feat: convert components to dynamic imports for improved performance

This PR introduces UUIDv7 implementations in both Python and SQL to establish the foundation for migrating from UUIDv4 to UUIDv7 as proposed in #19754.

ID generation algorithm of existing models are not changed, and new models should use UUIDv7 for ID generation.

Close #19754.

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -8,13 +8,13 @@ body:
       label: Self Checks
       description: "To make sure we get to you in time, please check the following :)"
       options:
+        - label: I have read the [Contributing Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) and [Language Policy](https://github.com/langgenius/dify/issues/1542).
+          required: true
         - label: This is only for bug report, if you would like to ask a question, please head to [Discussions](https://github.com/langgenius/dify/discussions/categories/general).
           required: true
         - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
           required: true
-        - label: I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
-          required: true
-        - label: "[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:)"
+        - label: I confirm that I am using English to submit this report, otherwise it will be closed.
           required: true
         - label: "Please do not modify this template :) and fill in all the required fields."
           required: true
@@ -42,20 +42,22 @@ body:
     attributes:
       label: Steps to reproduce
       description: We highly suggest including screenshots and a bug report log. Please use the right markdown syntax for code blocks.
-      placeholder: Having detailed steps helps us reproduce the bug.
+      placeholder: Having detailed steps helps us reproduce the bug. If you have logs, please use fenced code blocks (triple backticks ```) to format them.
     validations:
       required: true
 
   - type: textarea
     attributes:
       label: ✔️ Expected Behavior
-      placeholder: What were you expecting?
+      description: Describe what you expected to happen.
+      placeholder: What were you expecting? Please do not copy and paste the steps to reproduce here.
     validations:
-      required: false
+      required: true
 
   - type: textarea
     attributes:
       label: ❌ Actual Behavior
-      placeholder: What happened instead?
+      description: Describe what actually happened.
+      placeholder: What happened instead? Please do not copy and paste the steps to reproduce here.
     validations:
       required: false

.github/ISSUE_TEMPLATE/config.yml

@@ -1,5 +1,11 @@
 blank_issues_enabled: false
 contact_links:
+  - name: "\U0001F4A1 Model Providers & Plugins"
+    url: "https://github.com/langgenius/dify-official-plugins/issues/new/choose"
+    about: Report issues with official plugins or model providers, you will need to provide the plugin version and other relevant details.
+  - name: "\U0001F4AC Documentation Issues"
+    url: "https://github.com/langgenius/dify-docs/issues/new"
+    about: Report issues with the documentation, such as typos, outdated information, or missing content. Please provide the specific section and details of the issue.
   - name: "\U0001F4E7 Discussions"
     url: https://github.com/langgenius/dify/discussions/categories/general
-    about: General discussions and request help from the community
+    about: General discussions and seek help from the community

.github/ISSUE_TEMPLATE/document_issue.yml

@@ -1,24 +0,0 @@
-name: "📚 Documentation Issue"
-description: Report issues in our documentation
-labels:
-  - documentation
-body:
-  - type: checkboxes
-    attributes:
-      label: Self Checks
-      description: "To make sure we get to you in time, please check the following :)"
-      options:
-        - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
-          required: true
-        - label: I confirm that I am using English to submit report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
-          required: true
-        - label: "[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:)"
-          required: true
-        - label: "Please do not modify this template :) and fill in all the required fields."
-          required: true
-  - type: textarea
-    attributes:
-      label: Provide a description of requested docs changes
-      placeholder: Briefly describe which document needs to be corrected and why.
-    validations:
-      required: true

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -8,11 +8,11 @@ body:
       label: Self Checks
       description: "To make sure we get to you in time, please check the following :)"
       options:
+        - label: I have read the [Contributing Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) and [Language Policy](https://github.com/langgenius/dify/issues/1542).
+          required: true
         - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
           required: true
-        - label: I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
-          required: true
-        - label: "[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:)"
+        - label: I confirm that I am using English to submit this report, otherwise it will be closed.
           required: true
         - label: "Please do not modify this template :) and fill in all the required fields."
           required: true

.github/ISSUE_TEMPLATE/translation_issue.yml

@@ -1,55 +0,0 @@
-name: "🌐 Localization/Translation issue"
-description: Report incorrect translations. [please use English :)]
-labels:
-  - translation
-body:
-  - type: checkboxes
-    attributes:
-      label: Self Checks
-      description: "To make sure we get to you in time, please check the following :)"
-      options:
-        - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
-          required: true
-        - label: I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
-          required: true
-        - label: "[FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:)"
-          required: true
-        - label: "Please do not modify this template :) and fill in all the required fields."
-          required: true
-  - type: input
-    attributes:
-      label: Dify version
-      description: Hover over system tray icon or look at Settings
-    validations:
-      required: true
-  - type: input
-    attributes:
-      label: Utility with translation issue
-      placeholder: Some area
-      description: Please input here the utility with the translation issue
-    validations:
-      required: true
-  - type: input
-    attributes:
-      label: 🌐 Language affected
-      placeholder: "German"
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: ❌ Actual phrase(s)
-      placeholder: What is there? Please include a screenshot as that is extremely helpful.
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: ✔️ Expected phrase(s)
-      placeholder: What was expected?
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: ℹ Why is the current translation wrong
-      placeholder: Why do you feel this is incorrect?
-    validations:
-      required: true

.github/workflows/api-tests.yml

@@ -47,15 +47,17 @@ jobs:
       - name: Run Unit tests
         run: |
           uv run --project api bash dev/pytest/pytest_unit_tests.sh
+
+      - name: Coverage Summary
+        run: |
+          set -x
           # Extract coverage percentage and create a summary
           TOTAL_COVERAGE=$(python -c 'import json; print(json.load(open("coverage.json"))["totals"]["percent_covered_display"])')
 
           # Create a detailed coverage summary
           echo "### Test Coverage Summary :test_tube:" >> $GITHUB_STEP_SUMMARY
           echo "Total Coverage: ${TOTAL_COVERAGE}%" >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
-          uv run --project api coverage report >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
+          uv run --project api coverage report --format=markdown >> $GITHUB_STEP_SUMMARY
 
       - name: Run dify config tests
         run: uv run --project api dev/pytest/pytest_config_tests.py

.gitignore

@@ -214,3 +214,4 @@ mise.toml
 
 # AI Assistant
 .roo/
+api/.env.backup

README.md

@@ -54,7 +54,7 @@
   <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
-Dify is an open-source LLM app development platform. Its intuitive interface combines agentic AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more, allowing you to quickly move from prototype to production.
+Dify is an open-source platform for developing LLM applications. Its intuitive interface combines agentic AI workflows, RAG pipelines, agent capabilities, model management, observability features, and more—allowing you to quickly move from prototype to production.
 
 ## Quick start
 
@@ -65,7 +65,7 @@ Dify is an open-source LLM app development platform. Its intuitive interface com
 
 </br>
 
-The easiest way to start the Dify server is through [docker compose](docker/docker-compose.yaml). Before running Dify with the following commands, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:
+The easiest way to start the Dify server is through [Docker Compose](docker/docker-compose.yaml). Before running Dify with the following commands, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:
 
 ```bash
 cd dify
@@ -205,6 +205,7 @@ If you'd like to configure a highly-available setup, there are community-contrib
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Using Terraform for Deployment
 
@@ -261,8 +262,8 @@ At the same time, please consider supporting Dify by sharing it on social media
 
 ## Security disclosure
 
-To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions to security@dify.ai and we will provide you with a more detailed answer.
+To protect your privacy, please avoid posting security issues on GitHub. Instead, report issues to security@dify.ai, and our team will respond with detailed answer.
 
 ## License
 
-This repository is available under the [Dify Open Source License](LICENSE), which is essentially Apache 2.0 with a few additional restrictions.
+This repository is licensed under the [Dify Open Source License](LICENSE), based on Apache 2.0 with additional conditions.

README_AR.md

@@ -188,6 +188,7 @@ docker compose up -d
 - [رسم بياني Helm من قبل @magicsong](https://github.com/magicsong/ai-charts)
 - [ملف YAML من قبل @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [ملف YAML من قبل @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 جديد! ملفات YAML (تدعم Dify v1.6.0) بواسطة @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### استخدام Terraform للتوزيع
 

README_BN.md

@@ -204,6 +204,8 @@ GitHub-এ ডিফাইকে স্টার দিয়ে রাখুন
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 নতুন! YAML ফাইলসমূহ (Dify v1.6.0 সমর্থিত) তৈরি করেছেন @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
+
 
 #### টেরাফর্ম ব্যবহার করে ডিপ্লয়
 

README_CN.md

@@ -194,9 +194,9 @@ docker compose up -d
 
 如果您需要自定义配置，请参考 [.env.example](docker/.env.example) 文件中的注释，并更新 `.env` 文件中对应的值。此外，您可能需要根据您的具体部署环境和需求对 `docker-compose.yaml` 文件本身进行调整，例如更改镜像版本、端口映射或卷挂载。完成任何更改后，请重新运行 `docker-compose up -d`。您可以在[此处](https://docs.dify.ai/getting-started/install-self-hosted/environments)找到可用环境变量的完整列表。
 
-#### 使用 Helm Chart 部署
+#### 使用 Helm Chart 或 Kubernetes 资源清单（YAML）部署
 
-使用 [Helm Chart](https://helm.sh/) 版本或者 YAML 文件，可以在 Kubernetes 上部署 Dify。
+使用 [Helm Chart](https://helm.sh/) 版本或者 Kubernetes 资源清单（YAML），可以在 Kubernetes 上部署 Dify。
 
 - [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
 - [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
@@ -204,6 +204,10 @@ docker compose up -d
 - [YAML 文件 by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
 
+- [🚀 NEW! YAML 文件 (支持 Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
+
+
+
 #### 使用 Terraform 部署
 
 使用 [terraform](https://www.terraform.io/) 一键将 Dify 部署到云平台

README_DE.md

@@ -203,6 +203,7 @@ Falls Sie eine hochverfügbare Konfiguration einrichten möchten, gibt es von de
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Terraform für die Bereitstellung verwenden
 

README_ES.md

@@ -203,6 +203,7 @@ Si desea configurar una configuración de alta disponibilidad, la comunidad prop
 - [Gráfico Helm por @magicsong](https://github.com/magicsong/ai-charts)
 - [Ficheros YAML por @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [Ficheros YAML por @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 ¡NUEVO! Archivos YAML (compatible con Dify v1.6.0) por @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Uso de Terraform para el despliegue
 

README_FR.md

@@ -201,6 +201,7 @@ Si vous souhaitez configurer une configuration haute disponibilité, la communau
 - [Helm Chart par @magicsong](https://github.com/magicsong/ai-charts)
 - [Fichier YAML par @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [Fichier YAML par @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NOUVEAU ! Fichiers YAML (compatible avec Dify v1.6.0) par @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Utilisation de Terraform pour le déploiement
 

README_JA.md

@@ -202,6 +202,7 @@ docker compose up -d
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 新着！YAML ファイル（Dify v1.6.0 対応）by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Terraformを使用したデプロイ
 

README_KL.md

@@ -201,6 +201,7 @@ If you'd like to configure a highly-available setup, there are community-contrib
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Terraform atorlugu pilersitsineq
 

README_KR.md

@@ -195,6 +195,7 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했
 - [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Terraform을 사용한 배포
 

README_PT.md

@@ -200,6 +200,7 @@ Se deseja configurar uma instalação de alta disponibilidade, há [Helm Charts]
 - [Helm Chart de @magicsong](https://github.com/magicsong/ai-charts)
 - [Arquivo YAML por @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [Arquivo YAML por @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NOVO! Arquivos YAML (Compatível com Dify v1.6.0) por @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Usando o Terraform para Implantação
 

README_SI.md

@@ -201,6 +201,7 @@ Star Dify on GitHub and be instantly notified of new releases.
 - [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
 - [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Uporaba Terraform za uvajanje
 

README_TR.md

@@ -194,6 +194,7 @@ Yüksek kullanılabilirliğe sahip bir kurulum yapılandırmak isterseniz, Dify'
 - [@BorisPolonsky tarafından Helm Chart](https://github.com/BorisPolonsky/dify-helm)
 - [@Winson-030 tarafından YAML dosyası](https://github.com/Winson-030/dify-kubernetes)
 - [@wyy-holding tarafından YAML dosyası](https://github.com/wyy-holding/dify-k8s)
+- [🚀 YENİ! YAML dosyaları (Dify v1.6.0 destekli) @Zhoneym tarafından](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Dağıtım için Terraform Kullanımı
 

README_TW.md

@@ -197,12 +197,13 @@ Dify 的所有功能都提供相應的 API，因此您可以輕鬆地將 Dify
 
 如果您需要自定義配置，請參考我們的 [.env.example](docker/.env.example) 文件中的註釋，並在您的 `.env` 文件中更新相應的值。此外，根據您特定的部署環境和需求，您可能需要調整 `docker-compose.yaml` 文件本身，例如更改映像版本、端口映射或卷掛載。進行任何更改後，請重新運行 `docker-compose up -d`。您可以在[這裡](https://docs.dify.ai/getting-started/install-self-hosted/environments)找到可用環境變數的完整列表。
 
-如果您想配置高可用性設置，社區貢獻的 [Helm Charts](https://helm.sh/) 和 YAML 文件允許在 Kubernetes 上部署 Dify。
+如果您想配置高可用性設置，社區貢獻的 [Helm Charts](https://helm.sh/) 和 Kubernetes 資源清單（YAML）允許在 Kubernetes 上部署 Dify。
 
 - [由 @LeoQuote 提供的 Helm Chart](https://github.com/douban/charts/tree/master/charts/dify)
 - [由 @BorisPolonsky 提供的 Helm Chart](https://github.com/BorisPolonsky/dify-helm)
 - [由 @Winson-030 提供的 YAML 文件](https://github.com/Winson-030/dify-kubernetes)
 - [由 @wyy-holding 提供的 YAML 文件](https://github.com/wyy-holding/dify-k8s)
+- [🚀 NEW! YAML 檔案（支援 Dify v1.6.0）by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 ### 使用 Terraform 進行部署
 

README_VI.md

@@ -196,6 +196,7 @@ Nếu bạn muốn cấu hình một cài đặt có độ sẵn sàng cao, có
 - [Helm Chart bởi @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
 - [Tệp YAML bởi @Winson-030](https://github.com/Winson-030/dify-kubernetes)
 - [Tệp YAML bởi @wyy-holding](https://github.com/wyy-holding/dify-k8s)
+- [🚀 MỚI! Tệp YAML (Hỗ trợ Dify v1.6.0) bởi @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)
 
 #### Sử dụng Terraform để Triển khai
 

api/.env.example

@@ -17,6 +17,11 @@ APP_WEB_URL=http://127.0.0.1:3000
 # Files URL
 FILES_URL=http://127.0.0.1:5001
 
+# INTERNAL_FILES_URL is used for plugin daemon communication within Docker network.
+# Set this to the internal Docker service URL for proper plugin file access.
+# Example: INTERNAL_FILES_URL=http://api:5001
+INTERNAL_FILES_URL=http://127.0.0.1:5001
+
 # The time in seconds after the signature is rejected
 FILES_ACCESS_TIMEOUT=300
 
@@ -444,6 +449,19 @@ MAX_VARIABLE_SIZE=204800
 # hybrid: Save new data to object storage, read from both object storage and RDBMS
 WORKFLOW_NODE_EXECUTION_STORAGE=rdbms
 
+# Repository configuration
+# Core workflow execution repository implementation
+CORE_WORKFLOW_EXECUTION_REPOSITORY=core.repositories.sqlalchemy_workflow_execution_repository.SQLAlchemyWorkflowExecutionRepository
+
+# Core workflow node execution repository implementation
+CORE_WORKFLOW_NODE_EXECUTION_REPOSITORY=core.repositories.sqlalchemy_workflow_node_execution_repository.SQLAlchemyWorkflowNodeExecutionRepository
+
+# API workflow node execution repository implementation
+API_WORKFLOW_NODE_EXECUTION_REPOSITORY=repositories.sqlalchemy_api_workflow_node_execution_repository.DifyAPISQLAlchemyWorkflowNodeExecutionRepository
+
+# API workflow run repository implementation
+API_WORKFLOW_RUN_REPOSITORY=repositories.sqlalchemy_api_workflow_run_repository.DifyAPISQLAlchemyWorkflowRunRepository
+
 # App configuration
 APP_MAX_EXECUTION_TIME=1200
 APP_MAX_ACTIVE_REQUESTS=0

api/configs/app_config.py

@@ -1,8 +1,11 @@
 import logging
+from pathlib import Path
 from typing import Any
 
 from pydantic.fields import FieldInfo
-from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict
+from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict, TomlConfigSettingsSource
+
+from libs.file_utils import search_file_upwards
 
 from .deploy import DeploymentConfig
 from .enterprise import EnterpriseFeatureConfig
@@ -99,4 +102,12 @@ class DifyConfig(
             RemoteSettingsSourceFactory(settings_cls),
             dotenv_settings,
             file_secret_settings,
+            TomlConfigSettingsSource(
+                settings_cls=settings_cls,
+                toml_file=search_file_upwards(
+                    base_dir_path=Path(__file__).parent,
+                    target_file_name="pyproject.toml",
+                    max_search_parent_depth=2,
+                ),
+            ),
         )

api/configs/feature/__init__.py

@@ -237,6 +237,13 @@ class FileAccessConfig(BaseSettings):
         default="",
     )
 
+    INTERNAL_FILES_URL: str = Field(
+        description="Internal base URL for file access within Docker network,"
+        " used for plugin daemon and internal service communication."
+        " Falls back to FILES_URL if not specified.",
+        default="",
+    )
+
     FILES_ACCESS_TIMEOUT: int = Field(
         description="Expiration time in seconds for file access URLs",
         default=300,
@@ -530,6 +537,33 @@ class WorkflowNodeExecutionConfig(BaseSettings):
     )
 
 
+class RepositoryConfig(BaseSettings):
+    """
+    Configuration for repository implementations
+    """
+
+    CORE_WORKFLOW_EXECUTION_REPOSITORY: str = Field(
+        description="Repository implementation for WorkflowExecution. Specify as a module path",
+        default="core.repositories.sqlalchemy_workflow_execution_repository.SQLAlchemyWorkflowExecutionRepository",
+    )
+
+    CORE_WORKFLOW_NODE_EXECUTION_REPOSITORY: str = Field(
+        description="Repository implementation for WorkflowNodeExecution. Specify as a module path",
+        default="core.repositories.sqlalchemy_workflow_node_execution_repository.SQLAlchemyWorkflowNodeExecutionRepository",
+    )
+
+    API_WORKFLOW_NODE_EXECUTION_REPOSITORY: str = Field(
+        description="Service-layer repository implementation for WorkflowNodeExecutionModel operations. "
+        "Specify as a module path",
+        default="repositories.sqlalchemy_api_workflow_node_execution_repository.DifyAPISQLAlchemyWorkflowNodeExecutionRepository",
+    )
+
+    API_WORKFLOW_RUN_REPOSITORY: str = Field(
+        description="Service-layer repository implementation for WorkflowRun operations. Specify as a module path",
+        default="repositories.sqlalchemy_api_workflow_run_repository.DifyAPISQLAlchemyWorkflowRunRepository",
+    )
+
+
 class AuthConfig(BaseSettings):
     """
     Configuration for authentication and OAuth
@@ -896,6 +930,7 @@ class FeatureConfig(
     MultiModalTransferConfig,
     PositionConfig,
     RagEtlConfig,
+    RepositoryConfig,
     SecurityConfig,
     ToolConfig,
     UpdateConfig,

api/configs/middleware/__init__.py

@@ -162,6 +162,11 @@ class DatabaseConfig(BaseSettings):
         default=3600,
     )
 
+    SQLALCHEMY_POOL_USE_LIFO: bool = Field(
+        description="If True, SQLAlchemy will use last-in-first-out way to retrieve connections from pool.",
+        default=False,
+    )
+
     SQLALCHEMY_POOL_PRE_PING: bool = Field(
         description="If True, enables connection pool pre-ping feature to check connections.",
         default=False,
@@ -199,6 +204,7 @@ class DatabaseConfig(BaseSettings):
             "pool_recycle": self.SQLALCHEMY_POOL_RECYCLE,
             "pool_pre_ping": self.SQLALCHEMY_POOL_PRE_PING,
             "connect_args": connect_args,
+            "pool_use_lifo": self.SQLALCHEMY_POOL_USE_LIFO,
         }
 
 
@@ -223,6 +229,10 @@ class CeleryConfig(DatabaseConfig):
         default=None,
     )
 
+    CELERY_SENTINEL_PASSWORD: Optional[str] = Field(
+        description="Password of the Redis Sentinel master.",
+        default=None,
+    )
     CELERY_SENTINEL_SOCKET_TIMEOUT: Optional[PositiveFloat] = Field(
         description="Timeout for Redis Sentinel socket operations in seconds.",
         default=0.1,

api/configs/packaging/__init__.py

@@ -1,17 +1,13 @@
 from pydantic import Field
-from pydantic_settings import BaseSettings
+
+from configs.packaging.pyproject import PyProjectConfig, PyProjectTomlConfig
 
 
-class PackagingInfo(BaseSettings):
+class PackagingInfo(PyProjectTomlConfig):
     """
     Packaging build information
     """
 
-    CURRENT_VERSION: str = Field(
-        description="Dify version",
-        default="1.5.0",
-    )
-
     COMMIT_SHA: str = Field(
         description="SHA-1 checksum of the git commit used to build the app",
         default="",

api/configs/packaging/pyproject.py

@@ -0,0 +1,17 @@
+from pydantic import BaseModel, Field
+from pydantic_settings import BaseSettings
+
+
+class PyProjectConfig(BaseModel):
+    version: str = Field(description="Dify version", default="")
+
+
+class PyProjectTomlConfig(BaseSettings):
+    """
+    configs in api/pyproject.toml
+    """
+
+    project: PyProjectConfig = Field(
+        description="configs in the project section of pyproject.toml",
+        default=PyProjectConfig(),
+    )

api/controllers/console/__init__.py

@@ -56,6 +56,7 @@ from .app import (
     conversation,
     conversation_variables,
     generator,
+    mcp_server,
     message,
     model_config,
     ops_trace,

api/controllers/console/app/app.py

@@ -151,6 +151,7 @@ class AppApi(Resource):
         parser.add_argument("icon", type=str, location="json")
         parser.add_argument("icon_background", type=str, location="json")
         parser.add_argument("use_icon_as_answer_icon", type=bool, location="json")
+        parser.add_argument("max_active_requests", type=int, location="json")
         args = parser.parse_args()
 
         app_service = AppService()

api/controllers/console/app/audio.py

@@ -90,23 +90,11 @@ class ChatMessageTextApi(Resource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                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
-            response = AudioService.transcript_tts(app_model=app_model, text=text, message_id=message_id, voice=voice)
+            voice = args.get("voice", None)
+
+            response = AudioService.transcript_tts(
+                app_model=app_model, text=text, voice=voice, message_id=message_id, is_draft=True
+            )
             return response
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")

api/controllers/console/app/mcp_server.py

@@ -0,0 +1,119 @@
+import json
+from enum import StrEnum
+
+from flask_login import current_user
+from flask_restful import Resource, marshal_with, reqparse
+from werkzeug.exceptions import NotFound
+
+from controllers.console import api
+from controllers.console.app.wraps import get_app_model
+from controllers.console.wraps import account_initialization_required, setup_required
+from extensions.ext_database import db
+from fields.app_fields import app_server_fields
+from libs.login import login_required
+from models.model import AppMCPServer
+
+
+class AppMCPServerStatus(StrEnum):
+    ACTIVE = "active"
+    INACTIVE = "inactive"
+
+
+class AppMCPServerController(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    @marshal_with(app_server_fields)
+    def get(self, app_model):
+        server = db.session.query(AppMCPServer).filter(AppMCPServer.app_id == app_model.id).first()
+        return server
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    @marshal_with(app_server_fields)
+    def post(self, app_model):
+        if not current_user.is_editor:
+            raise NotFound()
+        parser = reqparse.RequestParser()
+        parser.add_argument("description", type=str, required=False, location="json")
+        parser.add_argument("parameters", type=dict, required=True, location="json")
+        args = parser.parse_args()
+
+        description = args.get("description")
+        if not description:
+            description = app_model.description or ""
+
+        server = AppMCPServer(
+            name=app_model.name,
+            description=description,
+            parameters=json.dumps(args["parameters"], ensure_ascii=False),
+            status=AppMCPServerStatus.ACTIVE,
+            app_id=app_model.id,
+            tenant_id=current_user.current_tenant_id,
+            server_code=AppMCPServer.generate_server_code(16),
+        )
+        db.session.add(server)
+        db.session.commit()
+        return server
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    @marshal_with(app_server_fields)
+    def put(self, app_model):
+        if not current_user.is_editor:
+            raise NotFound()
+        parser = reqparse.RequestParser()
+        parser.add_argument("id", type=str, required=True, location="json")
+        parser.add_argument("description", type=str, required=False, location="json")
+        parser.add_argument("parameters", type=dict, required=True, location="json")
+        parser.add_argument("status", type=str, required=False, location="json")
+        args = parser.parse_args()
+        server = db.session.query(AppMCPServer).filter(AppMCPServer.id == args["id"]).first()
+        if not server:
+            raise NotFound()
+
+        description = args.get("description")
+        if description is None:
+            pass
+        elif not description:
+            server.description = app_model.description or ""
+        else:
+            server.description = description
+
+        server.parameters = json.dumps(args["parameters"], ensure_ascii=False)
+        if args["status"]:
+            if args["status"] not in [status.value for status in AppMCPServerStatus]:
+                raise ValueError("Invalid status")
+            server.status = args["status"]
+        db.session.commit()
+        return server
+
+
+class AppMCPServerRefreshController(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @marshal_with(app_server_fields)
+    def get(self, server_id):
+        if not current_user.is_editor:
+            raise NotFound()
+        server = (
+            db.session.query(AppMCPServer)
+            .filter(AppMCPServer.id == server_id)
+            .filter(AppMCPServer.tenant_id == current_user.current_tenant_id)
+            .first()
+        )
+        if not server:
+            raise NotFound()
+        server.server_code = AppMCPServer.generate_server_code(16)
+        db.session.commit()
+        return server
+
+
+api.add_resource(AppMCPServerController, "/apps/<uuid:app_id>/server")
+api.add_resource(AppMCPServerRefreshController, "/apps/<uuid:server_id>/server/refresh")

api/controllers/console/app/statistic.py

@@ -2,6 +2,7 @@ from datetime import datetime
 from decimal import Decimal
 
 import pytz
+import sqlalchemy as sa
 from flask import jsonify
 from flask_login import current_user
 from flask_restful import Resource, reqparse
@@ -9,10 +10,11 @@ from flask_restful import Resource, reqparse
 from controllers.console import api
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, setup_required
+from core.app.entities.app_invoke_entities import InvokeFrom
 from extensions.ext_database import db
 from libs.helper import DatetimeString
 from libs.login import login_required
-from models.model import AppMode
+from models import AppMode, Message
 
 
 class DailyMessageStatistic(Resource):
@@ -85,46 +87,41 @@ class DailyConversationStatistic(Resource):
         parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
         args = parser.parse_args()
 
-        sql_query = """SELECT
-    DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
-    COUNT(DISTINCT messages.conversation_id) AS conversation_count
-FROM
-    messages
-WHERE
-    app_id = :app_id"""
-        arg_dict = {"tz": account.timezone, "app_id": app_model.id}
-
         timezone = pytz.timezone(account.timezone)
         utc_timezone = pytz.utc
 
+        stmt = (
+            sa.select(
+                sa.func.date(
+                    sa.func.date_trunc("day", sa.text("created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz"))
+                ).label("date"),
+                sa.func.count(sa.distinct(Message.conversation_id)).label("conversation_count"),
+            )
+            .select_from(Message)
+            .where(Message.app_id == app_model.id, Message.invoke_from != InvokeFrom.DEBUGGER.value)
+        )
+
         if args["start"]:
             start_datetime = datetime.strptime(args["start"], "%Y-%m-%d %H:%M")
             start_datetime = start_datetime.replace(second=0)
-
             start_datetime_timezone = timezone.localize(start_datetime)
             start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
-
-            sql_query += " AND created_at >= :start"
-            arg_dict["start"] = start_datetime_utc
+            stmt = stmt.where(Message.created_at >= start_datetime_utc)
 
         if args["end"]:
             end_datetime = datetime.strptime(args["end"], "%Y-%m-%d %H:%M")
             end_datetime = end_datetime.replace(second=0)
-
             end_datetime_timezone = timezone.localize(end_datetime)
             end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
+            stmt = stmt.where(Message.created_at < end_datetime_utc)
 
-            sql_query += " AND created_at < :end"
-            arg_dict["end"] = end_datetime_utc
-
-        sql_query += " GROUP BY date ORDER BY date"
+        stmt = stmt.group_by("date").order_by("date")
 
         response_data = []
-
         with db.engine.begin() as conn:
-            rs = conn.execute(db.text(sql_query), arg_dict)
-            for i in rs:
-                response_data.append({"date": str(i.date), "conversation_count": i.conversation_count})
+            rs = conn.execute(stmt, {"tz": account.timezone})
+            for row in rs:
+                response_data.append({"date": str(row.date), "conversation_count": row.conversation_count})
 
         return jsonify({"data": response_data})
 

api/controllers/console/app/workflow_draft_variable.py

@@ -68,13 +68,18 @@ def _create_pagination_parser():
     return parser
 
 
+def _serialize_variable_type(workflow_draft_var: WorkflowDraftVariable) -> str:
+    value_type = workflow_draft_var.value_type
+    return value_type.exposed_type().value
+
+
 _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS = {
     "id": fields.String,
     "type": fields.String(attribute=lambda model: model.get_variable_type()),
     "name": fields.String,
     "description": fields.String,
     "selector": fields.List(fields.String, attribute=lambda model: model.get_selector()),
-    "value_type": fields.String,
+    "value_type": fields.String(attribute=_serialize_variable_type),
     "edited": fields.Boolean(attribute=lambda model: model.edited),
     "visible": fields.Boolean,
 }
@@ -90,7 +95,7 @@ _WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS = {
     "name": fields.String,
     "description": fields.String,
     "selector": fields.List(fields.String, attribute=lambda model: model.get_selector()),
-    "value_type": fields.String,
+    "value_type": fields.String(attribute=_serialize_variable_type),
     "edited": fields.Boolean(attribute=lambda model: model.edited),
     "visible": fields.Boolean,
 }
@@ -396,7 +401,7 @@ class EnvironmentVariableCollectionApi(Resource):
                     "name": v.name,
                     "description": v.description,
                     "selector": v.selector,
-                    "value_type": v.value_type.value,
+                    "value_type": v.value_type.exposed_type().value,
                     "value": v.value,
                     # Do not track edited for env vars.
                     "edited": False,

api/controllers/console/app/wraps.py

@@ -35,8 +35,6 @@ def get_app_model(view: Optional[Callable] = None, *, mode: Union[AppMode, list[
                 raise AppNotFoundError()
 
             app_mode = AppMode.value_of(app_model.mode)
-            if app_mode == AppMode.CHANNEL:
-                raise AppNotFoundError()
 
             if mode is not None:
                 if isinstance(mode, list):

api/controllers/console/auth/data_source_oauth.py

@@ -41,7 +41,7 @@ class OAuthDataSource(Resource):
             if not internal_secret:
                 return ({"error": "Internal secret is not set"},)
             oauth_provider.save_internal_access_token(internal_secret)
-            return {"data": ""}
+            return {"data": "internal"}
         else:
             auth_url = oauth_provider.get_authorization_url()
             return {"data": auth_url}, 200

api/controllers/console/explore/audio.py

@@ -18,7 +18,6 @@ from controllers.console.app.error import (
 from controllers.console.explore.wraps import InstalledAppResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import AppMode
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -79,19 +78,9 @@ class ChatTextApi(InstalledAppResource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech")
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
-            response = AudioService.transcript_tts(app_model=app_model, message_id=message_id, voice=voice, text=text)
+            voice = args.get("voice", None)
+
+            response = AudioService.transcript_tts(app_model=app_model, text=text, voice=voice, message_id=message_id)
             return response
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")

api/controllers/console/version.py

@@ -18,7 +18,7 @@ class VersionApi(Resource):
         check_update_url = dify_config.CHECK_UPDATE_URL
 
         result = {
-            "version": dify_config.CURRENT_VERSION,
+            "version": dify_config.project.version,
             "release_date": "",
             "release_notes": "",
             "can_auto_update": False,

api/controllers/console/workspace/members.py

@@ -85,6 +85,7 @@ class MemberInviteEmailApi(Resource):
         return {
             "result": "success",
             "invitation_results": invitation_results,
+            "tenant_id": str(current_user.current_tenant.id),
         }, 201
 
 
@@ -110,7 +111,7 @@ class MemberCancelInviteApi(Resource):
             except Exception as e:
                 raise ValueError(str(e))
 
-        return {"result": "success"}, 204
+        return {"result": "success", "tenant_id": str(current_user.current_tenant.id)}, 200
 
 
 class MemberUpdateRoleApi(Resource):

api/controllers/console/workspace/plugin.py

@@ -13,6 +13,7 @@ from core.model_runtime.utils.encoders import jsonable_encoder
 from core.plugin.impl.exc import PluginDaemonClientSideError
 from libs.login import login_required
 from models.account import TenantPluginPermission
+from services.plugin.plugin_parameter_service import PluginParameterService
 from services.plugin.plugin_permission_service import PluginPermissionService
 from services.plugin.plugin_service import PluginService
 
@@ -497,6 +498,42 @@ class PluginFetchPermissionApi(Resource):
         )
 
 
+class PluginFetchDynamicSelectOptionsApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        # check if the user is admin or owner
+        if not current_user.is_admin_or_owner:
+            raise Forbidden()
+
+        tenant_id = current_user.current_tenant_id
+        user_id = current_user.id
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("plugin_id", type=str, required=True, location="args")
+        parser.add_argument("provider", type=str, required=True, location="args")
+        parser.add_argument("action", type=str, required=True, location="args")
+        parser.add_argument("parameter", type=str, required=True, location="args")
+        parser.add_argument("provider_type", type=str, required=True, location="args")
+        args = parser.parse_args()
+
+        try:
+            options = PluginParameterService.get_dynamic_select_options(
+                tenant_id,
+                user_id,
+                args["plugin_id"],
+                args["provider"],
+                args["action"],
+                args["parameter"],
+                args["provider_type"],
+            )
+        except PluginDaemonClientSideError as e:
+            raise ValueError(e)
+
+        return jsonable_encoder({"options": options})
+
+
 api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key")
 api.add_resource(PluginListApi, "/workspaces/current/plugin/list")
 api.add_resource(PluginListLatestVersionsApi, "/workspaces/current/plugin/list/latest-versions")
@@ -521,3 +558,5 @@ api.add_resource(PluginFetchMarketplacePkgApi, "/workspaces/current/plugin/marke
 
 api.add_resource(PluginChangePermissionApi, "/workspaces/current/plugin/permission/change")
 api.add_resource(PluginFetchPermissionApi, "/workspaces/current/plugin/permission/fetch")
+
+api.add_resource(PluginFetchDynamicSelectOptionsApi, "/workspaces/current/plugin/parameters/dynamic-options")

api/controllers/console/workspace/tool_providers.py

@@ -1,6 +1,7 @@
 import io
+from urllib.parse import urlparse
 
-from flask import send_file
+from flask import redirect, send_file
 from flask_login import current_user
 from flask_restful import Resource, reqparse
 from sqlalchemy.orm import Session
@@ -9,17 +10,34 @@ from werkzeug.exceptions import Forbidden
 from configs import dify_config
 from controllers.console import api
 from controllers.console.wraps import account_initialization_required, enterprise_license_required, setup_required
+from core.mcp.auth.auth_flow import auth, handle_callback
+from core.mcp.auth.auth_provider import OAuthClientProvider
+from core.mcp.error import MCPAuthError, MCPError
+from core.mcp.mcp_client import MCPClient
 from core.model_runtime.utils.encoders import jsonable_encoder
 from extensions.ext_database import db
 from libs.helper import alphanumeric, uuid_value
 from libs.login import login_required
 from services.tools.api_tools_manage_service import ApiToolManageService
 from services.tools.builtin_tools_manage_service import BuiltinToolManageService
+from services.tools.mcp_tools_mange_service import MCPToolManageService
 from services.tools.tool_labels_service import ToolLabelsService
 from services.tools.tools_manage_service import ToolCommonService
+from services.tools.tools_transform_service import ToolTransformService
 from services.tools.workflow_tools_manage_service import WorkflowToolManageService
 
 
+def is_valid_url(url: str) -> bool:
+    if not url:
+        return False
+
+    try:
+        parsed = urlparse(url)
+        return all([parsed.scheme, parsed.netloc]) and parsed.scheme in ["http", "https"]
+    except Exception:
+        return False
+
+
 class ToolProviderListApi(Resource):
     @setup_required
     @login_required
@@ -34,7 +52,7 @@ class ToolProviderListApi(Resource):
         req.add_argument(
             "type",
             type=str,
-            choices=["builtin", "model", "api", "workflow"],
+            choices=["builtin", "model", "api", "workflow", "mcp"],
             required=False,
             nullable=True,
             location="args",
@@ -613,6 +631,166 @@ class ToolLabelsApi(Resource):
         return jsonable_encoder(ToolLabelsService.list_tool_labels())
 
 
+class ToolProviderMCPApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("server_url", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("name", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon_type", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon_background", type=str, required=False, nullable=True, location="json", default="")
+        parser.add_argument("server_identifier", type=str, required=True, nullable=False, location="json")
+        args = parser.parse_args()
+        user = current_user
+        if not is_valid_url(args["server_url"]):
+            raise ValueError("Server URL is not valid.")
+        return jsonable_encoder(
+            MCPToolManageService.create_mcp_provider(
+                tenant_id=user.current_tenant_id,
+                server_url=args["server_url"],
+                name=args["name"],
+                icon=args["icon"],
+                icon_type=args["icon_type"],
+                icon_background=args["icon_background"],
+                user_id=user.id,
+                server_identifier=args["server_identifier"],
+            )
+        )
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def put(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("server_url", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("name", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon_type", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("icon_background", type=str, required=False, nullable=True, location="json")
+        parser.add_argument("provider_id", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("server_identifier", type=str, required=True, nullable=False, location="json")
+        args = parser.parse_args()
+        if not is_valid_url(args["server_url"]):
+            if "[__HIDDEN__]" in args["server_url"]:
+                pass
+            else:
+                raise ValueError("Server URL is not valid.")
+        MCPToolManageService.update_mcp_provider(
+            tenant_id=current_user.current_tenant_id,
+            provider_id=args["provider_id"],
+            server_url=args["server_url"],
+            name=args["name"],
+            icon=args["icon"],
+            icon_type=args["icon_type"],
+            icon_background=args["icon_background"],
+            server_identifier=args["server_identifier"],
+        )
+        return {"result": "success"}
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def delete(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("provider_id", type=str, required=True, nullable=False, location="json")
+        args = parser.parse_args()
+        MCPToolManageService.delete_mcp_tool(tenant_id=current_user.current_tenant_id, provider_id=args["provider_id"])
+        return {"result": "success"}
+
+
+class ToolMCPAuthApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("provider_id", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("authorization_code", type=str, required=False, nullable=True, location="json")
+        args = parser.parse_args()
+        provider_id = args["provider_id"]
+        tenant_id = current_user.current_tenant_id
+        provider = MCPToolManageService.get_mcp_provider_by_provider_id(provider_id, tenant_id)
+        if not provider:
+            raise ValueError("provider not found")
+        try:
+            with MCPClient(
+                provider.decrypted_server_url,
+                provider_id,
+                tenant_id,
+                authed=False,
+                authorization_code=args["authorization_code"],
+                for_list=True,
+            ):
+                MCPToolManageService.update_mcp_provider_credentials(
+                    mcp_provider=provider,
+                    credentials=provider.decrypted_credentials,
+                    authed=True,
+                )
+                return {"result": "success"}
+
+        except MCPAuthError:
+            auth_provider = OAuthClientProvider(provider_id, tenant_id, for_list=True)
+            return auth(auth_provider, provider.decrypted_server_url, args["authorization_code"])
+        except MCPError as e:
+            MCPToolManageService.update_mcp_provider_credentials(
+                mcp_provider=provider,
+                credentials={},
+                authed=False,
+            )
+            raise ValueError(f"Failed to connect to MCP server: {e}") from e
+
+
+class ToolMCPDetailApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, provider_id):
+        user = current_user
+        provider = MCPToolManageService.get_mcp_provider_by_provider_id(provider_id, user.current_tenant_id)
+        return jsonable_encoder(ToolTransformService.mcp_provider_to_user_provider(provider, for_list=True))
+
+
+class ToolMCPListAllApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        user = current_user
+        tenant_id = user.current_tenant_id
+
+        tools = MCPToolManageService.retrieve_mcp_tools(tenant_id=tenant_id)
+
+        return [tool.to_dict() for tool in tools]
+
+
+class ToolMCPUpdateApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, provider_id):
+        tenant_id = current_user.current_tenant_id
+        tools = MCPToolManageService.list_mcp_tool_from_remote_server(
+            tenant_id=tenant_id,
+            provider_id=provider_id,
+        )
+        return jsonable_encoder(tools)
+
+
+class ToolMCPCallbackApi(Resource):
+    def get(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("code", type=str, required=True, nullable=False, location="args")
+        parser.add_argument("state", type=str, required=True, nullable=False, location="args")
+        args = parser.parse_args()
+        state_key = args["state"]
+        authorization_code = args["code"]
+        handle_callback(state_key, authorization_code)
+        return redirect(f"{dify_config.CONSOLE_WEB_URL}/oauth-callback")
+
+
 # tool provider
 api.add_resource(ToolProviderListApi, "/workspaces/current/tool-providers")
 
@@ -647,8 +825,15 @@ api.add_resource(ToolWorkflowProviderDeleteApi, "/workspaces/current/tool-provid
 api.add_resource(ToolWorkflowProviderGetApi, "/workspaces/current/tool-provider/workflow/get")
 api.add_resource(ToolWorkflowProviderListToolApi, "/workspaces/current/tool-provider/workflow/tools")
 
+# mcp tool provider
+api.add_resource(ToolMCPDetailApi, "/workspaces/current/tool-provider/mcp/tools/<path:provider_id>")
+api.add_resource(ToolProviderMCPApi, "/workspaces/current/tool-provider/mcp")
+api.add_resource(ToolMCPUpdateApi, "/workspaces/current/tool-provider/mcp/update/<path:provider_id>")
+api.add_resource(ToolMCPAuthApi, "/workspaces/current/tool-provider/mcp/auth")
+api.add_resource(ToolMCPCallbackApi, "/mcp/oauth/callback")
+
 api.add_resource(ToolBuiltinListApi, "/workspaces/current/tools/builtin")
 api.add_resource(ToolApiListApi, "/workspaces/current/tools/api")
+api.add_resource(ToolMCPListAllApi, "/workspaces/current/tools/mcp")
 api.add_resource(ToolWorkflowListApi, "/workspaces/current/tools/workflow")
-
 api.add_resource(ToolLabelsApi, "/workspaces/current/tool-labels")

api/controllers/files/upload.py

@@ -87,7 +87,5 @@ class PluginUploadFileApi(Resource):
         except services.errors.file.UnsupportedFileTypeError:
             raise UnsupportedFileTypeError()
 
-        return tool_file, 201
-
 
 api.add_resource(PluginUploadFileApi, "/files/upload/for-plugin")

api/controllers/inner_api/plugin/plugin.py

@@ -17,6 +17,7 @@ from core.plugin.entities.request import (
     RequestInvokeApp,
     RequestInvokeEncrypt,
     RequestInvokeLLM,
+    RequestInvokeLLMWithStructuredOutput,
     RequestInvokeModeration,
     RequestInvokeParameterExtractorNode,
     RequestInvokeQuestionClassifierNode,
@@ -47,6 +48,21 @@ class PluginInvokeLLMApi(Resource):
         return length_prefixed_response(0xF, generator())
 
 
+class PluginInvokeLLMWithStructuredOutputApi(Resource):
+    @setup_required
+    @plugin_inner_api_only
+    @get_user_tenant
+    @plugin_data(payload_type=RequestInvokeLLMWithStructuredOutput)
+    def post(self, user_model: Account | EndUser, tenant_model: Tenant, payload: RequestInvokeLLMWithStructuredOutput):
+        def generator():
+            response = PluginModelBackwardsInvocation.invoke_llm_with_structured_output(
+                user_model.id, tenant_model, payload
+            )
+            return PluginModelBackwardsInvocation.convert_to_event_stream(response)
+
+        return length_prefixed_response(0xF, generator())
+
+
 class PluginInvokeTextEmbeddingApi(Resource):
     @setup_required
     @plugin_inner_api_only
@@ -291,6 +307,7 @@ class PluginFetchAppInfoApi(Resource):
 
 
 api.add_resource(PluginInvokeLLMApi, "/invoke/llm")
+api.add_resource(PluginInvokeLLMWithStructuredOutputApi, "/invoke/llm/structured-output")
 api.add_resource(PluginInvokeTextEmbeddingApi, "/invoke/text-embedding")
 api.add_resource(PluginInvokeRerankApi, "/invoke/rerank")
 api.add_resource(PluginInvokeTTSApi, "/invoke/tts")

api/controllers/inner_api/workspace/workspace.py

@@ -29,7 +29,19 @@ class EnterpriseWorkspace(Resource):
 
         tenant_was_created.send(tenant)
 
-        return {"message": "enterprise workspace created."}
+        resp = {
+            "id": tenant.id,
+            "name": tenant.name,
+            "plan": tenant.plan,
+            "status": tenant.status,
+            "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,
+        }
 
 
 class EnterpriseWorkspaceNoOwnerEmail(Resource):

api/controllers/mcp/__init__.py

@@ -0,0 +1,8 @@
+from flask import Blueprint
+
+from libs.external_api import ExternalApi
+
+bp = Blueprint("mcp", __name__, url_prefix="/mcp")
+api = ExternalApi(bp)
+
+from . import mcp

api/controllers/mcp/mcp.py

@@ -0,0 +1,104 @@
+from flask_restful import Resource, reqparse
+from pydantic import ValidationError
+
+from controllers.console.app.mcp_server import AppMCPServerStatus
+from controllers.mcp import api
+from core.app.app_config.entities import VariableEntity
+from core.mcp import types
+from core.mcp.server.streamable_http import MCPServerStreamableHTTPRequestHandler
+from core.mcp.types import ClientNotification, ClientRequest
+from core.mcp.utils import create_mcp_error_response
+from extensions.ext_database import db
+from libs import helper
+from models.model import App, AppMCPServer, AppMode
+
+
+class MCPAppApi(Resource):
+    def post(self, server_code):
+        def int_or_str(value):
+            if isinstance(value, (int, str)):
+                return value
+            else:
+                return None
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("jsonrpc", type=str, required=True, location="json")
+        parser.add_argument("method", type=str, required=True, location="json")
+        parser.add_argument("params", type=dict, required=False, location="json")
+        parser.add_argument("id", type=int_or_str, required=False, location="json")
+        args = parser.parse_args()
+
+        request_id = args.get("id")
+
+        server = db.session.query(AppMCPServer).filter(AppMCPServer.server_code == server_code).first()
+        if not server:
+            return helper.compact_generate_response(
+                create_mcp_error_response(request_id, types.INVALID_REQUEST, "Server Not Found")
+            )
+
+        if server.status != AppMCPServerStatus.ACTIVE:
+            return helper.compact_generate_response(
+                create_mcp_error_response(request_id, types.INVALID_REQUEST, "Server is not active")
+            )
+
+        app = db.session.query(App).filter(App.id == server.app_id).first()
+        if not app:
+            return helper.compact_generate_response(
+                create_mcp_error_response(request_id, types.INVALID_REQUEST, "App Not Found")
+            )
+
+        if app.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}:
+            workflow = app.workflow
+            if workflow is None:
+                return helper.compact_generate_response(
+                    create_mcp_error_response(request_id, types.INVALID_REQUEST, "App is unavailable")
+                )
+
+            user_input_form = workflow.user_input_form(to_old_structure=True)
+        else:
+            app_model_config = app.app_model_config
+            if app_model_config is None:
+                return helper.compact_generate_response(
+                    create_mcp_error_response(request_id, types.INVALID_REQUEST, "App is unavailable")
+                )
+
+            features_dict = app_model_config.to_dict()
+            user_input_form = features_dict.get("user_input_form", [])
+        converted_user_input_form: list[VariableEntity] = []
+        try:
+            for item in user_input_form:
+                variable_type = item.get("type", "") or list(item.keys())[0]
+                variable = item[variable_type]
+                converted_user_input_form.append(
+                    VariableEntity(
+                        type=variable_type,
+                        variable=variable.get("variable"),
+                        description=variable.get("description") or "",
+                        label=variable.get("label"),
+                        required=variable.get("required", False),
+                        max_length=variable.get("max_length"),
+                        options=variable.get("options") or [],
+                    )
+                )
+        except ValidationError as e:
+            return helper.compact_generate_response(
+                create_mcp_error_response(request_id, types.INVALID_PARAMS, f"Invalid user_input_form: {str(e)}")
+            )
+
+        try:
+            request: ClientRequest | ClientNotification = ClientRequest.model_validate(args)
+        except ValidationError as e:
+            try:
+                notification = ClientNotification.model_validate(args)
+                request = notification
+            except ValidationError as e:
+                return helper.compact_generate_response(
+                    create_mcp_error_response(request_id, types.INVALID_PARAMS, f"Invalid MCP request: {str(e)}")
+                )
+
+        mcp_server_handler = MCPServerStreamableHTTPRequestHandler(app, request, converted_user_input_form)
+        response = mcp_server_handler.handle()
+        return helper.compact_generate_response(response)
+
+
+api.add_resource(MCPAppApi, "/server/<string:server_code>/mcp")

api/controllers/service_api/app/audio.py

@@ -20,7 +20,7 @@ from controllers.service_api.app.error import (
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppMode, EndUser
+from models.model import App, EndUser
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -78,20 +78,9 @@ class TextApi(Resource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {})
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
+            voice = args.get("voice", None)
             response = AudioService.transcript_tts(
-                app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text
+                app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id
             )
 
             return response

api/controllers/service_api/app/workflow.py

@@ -3,7 +3,7 @@ import logging
 from dateutil.parser import isoparse
 from flask_restful import Resource, fields, marshal_with, reqparse
 from flask_restful.inputs import int_range
-from sqlalchemy.orm import Session
+from sqlalchemy.orm import Session, sessionmaker
 from werkzeug.exceptions import InternalServerError
 
 from controllers.service_api import api
@@ -30,7 +30,7 @@ from fields.workflow_app_log_fields import workflow_app_log_pagination_fields
 from libs import helper
 from libs.helper import TimestampField
 from models.model import App, AppMode, EndUser
-from models.workflow import WorkflowRun
+from repositories.factory import DifyAPIRepositoryFactory
 from services.app_generate_service import AppGenerateService
 from services.errors.llm import InvokeRateLimitError
 from services.workflow_app_service import WorkflowAppService
@@ -63,7 +63,15 @@ class WorkflowRunDetailApi(Resource):
         if app_mode not in [AppMode.WORKFLOW, AppMode.ADVANCED_CHAT]:
             raise NotWorkflowAppError()
 
-        workflow_run = db.session.query(WorkflowRun).filter(WorkflowRun.id == workflow_run_id).first()
+        # Use repository to get workflow run
+        session_maker = sessionmaker(bind=db.engine, expire_on_commit=False)
+        workflow_run_repo = DifyAPIRepositoryFactory.create_api_workflow_run_repository(session_maker)
+
+        workflow_run = workflow_run_repo.get_workflow_run_by_id(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            run_id=workflow_run_id,
+        )
         return workflow_run
 
 

api/controllers/service_api/dataset/dataset.py

@@ -133,6 +133,22 @@ class DatasetListApi(DatasetApiResource):
         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         try:
             dataset = DatasetService.create_empty_dataset(
                 tenant_id=tenant_id,
@@ -265,10 +281,20 @@ class DatasetApi(DatasetApiResource):
         data = request.get_json()
 
         # check embedding model setting
-        if data.get("indexing_technique") == "high_quality":
+        if data.get("indexing_technique") == "high_quality" or data.get("embedding_model_provider"):
             DatasetService.check_embedding_model_setting(
                 dataset.tenant_id, data.get("embedding_model_provider"), data.get("embedding_model")
             )
+        if (
+            data.get("retrieval_model")
+            and data.get("retrieval_model").get("reranking_model")
+            and data.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                dataset.tenant_id,
+                data.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                data.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
 
         # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
         DatasetPermissionService.check_permission(

api/controllers/service_api/dataset/document.py

@@ -3,7 +3,7 @@ import json
 from flask import request
 from flask_restful import marshal, reqparse
 from sqlalchemy import desc, select
-from werkzeug.exceptions import NotFound
+from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from controllers.common.errors import FilenameNotExistsError
@@ -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,
@@ -29,7 +30,7 @@ from extensions.ext_database import db
 from fields.document_fields import document_fields, document_status_fields
 from libs.login import current_user
 from models.dataset import Dataset, Document, DocumentSegment
-from services.dataset_service import DocumentService
+from services.dataset_service import DatasetService, DocumentService
 from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig
 from services.file_service import FileService
 
@@ -59,6 +60,7 @@ class DocumentAddByTextApi(DatasetApiResource):
         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
         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()
@@ -74,6 +76,21 @@ class DocumentAddByTextApi(DatasetApiResource):
         if text is None or name is None:
             raise ValueError("Both 'text' and 'name' must be non-null values.")
 
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         upload_file = FileService.upload_text(text=str(text), text_name=str(name))
         data_source = {
             "type": "upload_file",
@@ -124,6 +141,17 @@ class DocumentUpdateByTextApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         # indexing_technique is already set in dataset since this is an update
         args["indexing_technique"] = dataset.indexing_technique
 
@@ -183,11 +211,29 @@ class DocumentAddByFileApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if dataset.provider == "external":
+            raise ValueError("External datasets are not supported.")
+
         indexing_technique = args.get("indexing_technique") or dataset.indexing_technique
         if not indexing_technique:
             raise ValueError("indexing_technique is required.")
         args["indexing_technique"] = indexing_technique
 
+        if "embedding_model_provider" in args:
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args["embedding_model_provider"], args["embedding_model"]
+            )
+        if (
+            "retrieval_model" in args
+            and args["retrieval_model"].get("reranking_model")
+            and args["retrieval_model"].get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args["retrieval_model"].get("reranking_model").get("reranking_provider_name"),
+                args["retrieval_model"].get("reranking_model").get("reranking_model_name"),
+            )
+
         # save file info
         file = request.files["file"]
         # check file
@@ -258,6 +304,9 @@ class DocumentUpdateByFileApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if dataset.provider == "external":
+            raise ValueError("External datasets are not supported.")
+
         # indexing_technique is already set in dataset since this is an update
         args["indexing_technique"] = dataset.indexing_technique
 
@@ -424,6 +473,101 @@ class DocumentIndexingStatusApi(DatasetApiResource):
         return data
 
 
+class DocumentDetailApi(DatasetApiResource):
+    METADATA_CHOICES = {"all", "only", "without"}
+
+    def get(self, tenant_id, dataset_id, document_id):
+        dataset_id = str(dataset_id)
+        document_id = str(document_id)
+
+        dataset = self.get_dataset(dataset_id, tenant_id)
+
+        document = DocumentService.get_document(dataset.id, document_id)
+
+        if not document:
+            raise NotFound("Document not found.")
+
+        if document.tenant_id != str(tenant_id):
+            raise Forbidden("No permission.")
+
+        metadata = request.args.get("metadata", "all")
+        if metadata not in self.METADATA_CHOICES:
+            raise InvalidMetadataError(f"Invalid metadata value: {metadata}")
+
+        if metadata == "only":
+            response = {"id": document.id, "doc_type": document.doc_type, "doc_metadata": document.doc_metadata_details}
+        elif metadata == "without":
+            dataset_process_rules = DatasetService.get_process_rules(dataset_id)
+            document_process_rules = document.dataset_process_rule.to_dict()
+            data_source_info = document.data_source_detail_dict
+            response = {
+                "id": document.id,
+                "position": document.position,
+                "data_source_type": document.data_source_type,
+                "data_source_info": data_source_info,
+                "dataset_process_rule_id": document.dataset_process_rule_id,
+                "dataset_process_rule": dataset_process_rules,
+                "document_process_rule": document_process_rules,
+                "name": document.name,
+                "created_from": document.created_from,
+                "created_by": document.created_by,
+                "created_at": document.created_at.timestamp(),
+                "tokens": document.tokens,
+                "indexing_status": document.indexing_status,
+                "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None,
+                "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None,
+                "indexing_latency": document.indexing_latency,
+                "error": document.error,
+                "enabled": document.enabled,
+                "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None,
+                "disabled_by": document.disabled_by,
+                "archived": document.archived,
+                "segment_count": document.segment_count,
+                "average_segment_length": document.average_segment_length,
+                "hit_count": document.hit_count,
+                "display_status": document.display_status,
+                "doc_form": document.doc_form,
+                "doc_language": document.doc_language,
+            }
+        else:
+            dataset_process_rules = DatasetService.get_process_rules(dataset_id)
+            document_process_rules = document.dataset_process_rule.to_dict()
+            data_source_info = document.data_source_detail_dict
+            response = {
+                "id": document.id,
+                "position": document.position,
+                "data_source_type": document.data_source_type,
+                "data_source_info": data_source_info,
+                "dataset_process_rule_id": document.dataset_process_rule_id,
+                "dataset_process_rule": dataset_process_rules,
+                "document_process_rule": document_process_rules,
+                "name": document.name,
+                "created_from": document.created_from,
+                "created_by": document.created_by,
+                "created_at": document.created_at.timestamp(),
+                "tokens": document.tokens,
+                "indexing_status": document.indexing_status,
+                "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None,
+                "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None,
+                "indexing_latency": document.indexing_latency,
+                "error": document.error,
+                "enabled": document.enabled,
+                "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None,
+                "disabled_by": document.disabled_by,
+                "archived": document.archived,
+                "doc_type": document.doc_type,
+                "doc_metadata": document.doc_metadata_details,
+                "segment_count": document.segment_count,
+                "average_segment_length": document.average_segment_length,
+                "hit_count": document.hit_count,
+                "display_status": document.display_status,
+                "doc_form": document.doc_form,
+                "doc_language": document.doc_language,
+            }
+
+        return response
+
+
 api.add_resource(
     DocumentAddByTextApi,
     "/datasets/<uuid:dataset_id>/document/create_by_text",
@@ -447,3 +591,4 @@ api.add_resource(
 api.add_resource(DocumentDeleteApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>")
 api.add_resource(DocumentListApi, "/datasets/<uuid:dataset_id>/documents")
 api.add_resource(DocumentIndexingStatusApi, "/datasets/<uuid:dataset_id>/documents/<string:batch>/indexing-status")
+api.add_resource(DocumentDetailApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>")

api/controllers/service_api/index.py

@@ -9,7 +9,7 @@ class IndexApi(Resource):
         return {
             "welcome": "Dify OpenAPI",
             "api_version": "v1",
-            "server_version": dify_config.CURRENT_VERSION,
+            "server_version": dify_config.project.version,
         }
 
 

api/controllers/service_api/wraps.py

@@ -11,13 +11,13 @@ from flask_restful import Resource
 from pydantic import BaseModel
 from sqlalchemy import select, update
 from sqlalchemy.orm import Session
-from werkzeug.exceptions import Forbidden, Unauthorized
+from werkzeug.exceptions import Forbidden, NotFound, Unauthorized
 
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client
 from libs.login import _get_user
 from models.account import Account, Tenant, TenantAccountJoin, TenantStatus
-from models.dataset import RateLimitLog
+from models.dataset import Dataset, RateLimitLog
 from models.model import ApiToken, App, EndUser
 from services.feature_service import FeatureService
 
@@ -317,3 +317,11 @@ def create_or_update_end_user_for_user_id(app_model: App, user_id: Optional[str]
 
 class DatasetApiResource(Resource):
     method_decorators = [validate_dataset_token]
+
+    def get_dataset(self, dataset_id: str, tenant_id: str) -> Dataset:
+        dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id, Dataset.tenant_id == tenant_id).first()
+
+        if not dataset:
+            raise NotFound("Dataset not found.")
+
+        return dataset

api/controllers/web/audio.py

@@ -19,7 +19,7 @@ from controllers.web.error import (
 from controllers.web.wraps import WebApiResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppMode
+from models.model import App
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -77,21 +77,9 @@ class TextApi(WebApiResource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {})
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
-
+            voice = args.get("voice", None)
             response = AudioService.transcript_tts(
-                app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text
+                app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id
             )
 
             return response

api/core/agent/base_agent_runner.py

@@ -3,6 +3,8 @@ import logging
 import uuid
 from typing import Optional, Union, cast
 
+from sqlalchemy import select
+
 from core.agent.entities import AgentEntity, AgentToolEntity
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
@@ -161,10 +163,14 @@ class BaseAgentRunner(AppRunner):
             if parameter.type == ToolParameter.ToolParameterType.SELECT:
                 enum = [option.value for option in parameter.options] if parameter.options else []
 
-            message_tool.parameters["properties"][parameter.name] = {
-                "type": parameter_type,
-                "description": parameter.llm_description or "",
-            }
+            message_tool.parameters["properties"][parameter.name] = (
+                {
+                    "type": parameter_type,
+                    "description": parameter.llm_description or "",
+                }
+                if parameter.input_schema is None
+                else parameter.input_schema
+            )
 
             if len(enum) > 0:
                 message_tool.parameters["properties"][parameter.name]["enum"] = enum
@@ -254,10 +260,14 @@ class BaseAgentRunner(AppRunner):
             if parameter.type == ToolParameter.ToolParameterType.SELECT:
                 enum = [option.value for option in parameter.options] if parameter.options else []
 
-            prompt_tool.parameters["properties"][parameter.name] = {
-                "type": parameter_type,
-                "description": parameter.llm_description or "",
-            }
+            prompt_tool.parameters["properties"][parameter.name] = (
+                {
+                    "type": parameter_type,
+                    "description": parameter.llm_description or "",
+                }
+                if parameter.input_schema is None
+                else parameter.input_schema
+            )
 
             if len(enum) > 0:
                 prompt_tool.parameters["properties"][parameter.name]["enum"] = enum
@@ -409,12 +419,15 @@ class BaseAgentRunner(AppRunner):
             if isinstance(prompt_message, SystemPromptMessage):
                 result.append(prompt_message)
 
-        messages: list[Message] = (
-            db.session.query(Message)
-            .filter(
-                Message.conversation_id == self.message.conversation_id,
+        messages = (
+            (
+                db.session.execute(
+                    select(Message)
+                    .where(Message.conversation_id == self.message.conversation_id)
+                    .order_by(Message.created_at.desc())
+                )
             )
-            .order_by(Message.created_at.desc())
+            .scalars()
             .all()
         )
 

api/core/agent/plugin_entities.py

@@ -85,7 +85,7 @@ class AgentStrategyEntity(BaseModel):
     description: I18nObject = Field(..., description="The description of the agent strategy")
     output_schema: Optional[dict] = None
     features: Optional[list[AgentFeature]] = None
-
+    meta_version: Optional[str] = None
     # pydantic configs
     model_config = ConfigDict(protected_namespaces=())
 

api/core/agent/strategy/plugin.py

@@ -15,10 +15,12 @@ class PluginAgentStrategy(BaseAgentStrategy):
 
     tenant_id: str
     declaration: AgentStrategyEntity
+    meta_version: str | None = None
 
-    def __init__(self, tenant_id: str, declaration: AgentStrategyEntity):
+    def __init__(self, tenant_id: str, declaration: AgentStrategyEntity, meta_version: str | None):
         self.tenant_id = tenant_id
         self.declaration = declaration
+        self.meta_version = meta_version
 
     def get_parameters(self) -> Sequence[AgentStrategyParameter]:
         return self.declaration.parameters

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

@@ -25,8 +25,10 @@ from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotA
 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 core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.repositories import DifyCoreRepositoryFactory
+from core.workflow.repositories.draft_variable_repository import (
+    DraftVariableSaverFactory,
+)
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
@@ -36,8 +38,10 @@ from libs.flask_utils import preserve_flask_contexts
 from models import Account, App, Conversation, EndUser, Message, Workflow, WorkflowNodeExecutionTriggeredFrom
 from models.enums import WorkflowRunTriggeredFrom
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
-from services.workflow_draft_variable_service import DraftVarLoader, WorkflowDraftVariableService
+from services.workflow_draft_variable_service import (
+    DraftVarLoader,
+    WorkflowDraftVariableService,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -178,14 +182,14 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             workflow_triggered_from = WorkflowRunTriggeredFrom.DEBUGGING
         else:
             workflow_triggered_from = WorkflowRunTriggeredFrom.APP_RUN
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=workflow_triggered_from,
         )
         # Create workflow node execution repository
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -255,14 +259,14 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
         # Create workflow execution(aka workflow run) repository
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
         )
         # Create workflow node execution repository
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -338,14 +342,14 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
         # Create workflow execution(aka workflow run) repository
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
         )
         # Create workflow node execution repository
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -451,6 +455,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
+            draft_var_saver_factory=self._get_draft_var_saver_factory(invoke_from),
         )
 
         return AdvancedChatAppGenerateResponseConverter.convert(response=response, invoke_from=invoke_from)
@@ -480,8 +485,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = AdvancedChatAppRunner(
@@ -524,6 +527,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         user: Union[Account, EndUser],
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -550,6 +554,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
+            draft_var_saver_factory=draft_var_saver_factory,
         )
 
         try:

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

@@ -16,9 +16,10 @@ from core.app.entities.queue_entities import (
     QueueTextChunkEvent,
 )
 from core.moderation.base import ModerationError
+from core.variables.variables import VariableUnion
 from core.workflow.callbacks import WorkflowCallback, WorkflowLoggingCallback
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariableKey
+from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
@@ -64,7 +65,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
         if not workflow:
             raise ValueError("Workflow not initialized")
 
-        user_id = None
+        user_id: str | None = None
         if self.application_generate_entity.invoke_from in {InvokeFrom.WEB_APP, InvokeFrom.SERVICE_API}:
             end_user = db.session.query(EndUser).filter(EndUser.id == self.application_generate_entity.user_id).first()
             if end_user:
@@ -136,23 +137,25 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
                 session.commit()
 
             # Create a variable pool.
-            system_inputs = {
-                SystemVariableKey.QUERY: query,
-                SystemVariableKey.FILES: files,
-                SystemVariableKey.CONVERSATION_ID: self.conversation.id,
-                SystemVariableKey.USER_ID: user_id,
-                SystemVariableKey.DIALOGUE_COUNT: self._dialogue_count,
-                SystemVariableKey.APP_ID: app_config.app_id,
-                SystemVariableKey.WORKFLOW_ID: app_config.workflow_id,
-                SystemVariableKey.WORKFLOW_EXECUTION_ID: self.application_generate_entity.workflow_run_id,
-            }
+            system_inputs = SystemVariable(
+                query=query,
+                files=files,
+                conversation_id=self.conversation.id,
+                user_id=user_id,
+                dialogue_count=self._dialogue_count,
+                app_id=app_config.app_id,
+                workflow_id=app_config.workflow_id,
+                workflow_execution_id=self.application_generate_entity.workflow_run_id,
+            )
 
             # init variable pool
             variable_pool = VariablePool(
                 system_variables=system_inputs,
                 user_inputs=inputs,
                 environment_variables=workflow.environment_variables,
-                conversation_variables=conversation_variables,
+                # Based on the definition of `VariableUnion`,
+                # `list[Variable]` can be safely used as `list[VariableUnion]` since they are compatible.
+                conversation_variables=cast(list[VariableUnion], conversation_variables),
             )
 
             # init graph

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

@@ -61,11 +61,12 @@ from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.model_runtime.entities.llm_entities import LLMUsage
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.workflow.entities.workflow_execution import WorkflowExecutionStatus, WorkflowType
-from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
 from core.workflow.nodes import NodeType
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.system_variable import SystemVariable
 from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
 from events.message_event import message_was_created
 from extensions.ext_database import db
@@ -94,6 +95,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         dialogue_count: int,
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
@@ -114,16 +116,16 @@ class AdvancedChatAppGenerateTaskPipeline:
 
         self._workflow_cycle_manager = WorkflowCycleManager(
             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_EXECUTION_ID: application_generate_entity.workflow_run_id,
-            },
+            workflow_system_variables=SystemVariable(
+                query=message.query,
+                files=application_generate_entity.files,
+                conversation_id=conversation.id,
+                user_id=user_session_id,
+                dialogue_count=dialogue_count,
+                app_id=application_generate_entity.app_config.app_id,
+                workflow_id=workflow.id,
+                workflow_execution_id=application_generate_entity.workflow_run_id,
+            ),
             workflow_info=CycleManagerWorkflowInfo(
                 workflow_id=workflow.id,
                 workflow_type=WorkflowType(workflow.type),
@@ -153,6 +155,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         self._conversation_name_generate_thread: Thread | None = None
         self._recorded_files: list[Mapping[str, Any]] = []
         self._workflow_run_id: str = ""
+        self._draft_var_saver_factory = draft_var_saver_factory
 
     def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -371,6 +374,7 @@ class AdvancedChatAppGenerateTaskPipeline:
                         workflow_node_execution=workflow_node_execution,
                     )
                     session.commit()
+                self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_finish_resp:
                     yield node_finish_resp
@@ -390,6 +394,8 @@ class AdvancedChatAppGenerateTaskPipeline:
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
                 )
+                if isinstance(event, QueueNodeExceptionEvent):
+                    self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_finish_resp:
                     yield node_finish_resp
@@ -759,3 +765,15 @@ class AdvancedChatAppGenerateTaskPipeline:
         if not message:
             raise ValueError(f"Message not found: {self._message_id}")
         return message
+
+    def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str):
+        with Session(db.engine) as session, session.begin():
+            saver = self._draft_var_saver_factory(
+                session=session,
+                app_id=self._application_generate_entity.app_config.app_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                node_execution_id=node_execution_id,
+                enclosing_node_id=event.in_loop_id or event.in_iteration_id,
+            )
+            saver.save(event.process_data, event.outputs)

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

@@ -26,7 +26,6 @@ from factories import file_factory
 from libs.flask_utils import preserve_flask_contexts
 from models import Account, App, EndUser
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -238,8 +237,6 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = AgentChatAppRunner()

api/core/app/apps/base_app_generator.py

@@ -1,10 +1,20 @@
 import json
 from collections.abc import Generator, Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Optional, Union, final
+
+from sqlalchemy.orm import Session
 
 from core.app.app_config.entities import VariableEntityType
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.file import File, FileUploadConfig
+from core.workflow.nodes.enums import NodeType
+from core.workflow.repositories.draft_variable_repository import (
+    DraftVariableSaver,
+    DraftVariableSaverFactory,
+    NoopDraftVariableSaver,
+)
 from factories import file_factory
+from services.workflow_draft_variable_service import DraftVariableSaver as DraftVariableSaverImpl
 
 if TYPE_CHECKING:
     from core.app.app_config.entities import VariableEntity
@@ -159,3 +169,38 @@ class BaseAppGenerator:
                         yield f"event: {message}\n\n"
 
             return gen()
+
+    @final
+    @staticmethod
+    def _get_draft_var_saver_factory(invoke_from: InvokeFrom) -> DraftVariableSaverFactory:
+        if invoke_from == InvokeFrom.DEBUGGER:
+
+            def draft_var_saver_factory(
+                session: Session,
+                app_id: str,
+                node_id: str,
+                node_type: NodeType,
+                node_execution_id: str,
+                enclosing_node_id: str | None = None,
+            ) -> DraftVariableSaver:
+                return DraftVariableSaverImpl(
+                    session=session,
+                    app_id=app_id,
+                    node_id=node_id,
+                    node_type=node_type,
+                    node_execution_id=node_execution_id,
+                    enclosing_node_id=enclosing_node_id,
+                )
+        else:
+
+            def draft_var_saver_factory(
+                session: Session,
+                app_id: str,
+                node_id: str,
+                node_type: NodeType,
+                node_execution_id: str,
+                enclosing_node_id: str | None = None,
+            ) -> DraftVariableSaver:
+                return NoopDraftVariableSaver()
+
+        return draft_var_saver_factory

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

@@ -25,7 +25,6 @@ from factories import file_factory
 from models.account import Account
 from models.model import App, EndUser
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -224,8 +223,6 @@ class ChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = ChatAppRunner()

api/core/app/apps/common/workflow_response_converter.py

@@ -44,6 +44,7 @@ from core.app.entities.task_entities import (
 )
 from core.file import FILE_MODEL_IDENTITY, File
 from core.tools.tool_manager import ToolManager
+from core.variables.segments import ArrayFileSegment, FileSegment, Segment
 from core.workflow.entities.workflow_execution import WorkflowExecution
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecution, WorkflowNodeExecutionStatus
 from core.workflow.nodes import NodeType
@@ -506,7 +507,8 @@ class WorkflowResponseConverter:
         # Convert to tuple to match Sequence type
         return tuple(flattened_files)
 
-    def _fetch_files_from_variable_value(self, value: Union[dict, list]) -> Sequence[Mapping[str, Any]]:
+    @classmethod
+    def _fetch_files_from_variable_value(cls, value: Union[dict, list, Segment]) -> Sequence[Mapping[str, Any]]:
         """
         Fetch files from variable value
         :param value: variable value
@@ -515,20 +517,30 @@ class WorkflowResponseConverter:
         if not value:
             return []
 
-        files = []
-        if isinstance(value, list):
+        files: list[Mapping[str, Any]] = []
+        if isinstance(value, FileSegment):
+            files.append(value.value.to_dict())
+        elif isinstance(value, ArrayFileSegment):
+            files.extend([i.to_dict() for i in value.value])
+        elif isinstance(value, File):
+            files.append(value.to_dict())
+        elif isinstance(value, list):
             for item in value:
-                file = self._get_file_var_from_value(item)
+                file = cls._get_file_var_from_value(item)
                 if file:
                     files.append(file)
-        elif isinstance(value, dict):
-            file = self._get_file_var_from_value(value)
+        elif isinstance(
+            value,
+            dict,
+        ):
+            file = cls._get_file_var_from_value(value)
             if file:
                 files.append(file)
 
         return files
 
-    def _get_file_var_from_value(self, value: Union[dict, list]) -> Mapping[str, Any] | None:
+    @classmethod
+    def _get_file_var_from_value(cls, value: Union[dict, list]) -> Mapping[str, Any] | None:
         """
         Get file var from value
         :param value: variable value

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

@@ -201,8 +201,6 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
             try:
                 # get message
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError()
 
                 # chatbot app
                 runner = CompletionAppRunner()

api/core/app/apps/message_based_app_generator.py

@@ -29,6 +29,7 @@ from models.enums import CreatorUserRole
 from models.model import App, AppMode, AppModelConfig, Conversation, EndUser, Message, MessageFile
 from services.errors.app_model_config import AppModelConfigBrokenError
 from services.errors.conversation import ConversationNotExistsError
+from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -251,7 +252,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
 
         return introduction or ""
 
-    def _get_conversation(self, conversation_id: str):
+    def _get_conversation(self, conversation_id: str) -> Conversation:
         """
         Get conversation by conversation id
         :param conversation_id: conversation id
@@ -260,11 +261,11 @@ class MessageBasedAppGenerator(BaseAppGenerator):
         conversation = db.session.query(Conversation).filter(Conversation.id == conversation_id).first()
 
         if not conversation:
-            raise ConversationNotExistsError()
+            raise ConversationNotExistsError("Conversation not exists")
 
         return conversation
 
-    def _get_message(self, message_id: str) -> Optional[Message]:
+    def _get_message(self, message_id: str) -> Message:
         """
         Get message by message id
         :param message_id: message id
@@ -272,4 +273,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
         """
         message = db.session.query(Message).filter(Message.id == message_id).first()
 
+        if message is None:
+            raise MessageNotExistsError("Message not exists")
+
         return message

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

@@ -23,8 +23,8 @@ from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerat
 from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse
 from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.repositories import DifyCoreRepositoryFactory
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
@@ -155,14 +155,14 @@ class WorkflowAppGenerator(BaseAppGenerator):
             workflow_triggered_from = WorkflowRunTriggeredFrom.DEBUGGING
         else:
             workflow_triggered_from = WorkflowRunTriggeredFrom.APP_RUN
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=workflow_triggered_from,
         )
         # Create workflow node execution repository
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -219,6 +219,9 @@ class WorkflowAppGenerator(BaseAppGenerator):
         # new thread with request context and contextvars
         context = contextvars.copy_context()
 
+        # release database connection, because the following new thread operations may take a long time
+        db.session.close()
+
         worker_thread = threading.Thread(
             target=self._generate_worker,
             kwargs={
@@ -233,6 +236,10 @@ class WorkflowAppGenerator(BaseAppGenerator):
 
         worker_thread.start()
 
+        draft_var_saver_factory = self._get_draft_var_saver_factory(
+            invoke_from,
+        )
+
         # return response or stream generator
         response = self._handle_response(
             application_generate_entity=application_generate_entity,
@@ -241,6 +248,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            draft_var_saver_factory=draft_var_saver_factory,
             stream=streaming,
         )
 
@@ -297,16 +305,14 @@ class WorkflowAppGenerator(BaseAppGenerator):
         # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
         # Create workflow execution(aka workflow run) repository
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
         )
         # Create workflow node execution repository
-        session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
-
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -381,16 +387,14 @@ class WorkflowAppGenerator(BaseAppGenerator):
         # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
         # Create workflow execution(aka workflow run) repository
-        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+        workflow_execution_repository = DifyCoreRepositoryFactory.create_workflow_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
             triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
         )
         # Create workflow node execution repository
-        session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
-
-        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+        workflow_node_execution_repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
             session_factory=session_factory,
             user=user,
             app_id=application_generate_entity.app_config.app_id,
@@ -471,6 +475,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
         user: Union[Account, EndUser],
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -491,6 +496,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            draft_var_saver_factory=draft_var_saver_factory,
             stream=stream,
         )
 

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

@@ -11,7 +11,7 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.workflow.callbacks import WorkflowCallback, WorkflowLoggingCallback
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariableKey
+from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
@@ -95,13 +95,14 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
             files = self.application_generate_entity.files
 
             # Create a variable pool.
-            system_inputs = {
-                SystemVariableKey.FILES: files,
-                SystemVariableKey.USER_ID: user_id,
-                SystemVariableKey.APP_ID: app_config.app_id,
-                SystemVariableKey.WORKFLOW_ID: app_config.workflow_id,
-                SystemVariableKey.WORKFLOW_EXECUTION_ID: self.application_generate_entity.workflow_execution_id,
-            }
+
+            system_inputs = SystemVariable(
+                files=files,
+                user_id=user_id,
+                app_id=app_config.app_id,
+                workflow_id=app_config.workflow_id,
+                workflow_execution_id=self.application_generate_entity.workflow_execution_id,
+            )
 
             variable_pool = VariablePool(
                 system_variables=system_inputs,

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

@@ -3,7 +3,6 @@ import time
 from collections.abc import Generator
 from typing import Optional, Union
 
-from sqlalchemy import select
 from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
@@ -55,9 +54,10 @@ from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTas
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.workflow.entities.workflow_execution import WorkflowExecution, WorkflowExecutionStatus, WorkflowType
-from core.workflow.enums import SystemVariableKey
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.system_variable import SystemVariable
 from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
 from extensions.ext_database import db
 from models.account import Account
@@ -67,7 +67,6 @@ from models.workflow import (
     Workflow,
     WorkflowAppLog,
     WorkflowAppLogCreatedFrom,
-    WorkflowRun,
 )
 
 logger = logging.getLogger(__name__)
@@ -87,6 +86,7 @@ class WorkflowAppGenerateTaskPipeline:
         stream: bool,
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
@@ -107,13 +107,13 @@ class WorkflowAppGenerateTaskPipeline:
 
         self._workflow_cycle_manager = WorkflowCycleManager(
             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_EXECUTION_ID: application_generate_entity.workflow_execution_id,
-            },
+            workflow_system_variables=SystemVariable(
+                files=application_generate_entity.files,
+                user_id=user_session_id,
+                app_id=application_generate_entity.app_config.app_id,
+                workflow_id=workflow.id,
+                workflow_execution_id=application_generate_entity.workflow_execution_id,
+            ),
             workflow_info=CycleManagerWorkflowInfo(
                 workflow_id=workflow.id,
                 workflow_type=WorkflowType(workflow.type),
@@ -131,6 +131,8 @@ class WorkflowAppGenerateTaskPipeline:
         self._application_generate_entity = application_generate_entity
         self._workflow_features_dict = workflow.features_dict
         self._workflow_run_id = ""
+        self._invoke_from = queue_manager._invoke_from
+        self._draft_var_saver_factory = draft_var_saver_factory
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -322,6 +324,8 @@ class WorkflowAppGenerateTaskPipeline:
                     workflow_node_execution=workflow_node_execution,
                 )
 
+                self._save_output_for_event(event, workflow_node_execution.id)
+
                 if node_success_response:
                     yield node_success_response
             elif isinstance(
@@ -339,6 +343,8 @@ class WorkflowAppGenerateTaskPipeline:
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
                 )
+                if isinstance(event, QueueNodeExceptionEvent):
+                    self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_failed_response:
                     yield node_failed_response
@@ -554,8 +560,6 @@ class WorkflowAppGenerateTaskPipeline:
             tts_publisher.publish(None)
 
     def _save_workflow_app_log(self, *, session: Session, workflow_execution: WorkflowExecution) -> None:
-        workflow_run = session.scalar(select(WorkflowRun).where(WorkflowRun.id == workflow_execution.id_))
-        assert workflow_run is not None
         invoke_from = self._application_generate_entity.invoke_from
         if invoke_from == InvokeFrom.SERVICE_API:
             created_from = WorkflowAppLogCreatedFrom.SERVICE_API
@@ -568,10 +572,10 @@ class WorkflowAppGenerateTaskPipeline:
             return
 
         workflow_app_log = WorkflowAppLog()
-        workflow_app_log.tenant_id = workflow_run.tenant_id
-        workflow_app_log.app_id = workflow_run.app_id
-        workflow_app_log.workflow_id = workflow_run.workflow_id
-        workflow_app_log.workflow_run_id = workflow_run.id
+        workflow_app_log.tenant_id = self._application_generate_entity.app_config.tenant_id
+        workflow_app_log.app_id = self._application_generate_entity.app_config.app_id
+        workflow_app_log.workflow_id = workflow_execution.workflow_id
+        workflow_app_log.workflow_run_id = workflow_execution.id_
         workflow_app_log.created_from = created_from.value
         workflow_app_log.created_by_role = self._created_by_role
         workflow_app_log.created_by = self._user_id
@@ -593,3 +597,15 @@ class WorkflowAppGenerateTaskPipeline:
         )
 
         return response
+
+    def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str):
+        with Session(db.engine) as session, session.begin():
+            saver = self._draft_var_saver_factory(
+                session=session,
+                app_id=self._application_generate_entity.app_config.app_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                node_execution_id=node_execution_id,
+                enclosing_node_id=event.in_loop_id or event.in_iteration_id,
+            )
+            saver.save(event.process_data, event.outputs)

api/core/app/apps/workflow_app_runner.py

@@ -1,8 +1,6 @@
 from collections.abc import Mapping
 from typing import Any, Optional, cast
 
-from sqlalchemy.orm import Session
-
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
 from core.app.apps.base_app_runner import AppRunner
 from core.app.entities.queue_entities import (
@@ -35,7 +33,6 @@ from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.graph_engine.entities.event import (
     AgentLogEvent,
-    BaseNodeEvent,
     GraphEngineEvent,
     GraphRunFailedEvent,
     GraphRunPartialSucceededEvent,
@@ -65,14 +62,12 @@ from core.workflow.graph_engine.entities.event import (
 from core.workflow.graph_engine.entities.graph import Graph
 from core.workflow.nodes import NodeType
 from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
+from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from models.model import App
 from models.workflow import Workflow
-from services.workflow_draft_variable_service import (
-    DraftVariableSaver,
-)
 
 
 class WorkflowBasedAppRunner(AppRunner):
@@ -172,7 +167,7 @@ class WorkflowBasedAppRunner(AppRunner):
 
         # init variable pool
         variable_pool = VariablePool(
-            system_variables={},
+            system_variables=SystemVariable.empty(),
             user_inputs={},
             environment_variables=workflow.environment_variables,
         )
@@ -269,7 +264,7 @@ class WorkflowBasedAppRunner(AppRunner):
 
         # init variable pool
         variable_pool = VariablePool(
-            system_variables={},
+            system_variables=SystemVariable.empty(),
             user_inputs={},
             environment_variables=workflow.environment_variables,
         )
@@ -400,7 +395,6 @@ class WorkflowBasedAppRunner(AppRunner):
                     in_loop_id=event.in_loop_id,
                 )
             )
-            self._save_draft_var_for_event(event)
 
         elif isinstance(event, NodeRunFailedEvent):
             self._publish_event(
@@ -464,7 +458,6 @@ class WorkflowBasedAppRunner(AppRunner):
                     in_loop_id=event.in_loop_id,
                 )
             )
-            self._save_draft_var_for_event(event)
 
         elif isinstance(event, NodeInIterationFailedEvent):
             self._publish_event(
@@ -718,30 +711,3 @@ class WorkflowBasedAppRunner(AppRunner):
 
     def _publish_event(self, event: AppQueueEvent) -> None:
         self.queue_manager.publish(event, PublishFrom.APPLICATION_MANAGER)
-
-    def _save_draft_var_for_event(self, event: BaseNodeEvent):
-        run_result = event.route_node_state.node_run_result
-        if run_result is None:
-            return
-        process_data = run_result.process_data
-        outputs = run_result.outputs
-        with Session(bind=db.engine) as session, session.begin():
-            draft_var_saver = DraftVariableSaver(
-                session=session,
-                app_id=self._get_app_id(),
-                node_id=event.node_id,
-                node_type=event.node_type,
-                # FIXME(QuantumGhost): rely on private state of queue_manager is not ideal.
-                invoke_from=self.queue_manager._invoke_from,
-                node_execution_id=event.id,
-                enclosing_node_id=event.in_loop_id or event.in_iteration_id or None,
-            )
-            draft_var_saver.save(process_data=process_data, outputs=outputs)
-
-
-def _remove_first_element_from_variable_string(key: str) -> str:
-    """
-    Remove the first element from the prefix.
-    """
-    prefix, remaining = key.split(".", maxsplit=1)
-    return remaining

api/core/app/task_pipeline/based_generate_task_pipeline.py

@@ -19,6 +19,7 @@ from core.app.entities.task_entities import (
 from core.errors.error import QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
 from core.moderation.output_moderation import ModerationRule, OutputModeration
+from models.enums import MessageStatus
 from models.model import Message
 
 logger = logging.getLogger(__name__)
@@ -62,7 +63,7 @@ class BasedGenerateTaskPipeline:
             return err
 
         err_desc = self._error_to_desc(err)
-        message.status = "error"
+        message.status = MessageStatus.ERROR
         message.error = err_desc
         return err
 

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -395,6 +395,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
         message.provider_response_latency = time.perf_counter() - self._start_at
         message.total_price = usage.total_price
         message.currency = usage.currency
+        self._task_state.llm_result.usage.latency = message.provider_response_latency
         message.message_metadata = self._task_state.metadata.model_dump_json()
 
         if trace_manager:

api/core/entities/parameter_entities.py

@@ -15,7 +15,15 @@ class CommonParameterType(StrEnum):
     MODEL_SELECTOR = "model-selector"
     TOOLS_SELECTOR = "array[tools]"
 
+    # Dynamic select parameter
+    # Once you are not sure about the available options until authorization is done
+    # eg: Select a Slack channel from a Slack workspace
+    DYNAMIC_SELECT = "dynamic-select"
+
     # TOOL_SELECTOR = "tool-selector"
+    # MCP object and array type parameters
+    ARRAY = "array"
+    OBJECT = "object"
 
 
 class AppSelectorScope(StrEnum):

api/core/file/helpers.py

@@ -21,7 +21,9 @@ def get_signed_file_url(upload_file_id: str) -> str:
 
 
 def get_signed_file_url_for_plugin(filename: str, mimetype: str, tenant_id: str, user_id: str) -> str:
-    url = f"{dify_config.FILES_URL}/files/upload/for-plugin"
+    # Plugin access should use internal URL for Docker network communication
+    base_url = dify_config.INTERNAL_FILES_URL or dify_config.FILES_URL
+    url = f"{base_url}/files/upload/for-plugin"
 
     if user_id is None:
         user_id = "DEFAULT-USER"

api/core/file/models.py

@@ -51,7 +51,7 @@ class File(BaseModel):
     # It should be set to `ToolFile.id` when `transfer_method` is `tool_file`.
     related_id: Optional[str] = None
     filename: Optional[str] = None
-    extension: Optional[str] = Field(default=None, description="File extension, should contains dot")
+    extension: Optional[str] = Field(default=None, description="File extension, should contain dot")
     mime_type: Optional[str] = None
     size: int = -1
 

api/core/file/upload_file_parser.py

@@ -1,67 +0,0 @@
-import base64
-import logging
-import time
-from typing import Optional
-
-from configs import dify_config
-from constants import IMAGE_EXTENSIONS
-from core.helper.url_signer import UrlSigner
-from extensions.ext_storage import storage
-
-
-class UploadFileParser:
-    @classmethod
-    def get_image_data(cls, upload_file, force_url: bool = False) -> Optional[str]:
-        if not upload_file:
-            return None
-
-        if upload_file.extension not in IMAGE_EXTENSIONS:
-            return None
-
-        if dify_config.MULTIMODAL_SEND_FORMAT == "url" or force_url:
-            return cls.get_signed_temp_image_url(upload_file.id)
-        else:
-            # get image file base64
-            try:
-                data = storage.load(upload_file.key)
-            except FileNotFoundError:
-                logging.exception(f"File not found: {upload_file.key}")
-                return None
-
-            encoded_string = base64.b64encode(data).decode("utf-8")
-            return f"data:{upload_file.mime_type};base64,{encoded_string}"
-
-    @classmethod
-    def get_signed_temp_image_url(cls, upload_file_id) -> str:
-        """
-        get signed url from upload file
-
-        :param upload_file_id: the id of UploadFile object
-        :return:
-        """
-        base_url = dify_config.FILES_URL
-        image_preview_url = f"{base_url}/files/{upload_file_id}/image-preview"
-
-        return UrlSigner.get_signed_url(url=image_preview_url, sign_key=upload_file_id, prefix="image-preview")
-
-    @classmethod
-    def verify_image_file_signature(cls, upload_file_id: str, timestamp: str, nonce: str, sign: str) -> bool:
-        """
-        verify signature
-
-        :param upload_file_id: file id
-        :param timestamp: timestamp
-        :param nonce: nonce
-        :param sign: signature
-        :return:
-        """
-        result = UrlSigner.verify(
-            sign_key=upload_file_id, timestamp=timestamp, nonce=nonce, sign=sign, prefix="image-preview"
-        )
-
-        # verify signature
-        if not result:
-            return False
-
-        current_time = int(time.time())
-        return current_time - int(timestamp) <= dify_config.FILES_ACCESS_TIMEOUT

api/core/helper/code_executor/template_transformer.py

@@ -5,6 +5,8 @@ from base64 import b64encode
 from collections.abc import Mapping
 from typing import Any
 
+from core.variables.utils import SegmentJSONEncoder
+
 
 class TemplateTransformer(ABC):
     _code_placeholder: str = "{{code}}"
@@ -28,7 +30,7 @@ class TemplateTransformer(ABC):
     def extract_result_str_from_response(cls, response: str):
         result = re.search(rf"{cls._result_tag}(.*){cls._result_tag}", response, re.DOTALL)
         if not result:
-            raise ValueError("Failed to parse result")
+            raise ValueError(f"Failed to parse result: no result tag found in response. Response: {response[:200]}...")
         return result.group(1)
 
     @classmethod
@@ -38,16 +40,49 @@ class TemplateTransformer(ABC):
         :param response: response
         :return:
         """
+
         try:
-            result = json.loads(cls.extract_result_str_from_response(response))
-        except json.JSONDecodeError:
-            raise ValueError("failed to parse response")
+            result_str = cls.extract_result_str_from_response(response)
+            result = json.loads(result_str)
+        except json.JSONDecodeError as e:
+            raise ValueError(f"Failed to parse JSON response: {str(e)}.")
+        except ValueError as e:
+            # Re-raise ValueError from extract_result_str_from_response
+            raise e
+        except Exception as e:
+            raise ValueError(f"Unexpected error during response transformation: {str(e)}")
+
         if not isinstance(result, dict):
-            raise ValueError("result must be a dict")
+            raise ValueError(f"Result must be a dict, got {type(result).__name__}")
         if not all(isinstance(k, str) for k in result):
-            raise ValueError("result keys must be strings")
+            raise ValueError("Result keys must be strings")
+
+        # Post-process the result to convert scientific notation strings back to numbers
+        result = cls._post_process_result(result)
         return result
 
+    @classmethod
+    def _post_process_result(cls, result: dict[Any, Any]) -> dict[Any, Any]:
+        """
+        Post-process the result to convert scientific notation strings back to numbers
+        """
+
+        def convert_scientific_notation(value):
+            if isinstance(value, str):
+                # Check if the string looks like scientific notation
+                if re.match(r"^-?\d+\.?\d*e[+-]\d+$", value, re.IGNORECASE):
+                    try:
+                        return float(value)
+                    except ValueError:
+                        pass
+            elif isinstance(value, dict):
+                return {k: convert_scientific_notation(v) for k, v in value.items()}
+            elif isinstance(value, list):
+                return [convert_scientific_notation(v) for v in value]
+            return value
+
+        return convert_scientific_notation(result)  # type: ignore[no-any-return]
+
     @classmethod
     @abstractmethod
     def get_runner_script(cls) -> str:
@@ -58,7 +93,7 @@ class TemplateTransformer(ABC):
 
     @classmethod
     def serialize_inputs(cls, inputs: Mapping[str, Any]) -> str:
-        inputs_json_str = json.dumps(inputs, ensure_ascii=False).encode()
+        inputs_json_str = json.dumps(inputs, ensure_ascii=False, cls=SegmentJSONEncoder).encode()
         input_base64_encoded = b64encode(inputs_json_str).decode("utf-8")
         return input_base64_encoded
 

api/core/helper/lru_cache.py

@@ -1,22 +0,0 @@
-from collections import OrderedDict
-from typing import Any
-
-
-class LRUCache:
-    def __init__(self, capacity: int):
-        self.cache: OrderedDict[Any, Any] = OrderedDict()
-        self.capacity = capacity
-
-    def get(self, key: Any) -> Any:
-        if key not in self.cache:
-            return None
-        else:
-            self.cache.move_to_end(key)  # move the key to the end of the OrderedDict
-            return self.cache[key]
-
-    def put(self, key: Any, value: Any) -> None:
-        if key in self.cache:
-            self.cache.move_to_end(key)
-        self.cache[key] = value
-        if len(self.cache) > self.capacity:
-            self.cache.popitem(last=False)  # pop the first item

api/core/indexing_runner.py

@@ -317,9 +317,10 @@ class IndexingRunner:
                 image_upload_file_ids = get_image_upload_file_ids(document.page_content)
                 for upload_file_id in image_upload_file_ids:
                     image_file = db.session.query(UploadFile).filter(UploadFile.id == upload_file_id).first()
+                    if image_file is None:
+                        continue
                     try:
-                        if image_file:
-                            storage.delete(image_file.key)
+                        storage.delete(image_file.key)
                     except Exception:
                         logging.exception(
                             "Delete image_files failed while indexing_estimate, \
@@ -534,7 +535,7 @@ class IndexingRunner:
         # chunk nodes by chunk size
         indexing_start_at = time.perf_counter()
         tokens = 0
-        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
+        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy":
             # create keyword index
             create_keyword_thread = threading.Thread(
                 target=self._process_keyword_index,
@@ -572,7 +573,7 @@ class IndexingRunner:
 
                 for future in futures:
                     tokens += future.result()
-        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
+        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy":
             create_keyword_thread.join()
         indexing_end_at = time.perf_counter()
 

api/core/llm_generator/output_parser/structured_output.py

@@ -0,0 +1,380 @@
+import json
+from collections.abc import Generator, Mapping, Sequence
+from copy import deepcopy
+from enum import StrEnum
+from typing import Any, Literal, Optional, cast, overload
+
+import json_repair
+from pydantic import TypeAdapter, ValidationError
+
+from core.llm_generator.output_parser.errors import OutputParserError
+from core.llm_generator.prompts import STRUCTURED_OUTPUT_PROMPT
+from core.model_manager import ModelInstance
+from core.model_runtime.callbacks.base_callback import Callback
+from core.model_runtime.entities.llm_entities import (
+    LLMResult,
+    LLMResultChunk,
+    LLMResultChunkDelta,
+    LLMResultChunkWithStructuredOutput,
+    LLMResultWithStructuredOutput,
+)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+)
+from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule
+
+
+class ResponseFormat(StrEnum):
+    """Constants for model response formats"""
+
+    JSON_SCHEMA = "json_schema"  # model's structured output mode. some model like gemini, gpt-4o,  support this mode.
+    JSON = "JSON"  # model's json mode. some model like claude support this mode.
+    JSON_OBJECT = "json_object"  # json mode's another alias. some model like deepseek-chat, qwen use this alias.
+
+
+class SpecialModelType(StrEnum):
+    """Constants for identifying model types"""
+
+    GEMINI = "gemini"
+    OLLAMA = "ollama"
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: Literal[True] = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: Literal[False] = False,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput: ...
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: bool = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
+
+
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: bool = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]:
+    """
+    Invoke large language model with structured output
+    1. This method invokes model_instance.invoke_llm with json_schema
+    2. Try to parse the result as structured output
+
+    :param prompt_messages: prompt messages
+    :param json_schema: json schema
+    :param model_parameters: model parameters
+    :param tools: tools for tool calling
+    :param stop: stop words
+    :param stream: is stream response
+    :param user: unique user id
+    :param callbacks: callbacks
+    :return: full response or stream response chunk generator result
+    """
+
+    # handle native json schema
+    model_parameters_with_json_schema: dict[str, Any] = {
+        **(model_parameters or {}),
+    }
+
+    if model_schema.support_structure_output:
+        model_parameters = _handle_native_json_schema(
+            provider, model_schema, json_schema, model_parameters_with_json_schema, model_schema.parameter_rules
+        )
+    else:
+        # Set appropriate response format based on model capabilities
+        _set_response_format(model_parameters_with_json_schema, model_schema.parameter_rules)
+
+        # handle prompt based schema
+        prompt_messages = _handle_prompt_based_schema(
+            prompt_messages=prompt_messages,
+            structured_output_schema=json_schema,
+        )
+
+    llm_result = model_instance.invoke_llm(
+        prompt_messages=list(prompt_messages),
+        model_parameters=model_parameters_with_json_schema,
+        tools=tools,
+        stop=stop,
+        stream=stream,
+        user=user,
+        callbacks=callbacks,
+    )
+
+    if isinstance(llm_result, LLMResult):
+        if not isinstance(llm_result.message.content, str):
+            raise OutputParserError(
+                f"Failed to parse structured output, LLM result is not a string: {llm_result.message.content}"
+            )
+
+        return LLMResultWithStructuredOutput(
+            structured_output=_parse_structured_output(llm_result.message.content),
+            model=llm_result.model,
+            message=llm_result.message,
+            usage=llm_result.usage,
+            system_fingerprint=llm_result.system_fingerprint,
+            prompt_messages=llm_result.prompt_messages,
+        )
+    else:
+
+        def generator() -> Generator[LLMResultChunkWithStructuredOutput, None, None]:
+            result_text: str = ""
+            prompt_messages: Sequence[PromptMessage] = []
+            system_fingerprint: Optional[str] = None
+            for event in llm_result:
+                if isinstance(event, LLMResultChunk):
+                    prompt_messages = event.prompt_messages
+                    system_fingerprint = event.system_fingerprint
+
+                    if isinstance(event.delta.message.content, str):
+                        result_text += event.delta.message.content
+                    elif isinstance(event.delta.message.content, list):
+                        for item in event.delta.message.content:
+                            if isinstance(item, TextPromptMessageContent):
+                                result_text += item.data
+
+                yield LLMResultChunkWithStructuredOutput(
+                    model=model_schema.model,
+                    prompt_messages=prompt_messages,
+                    system_fingerprint=system_fingerprint,
+                    delta=event.delta,
+                )
+
+            yield LLMResultChunkWithStructuredOutput(
+                structured_output=_parse_structured_output(result_text),
+                model=model_schema.model,
+                prompt_messages=prompt_messages,
+                system_fingerprint=system_fingerprint,
+                delta=LLMResultChunkDelta(
+                    index=0,
+                    message=AssistantPromptMessage(content=""),
+                    usage=None,
+                    finish_reason=None,
+                ),
+            )
+
+        return generator()
+
+
+def _handle_native_json_schema(
+    provider: str,
+    model_schema: AIModelEntity,
+    structured_output_schema: Mapping,
+    model_parameters: dict,
+    rules: list[ParameterRule],
+) -> dict:
+    """
+    Handle structured output for models with native JSON schema support.
+
+    :param model_parameters: Model parameters to update
+    :param rules: Model parameter rules
+    :return: Updated model parameters with JSON schema configuration
+    """
+    # Process schema according to model requirements
+    schema_json = _prepare_schema_for_model(provider, model_schema, structured_output_schema)
+
+    # Set JSON schema in parameters
+    model_parameters["json_schema"] = json.dumps(schema_json, ensure_ascii=False)
+
+    # Set appropriate response format if required by the model
+    for rule in rules:
+        if rule.name == "response_format" and ResponseFormat.JSON_SCHEMA.value in rule.options:
+            model_parameters["response_format"] = ResponseFormat.JSON_SCHEMA.value
+
+    return model_parameters
+
+
+def _set_response_format(model_parameters: dict, rules: list) -> None:
+    """
+    Set the appropriate response format parameter based on model rules.
+
+    :param model_parameters: Model parameters to update
+    :param rules: Model parameter rules
+    """
+    for rule in rules:
+        if rule.name == "response_format":
+            if ResponseFormat.JSON.value in rule.options:
+                model_parameters["response_format"] = ResponseFormat.JSON.value
+            elif ResponseFormat.JSON_OBJECT.value in rule.options:
+                model_parameters["response_format"] = ResponseFormat.JSON_OBJECT.value
+
+
+def _handle_prompt_based_schema(
+    prompt_messages: Sequence[PromptMessage], structured_output_schema: Mapping
+) -> list[PromptMessage]:
+    """
+    Handle structured output for models without native JSON schema support.
+    This function modifies the prompt messages to include schema-based output requirements.
+
+    Args:
+        prompt_messages: Original sequence of prompt messages
+
+    Returns:
+        list[PromptMessage]: Updated prompt messages with structured output requirements
+    """
+    # Convert schema to string format
+    schema_str = json.dumps(structured_output_schema, ensure_ascii=False)
+
+    # Find existing system prompt with schema placeholder
+    system_prompt = next(
+        (prompt for prompt in prompt_messages if isinstance(prompt, SystemPromptMessage)),
+        None,
+    )
+    structured_output_prompt = STRUCTURED_OUTPUT_PROMPT.replace("{{schema}}", schema_str)
+    # Prepare system prompt content
+    system_prompt_content = (
+        structured_output_prompt + "\n\n" + system_prompt.content
+        if system_prompt and isinstance(system_prompt.content, str)
+        else structured_output_prompt
+    )
+    system_prompt = SystemPromptMessage(content=system_prompt_content)
+
+    # Extract content from the last user message
+
+    filtered_prompts = [prompt for prompt in prompt_messages if not isinstance(prompt, SystemPromptMessage)]
+    updated_prompt = [system_prompt] + filtered_prompts
+
+    return updated_prompt
+
+
+def _parse_structured_output(result_text: str) -> Mapping[str, Any]:
+    structured_output: Mapping[str, Any] = {}
+    parsed: Mapping[str, Any] = {}
+    try:
+        parsed = TypeAdapter(Mapping).validate_json(result_text)
+        if not isinstance(parsed, dict):
+            raise OutputParserError(f"Failed to parse structured output: {result_text}")
+        structured_output = parsed
+    except ValidationError:
+        # if the result_text is not a valid json, try to repair it
+        temp_parsed = json_repair.loads(result_text)
+        if not isinstance(temp_parsed, dict):
+            # handle reasoning model like deepseek-r1 got '<think>\n\n</think>\n' prefix
+            if isinstance(temp_parsed, list):
+                temp_parsed = next((item for item in temp_parsed if isinstance(item, dict)), {})
+            else:
+                raise OutputParserError(f"Failed to parse structured output: {result_text}")
+        structured_output = cast(dict, temp_parsed)
+    return structured_output
+
+
+def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping) -> dict:
+    """
+    Prepare JSON schema based on model requirements.
+
+    Different models have different requirements for JSON schema formatting.
+    This function handles these differences.
+
+    :param schema: The original JSON schema
+    :return: Processed schema compatible with the current model
+    """
+
+    # Deep copy to avoid modifying the original schema
+    processed_schema = dict(deepcopy(schema))
+
+    # Convert boolean types to string types (common requirement)
+    convert_boolean_to_string(processed_schema)
+
+    # Apply model-specific transformations
+    if SpecialModelType.GEMINI in model_schema.model:
+        remove_additional_properties(processed_schema)
+        return processed_schema
+    elif SpecialModelType.OLLAMA in provider:
+        return processed_schema
+    else:
+        # Default format with name field
+        return {"schema": processed_schema, "name": "llm_response"}
+
+
+def remove_additional_properties(schema: dict) -> None:
+    """
+    Remove additionalProperties fields from JSON schema.
+    Used for models like Gemini that don't support this property.
+
+    :param schema: JSON schema to modify in-place
+    """
+    if not isinstance(schema, dict):
+        return
+
+    # Remove additionalProperties at current level
+    schema.pop("additionalProperties", None)
+
+    # Process nested structures recursively
+    for value in schema.values():
+        if isinstance(value, dict):
+            remove_additional_properties(value)
+        elif isinstance(value, list):
+            for item in value:
+                if isinstance(item, dict):
+                    remove_additional_properties(item)
+
+
+def convert_boolean_to_string(schema: dict) -> None:
+    """
+    Convert boolean type specifications to string in JSON schema.
+
+    :param schema: JSON schema to modify in-place
+    """
+    if not isinstance(schema, dict):
+        return
+
+    # Check for boolean type at current level
+    if schema.get("type") == "boolean":
+        schema["type"] = "string"
+
+    # Process nested dictionaries and lists recursively
+    for value in schema.values():
+        if isinstance(value, dict):
+            convert_boolean_to_string(value)
+        elif isinstance(value, list):
+            for item in value:
+                if isinstance(item, dict):
+                    convert_boolean_to_string(item)

api/core/llm_generator/prompts.py

@@ -291,3 +291,21 @@ Your task is to convert simple user descriptions into properly formatted JSON Sc
 
 Now, generate a JSON Schema based on my description
 """  # noqa: E501
+
+STRUCTURED_OUTPUT_PROMPT = """You’re a helpful AI assistant. You could answer questions and output in JSON format.
+constraints:
+    - You must output in JSON format.
+    - Do not output boolean value, use string type instead.
+    - Do not output integer or float value, use number type instead.
+eg:
+    Here is the JSON schema:
+    {"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"}
+
+    Here is the user's question:
+    My name is John Doe and I am 30 years old.
+
+    output:
+    {"name": "John Doe", "age": 30}
+Here is the JSON schema:
+{{schema}}
+"""  # noqa: E501

api/core/mcp/auth/auth_flow.py

@@ -0,0 +1,342 @@
+import base64
+import hashlib
+import json
+import os
+import secrets
+import urllib.parse
+from typing import Optional
+from urllib.parse import urljoin
+
+import requests
+from pydantic import BaseModel, ValidationError
+
+from core.mcp.auth.auth_provider import OAuthClientProvider
+from core.mcp.types import (
+    OAuthClientInformation,
+    OAuthClientInformationFull,
+    OAuthClientMetadata,
+    OAuthMetadata,
+    OAuthTokens,
+)
+from extensions.ext_redis import redis_client
+
+LATEST_PROTOCOL_VERSION = "1.0"
+OAUTH_STATE_EXPIRY_SECONDS = 5 * 60  # 5 minutes expiry
+OAUTH_STATE_REDIS_KEY_PREFIX = "oauth_state:"
+
+
+class OAuthCallbackState(BaseModel):
+    provider_id: str
+    tenant_id: str
+    server_url: str
+    metadata: OAuthMetadata | None = None
+    client_information: OAuthClientInformation
+    code_verifier: str
+    redirect_uri: str
+
+
+def generate_pkce_challenge() -> tuple[str, str]:
+    """Generate PKCE challenge and verifier."""
+    code_verifier = base64.urlsafe_b64encode(os.urandom(40)).decode("utf-8")
+    code_verifier = code_verifier.replace("=", "").replace("+", "-").replace("/", "_")
+
+    code_challenge_hash = hashlib.sha256(code_verifier.encode("utf-8")).digest()
+    code_challenge = base64.urlsafe_b64encode(code_challenge_hash).decode("utf-8")
+    code_challenge = code_challenge.replace("=", "").replace("+", "-").replace("/", "_")
+
+    return code_verifier, code_challenge
+
+
+def _create_secure_redis_state(state_data: OAuthCallbackState) -> str:
+    """Create a secure state parameter by storing state data in Redis and returning a random state key."""
+    # Generate a secure random state key
+    state_key = secrets.token_urlsafe(32)
+
+    # Store the state data in Redis with expiration
+    redis_key = f"{OAUTH_STATE_REDIS_KEY_PREFIX}{state_key}"
+    redis_client.setex(redis_key, OAUTH_STATE_EXPIRY_SECONDS, state_data.model_dump_json())
+
+    return state_key
+
+
+def _retrieve_redis_state(state_key: str) -> OAuthCallbackState:
+    """Retrieve and decode OAuth state data from Redis using the state key, then delete it."""
+    redis_key = f"{OAUTH_STATE_REDIS_KEY_PREFIX}{state_key}"
+
+    # Get state data from Redis
+    state_data = redis_client.get(redis_key)
+
+    if not state_data:
+        raise ValueError("State parameter has expired or does not exist")
+
+    # Delete the state data from Redis immediately after retrieval to prevent reuse
+    redis_client.delete(redis_key)
+
+    try:
+        # Parse and validate the state data
+        oauth_state = OAuthCallbackState.model_validate_json(state_data)
+
+        return oauth_state
+    except ValidationError as e:
+        raise ValueError(f"Invalid state parameter: {str(e)}")
+
+
+def handle_callback(state_key: str, authorization_code: str) -> OAuthCallbackState:
+    """Handle the callback from the OAuth provider."""
+    # Retrieve state data from Redis (state is automatically deleted after retrieval)
+    full_state_data = _retrieve_redis_state(state_key)
+
+    tokens = exchange_authorization(
+        full_state_data.server_url,
+        full_state_data.metadata,
+        full_state_data.client_information,
+        authorization_code,
+        full_state_data.code_verifier,
+        full_state_data.redirect_uri,
+    )
+    provider = OAuthClientProvider(full_state_data.provider_id, full_state_data.tenant_id, for_list=True)
+    provider.save_tokens(tokens)
+    return full_state_data
+
+
+def discover_oauth_metadata(server_url: str, protocol_version: Optional[str] = None) -> Optional[OAuthMetadata]:
+    """Looks up RFC 8414 OAuth 2.0 Authorization Server Metadata."""
+    url = urljoin(server_url, "/.well-known/oauth-authorization-server")
+
+    try:
+        headers = {"MCP-Protocol-Version": protocol_version or LATEST_PROTOCOL_VERSION}
+        response = requests.get(url, headers=headers)
+        if response.status_code == 404:
+            return None
+        if not response.ok:
+            raise ValueError(f"HTTP {response.status_code} trying to load well-known OAuth metadata")
+        return OAuthMetadata.model_validate(response.json())
+    except requests.RequestException as e:
+        if isinstance(e, requests.ConnectionError):
+            response = requests.get(url)
+            if response.status_code == 404:
+                return None
+            if not response.ok:
+                raise ValueError(f"HTTP {response.status_code} trying to load well-known OAuth metadata")
+            return OAuthMetadata.model_validate(response.json())
+        raise
+
+
+def start_authorization(
+    server_url: str,
+    metadata: Optional[OAuthMetadata],
+    client_information: OAuthClientInformation,
+    redirect_url: str,
+    provider_id: str,
+    tenant_id: str,
+) -> tuple[str, str]:
+    """Begins the authorization flow with secure Redis state storage."""
+    response_type = "code"
+    code_challenge_method = "S256"
+
+    if metadata:
+        authorization_url = metadata.authorization_endpoint
+        if response_type not in metadata.response_types_supported:
+            raise ValueError(f"Incompatible auth server: does not support response type {response_type}")
+        if (
+            not metadata.code_challenge_methods_supported
+            or code_challenge_method not in metadata.code_challenge_methods_supported
+        ):
+            raise ValueError(
+                f"Incompatible auth server: does not support code challenge method {code_challenge_method}"
+            )
+    else:
+        authorization_url = urljoin(server_url, "/authorize")
+
+    code_verifier, code_challenge = generate_pkce_challenge()
+
+    # Prepare state data with all necessary information
+    state_data = OAuthCallbackState(
+        provider_id=provider_id,
+        tenant_id=tenant_id,
+        server_url=server_url,
+        metadata=metadata,
+        client_information=client_information,
+        code_verifier=code_verifier,
+        redirect_uri=redirect_url,
+    )
+
+    # Store state data in Redis and generate secure state key
+    state_key = _create_secure_redis_state(state_data)
+
+    params = {
+        "response_type": response_type,
+        "client_id": client_information.client_id,
+        "code_challenge": code_challenge,
+        "code_challenge_method": code_challenge_method,
+        "redirect_uri": redirect_url,
+        "state": state_key,
+    }
+
+    authorization_url = f"{authorization_url}?{urllib.parse.urlencode(params)}"
+    return authorization_url, code_verifier
+
+
+def exchange_authorization(
+    server_url: str,
+    metadata: Optional[OAuthMetadata],
+    client_information: OAuthClientInformation,
+    authorization_code: str,
+    code_verifier: str,
+    redirect_uri: str,
+) -> OAuthTokens:
+    """Exchanges an authorization code for an access token."""
+    grant_type = "authorization_code"
+
+    if metadata:
+        token_url = metadata.token_endpoint
+        if metadata.grant_types_supported and grant_type not in metadata.grant_types_supported:
+            raise ValueError(f"Incompatible auth server: does not support grant type {grant_type}")
+    else:
+        token_url = urljoin(server_url, "/token")
+
+    params = {
+        "grant_type": grant_type,
+        "client_id": client_information.client_id,
+        "code": authorization_code,
+        "code_verifier": code_verifier,
+        "redirect_uri": redirect_uri,
+    }
+
+    if client_information.client_secret:
+        params["client_secret"] = client_information.client_secret
+
+    response = requests.post(token_url, data=params)
+    if not response.ok:
+        raise ValueError(f"Token exchange failed: HTTP {response.status_code}")
+    return OAuthTokens.model_validate(response.json())
+
+
+def refresh_authorization(
+    server_url: str,
+    metadata: Optional[OAuthMetadata],
+    client_information: OAuthClientInformation,
+    refresh_token: str,
+) -> OAuthTokens:
+    """Exchange a refresh token for an updated access token."""
+    grant_type = "refresh_token"
+
+    if metadata:
+        token_url = metadata.token_endpoint
+        if metadata.grant_types_supported and grant_type not in metadata.grant_types_supported:
+            raise ValueError(f"Incompatible auth server: does not support grant type {grant_type}")
+    else:
+        token_url = urljoin(server_url, "/token")
+
+    params = {
+        "grant_type": grant_type,
+        "client_id": client_information.client_id,
+        "refresh_token": refresh_token,
+    }
+
+    if client_information.client_secret:
+        params["client_secret"] = client_information.client_secret
+
+    response = requests.post(token_url, data=params)
+    if not response.ok:
+        raise ValueError(f"Token refresh failed: HTTP {response.status_code}")
+    return OAuthTokens.model_validate(response.json())
+
+
+def register_client(
+    server_url: str,
+    metadata: Optional[OAuthMetadata],
+    client_metadata: OAuthClientMetadata,
+) -> OAuthClientInformationFull:
+    """Performs OAuth 2.0 Dynamic Client Registration."""
+    if metadata:
+        if not metadata.registration_endpoint:
+            raise ValueError("Incompatible auth server: does not support dynamic client registration")
+        registration_url = metadata.registration_endpoint
+    else:
+        registration_url = urljoin(server_url, "/register")
+
+    response = requests.post(
+        registration_url,
+        json=client_metadata.model_dump(),
+        headers={"Content-Type": "application/json"},
+    )
+    if not response.ok:
+        response.raise_for_status()
+    return OAuthClientInformationFull.model_validate(response.json())
+
+
+def auth(
+    provider: OAuthClientProvider,
+    server_url: str,
+    authorization_code: Optional[str] = None,
+    state_param: Optional[str] = None,
+    for_list: bool = False,
+) -> dict[str, str]:
+    """Orchestrates the full auth flow with a server using secure Redis state storage."""
+    metadata = discover_oauth_metadata(server_url)
+
+    # Handle client registration if needed
+    client_information = provider.client_information()
+    if not client_information:
+        if authorization_code is not None:
+            raise ValueError("Existing OAuth client information is required when exchanging an authorization code")
+        try:
+            full_information = register_client(server_url, metadata, provider.client_metadata)
+        except requests.RequestException as e:
+            raise ValueError(f"Could not register OAuth client: {e}")
+        provider.save_client_information(full_information)
+        client_information = full_information
+
+    # Exchange authorization code for tokens
+    if authorization_code is not None:
+        if not state_param:
+            raise ValueError("State parameter is required when exchanging authorization code")
+
+        try:
+            # Retrieve state data from Redis using state key
+            full_state_data = _retrieve_redis_state(state_param)
+
+            code_verifier = full_state_data.code_verifier
+            redirect_uri = full_state_data.redirect_uri
+
+            if not code_verifier or not redirect_uri:
+                raise ValueError("Missing code_verifier or redirect_uri in state data")
+
+        except (json.JSONDecodeError, ValueError) as e:
+            raise ValueError(f"Invalid state parameter: {e}")
+
+        tokens = exchange_authorization(
+            server_url,
+            metadata,
+            client_information,
+            authorization_code,
+            code_verifier,
+            redirect_uri,
+        )
+        provider.save_tokens(tokens)
+        return {"result": "success"}
+
+    provider_tokens = provider.tokens()
+
+    # Handle token refresh or new authorization
+    if provider_tokens and provider_tokens.refresh_token:
+        try:
+            new_tokens = refresh_authorization(server_url, metadata, client_information, provider_tokens.refresh_token)
+            provider.save_tokens(new_tokens)
+            return {"result": "success"}
+        except Exception as e:
+            raise ValueError(f"Could not refresh OAuth tokens: {e}")
+
+    # Start new authorization flow
+    authorization_url, code_verifier = start_authorization(
+        server_url,
+        metadata,
+        client_information,
+        provider.redirect_url,
+        provider.mcp_provider.id,
+        provider.mcp_provider.tenant_id,
+    )
+
+    provider.save_code_verifier(code_verifier)
+    return {"authorization_url": authorization_url}

api/core/mcp/auth/auth_provider.py

@@ -0,0 +1,81 @@
+from typing import Optional
+
+from configs import dify_config
+from core.mcp.types import (
+    OAuthClientInformation,
+    OAuthClientInformationFull,
+    OAuthClientMetadata,
+    OAuthTokens,
+)
+from models.tools import MCPToolProvider
+from services.tools.mcp_tools_mange_service import MCPToolManageService
+
+LATEST_PROTOCOL_VERSION = "1.0"
+
+
+class OAuthClientProvider:
+    mcp_provider: MCPToolProvider
+
+    def __init__(self, provider_id: str, tenant_id: str, for_list: bool = False):
+        if for_list:
+            self.mcp_provider = MCPToolManageService.get_mcp_provider_by_provider_id(provider_id, tenant_id)
+        else:
+            self.mcp_provider = MCPToolManageService.get_mcp_provider_by_server_identifier(provider_id, tenant_id)
+
+    @property
+    def redirect_url(self) -> str:
+        """The URL to redirect the user agent to after authorization."""
+        return dify_config.CONSOLE_API_URL + "/console/api/mcp/oauth/callback"
+
+    @property
+    def client_metadata(self) -> OAuthClientMetadata:
+        """Metadata about this OAuth client."""
+        return OAuthClientMetadata(
+            redirect_uris=[self.redirect_url],
+            token_endpoint_auth_method="none",
+            grant_types=["authorization_code", "refresh_token"],
+            response_types=["code"],
+            client_name="Dify",
+            client_uri="https://github.com/langgenius/dify",
+        )
+
+    def client_information(self) -> Optional[OAuthClientInformation]:
+        """Loads information about this OAuth client."""
+        client_information = self.mcp_provider.decrypted_credentials.get("client_information", {})
+        if not client_information:
+            return None
+        return OAuthClientInformation.model_validate(client_information)
+
+    def save_client_information(self, client_information: OAuthClientInformationFull) -> None:
+        """Saves client information after dynamic registration."""
+        MCPToolManageService.update_mcp_provider_credentials(
+            self.mcp_provider,
+            {"client_information": client_information.model_dump()},
+        )
+
+    def tokens(self) -> Optional[OAuthTokens]:
+        """Loads any existing OAuth tokens for the current session."""
+        credentials = self.mcp_provider.decrypted_credentials
+        if not credentials:
+            return None
+        return OAuthTokens(
+            access_token=credentials.get("access_token", ""),
+            token_type=credentials.get("token_type", "Bearer"),
+            expires_in=int(credentials.get("expires_in", "3600") or 3600),
+            refresh_token=credentials.get("refresh_token", ""),
+        )
+
+    def save_tokens(self, tokens: OAuthTokens) -> None:
+        """Stores new OAuth tokens for the current session."""
+        # update mcp provider credentials
+        token_dict = tokens.model_dump()
+        MCPToolManageService.update_mcp_provider_credentials(self.mcp_provider, token_dict, authed=True)
+
+    def save_code_verifier(self, code_verifier: str) -> None:
+        """Saves a PKCE code verifier for the current session."""
+        MCPToolManageService.update_mcp_provider_credentials(self.mcp_provider, {"code_verifier": code_verifier})
+
+    def code_verifier(self) -> str:
+        """Loads the PKCE code verifier for the current session."""
+        # get code verifier from mcp provider credentials
+        return str(self.mcp_provider.decrypted_credentials.get("code_verifier", ""))

api/core/mcp/client/sse_client.py

@@ -0,0 +1,361 @@
+import logging
+import queue
+from collections.abc import Generator
+from concurrent.futures import ThreadPoolExecutor
+from contextlib import contextmanager
+from typing import Any, TypeAlias, final
+from urllib.parse import urljoin, urlparse
+
+import httpx
+from sseclient import SSEClient
+
+from core.mcp import types
+from core.mcp.error import MCPAuthError, MCPConnectionError
+from core.mcp.types import SessionMessage
+from core.mcp.utils import create_ssrf_proxy_mcp_http_client, ssrf_proxy_sse_connect
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_QUEUE_READ_TIMEOUT = 3
+
+
+@final
+class _StatusReady:
+    def __init__(self, endpoint_url: str):
+        self._endpoint_url = endpoint_url
+
+
+@final
+class _StatusError:
+    def __init__(self, exc: Exception):
+        self._exc = exc
+
+
+# Type aliases for better readability
+ReadQueue: TypeAlias = queue.Queue[SessionMessage | Exception | None]
+WriteQueue: TypeAlias = queue.Queue[SessionMessage | Exception | None]
+StatusQueue: TypeAlias = queue.Queue[_StatusReady | _StatusError]
+
+
+def remove_request_params(url: str) -> str:
+    """Remove request parameters from URL, keeping only the path."""
+    return urljoin(url, urlparse(url).path)
+
+
+class SSETransport:
+    """SSE client transport implementation."""
+
+    def __init__(
+        self,
+        url: str,
+        headers: dict[str, Any] | None = None,
+        timeout: float = 5.0,
+        sse_read_timeout: float = 5 * 60,
+    ) -> None:
+        """Initialize the SSE transport.
+
+        Args:
+            url: The SSE endpoint URL.
+            headers: Optional headers to include in requests.
+            timeout: HTTP timeout for regular operations.
+            sse_read_timeout: Timeout for SSE read operations.
+        """
+        self.url = url
+        self.headers = headers or {}
+        self.timeout = timeout
+        self.sse_read_timeout = sse_read_timeout
+        self.endpoint_url: str | None = None
+
+    def _validate_endpoint_url(self, endpoint_url: str) -> bool:
+        """Validate that the endpoint URL matches the connection origin.
+
+        Args:
+            endpoint_url: The endpoint URL to validate.
+
+        Returns:
+            True if valid, False otherwise.
+        """
+        url_parsed = urlparse(self.url)
+        endpoint_parsed = urlparse(endpoint_url)
+
+        return url_parsed.netloc == endpoint_parsed.netloc and url_parsed.scheme == endpoint_parsed.scheme
+
+    def _handle_endpoint_event(self, sse_data: str, status_queue: StatusQueue) -> None:
+        """Handle an 'endpoint' SSE event.
+
+        Args:
+            sse_data: The SSE event data.
+            status_queue: Queue to put status updates.
+        """
+        endpoint_url = urljoin(self.url, sse_data)
+        logger.info(f"Received endpoint URL: {endpoint_url}")
+
+        if not self._validate_endpoint_url(endpoint_url):
+            error_msg = f"Endpoint origin does not match connection origin: {endpoint_url}"
+            logger.error(error_msg)
+            status_queue.put(_StatusError(ValueError(error_msg)))
+            return
+
+        status_queue.put(_StatusReady(endpoint_url))
+
+    def _handle_message_event(self, sse_data: str, read_queue: ReadQueue) -> None:
+        """Handle a 'message' SSE event.
+
+        Args:
+            sse_data: The SSE event data.
+            read_queue: Queue to put parsed messages.
+        """
+        try:
+            message = types.JSONRPCMessage.model_validate_json(sse_data)
+            logger.debug(f"Received server message: {message}")
+            session_message = SessionMessage(message)
+            read_queue.put(session_message)
+        except Exception as exc:
+            logger.exception("Error parsing server message")
+            read_queue.put(exc)
+
+    def _handle_sse_event(self, sse, read_queue: ReadQueue, status_queue: StatusQueue) -> None:
+        """Handle a single SSE event.
+
+        Args:
+            sse: The SSE event object.
+            read_queue: Queue for message events.
+            status_queue: Queue for status events.
+        """
+        match sse.event:
+            case "endpoint":
+                self._handle_endpoint_event(sse.data, status_queue)
+            case "message":
+                self._handle_message_event(sse.data, read_queue)
+            case _:
+                logger.warning(f"Unknown SSE event: {sse.event}")
+
+    def sse_reader(self, event_source, read_queue: ReadQueue, status_queue: StatusQueue) -> None:
+        """Read and process SSE events.
+
+        Args:
+            event_source: The SSE event source.
+            read_queue: Queue to put received messages.
+            status_queue: Queue to put status updates.
+        """
+        try:
+            for sse in event_source.iter_sse():
+                self._handle_sse_event(sse, read_queue, status_queue)
+        except httpx.ReadError as exc:
+            logger.debug(f"SSE reader shutting down normally: {exc}")
+        except Exception as exc:
+            read_queue.put(exc)
+        finally:
+            read_queue.put(None)
+
+    def _send_message(self, client: httpx.Client, endpoint_url: str, message: SessionMessage) -> None:
+        """Send a single message to the server.
+
+        Args:
+            client: HTTP client to use.
+            endpoint_url: The endpoint URL to send to.
+            message: The message to send.
+        """
+        response = client.post(
+            endpoint_url,
+            json=message.message.model_dump(
+                by_alias=True,
+                mode="json",
+                exclude_none=True,
+            ),
+        )
+        response.raise_for_status()
+        logger.debug(f"Client message sent successfully: {response.status_code}")
+
+    def post_writer(self, client: httpx.Client, endpoint_url: str, write_queue: WriteQueue) -> None:
+        """Handle writing messages to the server.
+
+        Args:
+            client: HTTP client to use.
+            endpoint_url: The endpoint URL to send messages to.
+            write_queue: Queue to read messages from.
+        """
+        try:
+            while True:
+                try:
+                    message = write_queue.get(timeout=DEFAULT_QUEUE_READ_TIMEOUT)
+                    if message is None:
+                        break
+                    if isinstance(message, Exception):
+                        write_queue.put(message)
+                        continue
+
+                    self._send_message(client, endpoint_url, message)
+
+                except queue.Empty:
+                    continue
+        except httpx.ReadError as exc:
+            logger.debug(f"Post writer shutting down normally: {exc}")
+        except Exception as exc:
+            logger.exception("Error writing messages")
+            write_queue.put(exc)
+        finally:
+            write_queue.put(None)
+
+    def _wait_for_endpoint(self, status_queue: StatusQueue) -> str:
+        """Wait for the endpoint URL from the status queue.
+
+        Args:
+            status_queue: Queue to read status from.
+
+        Returns:
+            The endpoint URL.
+
+        Raises:
+            ValueError: If endpoint URL is not received or there's an error.
+        """
+        try:
+            status = status_queue.get(timeout=1)
+        except queue.Empty:
+            raise ValueError("failed to get endpoint URL")
+
+        if isinstance(status, _StatusReady):
+            return status._endpoint_url
+        elif isinstance(status, _StatusError):
+            raise status._exc
+        else:
+            raise ValueError("failed to get endpoint URL")
+
+    def connect(
+        self,
+        executor: ThreadPoolExecutor,
+        client: httpx.Client,
+        event_source,
+    ) -> tuple[ReadQueue, WriteQueue]:
+        """Establish connection and start worker threads.
+
+        Args:
+            executor: Thread pool executor.
+            client: HTTP client.
+            event_source: SSE event source.
+
+        Returns:
+            Tuple of (read_queue, write_queue).
+        """
+        read_queue: ReadQueue = queue.Queue()
+        write_queue: WriteQueue = queue.Queue()
+        status_queue: StatusQueue = queue.Queue()
+
+        # Start SSE reader thread
+        executor.submit(self.sse_reader, event_source, read_queue, status_queue)
+
+        # Wait for endpoint URL
+        endpoint_url = self._wait_for_endpoint(status_queue)
+        self.endpoint_url = endpoint_url
+
+        # Start post writer thread
+        executor.submit(self.post_writer, client, endpoint_url, write_queue)
+
+        return read_queue, write_queue
+
+
+@contextmanager
+def sse_client(
+    url: str,
+    headers: dict[str, Any] | None = None,
+    timeout: float = 5.0,
+    sse_read_timeout: float = 5 * 60,
+) -> Generator[tuple[ReadQueue, WriteQueue], None, None]:
+    """
+    Client transport for SSE.
+    `sse_read_timeout` determines how long (in seconds) the client will wait for a new
+    event before disconnecting. All other HTTP operations are controlled by `timeout`.
+
+    Args:
+        url: The SSE endpoint URL.
+        headers: Optional headers to include in requests.
+        timeout: HTTP timeout for regular operations.
+        sse_read_timeout: Timeout for SSE read operations.
+
+    Yields:
+        Tuple of (read_queue, write_queue) for message communication.
+    """
+    transport = SSETransport(url, headers, timeout, sse_read_timeout)
+
+    read_queue: ReadQueue | None = None
+    write_queue: WriteQueue | None = None
+
+    with ThreadPoolExecutor() as executor:
+        try:
+            with create_ssrf_proxy_mcp_http_client(headers=transport.headers) as client:
+                with ssrf_proxy_sse_connect(
+                    url, timeout=httpx.Timeout(timeout, read=sse_read_timeout), client=client
+                ) as event_source:
+                    event_source.response.raise_for_status()
+
+                    read_queue, write_queue = transport.connect(executor, client, event_source)
+
+                    yield read_queue, write_queue
+
+        except httpx.HTTPStatusError as exc:
+            if exc.response.status_code == 401:
+                raise MCPAuthError()
+            raise MCPConnectionError()
+        except Exception:
+            logger.exception("Error connecting to SSE endpoint")
+            raise
+        finally:
+            # Clean up queues
+            if read_queue:
+                read_queue.put(None)
+            if write_queue:
+                write_queue.put(None)
+
+
+def send_message(http_client: httpx.Client, endpoint_url: str, session_message: SessionMessage) -> None:
+    """
+    Send a message to the server using the provided HTTP client.
+
+    Args:
+        http_client: The HTTP client to use for sending
+        endpoint_url: The endpoint URL to send the message to
+        session_message: The message to send
+    """
+    try:
+        response = http_client.post(
+            endpoint_url,
+            json=session_message.message.model_dump(
+                by_alias=True,
+                mode="json",
+                exclude_none=True,
+            ),
+        )
+        response.raise_for_status()
+        logger.debug(f"Client message sent successfully: {response.status_code}")
+    except Exception as exc:
+        logger.exception("Error sending message")
+        raise
+
+
+def read_messages(
+    sse_client: SSEClient,
+) -> Generator[SessionMessage | Exception, None, None]:
+    """
+    Read messages from the SSE client.
+
+    Args:
+        sse_client: The SSE client to read from
+
+    Yields:
+        SessionMessage or Exception for each event received
+    """
+    try:
+        for sse in sse_client.events():
+            if sse.event == "message":
+                try:
+                    message = types.JSONRPCMessage.model_validate_json(sse.data)
+                    logger.debug(f"Received server message: {message}")
+                    yield SessionMessage(message)
+                except Exception as exc:
+                    logger.exception("Error parsing server message")
+                    yield exc
+            else:
+                logger.warning(f"Unknown SSE event: {sse.event}")
+    except Exception as exc:
+        logger.exception("Error reading SSE messages")
+        yield exc

api/core/mcp/client/streamable_client.py

@@ -0,0 +1,476 @@
+"""
+StreamableHTTP Client Transport Module
+
+This module implements the StreamableHTTP transport for MCP clients,
+providing support for HTTP POST requests with optional SSE streaming responses
+and session management.
+"""
+
+import logging
+import queue
+from collections.abc import Callable, Generator
+from concurrent.futures import ThreadPoolExecutor
+from contextlib import contextmanager
+from dataclasses import dataclass
+from datetime import timedelta
+from typing import Any, cast
+
+import httpx
+from httpx_sse import EventSource, ServerSentEvent
+
+from core.mcp.types import (
+    ClientMessageMetadata,
+    ErrorData,
+    JSONRPCError,
+    JSONRPCMessage,
+    JSONRPCNotification,
+    JSONRPCRequest,
+    JSONRPCResponse,
+    RequestId,
+    SessionMessage,
+)
+from core.mcp.utils import create_ssrf_proxy_mcp_http_client, ssrf_proxy_sse_connect
+
+logger = logging.getLogger(__name__)
+
+
+SessionMessageOrError = SessionMessage | Exception | None
+# Queue types with clearer names for their roles
+ServerToClientQueue = queue.Queue[SessionMessageOrError]  # Server to client messages
+ClientToServerQueue = queue.Queue[SessionMessage | None]  # Client to server messages
+GetSessionIdCallback = Callable[[], str | None]
+
+MCP_SESSION_ID = "mcp-session-id"
+LAST_EVENT_ID = "last-event-id"
+CONTENT_TYPE = "content-type"
+ACCEPT = "Accept"
+
+
+JSON = "application/json"
+SSE = "text/event-stream"
+
+DEFAULT_QUEUE_READ_TIMEOUT = 3
+
+
+class StreamableHTTPError(Exception):
+    """Base exception for StreamableHTTP transport errors."""
+
+    pass
+
+
+class ResumptionError(StreamableHTTPError):
+    """Raised when resumption request is invalid."""
+
+    pass
+
+
+@dataclass
+class RequestContext:
+    """Context for a request operation."""
+
+    client: httpx.Client
+    headers: dict[str, str]
+    session_id: str | None
+    session_message: SessionMessage
+    metadata: ClientMessageMetadata | None
+    server_to_client_queue: ServerToClientQueue  # Renamed for clarity
+    sse_read_timeout: timedelta
+
+
+class StreamableHTTPTransport:
+    """StreamableHTTP client transport implementation."""
+
+    def __init__(
+        self,
+        url: str,
+        headers: dict[str, Any] | None = None,
+        timeout: timedelta = timedelta(seconds=30),
+        sse_read_timeout: timedelta = timedelta(seconds=60 * 5),
+    ) -> None:
+        """Initialize the StreamableHTTP transport.
+
+        Args:
+            url: The endpoint URL.
+            headers: Optional headers to include in requests.
+            timeout: HTTP timeout for regular operations.
+            sse_read_timeout: Timeout for SSE read operations.
+        """
+        self.url = url
+        self.headers = headers or {}
+        self.timeout = timeout
+        self.sse_read_timeout = sse_read_timeout
+        self.session_id: str | None = None
+        self.request_headers = {
+            ACCEPT: f"{JSON}, {SSE}",
+            CONTENT_TYPE: JSON,
+            **self.headers,
+        }
+
+    def _update_headers_with_session(self, base_headers: dict[str, str]) -> dict[str, str]:
+        """Update headers with session ID if available."""
+        headers = base_headers.copy()
+        if self.session_id:
+            headers[MCP_SESSION_ID] = self.session_id
+        return headers
+
+    def _is_initialization_request(self, message: JSONRPCMessage) -> bool:
+        """Check if the message is an initialization request."""
+        return isinstance(message.root, JSONRPCRequest) and message.root.method == "initialize"
+
+    def _is_initialized_notification(self, message: JSONRPCMessage) -> bool:
+        """Check if the message is an initialized notification."""
+        return isinstance(message.root, JSONRPCNotification) and message.root.method == "notifications/initialized"
+
+    def _maybe_extract_session_id_from_response(
+        self,
+        response: httpx.Response,
+    ) -> None:
+        """Extract and store session ID from response headers."""
+        new_session_id = response.headers.get(MCP_SESSION_ID)
+        if new_session_id:
+            self.session_id = new_session_id
+            logger.info(f"Received session ID: {self.session_id}")
+
+    def _handle_sse_event(
+        self,
+        sse: ServerSentEvent,
+        server_to_client_queue: ServerToClientQueue,
+        original_request_id: RequestId | None = None,
+        resumption_callback: Callable[[str], None] | None = None,
+    ) -> bool:
+        """Handle an SSE event, returning True if the response is complete."""
+        if sse.event == "message":
+            try:
+                message = JSONRPCMessage.model_validate_json(sse.data)
+                logger.debug(f"SSE message: {message}")
+
+                # If this is a response and we have original_request_id, replace it
+                if original_request_id is not None and isinstance(message.root, JSONRPCResponse | JSONRPCError):
+                    message.root.id = original_request_id
+
+                session_message = SessionMessage(message)
+                # Put message in queue that goes to client
+                server_to_client_queue.put(session_message)
+
+                # Call resumption token callback if we have an ID
+                if sse.id and resumption_callback:
+                    resumption_callback(sse.id)
+
+                # If this is a response or error return True indicating completion
+                # Otherwise, return False to continue listening
+                return isinstance(message.root, JSONRPCResponse | JSONRPCError)
+
+            except Exception as exc:
+                # Put exception in queue that goes to client
+                server_to_client_queue.put(exc)
+                return False
+        elif sse.event == "ping":
+            logger.debug("Received ping event")
+            return False
+        else:
+            logger.warning(f"Unknown SSE event: {sse.event}")
+            return False
+
+    def handle_get_stream(
+        self,
+        client: httpx.Client,
+        server_to_client_queue: ServerToClientQueue,
+    ) -> None:
+        """Handle GET stream for server-initiated messages."""
+        try:
+            if not self.session_id:
+                return
+
+            headers = self._update_headers_with_session(self.request_headers)
+
+            with ssrf_proxy_sse_connect(
+                self.url,
+                headers=headers,
+                timeout=httpx.Timeout(self.timeout.seconds, read=self.sse_read_timeout.seconds),
+                client=client,
+                method="GET",
+            ) as event_source:
+                event_source.response.raise_for_status()
+                logger.debug("GET SSE connection established")
+
+                for sse in event_source.iter_sse():
+                    self._handle_sse_event(sse, server_to_client_queue)
+
+        except Exception as exc:
+            logger.debug(f"GET stream error (non-fatal): {exc}")
+
+    def _handle_resumption_request(self, ctx: RequestContext) -> None:
+        """Handle a resumption request using GET with SSE."""
+        headers = self._update_headers_with_session(ctx.headers)
+        if ctx.metadata and ctx.metadata.resumption_token:
+            headers[LAST_EVENT_ID] = ctx.metadata.resumption_token
+        else:
+            raise ResumptionError("Resumption request requires a resumption token")
+
+        # Extract original request ID to map responses
+        original_request_id = None
+        if isinstance(ctx.session_message.message.root, JSONRPCRequest):
+            original_request_id = ctx.session_message.message.root.id
+
+        with ssrf_proxy_sse_connect(
+            self.url,
+            headers=headers,
+            timeout=httpx.Timeout(self.timeout.seconds, read=ctx.sse_read_timeout.seconds),
+            client=ctx.client,
+            method="GET",
+        ) as event_source:
+            event_source.response.raise_for_status()
+            logger.debug("Resumption GET SSE connection established")
+
+            for sse in event_source.iter_sse():
+                is_complete = self._handle_sse_event(
+                    sse,
+                    ctx.server_to_client_queue,
+                    original_request_id,
+                    ctx.metadata.on_resumption_token_update if ctx.metadata else None,
+                )
+                if is_complete:
+                    break
+
+    def _handle_post_request(self, ctx: RequestContext) -> None:
+        """Handle a POST request with response processing."""
+        headers = self._update_headers_with_session(ctx.headers)
+        message = ctx.session_message.message
+        is_initialization = self._is_initialization_request(message)
+
+        with ctx.client.stream(
+            "POST",
+            self.url,
+            json=message.model_dump(by_alias=True, mode="json", exclude_none=True),
+            headers=headers,
+        ) as response:
+            if response.status_code == 202:
+                logger.debug("Received 202 Accepted")
+                return
+
+            if response.status_code == 404:
+                if isinstance(message.root, JSONRPCRequest):
+                    self._send_session_terminated_error(
+                        ctx.server_to_client_queue,
+                        message.root.id,
+                    )
+                return
+
+            response.raise_for_status()
+            if is_initialization:
+                self._maybe_extract_session_id_from_response(response)
+
+            content_type = cast(str, response.headers.get(CONTENT_TYPE, "").lower())
+
+            if content_type.startswith(JSON):
+                self._handle_json_response(response, ctx.server_to_client_queue)
+            elif content_type.startswith(SSE):
+                self._handle_sse_response(response, ctx)
+            else:
+                self._handle_unexpected_content_type(
+                    content_type,
+                    ctx.server_to_client_queue,
+                )
+
+    def _handle_json_response(
+        self,
+        response: httpx.Response,
+        server_to_client_queue: ServerToClientQueue,
+    ) -> None:
+        """Handle JSON response from the server."""
+        try:
+            content = response.read()
+            message = JSONRPCMessage.model_validate_json(content)
+            session_message = SessionMessage(message)
+            server_to_client_queue.put(session_message)
+        except Exception as exc:
+            server_to_client_queue.put(exc)
+
+    def _handle_sse_response(self, response: httpx.Response, ctx: RequestContext) -> None:
+        """Handle SSE response from the server."""
+        try:
+            event_source = EventSource(response)
+            for sse in event_source.iter_sse():
+                is_complete = self._handle_sse_event(
+                    sse,
+                    ctx.server_to_client_queue,
+                    resumption_callback=(ctx.metadata.on_resumption_token_update if ctx.metadata else None),
+                )
+                if is_complete:
+                    break
+        except Exception as e:
+            ctx.server_to_client_queue.put(e)
+
+    def _handle_unexpected_content_type(
+        self,
+        content_type: str,
+        server_to_client_queue: ServerToClientQueue,
+    ) -> None:
+        """Handle unexpected content type in response."""
+        error_msg = f"Unexpected content type: {content_type}"
+        logger.error(error_msg)
+        server_to_client_queue.put(ValueError(error_msg))
+
+    def _send_session_terminated_error(
+        self,
+        server_to_client_queue: ServerToClientQueue,
+        request_id: RequestId,
+    ) -> None:
+        """Send a session terminated error response."""
+        jsonrpc_error = JSONRPCError(
+            jsonrpc="2.0",
+            id=request_id,
+            error=ErrorData(code=32600, message="Session terminated by server"),
+        )
+        session_message = SessionMessage(JSONRPCMessage(jsonrpc_error))
+        server_to_client_queue.put(session_message)
+
+    def post_writer(
+        self,
+        client: httpx.Client,
+        client_to_server_queue: ClientToServerQueue,
+        server_to_client_queue: ServerToClientQueue,
+        start_get_stream: Callable[[], None],
+    ) -> None:
+        """Handle writing requests to the server.
+
+        This method processes messages from the client_to_server_queue and sends them to the server.
+        Responses are written to the server_to_client_queue.
+        """
+        while True:
+            try:
+                # Read message from client queue with timeout to check stop_event periodically
+                session_message = client_to_server_queue.get(timeout=DEFAULT_QUEUE_READ_TIMEOUT)
+                if session_message is None:
+                    break
+
+                message = session_message.message
+                metadata = (
+                    session_message.metadata if isinstance(session_message.metadata, ClientMessageMetadata) else None
+                )
+
+                # Check if this is a resumption request
+                is_resumption = bool(metadata and metadata.resumption_token)
+
+                logger.debug(f"Sending client message: {message}")
+
+                # Handle initialized notification
+                if self._is_initialized_notification(message):
+                    start_get_stream()
+
+                ctx = RequestContext(
+                    client=client,
+                    headers=self.request_headers,
+                    session_id=self.session_id,
+                    session_message=session_message,
+                    metadata=metadata,
+                    server_to_client_queue=server_to_client_queue,  # Queue to write responses to client
+                    sse_read_timeout=self.sse_read_timeout,
+                )
+
+                if is_resumption:
+                    self._handle_resumption_request(ctx)
+                else:
+                    self._handle_post_request(ctx)
+            except queue.Empty:
+                continue
+            except Exception as exc:
+                server_to_client_queue.put(exc)
+
+    def terminate_session(self, client: httpx.Client) -> None:
+        """Terminate the session by sending a DELETE request."""
+        if not self.session_id:
+            return
+
+        try:
+            headers = self._update_headers_with_session(self.request_headers)
+            response = client.delete(self.url, headers=headers)
+
+            if response.status_code == 405:
+                logger.debug("Server does not allow session termination")
+            elif response.status_code != 200:
+                logger.warning(f"Session termination failed: {response.status_code}")
+        except Exception as exc:
+            logger.warning(f"Session termination failed: {exc}")
+
+    def get_session_id(self) -> str | None:
+        """Get the current session ID."""
+        return self.session_id
+
+
+@contextmanager
+def streamablehttp_client(
+    url: str,
+    headers: dict[str, Any] | None = None,
+    timeout: timedelta = timedelta(seconds=30),
+    sse_read_timeout: timedelta = timedelta(seconds=60 * 5),
+    terminate_on_close: bool = True,
+) -> Generator[
+    tuple[
+        ServerToClientQueue,  # Queue for receiving messages FROM server
+        ClientToServerQueue,  # Queue for sending messages TO server
+        GetSessionIdCallback,
+    ],
+    None,
+    None,
+]:
+    """
+    Client transport for StreamableHTTP.
+
+    `sse_read_timeout` determines how long (in seconds) the client will wait for a new
+    event before disconnecting. All other HTTP operations are controlled by `timeout`.
+
+    Yields:
+        Tuple containing:
+            - server_to_client_queue: Queue for reading messages FROM the server
+            - client_to_server_queue: Queue for sending messages TO the server
+            - get_session_id_callback: Function to retrieve the current session ID
+    """
+    transport = StreamableHTTPTransport(url, headers, timeout, sse_read_timeout)
+
+    # Create queues with clear directional meaning
+    server_to_client_queue: ServerToClientQueue = queue.Queue()  # For messages FROM server TO client
+    client_to_server_queue: ClientToServerQueue = queue.Queue()  # For messages FROM client TO server
+
+    with ThreadPoolExecutor(max_workers=2) as executor:
+        try:
+            with create_ssrf_proxy_mcp_http_client(
+                headers=transport.request_headers,
+                timeout=httpx.Timeout(transport.timeout.seconds, read=transport.sse_read_timeout.seconds),
+            ) as client:
+                # Define callbacks that need access to thread pool
+                def start_get_stream() -> None:
+                    """Start a worker thread to handle server-initiated messages."""
+                    executor.submit(transport.handle_get_stream, client, server_to_client_queue)
+
+                # Start the post_writer worker thread
+                executor.submit(
+                    transport.post_writer,
+                    client,
+                    client_to_server_queue,  # Queue for messages FROM client TO server
+                    server_to_client_queue,  # Queue for messages FROM server TO client
+                    start_get_stream,
+                )
+
+                try:
+                    yield (
+                        server_to_client_queue,  # Queue for receiving messages FROM server
+                        client_to_server_queue,  # Queue for sending messages TO server
+                        transport.get_session_id,
+                    )
+                finally:
+                    if transport.session_id and terminate_on_close:
+                        transport.terminate_session(client)
+
+                    # Signal threads to stop
+                    client_to_server_queue.put(None)
+        finally:
+            # Clear any remaining items and add None sentinel to unblock any waiting threads
+            try:
+                while not client_to_server_queue.empty():
+                    client_to_server_queue.get_nowait()
+            except queue.Empty:
+                pass
+
+            client_to_server_queue.put(None)
+            server_to_client_queue.put(None)

api/core/mcp/entities.py

@@ -0,0 +1,19 @@
+from dataclasses import dataclass
+from typing import Any, Generic, TypeVar
+
+from core.mcp.session.base_session import BaseSession
+from core.mcp.types import LATEST_PROTOCOL_VERSION, RequestId, RequestParams
+
+SUPPORTED_PROTOCOL_VERSIONS: list[str] = ["2024-11-05", LATEST_PROTOCOL_VERSION]
+
+
+SessionT = TypeVar("SessionT", bound=BaseSession[Any, Any, Any, Any, Any])
+LifespanContextT = TypeVar("LifespanContextT")
+
+
+@dataclass
+class RequestContext(Generic[SessionT, LifespanContextT]):
+    request_id: RequestId
+    meta: RequestParams.Meta | None
+    session: SessionT
+    lifespan_context: LifespanContextT

api/core/mcp/error.py

@@ -0,0 +1,10 @@
+class MCPError(Exception):
+    pass
+
+
+class MCPConnectionError(MCPError):
+    pass
+
+
+class MCPAuthError(MCPConnectionError):
+    pass

api/core/mcp/mcp_client.py

@@ -0,0 +1,150 @@
+import logging
+from collections.abc import Callable
+from contextlib import AbstractContextManager, ExitStack
+from types import TracebackType
+from typing import Any, Optional, cast
+from urllib.parse import urlparse
+
+from core.mcp.client.sse_client import sse_client
+from core.mcp.client.streamable_client import streamablehttp_client
+from core.mcp.error import MCPAuthError, MCPConnectionError
+from core.mcp.session.client_session import ClientSession
+from core.mcp.types import Tool
+
+logger = logging.getLogger(__name__)
+
+
+class MCPClient:
+    def __init__(
+        self,
+        server_url: str,
+        provider_id: str,
+        tenant_id: str,
+        authed: bool = True,
+        authorization_code: Optional[str] = None,
+        for_list: bool = False,
+    ):
+        # Initialize info
+        self.provider_id = provider_id
+        self.tenant_id = tenant_id
+        self.client_type = "streamable"
+        self.server_url = server_url
+
+        # Authentication info
+        self.authed = authed
+        self.authorization_code = authorization_code
+        if authed:
+            from core.mcp.auth.auth_provider import OAuthClientProvider
+
+            self.provider = OAuthClientProvider(self.provider_id, self.tenant_id, for_list=for_list)
+            self.token = self.provider.tokens()
+
+        # Initialize session and client objects
+        self._session: Optional[ClientSession] = None
+        self._streams_context: Optional[AbstractContextManager[Any]] = None
+        self._session_context: Optional[ClientSession] = None
+        self.exit_stack = ExitStack()
+
+        # Whether the client has been initialized
+        self._initialized = False
+
+    def __enter__(self):
+        self._initialize()
+        self._initialized = True
+        return self
+
+    def __exit__(
+        self, exc_type: Optional[type], exc_value: Optional[BaseException], traceback: Optional[TracebackType]
+    ):
+        self.cleanup()
+
+    def _initialize(
+        self,
+    ):
+        """Initialize the client with fallback to SSE if streamable connection fails"""
+        connection_methods: dict[str, Callable[..., AbstractContextManager[Any]]] = {
+            "mcp": streamablehttp_client,
+            "sse": sse_client,
+        }
+
+        parsed_url = urlparse(self.server_url)
+        path = parsed_url.path
+        method_name = path.rstrip("/").split("/")[-1] if path else ""
+        try:
+            client_factory = connection_methods[method_name]
+            self.connect_server(client_factory, method_name)
+        except KeyError:
+            try:
+                self.connect_server(sse_client, "sse")
+            except MCPConnectionError:
+                self.connect_server(streamablehttp_client, "mcp")
+
+    def connect_server(
+        self, client_factory: Callable[..., AbstractContextManager[Any]], method_name: str, first_try: bool = True
+    ):
+        from core.mcp.auth.auth_flow import auth
+
+        try:
+            headers = (
+                {"Authorization": f"{self.token.token_type.capitalize()} {self.token.access_token}"}
+                if self.authed and self.token
+                else {}
+            )
+            self._streams_context = client_factory(url=self.server_url, headers=headers)
+            if self._streams_context is None:
+                raise MCPConnectionError("Failed to create connection context")
+
+            # Use exit_stack to manage context managers properly
+            if method_name == "mcp":
+                read_stream, write_stream, _ = self.exit_stack.enter_context(self._streams_context)
+                streams = (read_stream, write_stream)
+            else:  # sse_client
+                streams = self.exit_stack.enter_context(self._streams_context)
+
+            self._session_context = ClientSession(*streams)
+            self._session = self.exit_stack.enter_context(self._session_context)
+            session = cast(ClientSession, self._session)
+            session.initialize()
+            return
+
+        except MCPAuthError:
+            if not self.authed:
+                raise
+            try:
+                auth(self.provider, self.server_url, self.authorization_code)
+            except Exception as e:
+                raise ValueError(f"Failed to authenticate: {e}")
+            self.token = self.provider.tokens()
+            if first_try:
+                return self.connect_server(client_factory, method_name, first_try=False)
+
+        except MCPConnectionError:
+            raise
+
+    def list_tools(self) -> list[Tool]:
+        """Connect to an MCP server running with SSE transport"""
+        # List available tools to verify connection
+        if not self._initialized or not self._session:
+            raise ValueError("Session not initialized.")
+        response = self._session.list_tools()
+        tools = response.tools
+        return tools
+
+    def invoke_tool(self, tool_name: str, tool_args: dict):
+        """Call a tool"""
+        if not self._initialized or not self._session:
+            raise ValueError("Session not initialized.")
+        return self._session.call_tool(tool_name, tool_args)
+
+    def cleanup(self):
+        """Clean up resources"""
+        try:
+            # ExitStack will handle proper cleanup of all managed context managers
+            self.exit_stack.close()
+            self._session = None
+            self._session_context = None
+            self._streams_context = None
+            self._initialized = False
+        except Exception as e:
+            logging.exception("Error during cleanup")
+            raise ValueError(f"Error during cleanup: {e}")

api/core/mcp/server/streamable_http.py

@@ -0,0 +1,228 @@
+import json
+import logging
+from collections.abc import Mapping
+from typing import Any, cast
+
+from configs import dify_config
+from controllers.web.passport import generate_session_id
+from core.app.app_config.entities import VariableEntity, VariableEntityType
+from core.app.entities.app_invoke_entities import InvokeFrom
+from core.app.features.rate_limiting.rate_limit import RateLimitGenerator
+from core.mcp import types
+from core.mcp.types import INTERNAL_ERROR, INVALID_PARAMS, METHOD_NOT_FOUND
+from core.mcp.utils import create_mcp_error_response
+from core.model_runtime.utils.encoders import jsonable_encoder
+from extensions.ext_database import db
+from models.model import App, AppMCPServer, AppMode, EndUser
+from services.app_generate_service import AppGenerateService
+
+"""
+Apply to MCP HTTP streamable server with stateless http
+"""
+logger = logging.getLogger(__name__)
+
+
+class MCPServerStreamableHTTPRequestHandler:
+    def __init__(
+        self, app: App, request: types.ClientRequest | types.ClientNotification, user_input_form: list[VariableEntity]
+    ):
+        self.app = app
+        self.request = request
+        mcp_server = db.session.query(AppMCPServer).filter(AppMCPServer.app_id == self.app.id).first()
+        if not mcp_server:
+            raise ValueError("MCP server not found")
+        self.mcp_server: AppMCPServer = mcp_server
+        self.end_user = self.retrieve_end_user()
+        self.user_input_form = user_input_form
+
+    @property
+    def request_type(self):
+        return type(self.request.root)
+
+    @property
+    def parameter_schema(self):
+        parameters, required = self._convert_input_form_to_parameters(self.user_input_form)
+        if self.app.mode in {AppMode.COMPLETION.value, AppMode.WORKFLOW.value}:
+            return {
+                "type": "object",
+                "properties": parameters,
+                "required": required,
+            }
+        return {
+            "type": "object",
+            "properties": {
+                "query": {"type": "string", "description": "User Input/Question content"},
+                **parameters,
+            },
+            "required": ["query", *required],
+        }
+
+    @property
+    def capabilities(self):
+        return types.ServerCapabilities(
+            tools=types.ToolsCapability(listChanged=False),
+        )
+
+    def response(self, response: types.Result | str):
+        if isinstance(response, str):
+            sse_content = f"event: ping\ndata: {response}\n\n".encode()
+            yield sse_content
+            return
+        json_response = types.JSONRPCResponse(
+            jsonrpc="2.0",
+            id=(self.request.root.model_extra or {}).get("id", 1),
+            result=response.model_dump(by_alias=True, mode="json", exclude_none=True),
+        )
+        json_data = json.dumps(jsonable_encoder(json_response))
+
+        sse_content = f"event: message\ndata: {json_data}\n\n".encode()
+
+        yield sse_content
+
+    def error_response(self, code: int, message: str, data=None):
+        request_id = (self.request.root.model_extra or {}).get("id", 1) or 1
+        return create_mcp_error_response(request_id, code, message, data)
+
+    def handle(self):
+        handle_map = {
+            types.InitializeRequest: self.initialize,
+            types.ListToolsRequest: self.list_tools,
+            types.CallToolRequest: self.invoke_tool,
+            types.InitializedNotification: self.handle_notification,
+            types.PingRequest: self.handle_ping,
+        }
+        try:
+            if self.request_type in handle_map:
+                return self.response(handle_map[self.request_type]())
+            else:
+                return self.error_response(METHOD_NOT_FOUND, f"Method not found: {self.request_type}")
+        except ValueError as e:
+            logger.exception("Invalid params")
+            return self.error_response(INVALID_PARAMS, str(e))
+        except Exception as e:
+            logger.exception("Internal server error")
+            return self.error_response(INTERNAL_ERROR, f"Internal server error: {str(e)}")
+
+    def handle_notification(self):
+        return "ping"
+
+    def handle_ping(self):
+        return types.EmptyResult()
+
+    def initialize(self):
+        request = cast(types.InitializeRequest, self.request.root)
+        client_info = request.params.clientInfo
+        client_name = f"{client_info.name}@{client_info.version}"
+        if not self.end_user:
+            end_user = EndUser(
+                tenant_id=self.app.tenant_id,
+                app_id=self.app.id,
+                type="mcp",
+                name=client_name,
+                session_id=generate_session_id(),
+                external_user_id=self.mcp_server.id,
+            )
+            db.session.add(end_user)
+            db.session.commit()
+        return types.InitializeResult(
+            protocolVersion=types.SERVER_LATEST_PROTOCOL_VERSION,
+            capabilities=self.capabilities,
+            serverInfo=types.Implementation(name="Dify", version=dify_config.project.version),
+            instructions=self.mcp_server.description,
+        )
+
+    def list_tools(self):
+        if not self.end_user:
+            raise ValueError("User not found")
+        return types.ListToolsResult(
+            tools=[
+                types.Tool(
+                    name=self.app.name,
+                    description=self.mcp_server.description,
+                    inputSchema=self.parameter_schema,
+                )
+            ],
+        )
+
+    def invoke_tool(self):
+        if not self.end_user:
+            raise ValueError("User not found")
+        request = cast(types.CallToolRequest, self.request.root)
+        args = request.params.arguments
+        if not args:
+            raise ValueError("No arguments provided")
+        if self.app.mode in {AppMode.WORKFLOW.value}:
+            args = {"inputs": args}
+        elif self.app.mode in {AppMode.COMPLETION.value}:
+            args = {"query": "", "inputs": args}
+        else:
+            args = {"query": args["query"], "inputs": {k: v for k, v in args.items() if k != "query"}}
+        response = AppGenerateService.generate(
+            self.app,
+            self.end_user,
+            args,
+            InvokeFrom.SERVICE_API,
+            streaming=self.app.mode == AppMode.AGENT_CHAT.value,
+        )
+        answer = ""
+        if isinstance(response, RateLimitGenerator):
+            for item in response.generator:
+                data = item
+                if isinstance(data, str) and data.startswith("data: "):
+                    try:
+                        json_str = data[6:].strip()
+                        parsed_data = json.loads(json_str)
+                        if parsed_data.get("event") == "agent_thought":
+                            answer += parsed_data.get("thought", "")
+                    except json.JSONDecodeError:
+                        continue
+        if isinstance(response, Mapping):
+            if self.app.mode in {
+                AppMode.ADVANCED_CHAT.value,
+                AppMode.COMPLETION.value,
+                AppMode.CHAT.value,
+                AppMode.AGENT_CHAT.value,
+            }:
+                answer = response["answer"]
+            elif self.app.mode in {AppMode.WORKFLOW.value}:
+                answer = json.dumps(response["data"]["outputs"], ensure_ascii=False)
+            else:
+                raise ValueError("Invalid app mode")
+            # Not support image yet
+        return types.CallToolResult(content=[types.TextContent(text=answer, type="text")])
+
+    def retrieve_end_user(self):
+        return (
+            db.session.query(EndUser)
+            .filter(EndUser.external_user_id == self.mcp_server.id, EndUser.type == "mcp")
+            .first()
+        )
+
+    def _convert_input_form_to_parameters(self, user_input_form: list[VariableEntity]):
+        parameters: dict[str, dict[str, Any]] = {}
+        required = []
+        for item in user_input_form:
+            parameters[item.variable] = {}
+            if item.type in (
+                VariableEntityType.FILE,
+                VariableEntityType.FILE_LIST,
+                VariableEntityType.EXTERNAL_DATA_TOOL,
+            ):
+                continue
+            if item.required:
+                required.append(item.variable)
+            # if the workflow republished, the parameters not changed
+            # we should not raise error here
+            try:
+                description = self.mcp_server.parameters_dict[item.variable]
+            except KeyError:
+                description = ""
+            parameters[item.variable]["description"] = description
+            if item.type in (VariableEntityType.TEXT_INPUT, VariableEntityType.PARAGRAPH):
+                parameters[item.variable]["type"] = "string"
+            elif item.type == VariableEntityType.SELECT:
+                parameters[item.variable]["type"] = "string"
+                parameters[item.variable]["enum"] = item.options
+            elif item.type == VariableEntityType.NUMBER:
+                parameters[item.variable]["type"] = "float"
+        return parameters, required

api/core/mcp/session/base_session.py

@@ -0,0 +1,415 @@
+import logging
+import queue
+from collections.abc import Callable
+from concurrent.futures import Future, ThreadPoolExecutor, TimeoutError
+from contextlib import ExitStack
+from datetime import timedelta
+from types import TracebackType
+from typing import Any, Generic, Self, TypeVar
+
+from httpx import HTTPStatusError
+from pydantic import BaseModel
+
+from core.mcp.error import MCPAuthError, MCPConnectionError
+from core.mcp.types import (
+    CancelledNotification,
+    ClientNotification,
+    ClientRequest,
+    ClientResult,
+    ErrorData,
+    JSONRPCError,
+    JSONRPCMessage,
+    JSONRPCNotification,
+    JSONRPCRequest,
+    JSONRPCResponse,
+    MessageMetadata,
+    RequestId,
+    RequestParams,
+    ServerMessageMetadata,
+    ServerNotification,
+    ServerRequest,
+    ServerResult,
+    SessionMessage,
+)
+
+SendRequestT = TypeVar("SendRequestT", ClientRequest, ServerRequest)
+SendResultT = TypeVar("SendResultT", ClientResult, ServerResult)
+SendNotificationT = TypeVar("SendNotificationT", ClientNotification, ServerNotification)
+ReceiveRequestT = TypeVar("ReceiveRequestT", ClientRequest, ServerRequest)
+ReceiveResultT = TypeVar("ReceiveResultT", bound=BaseModel)
+ReceiveNotificationT = TypeVar("ReceiveNotificationT", ClientNotification, ServerNotification)
+DEFAULT_RESPONSE_READ_TIMEOUT = 1.0
+
+
+class RequestResponder(Generic[ReceiveRequestT, SendResultT]):
+    """Handles responding to MCP requests and manages request lifecycle.
+
+    This class MUST be used as a context manager to ensure proper cleanup and
+    cancellation handling:
+
+    Example:
+        with request_responder as resp:
+            resp.respond(result)
+
+    The context manager ensures:
+    1. Proper cancellation scope setup and cleanup
+    2. Request completion tracking
+    3. Cleanup of in-flight requests
+    """
+
+    request: ReceiveRequestT
+    _session: Any
+    _on_complete: Callable[["RequestResponder[ReceiveRequestT, SendResultT]"], Any]
+
+    def __init__(
+        self,
+        request_id: RequestId,
+        request_meta: RequestParams.Meta | None,
+        request: ReceiveRequestT,
+        session: """BaseSession[
+            SendRequestT,
+            SendNotificationT,
+            SendResultT,
+            ReceiveRequestT,
+            ReceiveNotificationT
+        ]""",
+        on_complete: Callable[["RequestResponder[ReceiveRequestT, SendResultT]"], Any],
+    ) -> None:
+        self.request_id = request_id
+        self.request_meta = request_meta
+        self.request = request
+        self._session = session
+        self._completed = False
+        self._on_complete = on_complete
+        self._entered = False  # Track if we're in a context manager
+
+    def __enter__(self) -> "RequestResponder[ReceiveRequestT, SendResultT]":
+        """Enter the context manager, enabling request cancellation tracking."""
+        self._entered = True
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_val: BaseException | None,
+        exc_tb: TracebackType | None,
+    ) -> None:
+        """Exit the context manager, performing cleanup and notifying completion."""
+        try:
+            if self._completed:
+                self._on_complete(self)
+        finally:
+            self._entered = False
+
+    def respond(self, response: SendResultT | ErrorData) -> None:
+        """Send a response for this request.
+
+        Must be called within a context manager block.
+        Raises:
+            RuntimeError: If not used within a context manager
+            AssertionError: If request was already responded to
+        """
+        if not self._entered:
+            raise RuntimeError("RequestResponder must be used as a context manager")
+        assert not self._completed, "Request already responded to"
+
+        self._completed = True
+
+        self._session._send_response(request_id=self.request_id, response=response)
+
+    def cancel(self) -> None:
+        """Cancel this request and mark it as completed."""
+        if not self._entered:
+            raise RuntimeError("RequestResponder must be used as a context manager")
+
+        self._completed = True  # Mark as completed so it's removed from in_flight
+        # Send an error response to indicate cancellation
+        self._session._send_response(
+            request_id=self.request_id,
+            response=ErrorData(code=0, message="Request cancelled", data=None),
+        )
+
+
+class BaseSession(
+    Generic[
+        SendRequestT,
+        SendNotificationT,
+        SendResultT,
+        ReceiveRequestT,
+        ReceiveNotificationT,
+    ],
+):
+    """
+    Implements an MCP "session" on top of read/write streams, including features
+    like request/response linking, notifications, and progress.
+
+    This class is a context manager that automatically starts processing
+    messages when entered.
+    """
+
+    _response_streams: dict[RequestId, queue.Queue[JSONRPCResponse | JSONRPCError]]
+    _request_id: int
+    _in_flight: dict[RequestId, RequestResponder[ReceiveRequestT, SendResultT]]
+    _receive_request_type: type[ReceiveRequestT]
+    _receive_notification_type: type[ReceiveNotificationT]
+
+    def __init__(
+        self,
+        read_stream: queue.Queue,
+        write_stream: queue.Queue,
+        receive_request_type: type[ReceiveRequestT],
+        receive_notification_type: type[ReceiveNotificationT],
+        # If none, reading will never time out
+        read_timeout_seconds: timedelta | None = None,
+    ) -> None:
+        self._read_stream = read_stream
+        self._write_stream = write_stream
+        self._response_streams = {}
+        self._request_id = 0
+        self._receive_request_type = receive_request_type
+        self._receive_notification_type = receive_notification_type
+        self._session_read_timeout_seconds = read_timeout_seconds
+        self._in_flight = {}
+        self._exit_stack = ExitStack()
+        # Initialize executor and future to None for proper cleanup checks
+        self._executor: ThreadPoolExecutor | None = None
+        self._receiver_future: Future | None = None
+
+    def __enter__(self) -> Self:
+        # The thread pool is dedicated to running `_receive_loop`. Setting `max_workers` to 1
+        # ensures no unnecessary threads are created.
+        self._executor = ThreadPoolExecutor(max_workers=1)
+        self._receiver_future = self._executor.submit(self._receive_loop)
+        return self
+
+    def check_receiver_status(self) -> None:
+        """`check_receiver_status` ensures that any exceptions raised during the
+        execution of `_receive_loop` are retrieved and propagated."""
+        if self._receiver_future and self._receiver_future.done():
+            self._receiver_future.result()
+
+    def __exit__(
+        self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: TracebackType | None
+    ) -> None:
+        self._read_stream.put(None)
+        self._write_stream.put(None)
+
+        # Wait for the receiver loop to finish
+        if self._receiver_future:
+            try:
+                self._receiver_future.result(timeout=5.0)  # Wait up to 5 seconds
+            except TimeoutError:
+                # If the receiver loop is still running after timeout, we'll force shutdown
+                pass
+
+        # Shutdown the executor
+        if self._executor:
+            self._executor.shutdown(wait=True)
+
+    def send_request(
+        self,
+        request: SendRequestT,
+        result_type: type[ReceiveResultT],
+        request_read_timeout_seconds: timedelta | None = None,
+        metadata: MessageMetadata = None,
+    ) -> ReceiveResultT:
+        """
+        Sends a request and wait for a response. Raises an McpError if the
+        response contains an error. If a request read timeout is provided, it
+        will take precedence over the session read timeout.
+
+        Do not use this method to emit notifications! Use send_notification()
+        instead.
+        """
+        self.check_receiver_status()
+
+        request_id = self._request_id
+        self._request_id = request_id + 1
+
+        response_queue: queue.Queue[JSONRPCResponse | JSONRPCError] = queue.Queue()
+        self._response_streams[request_id] = response_queue
+
+        try:
+            jsonrpc_request = JSONRPCRequest(
+                jsonrpc="2.0",
+                id=request_id,
+                **request.model_dump(by_alias=True, mode="json", exclude_none=True),
+            )
+
+            self._write_stream.put(SessionMessage(message=JSONRPCMessage(jsonrpc_request), metadata=metadata))
+            timeout = DEFAULT_RESPONSE_READ_TIMEOUT
+            if request_read_timeout_seconds is not None:
+                timeout = float(request_read_timeout_seconds.total_seconds())
+            elif self._session_read_timeout_seconds is not None:
+                timeout = float(self._session_read_timeout_seconds.total_seconds())
+            while True:
+                try:
+                    response_or_error = response_queue.get(timeout=timeout)
+                    break
+                except queue.Empty:
+                    self.check_receiver_status()
+                    continue
+
+            if response_or_error is None:
+                raise MCPConnectionError(
+                    ErrorData(
+                        code=500,
+                        message="No response received",
+                    )
+                )
+            elif isinstance(response_or_error, JSONRPCError):
+                if response_or_error.error.code == 401:
+                    raise MCPAuthError(
+                        ErrorData(code=response_or_error.error.code, message=response_or_error.error.message)
+                    )
+                else:
+                    raise MCPConnectionError(
+                        ErrorData(code=response_or_error.error.code, message=response_or_error.error.message)
+                    )
+            else:
+                return result_type.model_validate(response_or_error.result)
+
+        finally:
+            self._response_streams.pop(request_id, None)
+
+    def send_notification(
+        self,
+        notification: SendNotificationT,
+        related_request_id: RequestId | None = None,
+    ) -> None:
+        """
+        Emits a notification, which is a one-way message that does not expect
+        a response.
+        """
+        self.check_receiver_status()
+
+        # Some transport implementations may need to set the related_request_id
+        # to attribute to the notifications to the request that triggered them.
+        jsonrpc_notification = JSONRPCNotification(
+            jsonrpc="2.0",
+            **notification.model_dump(by_alias=True, mode="json", exclude_none=True),
+        )
+        session_message = SessionMessage(
+            message=JSONRPCMessage(jsonrpc_notification),
+            metadata=ServerMessageMetadata(related_request_id=related_request_id) if related_request_id else None,
+        )
+        self._write_stream.put(session_message)
+
+    def _send_response(self, request_id: RequestId, response: SendResultT | ErrorData) -> None:
+        if isinstance(response, ErrorData):
+            jsonrpc_error = JSONRPCError(jsonrpc="2.0", id=request_id, error=response)
+            session_message = SessionMessage(message=JSONRPCMessage(jsonrpc_error))
+            self._write_stream.put(session_message)
+        else:
+            jsonrpc_response = JSONRPCResponse(
+                jsonrpc="2.0",
+                id=request_id,
+                result=response.model_dump(by_alias=True, mode="json", exclude_none=True),
+            )
+            session_message = SessionMessage(message=JSONRPCMessage(jsonrpc_response))
+            self._write_stream.put(session_message)
+
+    def _receive_loop(self) -> None:
+        """
+        Main message processing loop.
+        In a real synchronous implementation, this would likely run in a separate thread.
+        """
+        while True:
+            try:
+                # Attempt to receive a message (this would be blocking in a synchronous context)
+                message = self._read_stream.get(timeout=DEFAULT_RESPONSE_READ_TIMEOUT)
+                if message is None:
+                    break
+                if isinstance(message, HTTPStatusError):
+                    response_queue = self._response_streams.get(self._request_id - 1)
+                    if response_queue is not None:
+                        response_queue.put(
+                            JSONRPCError(
+                                jsonrpc="2.0",
+                                id=self._request_id - 1,
+                                error=ErrorData(code=message.response.status_code, message=message.args[0]),
+                            )
+                        )
+                    else:
+                        self._handle_incoming(RuntimeError(f"Received response with an unknown request ID: {message}"))
+                elif isinstance(message, Exception):
+                    self._handle_incoming(message)
+                elif isinstance(message.message.root, JSONRPCRequest):
+                    validated_request = self._receive_request_type.model_validate(
+                        message.message.root.model_dump(by_alias=True, mode="json", exclude_none=True)
+                    )
+
+                    responder = RequestResponder(
+                        request_id=message.message.root.id,
+                        request_meta=validated_request.root.params.meta if validated_request.root.params else None,
+                        request=validated_request,
+                        session=self,
+                        on_complete=lambda r: self._in_flight.pop(r.request_id, None),
+                    )
+
+                    self._in_flight[responder.request_id] = responder
+                    self._received_request(responder)
+
+                    if not responder._completed:
+                        self._handle_incoming(responder)
+
+                elif isinstance(message.message.root, JSONRPCNotification):
+                    try:
+                        notification = self._receive_notification_type.model_validate(
+                            message.message.root.model_dump(by_alias=True, mode="json", exclude_none=True)
+                        )
+                        # Handle cancellation notifications
+                        if isinstance(notification.root, CancelledNotification):
+                            cancelled_id = notification.root.params.requestId
+                            if cancelled_id in self._in_flight:
+                                self._in_flight[cancelled_id].cancel()
+                        else:
+                            self._received_notification(notification)
+                            self._handle_incoming(notification)
+                    except Exception as e:
+                        # For other validation errors, log and continue
+                        logging.warning(f"Failed to validate notification: {e}. Message was: {message.message.root}")
+                else:  # Response or error
+                    response_queue = self._response_streams.get(message.message.root.id)
+                    if response_queue is not None:
+                        response_queue.put(message.message.root)
+                    else:
+                        self._handle_incoming(RuntimeError(f"Server Error: {message}"))
+            except queue.Empty:
+                continue
+            except Exception as e:
+                logging.exception("Error in message processing loop")
+                raise
+
+    def _received_request(self, responder: RequestResponder[ReceiveRequestT, SendResultT]) -> None:
+        """
+        Can be overridden by subclasses to handle a request without needing to
+        listen on the message stream.
+
+        If the request is responded to within this method, it will not be
+        forwarded on to the message stream.
+        """
+        pass
+
+    def _received_notification(self, notification: ReceiveNotificationT) -> None:
+        """
+        Can be overridden by subclasses to handle a notification without needing
+        to listen on the message stream.
+        """
+        pass
+
+    def send_progress_notification(
+        self, progress_token: str | int, progress: float, total: float | None = None
+    ) -> None:
+        """
+        Sends a progress notification for a request that is currently being
+        processed.
+        """
+        pass
+
+    def _handle_incoming(
+        self,
+        req: RequestResponder[ReceiveRequestT, SendResultT] | ReceiveNotificationT | Exception,
+    ) -> None:
+        """A generic handler for incoming messages. Overwritten by subclasses."""
+        pass

api/core/mcp/session/client_session.py

@@ -0,0 +1,365 @@
+from datetime import timedelta
+from typing import Any, Protocol
+
+from pydantic import AnyUrl, TypeAdapter
+
+from configs import dify_config
+from core.mcp import types
+from core.mcp.entities import SUPPORTED_PROTOCOL_VERSIONS, RequestContext
+from core.mcp.session.base_session import BaseSession, RequestResponder
+
+DEFAULT_CLIENT_INFO = types.Implementation(name="Dify", version=dify_config.project.version)
+
+
+class SamplingFnT(Protocol):
+    def __call__(
+        self,
+        context: RequestContext["ClientSession", Any],
+        params: types.CreateMessageRequestParams,
+    ) -> types.CreateMessageResult | types.ErrorData: ...
+
+
+class ListRootsFnT(Protocol):
+    def __call__(self, context: RequestContext["ClientSession", Any]) -> types.ListRootsResult | types.ErrorData: ...
+
+
+class LoggingFnT(Protocol):
+    def __call__(
+        self,
+        params: types.LoggingMessageNotificationParams,
+    ) -> None: ...
+
+
+class MessageHandlerFnT(Protocol):
+    def __call__(
+        self,
+        message: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
+    ) -> None: ...
+
+
+def _default_message_handler(
+    message: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
+) -> None:
+    if isinstance(message, Exception):
+        raise ValueError(str(message))
+    elif isinstance(message, (types.ServerNotification | RequestResponder)):
+        pass
+
+
+def _default_sampling_callback(
+    context: RequestContext["ClientSession", Any],
+    params: types.CreateMessageRequestParams,
+) -> types.CreateMessageResult | types.ErrorData:
+    return types.ErrorData(
+        code=types.INVALID_REQUEST,
+        message="Sampling not supported",
+    )
+
+
+def _default_list_roots_callback(
+    context: RequestContext["ClientSession", Any],
+) -> types.ListRootsResult | types.ErrorData:
+    return types.ErrorData(
+        code=types.INVALID_REQUEST,
+        message="List roots not supported",
+    )
+
+
+def _default_logging_callback(
+    params: types.LoggingMessageNotificationParams,
+) -> None:
+    pass
+
+
+ClientResponse: TypeAdapter[types.ClientResult | types.ErrorData] = TypeAdapter(types.ClientResult | types.ErrorData)
+
+
+class ClientSession(
+    BaseSession[
+        types.ClientRequest,
+        types.ClientNotification,
+        types.ClientResult,
+        types.ServerRequest,
+        types.ServerNotification,
+    ]
+):
+    def __init__(
+        self,
+        read_stream,
+        write_stream,
+        read_timeout_seconds: timedelta | None = None,
+        sampling_callback: SamplingFnT | None = None,
+        list_roots_callback: ListRootsFnT | None = None,
+        logging_callback: LoggingFnT | None = None,
+        message_handler: MessageHandlerFnT | None = None,
+        client_info: types.Implementation | None = None,
+    ) -> None:
+        super().__init__(
+            read_stream,
+            write_stream,
+            types.ServerRequest,
+            types.ServerNotification,
+            read_timeout_seconds=read_timeout_seconds,
+        )
+        self._client_info = client_info or DEFAULT_CLIENT_INFO
+        self._sampling_callback = sampling_callback or _default_sampling_callback
+        self._list_roots_callback = list_roots_callback or _default_list_roots_callback
+        self._logging_callback = logging_callback or _default_logging_callback
+        self._message_handler = message_handler or _default_message_handler
+
+    def initialize(self) -> types.InitializeResult:
+        sampling = types.SamplingCapability()
+        roots = types.RootsCapability(
+            # TODO: Should this be based on whether we
+            # _will_ send notifications, or only whether
+            # they're supported?
+            listChanged=True,
+        )
+
+        result = self.send_request(
+            types.ClientRequest(
+                types.InitializeRequest(
+                    method="initialize",
+                    params=types.InitializeRequestParams(
+                        protocolVersion=types.LATEST_PROTOCOL_VERSION,
+                        capabilities=types.ClientCapabilities(
+                            sampling=sampling,
+                            experimental=None,
+                            roots=roots,
+                        ),
+                        clientInfo=self._client_info,
+                    ),
+                )
+            ),
+            types.InitializeResult,
+        )
+
+        if result.protocolVersion not in SUPPORTED_PROTOCOL_VERSIONS:
+            raise RuntimeError(f"Unsupported protocol version from the server: {result.protocolVersion}")
+
+        self.send_notification(
+            types.ClientNotification(types.InitializedNotification(method="notifications/initialized"))
+        )
+
+        return result
+
+    def send_ping(self) -> types.EmptyResult:
+        """Send a ping request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.PingRequest(
+                    method="ping",
+                )
+            ),
+            types.EmptyResult,
+        )
+
+    def send_progress_notification(
+        self, progress_token: str | int, progress: float, total: float | None = None
+    ) -> None:
+        """Send a progress notification."""
+        self.send_notification(
+            types.ClientNotification(
+                types.ProgressNotification(
+                    method="notifications/progress",
+                    params=types.ProgressNotificationParams(
+                        progressToken=progress_token,
+                        progress=progress,
+                        total=total,
+                    ),
+                ),
+            )
+        )
+
+    def set_logging_level(self, level: types.LoggingLevel) -> types.EmptyResult:
+        """Send a logging/setLevel request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.SetLevelRequest(
+                    method="logging/setLevel",
+                    params=types.SetLevelRequestParams(level=level),
+                )
+            ),
+            types.EmptyResult,
+        )
+
+    def list_resources(self) -> types.ListResourcesResult:
+        """Send a resources/list request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.ListResourcesRequest(
+                    method="resources/list",
+                )
+            ),
+            types.ListResourcesResult,
+        )
+
+    def list_resource_templates(self) -> types.ListResourceTemplatesResult:
+        """Send a resources/templates/list request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.ListResourceTemplatesRequest(
+                    method="resources/templates/list",
+                )
+            ),
+            types.ListResourceTemplatesResult,
+        )
+
+    def read_resource(self, uri: AnyUrl) -> types.ReadResourceResult:
+        """Send a resources/read request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.ReadResourceRequest(
+                    method="resources/read",
+                    params=types.ReadResourceRequestParams(uri=uri),
+                )
+            ),
+            types.ReadResourceResult,
+        )
+
+    def subscribe_resource(self, uri: AnyUrl) -> types.EmptyResult:
+        """Send a resources/subscribe request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.SubscribeRequest(
+                    method="resources/subscribe",
+                    params=types.SubscribeRequestParams(uri=uri),
+                )
+            ),
+            types.EmptyResult,
+        )
+
+    def unsubscribe_resource(self, uri: AnyUrl) -> types.EmptyResult:
+        """Send a resources/unsubscribe request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.UnsubscribeRequest(
+                    method="resources/unsubscribe",
+                    params=types.UnsubscribeRequestParams(uri=uri),
+                )
+            ),
+            types.EmptyResult,
+        )
+
+    def call_tool(
+        self,
+        name: str,
+        arguments: dict[str, Any] | None = None,
+        read_timeout_seconds: timedelta | None = None,
+    ) -> types.CallToolResult:
+        """Send a tools/call request."""
+
+        return self.send_request(
+            types.ClientRequest(
+                types.CallToolRequest(
+                    method="tools/call",
+                    params=types.CallToolRequestParams(name=name, arguments=arguments),
+                )
+            ),
+            types.CallToolResult,
+            request_read_timeout_seconds=read_timeout_seconds,
+        )
+
+    def list_prompts(self) -> types.ListPromptsResult:
+        """Send a prompts/list request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.ListPromptsRequest(
+                    method="prompts/list",
+                )
+            ),
+            types.ListPromptsResult,
+        )
+
+    def get_prompt(self, name: str, arguments: dict[str, str] | None = None) -> types.GetPromptResult:
+        """Send a prompts/get request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.GetPromptRequest(
+                    method="prompts/get",
+                    params=types.GetPromptRequestParams(name=name, arguments=arguments),
+                )
+            ),
+            types.GetPromptResult,
+        )
+
+    def complete(
+        self,
+        ref: types.ResourceReference | types.PromptReference,
+        argument: dict[str, str],
+    ) -> types.CompleteResult:
+        """Send a completion/complete request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.CompleteRequest(
+                    method="completion/complete",
+                    params=types.CompleteRequestParams(
+                        ref=ref,
+                        argument=types.CompletionArgument(**argument),
+                    ),
+                )
+            ),
+            types.CompleteResult,
+        )
+
+    def list_tools(self) -> types.ListToolsResult:
+        """Send a tools/list request."""
+        return self.send_request(
+            types.ClientRequest(
+                types.ListToolsRequest(
+                    method="tools/list",
+                )
+            ),
+            types.ListToolsResult,
+        )
+
+    def send_roots_list_changed(self) -> None:
+        """Send a roots/list_changed notification."""
+        self.send_notification(
+            types.ClientNotification(
+                types.RootsListChangedNotification(
+                    method="notifications/roots/list_changed",
+                )
+            )
+        )
+
+    def _received_request(self, responder: RequestResponder[types.ServerRequest, types.ClientResult]) -> None:
+        ctx = RequestContext[ClientSession, Any](
+            request_id=responder.request_id,
+            meta=responder.request_meta,
+            session=self,
+            lifespan_context=None,
+        )
+
+        match responder.request.root:
+            case types.CreateMessageRequest(params=params):
+                with responder:
+                    response = self._sampling_callback(ctx, params)
+                    client_response = ClientResponse.validate_python(response)
+                    responder.respond(client_response)
+
+            case types.ListRootsRequest():
+                with responder:
+                    list_roots_response = self._list_roots_callback(ctx)
+                    client_response = ClientResponse.validate_python(list_roots_response)
+                    responder.respond(client_response)
+
+            case types.PingRequest():
+                with responder:
+                    return responder.respond(types.ClientResult(root=types.EmptyResult()))
+
+    def _handle_incoming(
+        self,
+        req: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
+    ) -> None:
+        """Handle incoming messages by forwarding to the message handler."""
+        self._message_handler(req)
+
+    def _received_notification(self, notification: types.ServerNotification) -> None:
+        """Handle notifications from the server."""
+        # Process specific notification types
+        match notification.root:
+            case types.LoggingMessageNotification(params=params):
+                self._logging_callback(params)
+            case _:
+                pass

api/core/mcp/utils.py

@@ -0,0 +1,114 @@
+import json
+
+import httpx
+
+from configs import dify_config
+from core.mcp.types import ErrorData, JSONRPCError
+from core.model_runtime.utils.encoders import jsonable_encoder
+
+HTTP_REQUEST_NODE_SSL_VERIFY = dify_config.HTTP_REQUEST_NODE_SSL_VERIFY
+
+STATUS_FORCELIST = [429, 500, 502, 503, 504]
+
+
+def create_ssrf_proxy_mcp_http_client(
+    headers: dict[str, str] | None = None,
+    timeout: httpx.Timeout | None = None,
+) -> httpx.Client:
+    """Create an HTTPX client with SSRF proxy configuration for MCP connections.
+
+    Args:
+        headers: Optional headers to include in the client
+        timeout: Optional timeout configuration
+
+    Returns:
+        Configured httpx.Client with proxy settings
+    """
+    if dify_config.SSRF_PROXY_ALL_URL:
+        return httpx.Client(
+            verify=HTTP_REQUEST_NODE_SSL_VERIFY,
+            headers=headers or {},
+            timeout=timeout,
+            follow_redirects=True,
+            proxy=dify_config.SSRF_PROXY_ALL_URL,
+        )
+    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, verify=HTTP_REQUEST_NODE_SSL_VERIFY),
+            "https://": httpx.HTTPTransport(
+                proxy=dify_config.SSRF_PROXY_HTTPS_URL, verify=HTTP_REQUEST_NODE_SSL_VERIFY
+            ),
+        }
+        return httpx.Client(
+            verify=HTTP_REQUEST_NODE_SSL_VERIFY,
+            headers=headers or {},
+            timeout=timeout,
+            follow_redirects=True,
+            mounts=proxy_mounts,
+        )
+    else:
+        return httpx.Client(
+            verify=HTTP_REQUEST_NODE_SSL_VERIFY,
+            headers=headers or {},
+            timeout=timeout,
+            follow_redirects=True,
+        )
+
+
+def ssrf_proxy_sse_connect(url, **kwargs):
+    """Connect to SSE endpoint with SSRF proxy protection.
+
+    This function creates an SSE connection using the configured proxy settings
+    to prevent SSRF attacks when connecting to external endpoints.
+
+    Args:
+        url: The SSE endpoint URL
+        **kwargs: Additional arguments passed to the SSE connection
+
+    Returns:
+        EventSource object for SSE streaming
+    """
+    from httpx_sse import connect_sse
+
+    # Extract client if provided, otherwise create one
+    client = kwargs.pop("client", None)
+    if client is None:
+        # Create client with SSRF proxy configuration
+        timeout = kwargs.pop(
+            "timeout",
+            httpx.Timeout(
+                timeout=dify_config.SSRF_DEFAULT_TIME_OUT,
+                connect=dify_config.SSRF_DEFAULT_CONNECT_TIME_OUT,
+                read=dify_config.SSRF_DEFAULT_READ_TIME_OUT,
+                write=dify_config.SSRF_DEFAULT_WRITE_TIME_OUT,
+            ),
+        )
+        headers = kwargs.pop("headers", {})
+        client = create_ssrf_proxy_mcp_http_client(headers=headers, timeout=timeout)
+        client_provided = False
+    else:
+        client_provided = True
+
+    # Extract method if provided, default to GET
+    method = kwargs.pop("method", "GET")
+
+    try:
+        return connect_sse(client, method, url, **kwargs)
+    except Exception:
+        # If we created the client, we need to clean it up on error
+        if not client_provided:
+            client.close()
+        raise
+
+
+def create_mcp_error_response(request_id: int | str | None, code: int, message: str, data=None):
+    """Create MCP error response"""
+    error_data = ErrorData(code=code, message=message, data=data)
+    json_response = JSONRPCError(
+        jsonrpc="2.0",
+        id=request_id or 1,
+        error=error_data,
+    )
+    json_data = json.dumps(jsonable_encoder(json_response))
+    sse_content = f"event: message\ndata: {json_data}\n\n".encode()
+    yield sse_content

api/core/memory/token_buffer_memory.py

@@ -1,6 +1,8 @@
 from collections.abc import Sequence
 from typing import Optional
 
+from sqlalchemy import select
+
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.file import file_manager
 from core.model_manager import ModelInstance
@@ -17,11 +19,15 @@ from core.prompt.utils.extract_thread_messages import extract_thread_messages
 from extensions.ext_database import db
 from factories import file_factory
 from models.model import AppMode, Conversation, Message, MessageFile
-from models.workflow import WorkflowRun
+from models.workflow import Workflow, WorkflowRun
 
 
 class TokenBufferMemory:
-    def __init__(self, conversation: Conversation, model_instance: ModelInstance) -> None:
+    def __init__(
+        self,
+        conversation: Conversation,
+        model_instance: ModelInstance,
+    ) -> None:
         self.conversation = conversation
         self.model_instance = model_instance
 
@@ -36,20 +42,8 @@ class TokenBufferMemory:
         app_record = self.conversation.app
 
         # fetch limited messages, and return reversed
-        query = (
-            db.session.query(
-                Message.id,
-                Message.query,
-                Message.answer,
-                Message.created_at,
-                Message.workflow_run_id,
-                Message.parent_message_id,
-                Message.answer_tokens,
-            )
-            .filter(
-                Message.conversation_id == self.conversation.id,
-            )
-            .order_by(Message.created_at.desc())
+        stmt = (
+            select(Message).where(Message.conversation_id == self.conversation.id).order_by(Message.created_at.desc())
         )
 
         if message_limit and message_limit > 0:
@@ -57,7 +51,9 @@ class TokenBufferMemory:
         else:
             message_limit = 500
 
-        messages = query.limit(message_limit).all()
+        stmt = stmt.limit(message_limit)
+
+        messages = db.session.scalars(stmt).all()
 
         # instead of all messages from the conversation, we only need to extract messages
         # that belong to the thread of last message
@@ -74,18 +70,20 @@ class TokenBufferMemory:
             files = db.session.query(MessageFile).filter(MessageFile.message_id == message.id).all()
             if files:
                 file_extra_config = None
-                if self.conversation.mode not in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
+                if self.conversation.mode in {AppMode.AGENT_CHAT, AppMode.COMPLETION, AppMode.CHAT}:
                     file_extra_config = FileUploadConfigManager.convert(self.conversation.model_config)
+                elif self.conversation.mode in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
+                    workflow_run = db.session.scalar(
+                        select(WorkflowRun).where(WorkflowRun.id == message.workflow_run_id)
+                    )
+                    if not workflow_run:
+                        raise ValueError(f"Workflow run not found: {message.workflow_run_id}")
+                    workflow = db.session.scalar(select(Workflow).where(Workflow.id == workflow_run.workflow_id))
+                    if not workflow:
+                        raise ValueError(f"Workflow not found: {workflow_run.workflow_id}")
+                    file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False)
                 else:
-                    if message.workflow_run_id:
-                        workflow_run = (
-                            db.session.query(WorkflowRun).filter(WorkflowRun.id == message.workflow_run_id).first()
-                        )
-
-                        if workflow_run and workflow_run.workflow:
-                            file_extra_config = FileUploadConfigManager.convert(
-                                workflow_run.workflow.features_dict, is_vision=False
-                            )
+                    raise AssertionError(f"Invalid app mode: {self.conversation.mode}")
 
                 detail = ImagePromptMessageContent.DETAIL.LOW
                 if file_extra_config and app_record:

api/core/model_runtime/entities/llm_entities.py

@@ -1,7 +1,7 @@
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from decimal import Decimal
 from enum import StrEnum
-from typing import Optional
+from typing import Any, Optional
 
 from pydantic import BaseModel, Field
 
@@ -53,6 +53,37 @@ class LLMUsage(ModelUsage):
             latency=0.0,
         )
 
+    @classmethod
+    def from_metadata(cls, metadata: dict) -> "LLMUsage":
+        """
+        Create LLMUsage instance from metadata dictionary with default values.
+
+        Args:
+            metadata: Dictionary containing usage metadata
+
+        Returns:
+            LLMUsage instance with values from metadata or defaults
+        """
+        total_tokens = metadata.get("total_tokens", 0)
+        completion_tokens = metadata.get("completion_tokens", 0)
+        if total_tokens > 0 and completion_tokens == 0:
+            completion_tokens = total_tokens
+
+        return cls(
+            prompt_tokens=metadata.get("prompt_tokens", 0),
+            completion_tokens=completion_tokens,
+            total_tokens=total_tokens,
+            prompt_unit_price=Decimal(str(metadata.get("prompt_unit_price", 0))),
+            completion_unit_price=Decimal(str(metadata.get("completion_unit_price", 0))),
+            total_price=Decimal(str(metadata.get("total_price", 0))),
+            currency=metadata.get("currency", "USD"),
+            prompt_price_unit=Decimal(str(metadata.get("prompt_price_unit", 0))),
+            completion_price_unit=Decimal(str(metadata.get("completion_price_unit", 0))),
+            prompt_price=Decimal(str(metadata.get("prompt_price", 0))),
+            completion_price=Decimal(str(metadata.get("completion_price", 0))),
+            latency=metadata.get("latency", 0.0),
+        )
+
     def plus(self, other: "LLMUsage") -> "LLMUsage":
         """
         Add two LLMUsage instances together.
@@ -101,6 +132,20 @@ class LLMResult(BaseModel):
     system_fingerprint: Optional[str] = None
 
 
+class LLMStructuredOutput(BaseModel):
+    """
+    Model class for llm structured output.
+    """
+
+    structured_output: Optional[Mapping[str, Any]] = None
+
+
+class LLMResultWithStructuredOutput(LLMResult, LLMStructuredOutput):
+    """
+    Model class for llm result with structured output.
+    """
+
+
 class LLMResultChunkDelta(BaseModel):
     """
     Model class for llm result chunk delta.
@@ -123,6 +168,12 @@ class LLMResultChunk(BaseModel):
     delta: LLMResultChunkDelta
 
 
+class LLMResultChunkWithStructuredOutput(LLMResultChunk, LLMStructuredOutput):
+    """
+    Model class for llm result chunk with structured output.
+    """
+
+
 class NumTokensResult(PriceInfo):
     """
     Model class for number of tokens result.

api/core/model_runtime/entities/provider_entities.py

@@ -123,6 +123,8 @@ class ProviderEntity(BaseModel):
     description: Optional[I18nObject] = None
     icon_small: Optional[I18nObject] = None
     icon_large: Optional[I18nObject] = None
+    icon_small_dark: Optional[I18nObject] = None
+    icon_large_dark: Optional[I18nObject] = None
     background: Optional[str] = None
     help: Optional[ProviderHelpEntity] = None
     supported_model_types: Sequence[ModelType]

api/core/ops/aliyun_trace/aliyun_trace.py

@@ -0,0 +1,488 @@
+import json
+import logging
+from collections.abc import Sequence
+from typing import Optional
+from urllib.parse import urljoin
+
+from opentelemetry.trace import Status, StatusCode
+from sqlalchemy.orm import Session, sessionmaker
+
+from core.ops.aliyun_trace.data_exporter.traceclient import (
+    TraceClient,
+    convert_datetime_to_nanoseconds,
+    convert_to_span_id,
+    convert_to_trace_id,
+    generate_span_id,
+)
+from core.ops.aliyun_trace.entities.aliyun_trace_entity import SpanData
+from core.ops.aliyun_trace.entities.semconv import (
+    GEN_AI_COMPLETION,
+    GEN_AI_FRAMEWORK,
+    GEN_AI_MODEL_NAME,
+    GEN_AI_PROMPT,
+    GEN_AI_PROMPT_TEMPLATE_TEMPLATE,
+    GEN_AI_PROMPT_TEMPLATE_VARIABLE,
+    GEN_AI_RESPONSE_FINISH_REASON,
+    GEN_AI_SESSION_ID,
+    GEN_AI_SPAN_KIND,
+    GEN_AI_SYSTEM,
+    GEN_AI_USAGE_INPUT_TOKENS,
+    GEN_AI_USAGE_OUTPUT_TOKENS,
+    GEN_AI_USAGE_TOTAL_TOKENS,
+    GEN_AI_USER_ID,
+    INPUT_VALUE,
+    OUTPUT_VALUE,
+    RETRIEVAL_DOCUMENT,
+    RETRIEVAL_QUERY,
+    TOOL_DESCRIPTION,
+    TOOL_NAME,
+    TOOL_PARAMETERS,
+    GenAISpanKind,
+)
+from core.ops.base_trace_instance import BaseTraceInstance
+from core.ops.entities.config_entity import AliyunConfig
+from core.ops.entities.trace_entity import (
+    BaseTraceInfo,
+    DatasetRetrievalTraceInfo,
+    GenerateNameTraceInfo,
+    MessageTraceInfo,
+    ModerationTraceInfo,
+    SuggestedQuestionTraceInfo,
+    ToolTraceInfo,
+    WorkflowTraceInfo,
+)
+from core.rag.models.document import Document
+from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
+from core.workflow.entities.workflow_node_execution import (
+    WorkflowNodeExecution,
+    WorkflowNodeExecutionMetadataKey,
+    WorkflowNodeExecutionStatus,
+)
+from core.workflow.nodes import NodeType
+from models import Account, App, EndUser, TenantAccountJoin, WorkflowNodeExecutionTriggeredFrom, db
+
+logger = logging.getLogger(__name__)
+
+
+class AliyunDataTrace(BaseTraceInstance):
+    def __init__(
+        self,
+        aliyun_config: AliyunConfig,
+    ):
+        super().__init__(aliyun_config)
+        base_url = aliyun_config.endpoint.rstrip("/")
+        endpoint = urljoin(base_url, f"adapt_{aliyun_config.license_key}/api/otlp/traces")
+        self.trace_client = TraceClient(service_name=aliyun_config.app_name, endpoint=endpoint)
+
+    def trace(self, trace_info: BaseTraceInfo):
+        if isinstance(trace_info, WorkflowTraceInfo):
+            self.workflow_trace(trace_info)
+        if isinstance(trace_info, MessageTraceInfo):
+            self.message_trace(trace_info)
+        if isinstance(trace_info, ModerationTraceInfo):
+            pass
+        if isinstance(trace_info, SuggestedQuestionTraceInfo):
+            self.suggested_question_trace(trace_info)
+        if isinstance(trace_info, DatasetRetrievalTraceInfo):
+            self.dataset_retrieval_trace(trace_info)
+        if isinstance(trace_info, ToolTraceInfo):
+            self.tool_trace(trace_info)
+        if isinstance(trace_info, GenerateNameTraceInfo):
+            pass
+
+    def api_check(self):
+        return self.trace_client.api_check()
+
+    def get_project_url(self):
+        try:
+            return self.trace_client.get_project_url()
+        except Exception as e:
+            logger.info(f"Aliyun get run url failed: {str(e)}", exc_info=True)
+            raise ValueError(f"Aliyun get run url failed: {str(e)}")
+
+    def workflow_trace(self, trace_info: WorkflowTraceInfo):
+        trace_id = convert_to_trace_id(trace_info.workflow_run_id)
+        workflow_span_id = convert_to_span_id(trace_info.workflow_run_id, "workflow")
+        self.add_workflow_span(trace_id, workflow_span_id, trace_info)
+
+        workflow_node_executions = self.get_workflow_node_executions(trace_info)
+        for node_execution in workflow_node_executions:
+            node_span = self.build_workflow_node_span(node_execution, trace_id, trace_info, workflow_span_id)
+            self.trace_client.add_span(node_span)
+
+    def message_trace(self, trace_info: MessageTraceInfo):
+        message_data = trace_info.message_data
+        if message_data is None:
+            return
+        message_id = trace_info.message_id
+
+        user_id = message_data.from_account_id
+        if message_data.from_end_user_id:
+            end_user_data: Optional[EndUser] = (
+                db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first()
+            )
+            if end_user_data is not None:
+                user_id = end_user_data.session_id
+
+        status: Status = Status(StatusCode.OK)
+        if trace_info.error:
+            status = Status(StatusCode.ERROR, trace_info.error)
+
+        trace_id = convert_to_trace_id(message_id)
+        message_span_id = convert_to_span_id(message_id, "message")
+        message_span = SpanData(
+            trace_id=trace_id,
+            parent_span_id=None,
+            span_id=message_span_id,
+            name="message",
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""),
+                GEN_AI_USER_ID: str(user_id),
+                GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value,
+                GEN_AI_FRAMEWORK: "dify",
+                INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                OUTPUT_VALUE: str(trace_info.outputs),
+            },
+            status=status,
+        )
+        self.trace_client.add_span(message_span)
+
+        app_model_config = getattr(trace_info.message_data, "app_model_config", {})
+        pre_prompt = getattr(app_model_config, "pre_prompt", "")
+        inputs_data = getattr(trace_info.message_data, "inputs", {})
+        llm_span = SpanData(
+            trace_id=trace_id,
+            parent_span_id=message_span_id,
+            span_id=convert_to_span_id(message_id, "llm"),
+            name="llm",
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""),
+                GEN_AI_USER_ID: str(user_id),
+                GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value,
+                GEN_AI_FRAMEWORK: "dify",
+                GEN_AI_MODEL_NAME: trace_info.metadata.get("ls_model_name", ""),
+                GEN_AI_SYSTEM: trace_info.metadata.get("ls_provider", ""),
+                GEN_AI_USAGE_INPUT_TOKENS: str(trace_info.message_tokens),
+                GEN_AI_USAGE_OUTPUT_TOKENS: str(trace_info.answer_tokens),
+                GEN_AI_USAGE_TOTAL_TOKENS: str(trace_info.total_tokens),
+                GEN_AI_PROMPT_TEMPLATE_VARIABLE: json.dumps(inputs_data, ensure_ascii=False),
+                GEN_AI_PROMPT_TEMPLATE_TEMPLATE: pre_prompt,
+                GEN_AI_PROMPT: json.dumps(trace_info.inputs, ensure_ascii=False),
+                GEN_AI_COMPLETION: str(trace_info.outputs),
+                INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                OUTPUT_VALUE: str(trace_info.outputs),
+            },
+            status=status,
+        )
+        self.trace_client.add_span(llm_span)
+
+    def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
+        if trace_info.message_data is None:
+            return
+        message_id = trace_info.message_id
+
+        documents_data = extract_retrieval_documents(trace_info.documents)
+        dataset_retrieval_span = SpanData(
+            trace_id=convert_to_trace_id(message_id),
+            parent_span_id=convert_to_span_id(message_id, "message"),
+            span_id=generate_span_id(),
+            name="dataset_retrieval",
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_SPAN_KIND: GenAISpanKind.RETRIEVER.value,
+                GEN_AI_FRAMEWORK: "dify",
+                RETRIEVAL_QUERY: str(trace_info.inputs),
+                RETRIEVAL_DOCUMENT: json.dumps(documents_data, ensure_ascii=False),
+                INPUT_VALUE: str(trace_info.inputs),
+                OUTPUT_VALUE: json.dumps(documents_data, ensure_ascii=False),
+            },
+        )
+        self.trace_client.add_span(dataset_retrieval_span)
+
+    def tool_trace(self, trace_info: ToolTraceInfo):
+        if trace_info.message_data is None:
+            return
+        message_id = trace_info.message_id
+
+        status: Status = Status(StatusCode.OK)
+        if trace_info.error:
+            status = Status(StatusCode.ERROR, trace_info.error)
+
+        tool_span = SpanData(
+            trace_id=convert_to_trace_id(message_id),
+            parent_span_id=convert_to_span_id(message_id, "message"),
+            span_id=generate_span_id(),
+            name=trace_info.tool_name,
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_SPAN_KIND: GenAISpanKind.TOOL.value,
+                GEN_AI_FRAMEWORK: "dify",
+                TOOL_NAME: trace_info.tool_name,
+                TOOL_DESCRIPTION: json.dumps(trace_info.tool_config, ensure_ascii=False),
+                TOOL_PARAMETERS: json.dumps(trace_info.tool_inputs, ensure_ascii=False),
+                INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                OUTPUT_VALUE: str(trace_info.tool_outputs),
+            },
+            status=status,
+        )
+        self.trace_client.add_span(tool_span)
+
+    def get_workflow_node_executions(self, trace_info: WorkflowTraceInfo) -> Sequence[WorkflowNodeExecution]:
+        # through workflow_run_id get all_nodes_execution using repository
+        session_factory = sessionmaker(bind=db.engine)
+        # Find the app's creator account
+        with Session(db.engine, expire_on_commit=False) as session:
+            # Get the app to find its creator
+            app_id = trace_info.metadata.get("app_id")
+            if not app_id:
+                raise ValueError("No app_id found in trace_info metadata")
+
+            app = session.query(App).filter(App.id == app_id).first()
+            if not app:
+                raise ValueError(f"App with id {app_id} not found")
+
+            if not app.created_by:
+                raise ValueError(f"App with id {app_id} has no creator (created_by is None)")
+
+            service_account = session.query(Account).filter(Account.id == app.created_by).first()
+            if not service_account:
+                raise ValueError(f"Creator account with id {app.created_by} not found for app {app_id}")
+            current_tenant = (
+                session.query(TenantAccountJoin).filter_by(account_id=service_account.id, current=True).first()
+            )
+            if not current_tenant:
+                raise ValueError(f"Current tenant not found for account {service_account.id}")
+            service_account.set_tenant_id(current_tenant.tenant_id)
+        workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
+            session_factory=session_factory,
+            user=service_account,
+            app_id=trace_info.metadata.get("app_id"),
+            triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN,
+        )
+        # Get all executions for this workflow run
+        workflow_node_executions = workflow_node_execution_repository.get_by_workflow_run(
+            workflow_run_id=trace_info.workflow_run_id
+        )
+        return workflow_node_executions
+
+    def build_workflow_node_span(
+        self, node_execution: WorkflowNodeExecution, trace_id: int, trace_info: WorkflowTraceInfo, workflow_span_id: int
+    ):
+        try:
+            if node_execution.node_type == NodeType.LLM:
+                node_span = self.build_workflow_llm_span(trace_id, workflow_span_id, trace_info, node_execution)
+            elif node_execution.node_type == NodeType.KNOWLEDGE_RETRIEVAL:
+                node_span = self.build_workflow_retrieval_span(trace_id, workflow_span_id, trace_info, node_execution)
+            elif node_execution.node_type == NodeType.TOOL:
+                node_span = self.build_workflow_tool_span(trace_id, workflow_span_id, trace_info, node_execution)
+            else:
+                node_span = self.build_workflow_task_span(trace_id, workflow_span_id, trace_info, node_execution)
+            return node_span
+        except Exception as e:
+            logging.debug(f"Error occurred in build_workflow_node_span: {e}", exc_info=True)
+            return None
+
+    def get_workflow_node_status(self, node_execution: WorkflowNodeExecution) -> Status:
+        span_status: Status = Status(StatusCode.UNSET)
+        if node_execution.status == WorkflowNodeExecutionStatus.SUCCEEDED:
+            span_status = Status(StatusCode.OK)
+        elif node_execution.status in [WorkflowNodeExecutionStatus.FAILED, WorkflowNodeExecutionStatus.EXCEPTION]:
+            span_status = Status(StatusCode.ERROR, str(node_execution.error))
+        return span_status
+
+    def build_workflow_task_span(
+        self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution
+    ) -> SpanData:
+        return SpanData(
+            trace_id=trace_id,
+            parent_span_id=workflow_span_id,
+            span_id=convert_to_span_id(node_execution.id, "node"),
+            name=node_execution.title,
+            start_time=convert_datetime_to_nanoseconds(node_execution.created_at),
+            end_time=convert_datetime_to_nanoseconds(node_execution.finished_at),
+            attributes={
+                GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id") or "",
+                GEN_AI_SPAN_KIND: GenAISpanKind.TASK.value,
+                GEN_AI_FRAMEWORK: "dify",
+                INPUT_VALUE: json.dumps(node_execution.inputs, ensure_ascii=False),
+                OUTPUT_VALUE: json.dumps(node_execution.outputs, ensure_ascii=False),
+            },
+            status=self.get_workflow_node_status(node_execution),
+        )
+
+    def build_workflow_tool_span(
+        self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution
+    ) -> SpanData:
+        tool_des = {}
+        if node_execution.metadata:
+            tool_des = node_execution.metadata.get(WorkflowNodeExecutionMetadataKey.TOOL_INFO, {})
+        return SpanData(
+            trace_id=trace_id,
+            parent_span_id=workflow_span_id,
+            span_id=convert_to_span_id(node_execution.id, "node"),
+            name=node_execution.title,
+            start_time=convert_datetime_to_nanoseconds(node_execution.created_at),
+            end_time=convert_datetime_to_nanoseconds(node_execution.finished_at),
+            attributes={
+                GEN_AI_SPAN_KIND: GenAISpanKind.TOOL.value,
+                GEN_AI_FRAMEWORK: "dify",
+                TOOL_NAME: node_execution.title,
+                TOOL_DESCRIPTION: json.dumps(tool_des, ensure_ascii=False),
+                TOOL_PARAMETERS: json.dumps(node_execution.inputs if node_execution.inputs else {}, ensure_ascii=False),
+                INPUT_VALUE: json.dumps(node_execution.inputs if node_execution.inputs else {}, ensure_ascii=False),
+                OUTPUT_VALUE: json.dumps(node_execution.outputs, ensure_ascii=False),
+            },
+            status=self.get_workflow_node_status(node_execution),
+        )
+
+    def build_workflow_retrieval_span(
+        self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution
+    ) -> SpanData:
+        input_value = ""
+        if node_execution.inputs:
+            input_value = str(node_execution.inputs.get("query", ""))
+        output_value = ""
+        if node_execution.outputs:
+            output_value = json.dumps(node_execution.outputs.get("result", []), ensure_ascii=False)
+        return SpanData(
+            trace_id=trace_id,
+            parent_span_id=workflow_span_id,
+            span_id=convert_to_span_id(node_execution.id, "node"),
+            name=node_execution.title,
+            start_time=convert_datetime_to_nanoseconds(node_execution.created_at),
+            end_time=convert_datetime_to_nanoseconds(node_execution.finished_at),
+            attributes={
+                GEN_AI_SPAN_KIND: GenAISpanKind.RETRIEVER.value,
+                GEN_AI_FRAMEWORK: "dify",
+                RETRIEVAL_QUERY: input_value,
+                RETRIEVAL_DOCUMENT: output_value,
+                INPUT_VALUE: input_value,
+                OUTPUT_VALUE: output_value,
+            },
+            status=self.get_workflow_node_status(node_execution),
+        )
+
+    def build_workflow_llm_span(
+        self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution
+    ) -> SpanData:
+        process_data = node_execution.process_data or {}
+        outputs = node_execution.outputs or {}
+        usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {})
+        return SpanData(
+            trace_id=trace_id,
+            parent_span_id=workflow_span_id,
+            span_id=convert_to_span_id(node_execution.id, "node"),
+            name=node_execution.title,
+            start_time=convert_datetime_to_nanoseconds(node_execution.created_at),
+            end_time=convert_datetime_to_nanoseconds(node_execution.finished_at),
+            attributes={
+                GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id") or "",
+                GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value,
+                GEN_AI_FRAMEWORK: "dify",
+                GEN_AI_MODEL_NAME: process_data.get("model_name", ""),
+                GEN_AI_SYSTEM: process_data.get("model_provider", ""),
+                GEN_AI_USAGE_INPUT_TOKENS: str(usage_data.get("prompt_tokens", 0)),
+                GEN_AI_USAGE_OUTPUT_TOKENS: str(usage_data.get("completion_tokens", 0)),
+                GEN_AI_USAGE_TOTAL_TOKENS: str(usage_data.get("total_tokens", 0)),
+                GEN_AI_PROMPT: json.dumps(process_data.get("prompts", []), ensure_ascii=False),
+                GEN_AI_COMPLETION: str(outputs.get("text", "")),
+                GEN_AI_RESPONSE_FINISH_REASON: outputs.get("finish_reason", ""),
+                INPUT_VALUE: json.dumps(process_data.get("prompts", []), ensure_ascii=False),
+                OUTPUT_VALUE: str(outputs.get("text", "")),
+            },
+            status=self.get_workflow_node_status(node_execution),
+        )
+
+    def add_workflow_span(self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo):
+        message_span_id = None
+        if trace_info.message_id:
+            message_span_id = convert_to_span_id(trace_info.message_id, "message")
+        user_id = trace_info.metadata.get("user_id")
+        status: Status = Status(StatusCode.OK)
+        if trace_info.error:
+            status = Status(StatusCode.ERROR, trace_info.error)
+        if message_span_id:  # chatflow
+            message_span = SpanData(
+                trace_id=trace_id,
+                parent_span_id=None,
+                span_id=message_span_id,
+                name="message",
+                start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+                end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+                attributes={
+                    GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id") or "",
+                    GEN_AI_USER_ID: str(user_id),
+                    GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value,
+                    GEN_AI_FRAMEWORK: "dify",
+                    INPUT_VALUE: trace_info.workflow_run_inputs.get("sys.query", ""),
+                    OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False),
+                },
+                status=status,
+            )
+            self.trace_client.add_span(message_span)
+
+        workflow_span = SpanData(
+            trace_id=trace_id,
+            parent_span_id=message_span_id,
+            span_id=workflow_span_id,
+            name="workflow",
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_USER_ID: str(user_id),
+                GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value,
+                GEN_AI_FRAMEWORK: "dify",
+                INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False),
+                OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False),
+            },
+            status=status,
+        )
+        self.trace_client.add_span(workflow_span)
+
+    def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
+        message_id = trace_info.message_id
+        status: Status = Status(StatusCode.OK)
+        if trace_info.error:
+            status = Status(StatusCode.ERROR, trace_info.error)
+        suggested_question_span = SpanData(
+            trace_id=convert_to_trace_id(message_id),
+            parent_span_id=convert_to_span_id(message_id, "message"),
+            span_id=convert_to_span_id(message_id, "suggested_question"),
+            name="suggested_question",
+            start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
+            end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
+            attributes={
+                GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value,
+                GEN_AI_FRAMEWORK: "dify",
+                GEN_AI_MODEL_NAME: trace_info.metadata.get("ls_model_name", ""),
+                GEN_AI_SYSTEM: trace_info.metadata.get("ls_provider", ""),
+                GEN_AI_PROMPT: json.dumps(trace_info.inputs, ensure_ascii=False),
+                GEN_AI_COMPLETION: json.dumps(trace_info.suggested_question, ensure_ascii=False),
+                INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False),
+            },
+            status=status,
+        )
+        self.trace_client.add_span(suggested_question_span)
+
+
+def extract_retrieval_documents(documents: list[Document]):
+    documents_data = []
+    for document in documents:
+        document_data = {
+            "content": document.page_content,
+            "metadata": {
+                "dataset_id": document.metadata.get("dataset_id"),
+                "doc_id": document.metadata.get("doc_id"),
+                "document_id": document.metadata.get("document_id"),
+            },
+            "score": document.metadata.get("score"),
+        }
+        documents_data.append(document_data)
+    return documents_data

api/core/ops/aliyun_trace/data_exporter/traceclient.py

@@ -0,0 +1,200 @@
+import hashlib
+import logging
+import random
+import socket
+import threading
+import uuid
+from collections import deque
+from collections.abc import Sequence
+from datetime import datetime
+from typing import Optional
+
+import requests
+from opentelemetry import trace as trace_api
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk.resources import Resource
+from opentelemetry.sdk.trace import ReadableSpan
+from opentelemetry.sdk.util.instrumentation import InstrumentationScope
+from opentelemetry.semconv.resource import ResourceAttributes
+
+from configs import dify_config
+from core.ops.aliyun_trace.entities.aliyun_trace_entity import SpanData
+
+INVALID_SPAN_ID = 0x0000000000000000
+INVALID_TRACE_ID = 0x00000000000000000000000000000000
+
+logger = logging.getLogger(__name__)
+
+
+class TraceClient:
+    def __init__(
+        self,
+        service_name: str,
+        endpoint: str,
+        max_queue_size: int = 1000,
+        schedule_delay_sec: int = 5,
+        max_export_batch_size: int = 50,
+    ):
+        self.endpoint = endpoint
+        self.resource = Resource(
+            attributes={
+                ResourceAttributes.SERVICE_NAME: service_name,
+                ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}",
+                ResourceAttributes.DEPLOYMENT_ENVIRONMENT: f"{dify_config.DEPLOY_ENV}-{dify_config.EDITION}",
+                ResourceAttributes.HOST_NAME: socket.gethostname(),
+            }
+        )
+        self.span_builder = SpanBuilder(self.resource)
+        self.exporter = OTLPSpanExporter(endpoint=endpoint)
+
+        self.max_queue_size = max_queue_size
+        self.schedule_delay_sec = schedule_delay_sec
+        self.max_export_batch_size = max_export_batch_size
+
+        self.queue: deque = deque(maxlen=max_queue_size)
+        self.condition = threading.Condition(threading.Lock())
+        self.done = False
+
+        self.worker_thread = threading.Thread(target=self._worker, daemon=True)
+        self.worker_thread.start()
+
+        self._spans_dropped = False
+
+    def export(self, spans: Sequence[ReadableSpan]):
+        self.exporter.export(spans)
+
+    def api_check(self):
+        try:
+            response = requests.head(self.endpoint, timeout=5)
+            if response.status_code == 405:
+                return True
+            else:
+                logger.debug(f"AliyunTrace API check failed: Unexpected status code: {response.status_code}")
+                return False
+        except requests.exceptions.RequestException as e:
+            logger.debug(f"AliyunTrace API check failed: {str(e)}")
+            raise ValueError(f"AliyunTrace API check failed: {str(e)}")
+
+    def get_project_url(self):
+        return "https://arms.console.aliyun.com/#/llm"
+
+    def add_span(self, span_data: SpanData):
+        if span_data is None:
+            return
+        span: ReadableSpan = self.span_builder.build_span(span_data)
+        with self.condition:
+            if len(self.queue) == self.max_queue_size:
+                if not self._spans_dropped:
+                    logger.warning("Queue is full, likely spans will be dropped.")
+                    self._spans_dropped = True
+
+            self.queue.appendleft(span)
+            if len(self.queue) >= self.max_export_batch_size:
+                self.condition.notify()
+
+    def _worker(self):
+        while not self.done:
+            with self.condition:
+                if len(self.queue) < self.max_export_batch_size and not self.done:
+                    self.condition.wait(timeout=self.schedule_delay_sec)
+            self._export_batch()
+
+    def _export_batch(self):
+        spans_to_export: list[ReadableSpan] = []
+        with self.condition:
+            while len(spans_to_export) < self.max_export_batch_size and self.queue:
+                spans_to_export.append(self.queue.pop())
+
+        if spans_to_export:
+            try:
+                self.exporter.export(spans_to_export)
+            except Exception as e:
+                logger.debug(f"Error exporting spans: {e}")
+
+    def shutdown(self):
+        with self.condition:
+            self.done = True
+            self.condition.notify_all()
+        self.worker_thread.join()
+        self._export_batch()
+        self.exporter.shutdown()
+
+
+class SpanBuilder:
+    def __init__(self, resource):
+        self.resource = resource
+        self.instrumentation_scope = InstrumentationScope(
+            __name__,
+            "",
+            None,
+            None,
+        )
+
+    def build_span(self, span_data: SpanData) -> ReadableSpan:
+        span_context = trace_api.SpanContext(
+            trace_id=span_data.trace_id,
+            span_id=span_data.span_id,
+            is_remote=False,
+            trace_flags=trace_api.TraceFlags(trace_api.TraceFlags.SAMPLED),
+            trace_state=None,
+        )
+
+        parent_span_context = None
+        if span_data.parent_span_id is not None:
+            parent_span_context = trace_api.SpanContext(
+                trace_id=span_data.trace_id,
+                span_id=span_data.parent_span_id,
+                is_remote=False,
+                trace_flags=trace_api.TraceFlags(trace_api.TraceFlags.SAMPLED),
+                trace_state=None,
+            )
+
+        span = ReadableSpan(
+            name=span_data.name,
+            context=span_context,
+            parent=parent_span_context,
+            resource=self.resource,
+            attributes=span_data.attributes,
+            events=span_data.events,
+            links=span_data.links,
+            kind=trace_api.SpanKind.INTERNAL,
+            status=span_data.status,
+            start_time=span_data.start_time,
+            end_time=span_data.end_time,
+            instrumentation_scope=self.instrumentation_scope,
+        )
+        return span
+
+
+def generate_span_id() -> int:
+    span_id = random.getrandbits(64)
+    while span_id == INVALID_SPAN_ID:
+        span_id = random.getrandbits(64)
+    return span_id
+
+
+def convert_to_trace_id(uuid_v4: Optional[str]) -> int:
+    try:
+        uuid_obj = uuid.UUID(uuid_v4)
+        return uuid_obj.int
+    except Exception as e:
+        raise ValueError(f"Invalid UUID input: {e}")
+
+
+def convert_to_span_id(uuid_v4: Optional[str], span_type: str) -> int:
+    try:
+        uuid_obj = uuid.UUID(uuid_v4)
+    except Exception as e:
+        raise ValueError(f"Invalid UUID input: {e}")
+    combined_key = f"{uuid_obj.hex}-{span_type}"
+    hash_bytes = hashlib.sha256(combined_key.encode("utf-8")).digest()
+    span_id = int.from_bytes(hash_bytes[:8], byteorder="big", signed=False)
+    return span_id
+
+
+def convert_datetime_to_nanoseconds(start_time_a: Optional[datetime]) -> Optional[int]:
+    if start_time_a is None:
+        return None
+    timestamp_in_seconds = start_time_a.timestamp()
+    timestamp_in_nanoseconds = int(timestamp_in_seconds * 1e9)
+    return timestamp_in_nanoseconds