_US: Europe (Frankfurt)
             zh_Hans: 欧洲 (法兰克福)
+            ja_JP: 欧州 (フランクフルト)
         - value: eu-west-1
           label:
             en_US: Europe (Ireland)
             zh_Hans: 欧洲（爱尔兰）
+            ja_JP: 欧州 (アイルランド)
         - value: eu-west-2
           label:
             en_US: Europe (London)
             zh_Hans: 欧洲西部 (伦敦)
+            ja_JP: 欧州 (ロンドン)
         - value: eu-west-3
           label:
             en_US: Europe (Paris)
             zh_Hans: 欧洲（巴黎）
+            ja_JP: 欧州 (パリ)
         - value: sa-east-1
           label:
             en_US: South America (São Paulo)
             zh_Hans: 南美洲（圣保罗）
+            ja_JP: 南米 (サンパウロ)
         - value: us-gov-west-1
           label:
             en_US: AWS GovCloud (US-West)
             zh_Hans: AWS GovCloud (US-West)
+            ja_JP: AWS GovCloud (米国西部)
+    - variable: bedrock_endpoint_url
+      label:
+        zh_Hans: Bedrock Endpoint URL
+        en_US: Bedrock Endpoint URL
+      type: text-input
+      required: false
+      placeholder:
+        zh_Hans: 在此输入您的 Bedrock Endpoint URL, 如：https://123456.cloudfront.net
+        en_US: Enter your Bedrock Endpoint URL, e.g. https://123456.cloudfront.net
     - variable: model_for_validation
       required: false
       label:

api/core/model_runtime/model_providers/bedrock/get_bedrock_client.py

@@ -13,6 +13,7 @@ def get_bedrock_client(service_name: str, credentials: Mapping[str, str]):
     client_config = Config(region_name=region_name)
     aws_access_key_id = credentials.get("aws_access_key_id")
     aws_secret_access_key = credentials.get("aws_secret_access_key")
+    bedrock_endpoint_url = credentials.get("bedrock_endpoint_url")
 
     if aws_access_key_id and aws_secret_access_key:
         # use aksk to call bedrock
@@ -21,6 +22,7 @@ def get_bedrock_client(service_name: str, credentials: Mapping[str, str]):
             config=client_config,
             aws_access_key_id=aws_access_key_id,
             aws_secret_access_key=aws_secret_access_key,
+            **({"endpoint_url": bedrock_endpoint_url} if bedrock_endpoint_url else {}),
         )
     else:
         # use iam without aksk to call

api/core/model_runtime/model_providers/bedrock/rerank/rerank.py

@@ -70,7 +70,7 @@ class BedrockRerankModel(RerankModel):
         rerankingConfiguration = {
             "type": "BEDROCK_RERANKING_MODEL",
             "bedrockRerankingConfiguration": {
-                "numberOfResults": top_n,
+                "numberOfResults": min(top_n, len(text_sources)),
                 "modelConfiguration": {
                     "modelArn": model_package_arn,
                 },

api/core/model_runtime/model_providers/cohere/llm/llm.py

@@ -677,16 +677,17 @@ class CohereLargeLanguageModel(LargeLanguageModel):
 
         :return: model schema
         """
-        # get model schema
-        models = self.predefined_models()
-        model_map = {model.model: model for model in models}
-
         mode = credentials.get("mode")
+        base_model_schema = None
+        for predefined_model in self.predefined_models():
+            if (
+                mode == "chat" and predefined_model.model == "command-light-chat"
+            ) or predefined_model.model == "command-light":
+                base_model_schema = predefined_model
+                break
 
-        if mode == "chat":
-            base_model_schema = model_map["command-light-chat"]
-        else:
-            base_model_schema = model_map["command-light"]
+        if not base_model_schema:
+            raise ValueError("Model not found")
 
         base_model_schema = cast(AIModelEntity, base_model_schema)
 

api/core/model_runtime/model_providers/deepseek/llm/_position.yaml

@@ -1,2 +1,3 @@
 - deepseek-chat
 - deepseek-coder
+- deepseek-reasoner

api/core/model_runtime/model_providers/deepseek/llm/deepseek-chat.yaml

@@ -10,7 +10,7 @@ features:
   - stream-tool-call
 model_properties:
   mode: chat
-  context_size: 128000
+  context_size: 64000
 parameter_rules:
   - name: temperature
     use_template: temperature

api/core/model_runtime/model_providers/deepseek/llm/deepseek-coder.yaml

@@ -10,7 +10,7 @@ features:
   - stream-tool-call
 model_properties:
   mode: chat
-  context_size: 128000
+  context_size: 64000
 parameter_rules:
   - name: temperature
     use_template: temperature