fix: gen-icon script phantom deps

Co-authored-by: cuihz <cuihz@knowbox.cn>

.devcontainer/post_create_command.sh

@@ -1,11 +1,12 @@
 #!/bin/bash
 
-cd web && npm install
+npm add -g pnpm@9.12.2
+cd web && pnpm install
 pipx install poetry
 
 echo 'alias start-api="cd /workspaces/dify/api && poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug"' >> ~/.bashrc
 echo 'alias start-worker="cd /workspaces/dify/api && poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion"' >> ~/.bashrc
-echo 'alias start-web="cd /workspaces/dify/web && npm run dev"' >> ~/.bashrc
+echo 'alias start-web="cd /workspaces/dify/web && pnpm dev"' >> ~/.bashrc
 echo 'alias start-containers="cd /workspaces/dify/docker && docker-compose -f docker-compose.middleware.yaml -p dify up -d"' >> ~/.bashrc
 
-source /home/vscode/.bashrc
+source /home/vscode/.bashrc

.github/workflows/api-tests.yml

@@ -27,19 +27,18 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Install Poetry
-        uses: abatilo/actions-poetry@v3
-
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: 'poetry'
           cache-dependency-path: |
             api/pyproject.toml
             api/poetry.lock
 
-      - name: Poetry check
+      - name: Install Poetry
+        uses: abatilo/actions-poetry@v3
+
+      - name: Check Poetry lockfile
         run: |
           poetry check -C api --lock
           poetry show -C api
@@ -47,6 +46,9 @@ jobs:
       - name: Install dependencies
         run: poetry install -C api --with dev
 
+      - name: Check dependencies in pyproject.toml
+        run: poetry run -C api bash dev/pytest/pytest_artifacts.sh
+
       - name: Run Unit tests
         run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
 

.github/workflows/build-push.yml

@@ -125,7 +125,7 @@ jobs:
         with:
           images: ${{ env[matrix.image_name_env] }}
           tags: |
-            type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') }}
+            type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') && !contains(github.ref, '-') }}
             type=ref,event=branch
             type=sha,enable=true,priority=100,prefix=,suffix=,format=long
             type=raw,value=${{ github.ref_name }},enable=${{ startsWith(github.ref, 'refs/tags/') }}

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

@@ -23,18 +23,17 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Install Poetry
-        uses: abatilo/actions-poetry@v3
-
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: 'poetry'
           cache-dependency-path: |
             api/pyproject.toml
             api/poetry.lock
 
+      - name: Install Poetry
+        uses: abatilo/actions-poetry@v3
+
       - name: Install dependencies
         run: poetry install -C api
 

.github/workflows/style.yml

@@ -24,15 +24,16 @@ jobs:
         with:
           files: api/**
 
-      - name: Install Poetry
-        uses: abatilo/actions-poetry@v3
-
       - name: Set up Python
         uses: actions/setup-python@v5
         if: steps.changed-files.outputs.any_changed == 'true'
         with:
           python-version: '3.10'
 
+      - name: Install Poetry
+        if: steps.changed-files.outputs.any_changed == 'true'
+        uses: abatilo/actions-poetry@v3
+
       - name: Python dependencies
         if: steps.changed-files.outputs.any_changed == 'true'
         run: poetry install -C api --only lint

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

@@ -42,7 +42,7 @@ jobs:
 
       - name: Run npm script
         if: env.FILES_CHANGED == 'true'
-        run: npm run auto-gen-i18n
+        run: pnpm run auto-gen-i18n
 
       - name: Create Pull Request
         if: env.FILES_CHANGED == 'true'

.gitignore

@@ -175,6 +175,8 @@ docker/volumes/pgvector/data/*
 docker/volumes/pgvecto_rs/data/*
 
 docker/nginx/conf.d/default.conf
+docker/nginx/ssl/*
+!docker/nginx/ssl/.gitkeep
 docker/middleware.env
 
 sdks/python-client/build
@@ -187,4 +189,7 @@ pyrightconfig.json
 api/.vscode
 
 .idea/
-.vscode
+.vscode
+
+# pnpm
+/.pnpm-store

LICENSE

@@ -6,8 +6,9 @@ Dify is licensed under the Apache License 2.0, with the following additional con
 
 a. Multi-tenant service: Unless explicitly authorized by Dify in writing, you may not use the Dify source code to operate a multi-tenant environment. 
     - Tenant Definition: Within the context of Dify, one tenant corresponds to one workspace. The workspace provides a separated area for each tenant's data and configurations.
-
-b. LOGO and copyright information: In the process of using Dify's frontend components, you may not remove or modify the LOGO or copyright information in the Dify console or applications. This restriction is inapplicable to uses of Dify that do not involve its frontend components.
+    
+b. LOGO and copyright information: In the process of using Dify's frontend, you may not remove or modify the LOGO or copyright information in the Dify console or applications. This restriction is inapplicable to uses of Dify that do not involve its frontend.
+    - Frontend Definition: For the purposes of this license, the "frontend" of Dify includes all components located in the `web/` directory when running Dify from the raw source code, or the "web" image when running Dify with Docker.
 
 Please contact business@dify.ai by email to inquire about licensing matters.
 

README.md

@@ -17,7 +17,7 @@
             alt="chat on Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="follow on Twitter"></a>
+            alt="follow on X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -196,10 +196,14 @@ If you'd like to configure a highly-available setup, there are community-contrib
 
 #### Using Terraform for Deployment
 
+Deploy Dify to Cloud Platform with a single click using [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Deploy Dify to Azure with a single click using [terraform](https://www.terraform.io/).
 - [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Contributing
 
 For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). 
@@ -219,7 +223,7 @@ At the same time, please consider supporting Dify by sharing it on social media
 * [Github Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
-* [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
+* [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
 
 ## Star history
 

README_AR.md

@@ -17,7 +17,7 @@
             alt="chat on Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="follow on Twitter"></a>
+            alt="follow on X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -179,10 +179,13 @@ docker compose up -d
 
 #### استخدام Terraform للتوزيع
 
+انشر Dify إلى منصة السحابة بنقرة واحدة باستخدام [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-استخدم [terraform](https://www.terraform.io/) لنشر Dify على Azure بنقرة واحدة.
 - [Azure Terraform بواسطة @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform بواسطة @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## المساهمة
 

README_CN.md

@@ -17,7 +17,7 @@
             alt="chat on Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="follow on Twitter"></a>
+            alt="follow on X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -202,10 +202,14 @@ docker compose up -d
 
 #### 使用 Terraform 部署
 
+使用 [terraform](https://www.terraform.io/) 一键将 Dify 部署到云平台
+
 ##### Azure Global
-使用 [terraform](https://www.terraform.io/) 一键部署 Dify 到 Azure。
 - [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Star History
 
 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
@@ -232,7 +236,7 @@ docker compose up -d
 - [GitHub Issues](https://github.com/langgenius/dify/issues)。👉：使用 Dify.AI 时遇到的错误和问题，请参阅[贡献指南](CONTRIBUTING.md)。
 - [电子邮件支持](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify)。👉：关于使用 Dify.AI 的问题。
 - [Discord](https://discord.gg/FngNHpbcY7)。👉：分享您的应用程序并与社区交流。
-- [Twitter](https://twitter.com/dify_ai)。👉：分享您的应用程序并与社区交流。
+- [X(Twitter)](https://twitter.com/dify_ai)。👉：分享您的应用程序并与社区交流。
 - [商业许可](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)。👉：有关商业用途许可 Dify.AI 的商业咨询。
  - [微信]() 👉：扫描下方二维码，添加微信好友，备注 Dify，我们将邀请您加入 Dify 社区。  
 <img src="./images/wechat.png" alt="wechat" width="100"/>

README_ES.md

@@ -17,7 +17,7 @@
             alt="chat en Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="seguir en Twitter"></a>
+            alt="seguir en X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Descargas de Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -204,10 +204,13 @@ Si desea configurar una configuración de alta disponibilidad, la comunidad prop
 
 #### Uso de Terraform para el despliegue
 
+Despliega Dify en una plataforma en la nube con un solo clic utilizando [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Utiliza [terraform](https://www.terraform.io/) para desplegar Dify en Azure con un solo clic.
 - [Azure Terraform por @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform por @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contribuir
 
@@ -228,7 +231,7 @@ Al mismo tiempo, considera apoyar a Dify compartiéndolo en redes sociales y en
 * [Discusión en GitHub](https://github.com/langgenius/dify/discussions). Lo mejor para: compartir comentarios y hacer preguntas.
 * [Reporte de problemas en GitHub](https://github.com/langgenius/dify/issues). Lo mejor para: errores que encuentres usando Dify.AI y propuestas de características. Consulta nuestra [Guía de contribución](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
-* [Twitter](https://twitter.com/dify_ai). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
+* [X(Twitter)](https://twitter.com/dify_ai). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
 
 ## Historial de Estrellas
 

README_FR.md

@@ -17,7 +17,7 @@
             alt="chat sur Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="suivre sur Twitter"></a>
+            alt="suivre sur X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Tirages Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -202,10 +202,13 @@ Si vous souhaitez configurer une configuration haute disponibilité, la communau
 
 #### Utilisation de Terraform pour le déploiement
 
+Déployez Dify sur une plateforme cloud en un clic en utilisant [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Utilisez [terraform](https://www.terraform.io/) pour déployer Dify sur Azure en un clic.
 - [Azure Terraform par @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform par @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contribuer
 
@@ -226,7 +229,7 @@ Dans le même temps, veuillez envisager de soutenir Dify en le partageant sur le
 * [Discussion GitHub](https://github.com/langgenius/dify/discussions). Meilleur pour: partager des commentaires et poser des questions.
 * [Problèmes GitHub](https://github.com/langgenius/dify/issues). Meilleur pour: les bogues que vous rencontrez en utilisant Dify.AI et les propositions de fonctionnalités. Consultez notre [Guide de contribution](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7). Meilleur pour: partager vos applications et passer du temps avec la communauté.
-* [Twitter](https://twitter.com/dify_ai). Meilleur pour: partager vos applications et passer du temps avec la communauté.
+* [X(Twitter)](https://twitter.com/dify_ai). Meilleur pour: partager vos applications et passer du temps avec la communauté.
 
 ## Historique des étoiles
 

README_JA.md

@@ -17,7 +17,7 @@
             alt="Discordでチャット"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="Twitterでフォロー"></a>
+            alt="X(Twitter)でフォロー"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -68,7 +68,7 @@ DifyはオープンソースのLLMアプリケーション開発プラットフ
   プロンプトの作成、モデルパフォーマンスの比較が行え、チャットベースのアプリに音声合成などの機能も追加できます。
 
 **4. RAGパイプライン**: 
-  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサーポイントも提供します。
+  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサポートも提供します。
 
 **5. エージェント機能**: 
   LLM Function CallingやReActに基づくエージェントの定義が可能で、AIエージェント用のプリビルトまたはカスタムツールを追加できます。Difyには、Google検索、DALL·E、Stable Diffusion、WolframAlphaなどのAIエージェント用の50以上の組み込みツールが提供します。
@@ -201,10 +201,13 @@ docker compose up -d
 
 #### Terraformを使用したデプロイ
 
-##### Azure Global
-[terraform](https://www.terraform.io/) を使用して、AzureにDifyをワンクリックでデプロイします。
-- [nikawangのAzure Terraform](https://github.com/nikawang/dify-azure-terraform)
+[terraform](https://www.terraform.io/) を使用して、ワンクリックでDifyをクラウドプラットフォームにデプロイします
 
+##### Azure Global
+- [@nikawangによるAzure Terraform](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [@sotazumによるGoogle Cloud Terraform](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## 貢献
 
@@ -225,7 +228,7 @@ docker compose up -d
 * [Github Discussion](https://github.com/langgenius/dify/discussions). 主に: フィードバックの共有や質問。
 * [GitHub Issues](https://github.com/langgenius/dify/issues). 主に: Dify.AIを使用する際に発生するエラーや問題については、[貢献ガイド](CONTRIBUTING_JA.md)を参照してください
 * [Discord](https://discord.gg/FngNHpbcY7). 主に: アプリケーションの共有やコミュニティとの交流。
-* [Twitter](https://twitter.com/dify_ai). 主に: アプリケーションの共有やコミュニティとの交流。
+* [X(Twitter)](https://twitter.com/dify_ai). 主に: アプリケーションの共有やコミュニティとの交流。
 
 
 

README_KL.md

@@ -17,7 +17,7 @@
             alt="chat on Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="follow on Twitter"></a>
+            alt="follow on X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -202,10 +202,13 @@ If you'd like to configure a highly-available setup, there are community-contrib
 
 #### Terraform atorlugu pilersitsineq
 
-##### Azure Global
-Atoruk [terraform](https://www.terraform.io/) Dify-mik Azure-mut ataatsikkut ikkussuilluarlugu.
-- [Azure Terraform atorlugu @nikawang](https://github.com/nikawang/dify-azure-terraform)
+wa'logh nIqHom neH ghun deployment toy'wI' [terraform](https://www.terraform.io/) lo'laH.
 
+##### Azure Global
+- [Azure Terraform mung @nikawang](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [Google Cloud Terraform qachlot @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contributing
 
@@ -228,7 +231,7 @@ At the same time, please consider supporting Dify by sharing it on social media
 ). Best for: sharing feedback and asking questions.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
-* [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
+* [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
 
 ## Star History
 

README_KR.md

@@ -17,7 +17,7 @@
             alt="chat on Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="follow on Twitter"></a>
+            alt="follow on X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -39,7 +39,6 @@
   <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
   <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
   <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
-
 </p>
 
 
@@ -195,10 +194,14 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했
 
 #### Terraform을 사용한 배포
 
+[terraform](https://www.terraform.io/)을 사용하여 단 한 번의 클릭으로 Dify를 클라우드 플랫폼에 배포하십시오
+
 ##### Azure Global
-[terraform](https://www.terraform.io/)을 사용하여 Azure에 Dify를 원클릭으로 배포하세요.
 - [nikawang의 Azure Terraform](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [sotazum의 Google Cloud Terraform](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## 기여
 
 코드에 기여하고 싶은 분들은 [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요.

README_TR.md

@@ -17,7 +17,7 @@
             alt="Discord'da sohbet et"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="Twitter'da takip et"></a>
+            alt="X(Twitter)'da takip et"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Çekmeleri" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -200,9 +200,13 @@ Yüksek kullanılabilirliğe sahip bir kurulum yapılandırmak isterseniz, Dify'
 
 #### Dağıtım için Terraform Kullanımı
 
+Dify'ı bulut platformuna tek tıklamayla dağıtın [terraform](https://www.terraform.io/) kullanarak
+
 ##### Azure Global
-[Terraform](https://www.terraform.io/) kullanarak Dify'ı Azure'a tek tıklamayla dağıtın.
-- [@nikawang tarafından Azure Terraform](https://github.com/nikawang/dify-azure-terraform)
+- [Azure Terraform tarafından @nikawang](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [Google Cloud Terraform tarafından @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Katkıda Bulunma
 
@@ -222,7 +226,7 @@ Aynı zamanda, lütfen Dify'ı sosyal medyada, etkinliklerde ve konferanslarda p
 * [Github Tartışmaları](https://github.com/langgenius/dify/discussions). En uygun: geri bildirim paylaşmak ve soru sormak için.
 * [GitHub Sorunları](https://github.com/langgenius/dify/issues). En uygun: Dify.AI kullanırken karşılaştığınız hatalar ve özellik önerileri için. [Katkı Kılavuzumuza](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) bakın.
 * [Discord](https://discord.gg/FngNHpbcY7). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
-* [Twitter](https://twitter.com/dify_ai). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
+* [X(Twitter)](https://twitter.com/dify_ai). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
 
 ## Star history
 

README_VI.md

@@ -17,7 +17,7 @@
             alt="chat trên Discord"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
         <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
-            alt="theo dõi trên Twitter"></a>
+            alt="theo dõi trên X(Twitter)"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
     <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
@@ -196,10 +196,14 @@ Nếu bạn muốn cấu hình một cài đặt có độ sẵn sàng cao, có
 
 #### Sử dụng Terraform để Triển khai
 
+Triển khai Dify lên nền tảng đám mây với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Triển khai Dify lên Azure chỉ với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/).
 - [Azure Terraform bởi @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform bởi @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Đóng góp
 
 Đối với những người muốn đóng góp mã, xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi. 
@@ -219,7 +223,7 @@ Triển khai Dify lên Azure chỉ với một cú nhấp chuột bằng cách s
 * [Thảo luận GitHub](https://github.com/langgenius/dify/discussions). Tốt nhất cho: chia sẻ phản hồi và đặt câu hỏi.
 * [Vấn đề GitHub](https://github.com/langgenius/dify/issues). Tốt nhất cho: lỗi bạn gặp phải khi sử dụng Dify.AI và đề xuất tính năng. Xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi.
 * [Discord](https://discord.gg/FngNHpbcY7). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
-* [Twitter](https://twitter.com/dify_ai). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
+* [X(Twitter)](https://twitter.com/dify_ai). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
 
 ## Lịch sử Yêu thích
 

api/.env.example

@@ -20,6 +20,9 @@ FILES_URL=http://127.0.0.1:5001
 # The time in seconds after the signature is rejected
 FILES_ACCESS_TIMEOUT=300
 
+# Access token expiration time in minutes
+ACCESS_TOKEN_EXPIRE_MINUTES=60
+
 # celery configuration
 CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1
 
@@ -39,7 +42,7 @@ DB_DATABASE=dify
 
 # Storage configuration
 # use for store upload files, private keys...
-# storage type: local, s3, azure-blob, google-storage, tencent-cos, huawei-obs, volcengine-tos
+# storage type: local, s3, aliyun-oss, azure-blob, baidu-obs, google-storage, huawei-obs, oci-storage, tencent-cos, volcengine-tos, supabase
 STORAGE_TYPE=local
 STORAGE_LOCAL_PATH=storage
 S3_USE_AWS_MANAGED_IAM=false
@@ -79,6 +82,12 @@ HUAWEI_OBS_SECRET_KEY=your-secret-key
 HUAWEI_OBS_ACCESS_KEY=your-access-key
 HUAWEI_OBS_SERVER=your-server-url
 
+# Baidu OBS Storage Configuration
+BAIDU_OBS_BUCKET_NAME=your-bucket-name
+BAIDU_OBS_SECRET_KEY=your-secret-key
+BAIDU_OBS_ACCESS_KEY=your-access-key
+BAIDU_OBS_ENDPOINT=your-server-url
+
 # OCI Storage configuration
 OCI_ENDPOINT=your-endpoint
 OCI_BUCKET_NAME=your-bucket-name
@@ -93,11 +102,16 @@ VOLCENGINE_TOS_ACCESS_KEY=your-access-key
 VOLCENGINE_TOS_SECRET_KEY=your-secret-key
 VOLCENGINE_TOS_REGION=your-region
 
+# Supabase Storage Configuration
+SUPABASE_BUCKET_NAME=your-bucket-name
+SUPABASE_API_KEY=your-access-key
+SUPABASE_URL=your-server-url
+
 # CORS configuration
 WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
 CONSOLE_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
 
-# Vector database configuration, support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector
+# Vector database configuration, support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, vikingdb
 VECTOR_STORE=weaviate
 
 # Weaviate configuration
@@ -197,6 +211,24 @@ OPENSEARCH_USER=admin
 OPENSEARCH_PASSWORD=admin
 OPENSEARCH_SECURE=true
 
+# Baidu configuration
+BAIDU_VECTOR_DB_ENDPOINT=http://127.0.0.1:5287
+BAIDU_VECTOR_DB_CONNECTION_TIMEOUT_MS=30000
+BAIDU_VECTOR_DB_ACCOUNT=root
+BAIDU_VECTOR_DB_API_KEY=dify
+BAIDU_VECTOR_DB_DATABASE=dify
+BAIDU_VECTOR_DB_SHARD=1
+BAIDU_VECTOR_DB_REPLICAS=3
+
+# ViKingDB configuration
+VIKINGDB_ACCESS_KEY=your-ak
+VIKINGDB_SECRET_KEY=your-sk
+VIKINGDB_REGION=cn-shanghai
+VIKINGDB_HOST=api-vikingdb.xxx.volces.com
+VIKINGDB_SCHEMA=http
+VIKINGDB_CONNECTION_TIMEOUT=30
+VIKINGDB_SOCKET_TIMEOUT=30
+
 # Upload configuration
 UPLOAD_FILE_SIZE_LIMIT=15
 UPLOAD_FILE_BATCH_LIMIT=5
@@ -265,6 +297,9 @@ HTTP_REQUEST_MAX_WRITE_TIMEOUT=600
 HTTP_REQUEST_NODE_MAX_BINARY_SIZE=10485760
 HTTP_REQUEST_NODE_MAX_TEXT_SIZE=1048576
 
+# Respect X-* headers to redirect clients
+RESPECT_XFORWARD_HEADERS_ENABLED=false
+
 # Log file path
 LOG_FILE=
 

api/README.md

@@ -85,3 +85,4 @@
    cd ../
    poetry run -C api bash dev/pytest/pytest_all_tests.sh
    ```
+

api/app.py

@@ -10,43 +10,20 @@ if os.environ.get("DEBUG", "false").lower() != "true":
     grpc.experimental.gevent.init_gevent()
 
 import json
-import logging
-import sys
 import threading
 import time
 import warnings
-from logging.handlers import RotatingFileHandler
 
-from flask import Flask, Response, request
-from flask_cors import CORS
-from werkzeug.exceptions import Unauthorized
+from flask import Response
 
-import contexts
-from commands import register_commands
-from configs import dify_config
+from app_factory import create_app
 
 # DO NOT REMOVE BELOW
-from events import event_handlers
-from extensions import (
-    ext_celery,
-    ext_code_based_extension,
-    ext_compress,
-    ext_database,
-    ext_hosting_provider,
-    ext_login,
-    ext_mail,
-    ext_migrate,
-    ext_redis,
-    ext_sentry,
-    ext_storage,
-)
+from events import event_handlers  # noqa: F401
 from extensions.ext_database import db
-from extensions.ext_login import login_manager
-from libs.passport import PassportService
 
 # TODO: Find a way to avoid importing models here
-from models import account, dataset, model, source, task, tool, tools, web
-from services.account_service import AccountService
+from models import account, dataset, model, source, task, tool, tools, web  # noqa: F401
 
 # DO NOT REMOVE ABOVE
 
@@ -59,187 +36,12 @@ if hasattr(time, "tzset"):
     time.tzset()
 
 
-class DifyApp(Flask):
-    pass
-
-
 # -------------
 # Configuration
 # -------------
-
-
 config_type = os.getenv("EDITION", default="SELF_HOSTED")  # ce edition first
 
 
-# ----------------------------
-# Application Factory Function
-# ----------------------------
-
-
-def create_flask_app_with_configs() -> Flask:
-    """
-    create a raw flask app
-    with configs loaded from .env file
-    """
-    dify_app = DifyApp(__name__)
-    dify_app.config.from_mapping(dify_config.model_dump())
-
-    # populate configs into system environment variables
-    for key, value in dify_app.config.items():
-        if isinstance(value, str):
-            os.environ[key] = value
-        elif isinstance(value, int | float | bool):
-            os.environ[key] = str(value)
-        elif value is None:
-            os.environ[key] = ""
-
-    return dify_app
-
-
-def create_app() -> Flask:
-    app = create_flask_app_with_configs()
-
-    app.secret_key = app.config["SECRET_KEY"]
-
-    log_handlers = None
-    log_file = app.config.get("LOG_FILE")
-    if log_file:
-        log_dir = os.path.dirname(log_file)
-        os.makedirs(log_dir, exist_ok=True)
-        log_handlers = [
-            RotatingFileHandler(
-                filename=log_file,
-                maxBytes=1024 * 1024 * 1024,
-                backupCount=5,
-            ),
-            logging.StreamHandler(sys.stdout),
-        ]
-
-    logging.basicConfig(
-        level=app.config.get("LOG_LEVEL"),
-        format=app.config.get("LOG_FORMAT"),
-        datefmt=app.config.get("LOG_DATEFORMAT"),
-        handlers=log_handlers,
-        force=True,
-    )
-    log_tz = app.config.get("LOG_TZ")
-    if log_tz:
-        from datetime import datetime
-
-        import pytz
-
-        timezone = pytz.timezone(log_tz)
-
-        def time_converter(seconds):
-            return datetime.utcfromtimestamp(seconds).astimezone(timezone).timetuple()
-
-        for handler in logging.root.handlers:
-            handler.formatter.converter = time_converter
-    initialize_extensions(app)
-    register_blueprints(app)
-    register_commands(app)
-
-    return app
-
-
-def initialize_extensions(app):
-    # Since the application instance is now created, pass it to each Flask
-    # extension instance to bind it to the Flask application instance (app)
-    ext_compress.init_app(app)
-    ext_code_based_extension.init()
-    ext_database.init_app(app)
-    ext_migrate.init(app, db)
-    ext_redis.init_app(app)
-    ext_storage.init_app(app)
-    ext_celery.init_app(app)
-    ext_login.init_app(app)
-    ext_mail.init_app(app)
-    ext_hosting_provider.init_app(app)
-    ext_sentry.init_app(app)
-
-
-# Flask-Login configuration
-@login_manager.request_loader
-def load_user_from_request(request_from_flask_login):
-    """Load user based on the request."""
-    if request.blueprint not in {"console", "inner_api"}:
-        return None
-    # Check if the user_id contains a dot, indicating the old format
-    auth_header = request.headers.get("Authorization", "")
-    if not auth_header:
-        auth_token = request.args.get("_token")
-        if not auth_token:
-            raise Unauthorized("Invalid Authorization token.")
-    else:
-        if " " not in auth_header:
-            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
-        auth_scheme, auth_token = auth_header.split(None, 1)
-        auth_scheme = auth_scheme.lower()
-        if auth_scheme != "bearer":
-            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
-
-    decoded = PassportService().verify(auth_token)
-    user_id = decoded.get("user_id")
-
-    account = AccountService.load_logged_in_account(account_id=user_id, token=auth_token)
-    if account:
-        contexts.tenant_id.set(account.current_tenant_id)
-    return account
-
-
-@login_manager.unauthorized_handler
-def unauthorized_handler():
-    """Handle unauthorized requests."""
-    return Response(
-        json.dumps({"code": "unauthorized", "message": "Unauthorized."}),
-        status=401,
-        content_type="application/json",
-    )
-
-
-# register blueprint routers
-def register_blueprints(app):
-    from controllers.console import bp as console_app_bp
-    from controllers.files import bp as files_bp
-    from controllers.inner_api import bp as inner_api_bp
-    from controllers.service_api import bp as service_api_bp
-    from controllers.web import bp as web_bp
-
-    CORS(
-        service_api_bp,
-        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
-        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
-    )
-    app.register_blueprint(service_api_bp)
-
-    CORS(
-        web_bp,
-        resources={r"/*": {"origins": app.config["WEB_API_CORS_ALLOW_ORIGINS"]}},
-        supports_credentials=True,
-        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
-        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
-        expose_headers=["X-Version", "X-Env"],
-    )
-
-    app.register_blueprint(web_bp)
-
-    CORS(
-        console_app_bp,
-        resources={r"/*": {"origins": app.config["CONSOLE_CORS_ALLOW_ORIGINS"]}},
-        supports_credentials=True,
-        allow_headers=["Content-Type", "Authorization"],
-        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
-        expose_headers=["X-Version", "X-Env"],
-    )
-
-    app.register_blueprint(console_app_bp)
-
-    CORS(files_bp, allow_headers=["Content-Type"], methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"])
-    app.register_blueprint(files_bp)
-
-    app.register_blueprint(inner_api_bp)
-
-
 # create app
 app = create_app()
 celery = app.extensions["celery"]

api/app_factory.py

@@ -0,0 +1,213 @@
+import os
+
+if os.environ.get("DEBUG", "false").lower() != "true":
+    from gevent import monkey
+
+    monkey.patch_all()
+
+    import grpc.experimental.gevent
+
+    grpc.experimental.gevent.init_gevent()
+
+import json
+import logging
+import sys
+from logging.handlers import RotatingFileHandler
+
+from flask import Flask, Response, request
+from flask_cors import CORS
+from werkzeug.exceptions import Unauthorized
+
+import contexts
+from commands import register_commands
+from configs import dify_config
+from extensions import (
+    ext_celery,
+    ext_code_based_extension,
+    ext_compress,
+    ext_database,
+    ext_hosting_provider,
+    ext_login,
+    ext_mail,
+    ext_migrate,
+    ext_proxy_fix,
+    ext_redis,
+    ext_sentry,
+    ext_storage,
+)
+from extensions.ext_database import db
+from extensions.ext_login import login_manager
+from libs.passport import PassportService
+from services.account_service import AccountService
+
+
+class DifyApp(Flask):
+    pass
+
+
+# ----------------------------
+# Application Factory Function
+# ----------------------------
+def create_flask_app_with_configs() -> Flask:
+    """
+    create a raw flask app
+    with configs loaded from .env file
+    """
+    dify_app = DifyApp(__name__)
+    dify_app.config.from_mapping(dify_config.model_dump())
+
+    # populate configs into system environment variables
+    for key, value in dify_app.config.items():
+        if isinstance(value, str):
+            os.environ[key] = value
+        elif isinstance(value, int | float | bool):
+            os.environ[key] = str(value)
+        elif value is None:
+            os.environ[key] = ""
+
+    return dify_app
+
+
+def create_app() -> Flask:
+    app = create_flask_app_with_configs()
+
+    app.secret_key = app.config["SECRET_KEY"]
+
+    log_handlers = None
+    log_file = app.config.get("LOG_FILE")
+    if log_file:
+        log_dir = os.path.dirname(log_file)
+        os.makedirs(log_dir, exist_ok=True)
+        log_handlers = [
+            RotatingFileHandler(
+                filename=log_file,
+                maxBytes=1024 * 1024 * 1024,
+                backupCount=5,
+            ),
+            logging.StreamHandler(sys.stdout),
+        ]
+
+    logging.basicConfig(
+        level=app.config.get("LOG_LEVEL"),
+        format=app.config.get("LOG_FORMAT"),
+        datefmt=app.config.get("LOG_DATEFORMAT"),
+        handlers=log_handlers,
+        force=True,
+    )
+    log_tz = app.config.get("LOG_TZ")
+    if log_tz:
+        from datetime import datetime
+
+        import pytz
+
+        timezone = pytz.timezone(log_tz)
+
+        def time_converter(seconds):
+            return datetime.utcfromtimestamp(seconds).astimezone(timezone).timetuple()
+
+        for handler in logging.root.handlers:
+            handler.formatter.converter = time_converter
+    initialize_extensions(app)
+    register_blueprints(app)
+    register_commands(app)
+
+    return app
+
+
+def initialize_extensions(app):
+    # Since the application instance is now created, pass it to each Flask
+    # extension instance to bind it to the Flask application instance (app)
+    ext_compress.init_app(app)
+    ext_code_based_extension.init()
+    ext_database.init_app(app)
+    ext_migrate.init(app, db)
+    ext_redis.init_app(app)
+    ext_storage.init_app(app)
+    ext_celery.init_app(app)
+    ext_login.init_app(app)
+    ext_mail.init_app(app)
+    ext_hosting_provider.init_app(app)
+    ext_sentry.init_app(app)
+    ext_proxy_fix.init_app(app)
+
+
+# Flask-Login configuration
+@login_manager.request_loader
+def load_user_from_request(request_from_flask_login):
+    """Load user based on the request."""
+    if request.blueprint not in {"console", "inner_api"}:
+        return None
+    # Check if the user_id contains a dot, indicating the old format
+    auth_header = request.headers.get("Authorization", "")
+    if not auth_header:
+        auth_token = request.args.get("_token")
+        if not auth_token:
+            raise Unauthorized("Invalid Authorization token.")
+    else:
+        if " " not in auth_header:
+            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
+        auth_scheme, auth_token = auth_header.split(None, 1)
+        auth_scheme = auth_scheme.lower()
+        if auth_scheme != "bearer":
+            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
+
+    decoded = PassportService().verify(auth_token)
+    user_id = decoded.get("user_id")
+
+    logged_in_account = AccountService.load_logged_in_account(account_id=user_id)
+    if logged_in_account:
+        contexts.tenant_id.set(logged_in_account.current_tenant_id)
+    return logged_in_account
+
+
+@login_manager.unauthorized_handler
+def unauthorized_handler():
+    """Handle unauthorized requests."""
+    return Response(
+        json.dumps({"code": "unauthorized", "message": "Unauthorized."}),
+        status=401,
+        content_type="application/json",
+    )
+
+
+# register blueprint routers
+def register_blueprints(app):
+    from controllers.console import bp as console_app_bp
+    from controllers.files import bp as files_bp
+    from controllers.inner_api import bp as inner_api_bp
+    from controllers.service_api import bp as service_api_bp
+    from controllers.web import bp as web_bp
+
+    CORS(
+        service_api_bp,
+        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+    )
+    app.register_blueprint(service_api_bp)
+
+    CORS(
+        web_bp,
+        resources={r"/*": {"origins": app.config["WEB_API_CORS_ALLOW_ORIGINS"]}},
+        supports_credentials=True,
+        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+        expose_headers=["X-Version", "X-Env"],
+    )
+
+    app.register_blueprint(web_bp)
+
+    CORS(
+        console_app_bp,
+        resources={r"/*": {"origins": app.config["CONSOLE_CORS_ALLOW_ORIGINS"]}},
+        supports_credentials=True,
+        allow_headers=["Content-Type", "Authorization"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+        expose_headers=["X-Version", "X-Env"],
+    )
+
+    app.register_blueprint(console_app_bp)
+
+    CORS(files_bp, allow_headers=["Content-Type"], methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"])
+    app.register_blueprint(files_bp)
+
+    app.register_blueprint(inner_api_bp)

api/commands.py

@@ -259,6 +259,25 @@ def migrate_knowledge_vector_database():
     skipped_count = 0
     total_count = 0
     vector_type = dify_config.VECTOR_STORE
+    upper_colletion_vector_types = {
+        VectorType.MILVUS,
+        VectorType.PGVECTOR,
+        VectorType.RELYT,
+        VectorType.WEAVIATE,
+        VectorType.ORACLE,
+        VectorType.ELASTICSEARCH,
+    }
+    lower_colletion_vector_types = {
+        VectorType.ANALYTICDB,
+        VectorType.CHROMA,
+        VectorType.MYSCALE,
+        VectorType.PGVECTO_RS,
+        VectorType.TIDB_VECTOR,
+        VectorType.OPENSEARCH,
+        VectorType.TENCENT,
+        VectorType.BAIDU,
+        VectorType.VIKINGDB,
+    }
     page = 1
     while True:
         try:
@@ -284,11 +303,9 @@ def migrate_knowledge_vector_database():
                         skipped_count = skipped_count + 1
                         continue
                 collection_name = ""
-                if vector_type == VectorType.WEAVIATE:
-                    dataset_id = dataset.id
+                dataset_id = dataset.id
+                if vector_type in upper_colletion_vector_types:
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": VectorType.WEAVIATE, "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.QDRANT:
                     if dataset.collection_binding_id:
                         dataset_collection_binding = (
@@ -301,55 +318,15 @@ def migrate_knowledge_vector_database():
                         else:
                             raise ValueError("Dataset Collection Binding not found")
                     else:
-                        dataset_id = dataset.id
                         collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": VectorType.QDRANT, "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
 
-                elif vector_type == VectorType.MILVUS:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": VectorType.MILVUS, "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.RELYT:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": "relyt", "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.TENCENT:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": VectorType.TENCENT, "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.PGVECTOR:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": VectorType.PGVECTOR, "vector_store": {"class_prefix": collection_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.OPENSEARCH:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.OPENSEARCH,
-                        "vector_store": {"class_prefix": collection_name},
-                    }
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.ANALYTICDB:
-                    dataset_id = dataset.id
-                    collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.ANALYTICDB,
-                        "vector_store": {"class_prefix": collection_name},
-                    }
-                    dataset.index_struct = json.dumps(index_struct_dict)
-                elif vector_type == VectorType.ELASTICSEARCH:
-                    dataset_id = dataset.id
-                    index_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {"type": "elasticsearch", "vector_store": {"class_prefix": index_name}}
-                    dataset.index_struct = json.dumps(index_struct_dict)
+                elif vector_type in lower_colletion_vector_types:
+                    collection_name = Dataset.gen_collection_name_by_id(dataset_id).lower()
                 else:
                     raise ValueError(f"Vector store {vector_type} is not supported.")
 
+                index_struct_dict = {"type": vector_type, "vector_store": {"class_prefix": collection_name}}
+                dataset.index_struct = json.dumps(index_struct_dict)
                 vector = Vector(dataset)
                 click.echo(f"Migrating dataset {dataset.id}.")
 

api/configs/feature/__init__.py

@@ -247,6 +247,12 @@ class HttpConfig(BaseSettings):
         default=None,
     )
 
+    RESPECT_XFORWARD_HEADERS_ENABLED: bool = Field(
+        description="Enable or disable the X-Forwarded-For Proxy Fix middleware from Werkzeug"
+        " to respect X-* headers to redirect clients",
+        default=False,
+    )
+
 
 class InnerAPIConfig(BaseSettings):
     """
@@ -354,9 +360,9 @@ class WorkflowConfig(BaseSettings):
     )
 
 
-class OAuthConfig(BaseSettings):
+class AuthConfig(BaseSettings):
     """
-    Configuration for OAuth authentication
+    Configuration for authentication and OAuth
     """
 
     OAUTH_REDIRECT_PATH: str = Field(
@@ -365,7 +371,7 @@ class OAuthConfig(BaseSettings):
     )
 
     GITHUB_CLIENT_ID: Optional[str] = Field(
-        description="GitHub OAuth client secret",
+        description="GitHub OAuth client ID",
         default=None,
     )
 
@@ -384,6 +390,11 @@ class OAuthConfig(BaseSettings):
         default=None,
     )
 
+    ACCESS_TOKEN_EXPIRE_MINUTES: PositiveInt = Field(
+        description="Expiration time for access tokens in minutes",
+        default=60,
+    )
+
 
 class ModerationConfig(BaseSettings):
     """
@@ -495,11 +506,16 @@ class DataSetConfig(BaseSettings):
     Configuration for dataset management
     """
 
-    CLEAN_DAY_SETTING: PositiveInt = Field(
-        description="Interval in days for dataset cleanup operations",
+    PLAN_SANDBOX_CLEAN_DAY_SETTING: PositiveInt = Field(
+        description="Interval in days for dataset cleanup operations - plan: sandbox",
         default=30,
     )
 
+    PLAN_PRO_CLEAN_DAY_SETTING: PositiveInt = Field(
+        description="Interval in days for dataset cleanup operations - plan: pro and team",
+        default=7,
+    )
+
     DATASET_OPERATOR_ENABLED: bool = Field(
         description="Enable or disable dataset operator functionality",
         default=False,
@@ -601,6 +617,7 @@ class PositionConfig(BaseSettings):
 class FeatureConfig(
     # place the configs in alphabet order
     AppExecutionConfig,
+    AuthConfig,  # Changed from OAuthConfig to AuthConfig
     BillingConfig,
     CodeExecutionSandboxConfig,
     DataSetConfig,
@@ -615,14 +632,13 @@ class FeatureConfig(
     MailConfig,
     ModelLoadBalanceConfig,
     ModerationConfig,
-    OAuthConfig,
+    PositionConfig,
     RagEtlConfig,
     SecurityConfig,
     ToolConfig,
     UpdateConfig,
     WorkflowConfig,
     WorkspaceConfig,
-    PositionConfig,
     # hosted services config
     HostedServiceConfig,
     CeleryBeatConfig,

api/configs/middleware/__init__.py

@@ -5,13 +5,14 @@ from pydantic import Field, NonNegativeInt, PositiveFloat, PositiveInt, computed
 from pydantic_settings import BaseSettings
 
 from configs.middleware.cache.redis_config import RedisConfig
-from configs.middleware.external.bedrock_config import BedrockConfig
 from configs.middleware.storage.aliyun_oss_storage_config import AliyunOSSStorageConfig
 from configs.middleware.storage.amazon_s3_storage_config import S3StorageConfig
 from configs.middleware.storage.azure_blob_storage_config import AzureBlobStorageConfig
+from configs.middleware.storage.baidu_obs_storage_config import BaiduOBSStorageConfig
 from configs.middleware.storage.google_cloud_storage_config import GoogleCloudStorageConfig
 from configs.middleware.storage.huawei_obs_storage_config import HuaweiCloudOBSStorageConfig
 from configs.middleware.storage.oci_storage_config import OCIStorageConfig
+from configs.middleware.storage.supabase_storage_config import SupabaseStorageConfig
 from configs.middleware.storage.tencent_cos_storage_config import TencentCloudCOSStorageConfig
 from configs.middleware.storage.volcengine_tos_storage_config import VolcengineTOSStorageConfig
 from configs.middleware.vdb.analyticdb_config import AnalyticdbConfig
@@ -27,13 +28,15 @@ from configs.middleware.vdb.qdrant_config import QdrantConfig
 from configs.middleware.vdb.relyt_config import RelytConfig
 from configs.middleware.vdb.tencent_vector_config import TencentVectorDBConfig
 from configs.middleware.vdb.tidb_vector_config import TiDBVectorConfig
+from configs.middleware.vdb.vikingdb_config import VikingDBConfig
 from configs.middleware.vdb.weaviate_config import WeaviateConfig
 
 
 class StorageConfig(BaseSettings):
     STORAGE_TYPE: str = Field(
         description="Type of storage to use."
-        " Options: 'local', 's3', 'azure-blob', 'aliyun-oss', 'google-storage'. Default is 'local'.",
+        " Options: 'local', 's3', 'aliyun-oss', 'azure-blob', 'baidu-obs', 'google-storage', 'huawei-obs', "
+        "'oci-storage', 'tencent-cos', 'volcengine-tos', 'supabase'. Default is 'local'.",
         default="local",
     )
 
@@ -191,6 +194,22 @@ class CeleryConfig(DatabaseConfig):
         return self.CELERY_BROKER_URL.startswith("rediss://") if self.CELERY_BROKER_URL else False
 
 
+class InternalTestConfig(BaseSettings):
+    """
+    Configuration settings for Internal Test
+    """
+
+    AWS_SECRET_ACCESS_KEY: Optional[str] = Field(
+        description="Internal test AWS secret access key",
+        default=None,
+    )
+
+    AWS_ACCESS_KEY_ID: Optional[str] = Field(
+        description="Internal test AWS access key ID",
+        default=None,
+    )
+
+
 class MiddlewareConfig(
     # place the configs in alphabet order
     CeleryConfig,
@@ -201,12 +220,14 @@ class MiddlewareConfig(
     StorageConfig,
     AliyunOSSStorageConfig,
     AzureBlobStorageConfig,
+    BaiduOBSStorageConfig,
     GoogleCloudStorageConfig,
-    TencentCloudCOSStorageConfig,
     HuaweiCloudOBSStorageConfig,
-    VolcengineTOSStorageConfig,
-    S3StorageConfig,
     OCIStorageConfig,
+    S3StorageConfig,
+    SupabaseStorageConfig,
+    TencentCloudCOSStorageConfig,
+    VolcengineTOSStorageConfig,
     # configs of vdb and vdb providers
     VectorStoreConfig,
     AnalyticdbConfig,
@@ -223,6 +244,7 @@ class MiddlewareConfig(
     TiDBVectorConfig,
     WeaviateConfig,
     ElasticsearchConfig,
-    BedrockConfig,
+    InternalTestConfig,
+    VikingDBConfig,
 ):
     pass

api/configs/middleware/external/bedrock_config.py

@@ -1,20 +0,0 @@
-from typing import Optional
-
-from pydantic import Field
-from pydantic_settings import BaseSettings
-
-
-class BedrockConfig(BaseSettings):
-    """
-    bedrock configs
-    """
-
-    AWS_SECRET_ACCESS_KEY: Optional[str] = Field(
-        description="AWS secret access key",
-        default=None,
-    )
-
-    AWS_ACCESS_KEY_ID: Optional[str] = Field(
-        description="AWS secret access id",
-        default=None,
-    )

api/configs/middleware/storage/baidu_obs_storage_config.py

@@ -0,0 +1,29 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class BaiduOBSStorageConfig(BaseModel):
+    """
+    Configuration settings for Baidu Object Storage Service (OBS)
+    """
+
+    BAIDU_OBS_BUCKET_NAME: Optional[str] = Field(
+        description="Name of the Baidu OBS bucket to store and retrieve objects (e.g., 'my-obs-bucket')",
+        default=None,
+    )
+
+    BAIDU_OBS_ACCESS_KEY: Optional[str] = Field(
+        description="Access Key ID for authenticating with Baidu OBS",
+        default=None,
+    )
+
+    BAIDU_OBS_SECRET_KEY: Optional[str] = Field(
+        description="Secret Access Key for authenticating with Baidu OBS",
+        default=None,
+    )
+
+    BAIDU_OBS_ENDPOINT: Optional[str] = Field(
+        description="URL of the Baidu OSS endpoint for your chosen region (e.g., 'https://.bj.bcebos.com')",
+        default=None,
+    )

api/configs/middleware/storage/supabase_storage_config.py

@@ -0,0 +1,24 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class SupabaseStorageConfig(BaseModel):
+    """
+    Configuration settings for Supabase Object Storage Service
+    """
+
+    SUPABASE_BUCKET_NAME: Optional[str] = Field(
+        description="Name of the Supabase bucket to store and retrieve objects (e.g., 'dify-bucket')",
+        default=None,
+    )
+
+    SUPABASE_API_KEY: Optional[str] = Field(
+        description="API KEY for authenticating with Supabase",
+        default=None,
+    )
+
+    SUPABASE_URL: Optional[str] = Field(
+        description="URL of the Supabase",
+        default=None,
+    )

api/configs/middleware/vdb/baidu_vector_config.py

@@ -0,0 +1,45 @@
+from typing import Optional
+
+from pydantic import Field, NonNegativeInt, PositiveInt
+from pydantic_settings import BaseSettings
+
+
+class BaiduVectorDBConfig(BaseSettings):
+    """
+    Configuration settings for Baidu Vector Database
+    """
+
+    BAIDU_VECTOR_DB_ENDPOINT: Optional[str] = Field(
+        description="URL of the Baidu Vector Database service (e.g., 'http://vdb.bj.baidubce.com')",
+        default=None,
+    )
+
+    BAIDU_VECTOR_DB_CONNECTION_TIMEOUT_MS: PositiveInt = Field(
+        description="Timeout in milliseconds for Baidu Vector Database operations (default is 30000 milliseconds)",
+        default=30000,
+    )
+
+    BAIDU_VECTOR_DB_ACCOUNT: Optional[str] = Field(
+        description="Account for authenticating with the Baidu Vector Database",
+        default=None,
+    )
+
+    BAIDU_VECTOR_DB_API_KEY: Optional[str] = Field(
+        description="API key for authenticating with the Baidu Vector Database service",
+        default=None,
+    )
+
+    BAIDU_VECTOR_DB_DATABASE: Optional[str] = Field(
+        description="Name of the specific Baidu Vector Database to connect to",
+        default=None,
+    )
+
+    BAIDU_VECTOR_DB_SHARD: PositiveInt = Field(
+        description="Number of shards for the Baidu Vector Database (default is 1)",
+        default=1,
+    )
+
+    BAIDU_VECTOR_DB_REPLICAS: NonNegativeInt = Field(
+        description="Number of replicas for the Baidu Vector Database (default is 3)",
+        default=3,
+    )

api/configs/middleware/vdb/oracle_config.py

@@ -14,7 +14,7 @@ class OracleConfig(BaseSettings):
         default=None,
     )
 
-    ORACLE_PORT: Optional[PositiveInt] = Field(
+    ORACLE_PORT: PositiveInt = Field(
         description="Port number on which the Oracle database server is listening (default is 1521)",
         default=1521,
     )

api/configs/middleware/vdb/pgvector_config.py

@@ -14,7 +14,7 @@ class PGVectorConfig(BaseSettings):
         default=None,
     )
 
-    PGVECTOR_PORT: Optional[PositiveInt] = Field(
+    PGVECTOR_PORT: PositiveInt = Field(
         description="Port number on which the PostgreSQL server is listening (default is 5433)",
         default=5433,
     )

api/configs/middleware/vdb/pgvectors_config.py

@@ -14,7 +14,7 @@ class PGVectoRSConfig(BaseSettings):
         default=None,
     )
 
-    PGVECTO_RS_PORT: Optional[PositiveInt] = Field(
+    PGVECTO_RS_PORT: PositiveInt = Field(
         description="Port number on which the PostgreSQL server with PGVecto.RS is listening (default is 5431)",
         default=5431,
     )

api/configs/middleware/vdb/vikingdb_config.py

@@ -0,0 +1,49 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class VikingDBConfig(BaseModel):
+    """
+    Configuration for connecting to Volcengine VikingDB.
+    Refer to the following documentation for details on obtaining credentials:
+    https://www.volcengine.com/docs/6291/65568
+    """
+
+    VIKINGDB_ACCESS_KEY: Optional[str] = Field(
+        description="The Access Key provided by Volcengine VikingDB for API authentication."
+        "Refer to the following documentation for details on obtaining credentials:"
+        "https://www.volcengine.com/docs/6291/65568",
+        default=None,
+    )
+
+    VIKINGDB_SECRET_KEY: Optional[str] = Field(
+        description="The Secret Key provided by Volcengine VikingDB for API authentication.",
+        default=None,
+    )
+
+    VIKINGDB_REGION: str = Field(
+        description="The region of the Volcengine VikingDB service.(e.g., 'cn-shanghai', 'cn-beijing').",
+        default="cn-shanghai",
+    )
+
+    VIKINGDB_HOST: str = Field(
+        description="The host of the Volcengine VikingDB service.(e.g., 'api-vikingdb.volces.com', \
+            'api-vikingdb.mlp.cn-shanghai.volces.com')",
+        default="api-vikingdb.mlp.cn-shanghai.volces.com",
+    )
+
+    VIKINGDB_SCHEME: str = Field(
+        description="The scheme of the Volcengine VikingDB service.(e.g., 'http', 'https').",
+        default="http",
+    )
+
+    VIKINGDB_CONNECTION_TIMEOUT: int = Field(
+        description="The connection timeout of the Volcengine VikingDB service.",
+        default=30,
+    )
+
+    VIKINGDB_SOCKET_TIMEOUT: int = Field(
+        description="The socket timeout of the Volcengine VikingDB service.",
+        default=30,
+    )

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.8.3",
+        default="0.9.2",
     )
 
     COMMIT_SHA: str = Field(

api/controllers/console/__init__.py

@@ -45,7 +45,6 @@ from .datasets import (
     external,
     file,
     hit_testing,
-    test_external,
     website,
 )
 

api/controllers/console/app/conversation.py

@@ -188,6 +188,7 @@ class ChatConversationApi(Resource):
                         subquery.c.from_end_user_session_id.ilike(keyword_filter),
                     ),
                 )
+                .group_by(Conversation.id)
             )
 
         account = current_user

api/controllers/console/auth/login.py

@@ -7,7 +7,7 @@ from flask_restful import Resource, reqparse
 import services
 from controllers.console import api
 from controllers.console.setup import setup_required
-from libs.helper import email, get_remote_ip
+from libs.helper import email, extract_remote_ip
 from libs.password import valid_password
 from models.account import Account
 from services.account_service import AccountService, TenantService
@@ -40,17 +40,16 @@ class LoginApi(Resource):
                 "data": "workspace not found, please contact system admin to invite you to join in a workspace",
             }
 
-        token = AccountService.login(account, ip_address=get_remote_ip(request))
+        token_pair = AccountService.login(account=account, ip_address=extract_remote_ip(request))
 
-        return {"result": "success", "data": token}
+        return {"result": "success", "data": token_pair.model_dump()}
 
 
 class LogoutApi(Resource):
     @setup_required
     def get(self):
         account = cast(Account, flask_login.current_user)
-        token = request.headers.get("Authorization", "").split(" ")[1]
-        AccountService.logout(account=account, token=token)
+        AccountService.logout(account=account)
         flask_login.logout_user()
         return {"result": "success"}
 
@@ -106,5 +105,19 @@ class ResetPasswordApi(Resource):
         return {"result": "success"}
 
 
+class RefreshTokenApi(Resource):
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("refresh_token", type=str, required=True, location="json")
+        args = parser.parse_args()
+
+        try:
+            new_token_pair = AccountService.refresh_token(args["refresh_token"])
+            return {"result": "success", "data": new_token_pair.model_dump()}
+        except Exception as e:
+            return {"result": "fail", "data": str(e)}, 401
+
+
 api.add_resource(LoginApi, "/login")
 api.add_resource(LogoutApi, "/logout")
+api.add_resource(RefreshTokenApi, "/refresh-token")

api/controllers/console/auth/oauth.py

@@ -9,7 +9,7 @@ from flask_restful import Resource
 from configs import dify_config
 from constants.languages import languages
 from extensions.ext_database import db
-from libs.helper import get_remote_ip
+from libs.helper import extract_remote_ip
 from libs.oauth import GitHubOAuth, GoogleOAuth, OAuthUserInfo
 from models.account import Account, AccountStatus
 from services.account_service import AccountService, RegisterService, TenantService
@@ -81,9 +81,14 @@ class OAuthCallback(Resource):
 
         TenantService.create_owner_tenant_if_not_exist(account)
 
-        token = AccountService.login(account, ip_address=get_remote_ip(request))
+        token_pair = AccountService.login(
+            account=account,
+            ip_address=extract_remote_ip(request),
+        )
 
-        return redirect(f"{dify_config.CONSOLE_WEB_URL}?console_token={token}")
+        return redirect(
+            f"{dify_config.CONSOLE_WEB_URL}?access_token={token_pair.access_token}&refresh_token={token_pair.refresh_token}"
+        )
 
 
 def _get_account_by_openid_or_email(provider: str, user_info: OAuthUserInfo) -> Optional[Account]:

api/controllers/console/datasets/datasets.py

@@ -613,10 +613,12 @@ class DatasetRetrievalSettingApi(Resource):
             case (
                 VectorType.MILVUS
                 | VectorType.RELYT
-                | VectorType.PGVECTOR
                 | VectorType.TIDB_VECTOR
                 | VectorType.CHROMA
                 | VectorType.TENCENT
+                | VectorType.PGVECTO_RS
+                | VectorType.BAIDU
+                | VectorType.VIKINGDB
             ):
                 return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
             case (
@@ -627,6 +629,7 @@ class DatasetRetrievalSettingApi(Resource):
                 | VectorType.MYSCALE
                 | VectorType.ORACLE
                 | VectorType.ELASTICSEARCH
+                | VectorType.PGVECTOR
             ):
                 return {
                     "retrieval_method": [
@@ -652,6 +655,8 @@ class DatasetRetrievalSettingMockApi(Resource):
                 | VectorType.CHROMA
                 | VectorType.TENCENT
                 | VectorType.PGVECTO_RS
+                | VectorType.BAIDU
+                | VectorType.VIKINGDB
             ):
                 return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
             case (

api/controllers/console/datasets/external.py

@@ -5,7 +5,6 @@ from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
 
 import services
 from controllers.console import api
-from controllers.console.app.error import ProviderNotInitializeError
 from controllers.console.datasets.error import DatasetNameDuplicateError
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
@@ -14,6 +13,7 @@ from libs.login import login_required
 from services.dataset_service import DatasetService
 from services.external_knowledge_service import ExternalDatasetService
 from services.hit_testing_service import HitTestingService
+from services.knowledge_service import ExternalDatasetTestService
 
 
 def _validate_name(name):
@@ -158,48 +158,6 @@ class ExternalApiUseCheckApi(Resource):
         return {"is_using": external_knowledge_api_is_using, "count": count}, 200
 
 
-class ExternalDatasetInitApi(Resource):
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def post(self):
-        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
-            raise Forbidden()
-
-        parser = reqparse.RequestParser()
-        parser.add_argument("external_knowledge_api_id", type=str, required=True, nullable=True, location="json")
-        # parser.add_argument('name', nullable=False, required=True,
-        #                     help='name is required. Name must be between 1 to 100 characters.',
-        #                     type=_validate_name)
-        # parser.add_argument('description', type=str, required=True, nullable=True, location='json')
-        parser.add_argument("data_source", type=dict, required=True, nullable=True, location="json")
-        parser.add_argument("process_parameter", type=dict, required=True, nullable=True, location="json")
-
-        args = parser.parse_args()
-
-        # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
-        if not current_user.is_dataset_editor:
-            raise Forbidden()
-
-        # validate args
-        ExternalDatasetService.document_create_args_validate(
-            current_user.current_tenant_id, args["external_knowledge_api_id"], args["process_parameter"]
-        )
-
-        try:
-            dataset, documents, batch = ExternalDatasetService.init_external_dataset(
-                tenant_id=current_user.current_tenant_id,
-                user_id=current_user.id,
-                args=args,
-            )
-        except Exception as ex:
-            raise ProviderNotInitializeError(ex.description)
-        response = {"dataset": dataset, "documents": documents, "batch": batch}
-
-        return response
-
-
 class ExternalDatasetCreateApi(Resource):
     @setup_required
     @login_required
@@ -275,8 +233,31 @@ class ExternalKnowledgeHitTestingApi(Resource):
             raise InternalServerError(str(e))
 
 
+class BedrockRetrievalApi(Resource):
+    # this api is only for internal testing
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("retrieval_setting", nullable=False, required=True, type=dict, location="json")
+        parser.add_argument(
+            "query",
+            nullable=False,
+            required=True,
+            type=str,
+        )
+        parser.add_argument("knowledge_id", nullable=False, required=True, type=str)
+        args = parser.parse_args()
+
+        # Call the knowledge retrieval service
+        result = ExternalDatasetTestService.knowledge_retrieval(
+            args["retrieval_setting"], args["query"], args["knowledge_id"]
+        )
+        return result, 200
+
+
 api.add_resource(ExternalKnowledgeHitTestingApi, "/datasets/<uuid:dataset_id>/external-hit-testing")
 api.add_resource(ExternalDatasetCreateApi, "/datasets/external")
 api.add_resource(ExternalApiTemplateListApi, "/datasets/external-knowledge-api")
 api.add_resource(ExternalApiTemplateApi, "/datasets/external-knowledge-api/<uuid:external_knowledge_api_id>")
 api.add_resource(ExternalApiUseCheckApi, "/datasets/external-knowledge-api/<uuid:external_knowledge_api_id>/use-check")
+# this api is only for internal test
+api.add_resource(BedrockRetrievalApi, "/test/retrieval")

api/controllers/console/datasets/hit_testing.py

@@ -1,88 +1,24 @@
-import logging
+from flask_restful import Resource
 
-from flask_login import current_user
-from flask_restful import Resource, marshal, reqparse
-from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
-
-import services
 from controllers.console import api
-from controllers.console.app.error import (
-    CompletionRequestError,
-    ProviderModelCurrentlyNotSupportError,
-    ProviderNotInitializeError,
-    ProviderQuotaExceededError,
-)
-from controllers.console.datasets.error import DatasetNotInitializedError
+from controllers.console.datasets.hit_testing_base import DatasetsHitTestingBase
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
-from core.errors.error import (
-    LLMBadRequestError,
-    ModelCurrentlyNotSupportError,
-    ProviderTokenNotInitError,
-    QuotaExceededError,
-)
-from core.model_runtime.errors.invoke import InvokeError
-from fields.hit_testing_fields import hit_testing_record_fields
 from libs.login import login_required
-from services.dataset_service import DatasetService
-from services.hit_testing_service import HitTestingService
 
 
-class HitTestingApi(Resource):
+class HitTestingApi(Resource, DatasetsHitTestingBase):
     @setup_required
     @login_required
     @account_initialization_required
     def post(self, dataset_id):
         dataset_id_str = str(dataset_id)
 
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
+        dataset = self.get_and_validate_dataset(dataset_id_str)
+        args = self.parse_args()
+        self.hit_testing_args_check(args)
 
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        parser = reqparse.RequestParser()
-        parser.add_argument("query", type=str, location="json")
-        parser.add_argument("retrieval_model", type=dict, required=False, location="json")
-        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
-        args = parser.parse_args()
-
-        HitTestingService.hit_testing_args_check(args)
-
-        try:
-            response = HitTestingService.retrieve(
-                dataset=dataset,
-                query=args["query"],
-                account=current_user,
-                retrieval_model=args["retrieval_model"],
-                external_retrieval_model=args["external_retrieval_model"],
-                limit=10,
-            )
-
-            return {"query": response["query"], "records": marshal(response["records"], hit_testing_record_fields)}
-        except services.errors.index.IndexNotInitializedError:
-            raise DatasetNotInitializedError()
-        except ProviderTokenNotInitError as ex:
-            raise ProviderNotInitializeError(ex.description)
-        except QuotaExceededError:
-            raise ProviderQuotaExceededError()
-        except ModelCurrentlyNotSupportError:
-            raise ProviderModelCurrentlyNotSupportError()
-        except LLMBadRequestError:
-            raise ProviderNotInitializeError(
-                "No Embedding Model or Reranking Model available. Please configure a valid provider "
-                "in the Settings -> Model Provider."
-            )
-        except InvokeError as e:
-            raise CompletionRequestError(e.description)
-        except ValueError as e:
-            raise ValueError(str(e))
-        except Exception as e:
-            logging.exception("Hit testing failed.")
-            raise InternalServerError(str(e))
+        return self.perform_hit_testing(dataset, args)
 
 
 api.add_resource(HitTestingApi, "/datasets/<uuid:dataset_id>/hit-testing")

api/controllers/console/datasets/hit_testing_base.py

@@ -0,0 +1,85 @@
+import logging
+
+from flask_login import current_user
+from flask_restful import marshal, reqparse
+from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
+
+import services.dataset_service
+from controllers.console.app.error import (
+    CompletionRequestError,
+    ProviderModelCurrentlyNotSupportError,
+    ProviderNotInitializeError,
+    ProviderQuotaExceededError,
+)
+from controllers.console.datasets.error import DatasetNotInitializedError
+from core.errors.error import (
+    LLMBadRequestError,
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
+from core.model_runtime.errors.invoke import InvokeError
+from fields.hit_testing_fields import hit_testing_record_fields
+from services.dataset_service import DatasetService
+from services.hit_testing_service import HitTestingService
+
+
+class DatasetsHitTestingBase:
+    @staticmethod
+    def get_and_validate_dataset(dataset_id: str):
+        dataset = DatasetService.get_dataset(dataset_id)
+        if dataset is None:
+            raise NotFound("Dataset not found.")
+
+        try:
+            DatasetService.check_dataset_permission(dataset, current_user)
+        except services.errors.account.NoPermissionError as e:
+            raise Forbidden(str(e))
+
+        return dataset
+
+    @staticmethod
+    def hit_testing_args_check(args):
+        HitTestingService.hit_testing_args_check(args)
+
+    @staticmethod
+    def parse_args():
+        parser = reqparse.RequestParser()
+
+        parser.add_argument("query", type=str, location="json")
+        parser.add_argument("retrieval_model", type=dict, required=False, location="json")
+        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
+        return parser.parse_args()
+
+    @staticmethod
+    def perform_hit_testing(dataset, args):
+        try:
+            response = HitTestingService.retrieve(
+                dataset=dataset,
+                query=args["query"],
+                account=current_user,
+                retrieval_model=args["retrieval_model"],
+                external_retrieval_model=args["external_retrieval_model"],
+                limit=10,
+            )
+            return {"query": response["query"], "records": marshal(response["records"], hit_testing_record_fields)}
+        except services.errors.index.IndexNotInitializedError:
+            raise DatasetNotInitializedError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except LLMBadRequestError:
+            raise ProviderNotInitializeError(
+                "No Embedding Model or Reranking Model available. Please configure a valid provider "
+                "in the Settings -> Model Provider."
+            )
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+        except ValueError as e:
+            raise ValueError(str(e))
+        except Exception as e:
+            logging.exception("Hit testing failed.")
+            raise InternalServerError(str(e))

api/controllers/console/datasets/test_external.py

@@ -1,33 +0,0 @@
-from flask_restful import Resource, reqparse
-
-from controllers.console import api
-from controllers.console.setup import setup_required
-from controllers.console.wraps import account_initialization_required
-from libs.login import login_required
-from services.external_knowledge_service import ExternalDatasetService
-
-
-class TestExternalApi(Resource):
-    def post(self):
-        parser = reqparse.RequestParser()
-        parser.add_argument("retrieval_setting", nullable=False, required=True, type=dict, location="json")
-        parser.add_argument(
-            "query",
-            nullable=False,
-            required=True,
-            type=str,
-        )
-        parser.add_argument(
-            "knowledge_id",
-            nullable=False,
-            required=True,
-            type=str,
-        )
-        args = parser.parse_args()
-        result = ExternalDatasetService.test_external_knowledge_retrieval(
-            args["retrieval_setting"], args["query"], args["knowledge_id"]
-        )
-        return result, 200
-
-
-api.add_resource(TestExternalApi, "/retrieval")

api/controllers/console/datasets/website.py

@@ -14,7 +14,9 @@ class WebsiteCrawlApi(Resource):
     @account_initialization_required
     def post(self):
         parser = reqparse.RequestParser()
-        parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, nullable=True, location="json")
+        parser.add_argument(
+            "provider", type=str, choices=["firecrawl", "jinareader"], required=True, nullable=True, location="json"
+        )
         parser.add_argument("url", type=str, required=True, nullable=True, location="json")
         parser.add_argument("options", type=dict, required=True, nullable=True, location="json")
         args = parser.parse_args()
@@ -33,7 +35,7 @@ class WebsiteCrawlStatusApi(Resource):
     @account_initialization_required
     def get(self, job_id: str):
         parser = reqparse.RequestParser()
-        parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, location="args")
+        parser.add_argument("provider", type=str, choices=["firecrawl", "jinareader"], required=True, location="args")
         args = parser.parse_args()
         # get crawl status
         try:

api/controllers/console/setup.py

@@ -4,7 +4,7 @@ from flask import request
 from flask_restful import Resource, reqparse
 
 from configs import dify_config
-from libs.helper import StrLen, email, get_remote_ip
+from libs.helper import StrLen, email, extract_remote_ip
 from libs.password import valid_password
 from models.model import DifySetup
 from services.account_service import RegisterService, TenantService
@@ -46,7 +46,7 @@ class SetupApi(Resource):
 
         # setup
         RegisterService.setup(
-            email=args["email"], name=args["name"], password=args["password"], ip_address=get_remote_ip(request)
+            email=args["email"], name=args["name"], password=args["password"], ip_address=extract_remote_ip(request)
         )
 
         return {"result": "success"}, 201

api/controllers/console/version.py

@@ -38,11 +38,52 @@ class VersionApi(Resource):
             return result
 
         content = json.loads(response.content)
-        result["version"] = content["version"]
-        result["release_date"] = content["releaseDate"]
-        result["release_notes"] = content["releaseNotes"]
-        result["can_auto_update"] = content["canAutoUpdate"]
+        if _has_new_version(latest_version=content["version"], current_version=f"{args.get('current_version')}"):
+            result["version"] = content["version"]
+            result["release_date"] = content["releaseDate"]
+            result["release_notes"] = content["releaseNotes"]
+            result["can_auto_update"] = content["canAutoUpdate"]
         return result
 
 
+def _has_new_version(*, latest_version: str, current_version: str) -> bool:
+    def parse_version(version: str) -> tuple:
+        # Split version into parts and pre-release suffix if any
+        parts = version.split("-")
+        version_parts = parts[0].split(".")
+        pre_release = parts[1] if len(parts) > 1 else None
+
+        # Validate version format
+        if len(version_parts) != 3:
+            raise ValueError(f"Invalid version format: {version}")
+
+        try:
+            # Convert version parts to integers
+            major, minor, patch = map(int, version_parts)
+            return (major, minor, patch, pre_release)
+        except ValueError:
+            raise ValueError(f"Invalid version format: {version}")
+
+    latest = parse_version(latest_version)
+    current = parse_version(current_version)
+
+    # Compare major, minor, and patch versions
+    for latest_part, current_part in zip(latest[:3], current[:3]):
+        if latest_part > current_part:
+            return True
+        elif latest_part < current_part:
+            return False
+
+    # If versions are equal, check pre-release suffixes
+    if latest[3] is None and current[3] is not None:
+        return True
+    elif latest[3] is not None and current[3] is None:
+        return False
+    elif latest[3] is not None and current[3] is not None:
+        # Simple string comparison for pre-release versions
+        return latest[3] > current[3]
+
+    return False
+
+
 api.add_resource(VersionApi, "/version")

api/controllers/console/workspace/model_providers.py

@@ -126,13 +126,12 @@ class ModelProviderIconApi(Resource):
     Get model provider icon
     """
 
-    @setup_required
-    @login_required
-    @account_initialization_required
     def get(self, provider: str, icon_type: str, lang: str):
         model_provider_service = ModelProviderService()
         icon, mimetype = model_provider_service.get_model_provider_icon(
-            provider=provider, icon_type=icon_type, lang=lang
+            provider=provider,
+            icon_type=icon_type,
+            lang=lang,
         )
 
         return send_file(io.BytesIO(icon), mimetype=mimetype)

api/controllers/console/workspace/models.py

@@ -72,8 +72,9 @@ class DefaultModelApi(Resource):
                     provider=model_setting["provider"],
                     model=model_setting["model"],
                 )
-            except Exception:
-                logging.warning(f"{model_setting['model_type']} save error")
+            except Exception as ex:
+                logging.exception(f"{model_setting['model_type']} save error: {ex}")
+                raise ex
 
         return {"result": "success"}
 

api/controllers/files/error.py

@@ -0,0 +1,7 @@
+from libs.exception import BaseHTTPException
+
+
+class UnsupportedFileTypeError(BaseHTTPException):
+    error_code = "unsupported_file_type"
+    description = "File type not allowed."
+    code = 415

api/controllers/files/image_preview.py

@@ -4,7 +4,7 @@ from werkzeug.exceptions import NotFound
 
 import services
 from controllers.files import api
-from libs.exception import BaseHTTPException
+from controllers.files.error import UnsupportedFileTypeError
 from services.account_service import TenantService
 from services.file_service import FileService
 
@@ -50,9 +50,3 @@ class WorkspaceWebappLogoApi(Resource):
 
 api.add_resource(ImagePreviewApi, "/files/<uuid:file_id>/image-preview")
 api.add_resource(WorkspaceWebappLogoApi, "/files/workspaces/<uuid:workspace_id>/webapp-logo")
-
-
-class UnsupportedFileTypeError(BaseHTTPException):
-    error_code = "unsupported_file_type"
-    description = "File type not allowed."
-    code = 415

api/controllers/files/tool_files.py

@@ -3,8 +3,8 @@ from flask_restful import Resource, reqparse
 from werkzeug.exceptions import Forbidden, NotFound
 
 from controllers.files import api
+from controllers.files.error import UnsupportedFileTypeError
 from core.tools.tool_file_manager import ToolFileManager
-from libs.exception import BaseHTTPException
 
 
 class ToolFilePreviewApi(Resource):
@@ -43,9 +43,3 @@ class ToolFilePreviewApi(Resource):
 
 
 api.add_resource(ToolFilePreviewApi, "/files/tools/<uuid:file_id>.<string:extension>")
-
-
-class UnsupportedFileTypeError(BaseHTTPException):
-    error_code = "unsupported_file_type"
-    description = "File type not allowed."
-    code = 415

api/controllers/service_api/__init__.py

@@ -5,7 +5,6 @@ from libs.external_api import ExternalApi
 bp = Blueprint("service_api", __name__, url_prefix="/v1")
 api = ExternalApi(bp)
 
-
 from . import index
 from .app import app, audio, completion, conversation, file, message, workflow
-from .dataset import dataset, document, segment
+from .dataset import dataset, document, hit_testing, segment

api/controllers/service_api/dataset/hit_testing.py

@@ -0,0 +1,17 @@
+from controllers.console.datasets.hit_testing_base import DatasetsHitTestingBase
+from controllers.service_api import api
+from controllers.service_api.wraps import DatasetApiResource
+
+
+class HitTestingApi(DatasetApiResource, DatasetsHitTestingBase):
+    def post(self, tenant_id, dataset_id):
+        dataset_id_str = str(dataset_id)
+
+        dataset = self.get_and_validate_dataset(dataset_id_str)
+        args = self.parse_args()
+        self.hit_testing_args_check(args)
+
+        return self.perform_hit_testing(dataset, args)
+
+
+api.add_resource(HitTestingApi, "/datasets/<uuid:dataset_id>/hit-testing")

api/core/agent/cot_agent_runner.py

@@ -369,7 +369,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
         return message
 
     def _organize_historic_prompt_messages(
-        self, current_session_messages: list[PromptMessage] = None
+        self, current_session_messages: Optional[list[PromptMessage]] = None
     ) -> list[PromptMessage]:
         """
         organize historic prompt messages

api/core/agent/cot_chat_agent_runner.py

@@ -27,7 +27,7 @@ class CotChatAgentRunner(CotAgentRunner):
 
         return SystemPromptMessage(content=system_prompt)
 
-    def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+    def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
         """
         Organize user query
         """

api/core/agent/cot_completion_agent_runner.py

@@ -1,4 +1,5 @@
 import json
+from typing import Optional
 
 from core.agent.cot_agent_runner import CotAgentRunner
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
@@ -21,7 +22,7 @@ class CotCompletionAgentRunner(CotAgentRunner):
 
         return system_prompt
 
-    def _organize_historic_prompt(self, current_session_messages: list[PromptMessage] = None) -> str:
+    def _organize_historic_prompt(self, current_session_messages: Optional[list[PromptMessage]] = None) -> str:
         """
         Organize historic prompt
         """

api/core/agent/fc_agent_runner.py

@@ -2,7 +2,7 @@ import json
 import logging
 from collections.abc import Generator
 from copy import deepcopy
-from typing import Any, Union
+from typing import Any, Optional, Union
 
 from core.agent.base_agent_runner import BaseAgentRunner
 from core.app.apps.base_app_queue_manager import PublishFrom
@@ -370,7 +370,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         return tool_calls
 
     def _init_system_message(
-        self, prompt_template: str, prompt_messages: list[PromptMessage] = None
+        self, prompt_template: str, prompt_messages: Optional[list[PromptMessage]] = None
     ) -> list[PromptMessage]:
         """
         Initialize system message
@@ -385,7 +385,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
 
         return prompt_messages
 
-    def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+    def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
         """
         Organize user query
         """

api/core/agent/output_parser/cot_output_parser.py

@@ -14,7 +14,7 @@ class CotAgentOutputParser:
     ) -> Generator[Union[str, AgentScratchpadUnit.Action], None, None]:
         def parse_action(json_str):
             try:
-                action = json.loads(json_str)
+                action = json.loads(json_str, strict=False)
                 action_name = None
                 action_input = None
 
@@ -62,6 +62,8 @@ class CotAgentOutputParser:
         thought_str = "thought:"
         thought_idx = 0
 
+        last_character = ""
+
         for response in llm_response:
             if response.delta.usage:
                 usage_dict["usage"] = response.delta.usage
@@ -74,35 +76,38 @@ class CotAgentOutputParser:
             while index < len(response):
                 steps = 1
                 delta = response[index : index + steps]
-                last_character = response[index - 1] if index > 0 else ""
+                yield_delta = False
 
                 if delta == "`":
+                    last_character = delta
                     code_block_cache += delta
                     code_block_delimiter_count += 1
                 else:
                     if not in_code_block:
                         if code_block_delimiter_count > 0:
+                            last_character = delta
                             yield code_block_cache
                         code_block_cache = ""
                     else:
+                        last_character = delta
                         code_block_cache += delta
                     code_block_delimiter_count = 0
 
                 if not in_code_block and not in_json:
                     if delta.lower() == action_str[action_idx] and action_idx == 0:
                         if last_character not in {"\n", " ", ""}:
+                            yield_delta = True
+                        else:
+                            last_character = delta
+                            action_cache += delta
+                            action_idx += 1
+                            if action_idx == len(action_str):
+                                action_cache = ""
+                                action_idx = 0
                             index += steps
-                            yield delta
                             continue
-
-                        action_cache += delta
-                        action_idx += 1
-                        if action_idx == len(action_str):
-                            action_cache = ""
-                            action_idx = 0
-                        index += steps
-                        continue
                     elif delta.lower() == action_str[action_idx] and action_idx > 0:
+                        last_character = delta
                         action_cache += delta
                         action_idx += 1
                         if action_idx == len(action_str):
@@ -112,24 +117,25 @@ class CotAgentOutputParser:
                         continue
                     else:
                         if action_cache:
+                            last_character = delta
                             yield action_cache
                             action_cache = ""
                             action_idx = 0
 
                     if delta.lower() == thought_str[thought_idx] and thought_idx == 0:
                         if last_character not in {"\n", " ", ""}:
+                            yield_delta = True
+                        else:
+                            last_character = delta
+                            thought_cache += delta
+                            thought_idx += 1
+                            if thought_idx == len(thought_str):
+                                thought_cache = ""
+                                thought_idx = 0
                             index += steps
-                            yield delta
                             continue
-
-                        thought_cache += delta
-                        thought_idx += 1
-                        if thought_idx == len(thought_str):
-                            thought_cache = ""
-                            thought_idx = 0
-                        index += steps
-                        continue
                     elif delta.lower() == thought_str[thought_idx] and thought_idx > 0:
+                        last_character = delta
                         thought_cache += delta
                         thought_idx += 1
                         if thought_idx == len(thought_str):
@@ -139,12 +145,20 @@ class CotAgentOutputParser:
                         continue
                     else:
                         if thought_cache:
+                            last_character = delta
                             yield thought_cache
                             thought_cache = ""
                             thought_idx = 0
 
+                    if yield_delta:
+                        index += steps
+                        last_character = delta
+                        yield delta
+                        continue
+
                 if code_block_delimiter_count == 3:
                     if in_code_block:
+                        last_character = delta
                         yield from extra_json_from_code_block(code_block_cache)
                         code_block_cache = ""
 
@@ -156,8 +170,10 @@ class CotAgentOutputParser:
                     if delta == "{":
                         json_quote_count += 1
                         in_json = True
+                        last_character = delta
                         json_cache += delta
                     elif delta == "}":
+                        last_character = delta
                         json_cache += delta
                         if json_quote_count > 0:
                             json_quote_count -= 1
@@ -168,16 +184,19 @@ class CotAgentOutputParser:
                                 continue
                     else:
                         if in_json:
+                            last_character = delta
                             json_cache += delta
 
                     if got_json:
                         got_json = False
+                        last_character = delta
                         yield parse_action(json_cache)
                         json_cache = ""
                         json_quote_count = 0
                         in_json = False
 
                 if not in_code_block and not in_json:
+                    last_character = delta
                     yield delta.replace("`", "")
 
                 index += steps

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

@@ -10,6 +10,7 @@ from flask import Flask, current_app
 from pydantic import ValidationError
 
 import contexts
+from constants import UUID_NIL
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
 from core.app.apps.advanced_chat.app_runner import AdvancedChatAppRunner
@@ -113,6 +114,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             # always enable retriever resource in debugger mode
             app_config.additional_features.show_retrieve_source = True
 
+        workflow_run_id = str(uuid.uuid4())
         # init application generate entity
         application_generate_entity = AdvancedChatAppGenerateEntity(
             task_id=str(uuid.uuid4()),
@@ -121,12 +123,13 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,
             extras=extras,
             trace_manager=trace_manager,
+            workflow_run_id=workflow_run_id,
         )
         contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
 

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

@@ -149,6 +149,9 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
                 SystemVariableKey.CONVERSATION_ID: self.conversation.id,
                 SystemVariableKey.USER_ID: user_id,
                 SystemVariableKey.DIALOGUE_COUNT: conversation_dialogue_count,
+                SystemVariableKey.APP_ID: app_config.app_id,
+                SystemVariableKey.WORKFLOW_ID: app_config.workflow_id,
+                SystemVariableKey.WORKFLOW_RUN_ID: self.application_generate_entity.workflow_run_id,
             }
 
             # init variable pool

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

@@ -45,6 +45,7 @@ from core.app.entities.task_entities import (
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
 from core.app.task_pipeline.message_cycle_manage import MessageCycleManage
 from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage
+from core.model_runtime.entities.llm_entities import LLMUsage
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.workflow.enums import SystemVariableKey
@@ -55,6 +56,7 @@ from models.account import Account
 from models.model import Conversation, EndUser, Message
 from models.workflow import (
     Workflow,
+    WorkflowNodeExecution,
     WorkflowRunStatus,
 )
 
@@ -71,6 +73,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
     _workflow: Workflow
     _user: Union[Account, EndUser]
     _workflow_system_variables: dict[SystemVariableKey, Any]
+    _wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
 
     def __init__(
         self,
@@ -107,9 +110,14 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             SystemVariableKey.FILES: application_generate_entity.files,
             SystemVariableKey.CONVERSATION_ID: conversation.id,
             SystemVariableKey.USER_ID: user_id,
+            SystemVariableKey.DIALOGUE_COUNT: conversation.dialogue_count,
+            SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
+            SystemVariableKey.WORKFLOW_ID: workflow.id,
+            SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
         }
 
         self._task_state = WorkflowTaskState()
+        self._wip_workflow_node_executions = {}
 
         self._conversation_name_generate_thread = None
 
@@ -231,7 +239,8 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             except Exception as e:
                 logger.error(e)
                 break
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if tts_publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self,
@@ -504,6 +513,10 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             self._message.total_price = usage.total_price
             self._message.currency = usage.currency
 
+            self._task_state.metadata["usage"] = jsonable_encoder(usage)
+        else:
+            self._task_state.metadata["usage"] = jsonable_encoder(LLMUsage.empty_usage())
+
         db.session.commit()
 
         message_was_created.send(

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

@@ -8,6 +8,7 @@ from typing import Any, Literal, Union, overload
 from flask import Flask, current_app
 from pydantic import ValidationError
 
+from constants import UUID_NIL
 from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfigManager
@@ -127,7 +128,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

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

@@ -8,6 +8,7 @@ from typing import Any, Literal, Union, overload
 from flask import Flask, current_app
 from pydantic import ValidationError
 
+from constants import UUID_NIL
 from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedError, PublishFrom
@@ -128,7 +129,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

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

@@ -99,6 +99,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
         user_id = user.id if isinstance(user, Account) else user.session_id
         trace_manager = TraceQueueManager(app_model.id, user_id)
 
+        workflow_run_id = str(uuid.uuid4())
         # init application generate entity
         application_generate_entity = WorkflowAppGenerateEntity(
             task_id=str(uuid.uuid4()),
@@ -110,6 +111,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             invoke_from=invoke_from,
             call_depth=call_depth,
             trace_manager=trace_manager,
+            workflow_run_id=workflow_run_id,
         )
         contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
 

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

@@ -90,6 +90,9 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
             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_RUN_ID: self.application_generate_entity.workflow_run_id,
             }
 
             variable_pool = VariablePool(

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

@@ -52,6 +52,7 @@ from models.workflow import (
     Workflow,
     WorkflowAppLog,
     WorkflowAppLogCreatedFrom,
+    WorkflowNodeExecution,
     WorkflowRun,
     WorkflowRunStatus,
 )
@@ -69,6 +70,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
     _task_state: WorkflowTaskState
     _application_generate_entity: WorkflowAppGenerateEntity
     _workflow_system_variables: dict[SystemVariableKey, Any]
+    _wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
 
     def __init__(
         self,
@@ -97,9 +99,13 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         self._workflow_system_variables = {
             SystemVariableKey.FILES: application_generate_entity.files,
             SystemVariableKey.USER_ID: user_id,
+            SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
+            SystemVariableKey.WORKFLOW_ID: workflow.id,
+            SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
         }
 
         self._task_state = WorkflowTaskState()
+        self._wip_workflow_node_executions = {}
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -212,7 +218,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             except Exception as e:
                 logger.error(e)
                 break
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if tts_publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self,

api/core/app/entities/app_invoke_entities.py

@@ -2,8 +2,9 @@ from collections.abc import Mapping
 from enum import Enum
 from typing import Any, Optional
 
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_validator
 
+from constants import UUID_NIL
 from core.app.app_config.entities import AppConfig, EasyUIBasedAppConfig, WorkflowUIBasedAppConfig
 from core.entities.provider_configuration import ProviderModelBundle
 from core.file.file_obj import FileVar
@@ -116,13 +117,36 @@ class EasyUIBasedAppGenerateEntity(AppGenerateEntity):
     model_config = ConfigDict(protected_namespaces=())
 
 
-class ChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
+class ConversationAppGenerateEntity(AppGenerateEntity):
+    """
+    Base entity for conversation-based app generation.
+    """
+
+    conversation_id: Optional[str] = None
+    parent_message_id: Optional[str] = Field(
+        default=None,
+        description=(
+            "Starting from v0.9.0, parent_message_id is used to support message regeneration for internal chat API."
+            "For service API, we need to ensure its forward compatibility, "
+            "so passing in the parent_message_id as request arg is not supported for now. "
+            "It needs to be set to UUID_NIL so that the subsequent processing will treat it as legacy messages."
+        ),
+    )
+
+    @field_validator("parent_message_id")
+    @classmethod
+    def validate_parent_message_id(cls, v, info: ValidationInfo):
+        if info.data.get("invoke_from") == InvokeFrom.SERVICE_API and v != UUID_NIL:
+            raise ValueError("parent_message_id should be UUID_NIL for service API")
+        return v
+
+
+class ChatAppGenerateEntity(ConversationAppGenerateEntity, EasyUIBasedAppGenerateEntity):
     """
     Chat Application Generate Entity.
     """
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
+    pass
 
 
 class CompletionAppGenerateEntity(EasyUIBasedAppGenerateEntity):
@@ -133,16 +157,15 @@ class CompletionAppGenerateEntity(EasyUIBasedAppGenerateEntity):
     pass
 
 
-class AgentChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
+class AgentChatAppGenerateEntity(ConversationAppGenerateEntity, EasyUIBasedAppGenerateEntity):
     """
     Agent Chat Application Generate Entity.
     """
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
+    pass
 
 
-class AdvancedChatAppGenerateEntity(AppGenerateEntity):
+class AdvancedChatAppGenerateEntity(ConversationAppGenerateEntity):
     """
     Advanced Chat Application Generate Entity.
     """
@@ -150,8 +173,7 @@ class AdvancedChatAppGenerateEntity(AppGenerateEntity):
     # app config
     app_config: WorkflowUIBasedAppConfig
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
+    workflow_run_id: Optional[str] = None
     query: str
 
     class SingleIterationRunEntity(BaseModel):
@@ -172,6 +194,7 @@ class WorkflowAppGenerateEntity(AppGenerateEntity):
 
     # app config
     app_config: WorkflowUIBasedAppConfig
+    workflow_run_id: Optional[str] = None
 
     class SingleIterationRunEntity(BaseModel):
         """

api/core/app/segments/exc.py

@@ -1,2 +1,2 @@
-class VariableError(Exception):
+class VariableError(ValueError):
     pass

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -248,7 +248,8 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
             else:
                 start_listener_time = time.time()
                 yield MessageAudioStreamResponse(audio=audio.audio, task_id=task_id)
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self, publisher: AppGeneratorTTSPublisher, trace_manager: Optional[TraceQueueManager] = None

api/core/app/task_pipeline/message_cycle_manage.py

@@ -1,8 +1,10 @@
+import logging
 from threading import Thread
 from typing import Optional, Union
 
 from flask import Flask, current_app
 
+from configs import dify_config
 from core.app.entities.app_invoke_entities import (
     AdvancedChatAppGenerateEntity,
     AgentChatAppGenerateEntity,
@@ -82,7 +84,9 @@ class MessageCycleManage:
                 try:
                     name = LLMGenerator.generate_conversation_name(app_model.tenant_id, query)
                     conversation.name = name
-                except:
+                except Exception as e:
+                    if dify_config.DEBUG:
+                        logging.exception(f"generate conversation name failed: {e}")
                     pass
 
                 db.session.merge(conversation)

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -57,6 +57,7 @@ class WorkflowCycleManage:
     _user: Union[Account, EndUser]
     _task_state: WorkflowTaskState
     _workflow_system_variables: dict[SystemVariableKey, Any]
+    _wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
 
     def _handle_workflow_run_start(self) -> WorkflowRun:
         max_sequence = (
@@ -85,6 +86,9 @@ class WorkflowCycleManage:
 
         # init workflow run
         workflow_run = WorkflowRun()
+        workflow_run_id = self._workflow_system_variables[SystemVariableKey.WORKFLOW_RUN_ID]
+        if workflow_run_id:
+            workflow_run.id = workflow_run_id
         workflow_run.tenant_id = self._workflow.tenant_id
         workflow_run.app_id = self._workflow.app_id
         workflow_run.sequence_number = new_sequence_number
@@ -248,6 +252,8 @@ class WorkflowCycleManage:
         db.session.refresh(workflow_node_execution)
         db.session.close()
 
+        self._wip_workflow_node_executions[workflow_node_execution.node_execution_id] = workflow_node_execution
+
         return workflow_node_execution
 
     def _handle_workflow_node_execution_success(self, event: QueueNodeSucceededEvent) -> WorkflowNodeExecution:
@@ -260,20 +266,36 @@ class WorkflowCycleManage:
 
         inputs = WorkflowEntry.handle_special_values(event.inputs)
         outputs = WorkflowEntry.handle_special_values(event.outputs)
+        execution_metadata = (
+            json.dumps(jsonable_encoder(event.execution_metadata)) if event.execution_metadata else None
+        )
+        finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
+        elapsed_time = (finished_at - event.start_at).total_seconds()
+
+        db.session.query(WorkflowNodeExecution).filter(WorkflowNodeExecution.id == workflow_node_execution.id).update(
+            {
+                WorkflowNodeExecution.status: WorkflowNodeExecutionStatus.SUCCEEDED.value,
+                WorkflowNodeExecution.inputs: json.dumps(inputs) if inputs else None,
+                WorkflowNodeExecution.process_data: json.dumps(event.process_data) if event.process_data else None,
+                WorkflowNodeExecution.outputs: json.dumps(outputs) if outputs else None,
+                WorkflowNodeExecution.execution_metadata: execution_metadata,
+                WorkflowNodeExecution.finished_at: finished_at,
+                WorkflowNodeExecution.elapsed_time: elapsed_time,
+            }
+        )
+
+        db.session.commit()
+        db.session.close()
 
         workflow_node_execution.status = WorkflowNodeExecutionStatus.SUCCEEDED.value
         workflow_node_execution.inputs = json.dumps(inputs) if inputs else None
         workflow_node_execution.process_data = json.dumps(event.process_data) if event.process_data else None
         workflow_node_execution.outputs = json.dumps(outputs) if outputs else None
-        workflow_node_execution.execution_metadata = (
-            json.dumps(jsonable_encoder(event.execution_metadata)) if event.execution_metadata else None
-        )
-        workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
-        workflow_node_execution.elapsed_time = (workflow_node_execution.finished_at - event.start_at).total_seconds()
+        workflow_node_execution.execution_metadata = execution_metadata
+        workflow_node_execution.finished_at = finished_at
+        workflow_node_execution.elapsed_time = elapsed_time
 
-        db.session.commit()
-        db.session.refresh(workflow_node_execution)
-        db.session.close()
+        self._wip_workflow_node_executions.pop(workflow_node_execution.node_execution_id)
 
         return workflow_node_execution
 
@@ -287,18 +309,33 @@ class WorkflowCycleManage:
 
         inputs = WorkflowEntry.handle_special_values(event.inputs)
         outputs = WorkflowEntry.handle_special_values(event.outputs)
+        finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
+        elapsed_time = (finished_at - event.start_at).total_seconds()
+
+        db.session.query(WorkflowNodeExecution).filter(WorkflowNodeExecution.id == workflow_node_execution.id).update(
+            {
+                WorkflowNodeExecution.status: WorkflowNodeExecutionStatus.FAILED.value,
+                WorkflowNodeExecution.error: event.error,
+                WorkflowNodeExecution.inputs: json.dumps(inputs) if inputs else None,
+                WorkflowNodeExecution.process_data: json.dumps(event.process_data) if event.process_data else None,
+                WorkflowNodeExecution.outputs: json.dumps(outputs) if outputs else None,
+                WorkflowNodeExecution.finished_at: finished_at,
+                WorkflowNodeExecution.elapsed_time: elapsed_time,
+            }
+        )
+
+        db.session.commit()
+        db.session.close()
 
         workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
         workflow_node_execution.error = event.error
-        workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
         workflow_node_execution.inputs = json.dumps(inputs) if inputs else None
         workflow_node_execution.process_data = json.dumps(event.process_data) if event.process_data else None
         workflow_node_execution.outputs = json.dumps(outputs) if outputs else None
-        workflow_node_execution.elapsed_time = (workflow_node_execution.finished_at - event.start_at).total_seconds()
+        workflow_node_execution.finished_at = finished_at
+        workflow_node_execution.elapsed_time = elapsed_time
 
-        db.session.commit()
-        db.session.refresh(workflow_node_execution)
-        db.session.close()
+        self._wip_workflow_node_executions.pop(workflow_node_execution.node_execution_id)
 
         return workflow_node_execution
 
@@ -675,17 +712,7 @@ class WorkflowCycleManage:
         :param node_execution_id: workflow node execution id
         :return:
         """
-        workflow_node_execution = (
-            db.session.query(WorkflowNodeExecution)
-            .filter(
-                WorkflowNodeExecution.tenant_id == self._application_generate_entity.app_config.tenant_id,
-                WorkflowNodeExecution.app_id == self._application_generate_entity.app_config.app_id,
-                WorkflowNodeExecution.workflow_id == self._workflow.id,
-                WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
-                WorkflowNodeExecution.node_execution_id == node_execution_id,
-            )
-            .first()
-        )
+        workflow_node_execution = self._wip_workflow_node_executions.get(node_execution_id)
 
         if not workflow_node_execution:
             raise Exception(f"Workflow node execution not found: {node_execution_id}")

api/core/callback_handler/agent_tool_callback_handler.py

@@ -1,9 +1,9 @@
-import os
 from collections.abc import Mapping, Sequence
 from typing import Any, Optional, TextIO, Union
 
 from pydantic import BaseModel
 
+from configs import dify_config
 from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.tools.entities.tool_entities import ToolInvokeMessage
@@ -50,7 +50,8 @@ class DifyAgentCallbackHandler(BaseModel):
         tool_inputs: Mapping[str, Any],
     ) -> None:
         """Do nothing."""
-        print_text("\n[on_tool_start] ToolCall:" + tool_name + "\n" + str(tool_inputs) + "\n", color=self.color)
+        if dify_config.DEBUG:
+            print_text("\n[on_tool_start] ToolCall:" + tool_name + "\n" + str(tool_inputs) + "\n", color=self.color)
 
     def on_tool_end(
         self,
@@ -62,11 +63,12 @@ class DifyAgentCallbackHandler(BaseModel):
         trace_manager: Optional[TraceQueueManager] = None,
     ) -> None:
         """If not the final action, print out observation."""
-        print_text("\n[on_tool_end]\n", color=self.color)
-        print_text("Tool: " + tool_name + "\n", color=self.color)
-        print_text("Inputs: " + str(tool_inputs) + "\n", color=self.color)
-        print_text("Outputs: " + str(tool_outputs)[:1000] + "\n", color=self.color)
-        print_text("\n")
+        if dify_config.DEBUG:
+            print_text("\n[on_tool_end]\n", color=self.color)
+            print_text("Tool: " + tool_name + "\n", color=self.color)
+            print_text("Inputs: " + str(tool_inputs) + "\n", color=self.color)
+            print_text("Outputs: " + str(tool_outputs)[:1000] + "\n", color=self.color)
+            print_text("\n")
 
         if trace_manager:
             trace_manager.add_trace_task(
@@ -82,30 +84,33 @@ class DifyAgentCallbackHandler(BaseModel):
 
     def on_tool_error(self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any) -> None:
         """Do nothing."""
-        print_text("\n[on_tool_error] Error: " + str(error) + "\n", color="red")
+        if dify_config.DEBUG:
+            print_text("\n[on_tool_error] Error: " + str(error) + "\n", color="red")
 
     def on_agent_start(self, thought: str) -> None:
         """Run on agent start."""
-        if thought:
-            print_text(
-                "\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\nThought: " + thought + "\n",
-                color=self.color,
-            )
-        else:
-            print_text("\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\n", color=self.color)
+        if dify_config.DEBUG:
+            if thought:
+                print_text(
+                    "\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\nThought: " + thought + "\n",
+                    color=self.color,
+                )
+            else:
+                print_text("\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\n", color=self.color)
 
     def on_agent_finish(self, color: Optional[str] = None, **kwargs: Any) -> None:
         """Run on agent end."""
-        print_text("\n[on_agent_finish]\n Loop: " + str(self.current_loop) + "\n", color=self.color)
+        if dify_config.DEBUG:
+            print_text("\n[on_agent_finish]\n Loop: " + str(self.current_loop) + "\n", color=self.color)
 
         self.current_loop += 1
 
     @property
     def ignore_agent(self) -> bool:
         """Whether to ignore agent callbacks."""
-        return not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != "true"
+        return not dify_config.DEBUG
 
     @property
     def ignore_chat_model(self) -> bool:
         """Whether to ignore chat model callbacks."""
-        return not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != "true"
+        return not dify_config.DEBUG

api/core/callback_handler/index_tool_callback_handler.py

@@ -44,7 +44,6 @@ class DatasetIndexToolCallbackHandler:
                 DocumentSegment.index_node_id == document.metadata["doc_id"]
             )
 
-            # if 'dataset_id' in document.metadata:
             if "dataset_id" in document.metadata:
                 query = query.filter(DocumentSegment.dataset_id == document.metadata["dataset_id"])
 

api/core/entities/provider_configuration.py

@@ -119,7 +119,7 @@ class ProviderConfiguration(BaseModel):
                         credentials = model_configuration.credentials
                         break
 
-            if self.custom_configuration.provider:
+            if not credentials and self.custom_configuration.provider:
                 credentials = self.custom_configuration.provider.credentials
 
             return credentials

api/core/file/message_file_parser.py

@@ -198,16 +198,34 @@ class MessageFileParser:
                     if "amazonaws.com" not in parsed_url.netloc:
                         return False
                     query_params = parse_qs(parsed_url.query)
-                    required_params = ["Signature", "Expires"]
-                    for param in required_params:
-                        if param not in query_params:
+
+                    def check_presign_v2(query_params):
+                        required_params = ["Signature", "Expires"]
+                        for param in required_params:
+                            if param not in query_params:
+                                return False
+                        if not query_params["Expires"][0].isdigit():
                             return False
-                    if not query_params["Expires"][0].isdigit():
-                        return False
-                    signature = query_params["Signature"][0]
-                    if not re.match(r"^[A-Za-z0-9+/]+={0,2}$", signature):
-                        return False
-                    return True
+                        signature = query_params["Signature"][0]
+                        if not re.match(r"^[A-Za-z0-9+/]+={0,2}$", signature):
+                            return False
+
+                        return True
+
+                    def check_presign_v4(query_params):
+                        required_params = ["X-Amz-Signature", "X-Amz-Expires"]
+                        for param in required_params:
+                            if param not in query_params:
+                                return False
+                        if not query_params["X-Amz-Expires"][0].isdigit():
+                            return False
+                        signature = query_params["X-Amz-Signature"][0]
+                        if not re.match(r"^[A-Za-z0-9+/]+={0,2}$", signature):
+                            return False
+
+                        return True
+
+                    return check_presign_v4(query_params) or check_presign_v2(query_params)
                 except Exception:
                     return False
 

api/core/indexing_runner.py

@@ -211,9 +211,9 @@ class IndexingRunner:
         tenant_id: str,
         extract_settings: list[ExtractSetting],
         tmp_processing_rule: dict,
-        doc_form: str = None,
+        doc_form: Optional[str] = None,
         doc_language: str = "English",
-        dataset_id: str = None,
+        dataset_id: Optional[str] = None,
         indexing_technique: str = "economy",
     ) -> dict:
         """

api/core/memory/token_buffer_memory.py

@@ -58,7 +58,11 @@ class TokenBufferMemory:
         # instead of all messages from the conversation, we only need to extract messages
         # that belong to the thread of last message
         thread_messages = extract_thread_messages(messages)
-        thread_messages.pop(0)
+
+        # for newly created message, its answer is temporarily empty, we don't need to add it to memory
+        if thread_messages and not thread_messages[0].answer:
+            thread_messages.pop(0)
+
         messages = list(reversed(thread_messages))
 
         message_file_parser = MessageFileParser(tenant_id=app_record.tenant_id, app_id=app_record.id)

api/core/model_manager.py

@@ -3,7 +3,7 @@ import os
 from collections.abc import Callable, Generator, Sequence
 from typing import IO, Optional, Union, cast
 
-from core.embedding.embedding_constant import EmbeddingInputType
+from core.entities.embedding_type import EmbeddingInputType
 from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
 from core.entities.provider_entities import ModelLoadBalancingConfiguration
 from core.errors.error import ProviderTokenNotInitError

api/core/model_runtime/callbacks/base_callback.py

@@ -1,3 +1,4 @@
+from abc import ABC, abstractmethod
 from typing import Optional
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
@@ -13,7 +14,7 @@ _TEXT_COLOR_MAPPING = {
 }
 
 
-class Callback:
+class Callback(ABC):
     """
     Base class for callbacks.
     Only for LLM.
@@ -21,6 +22,7 @@ class Callback:
 
     raise_error: bool = False
 
+    @abstractmethod
     def on_before_invoke(
         self,
         llm_instance: AIModel,
@@ -48,6 +50,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_new_chunk(
         self,
         llm_instance: AIModel,
@@ -77,6 +80,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_after_invoke(
         self,
         llm_instance: AIModel,
@@ -106,6 +110,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_invoke_error(
         self,
         llm_instance: AIModel,

api/core/model_runtime/docs/en_US/customizable_model_scale_out.md

@@ -0,0 +1,310 @@
+## Custom Integration of Pre-defined Models
+
+### Introduction
+
+After completing the vendors integration, the next step is to connect the vendor's models. To illustrate the entire connection process, we will use Xinference as an example to demonstrate a complete vendor integration.
+
+It is important to note that for custom models, each model connection requires a complete vendor credential.
+
+Unlike pre-defined models, a custom vendor integration always includes the following two parameters, which do not need to be defined in the vendor YAML file.
+
+![](images/index/image-3.png)
+
+As mentioned earlier, vendors do not need to implement validate_provider_credential. The runtime will automatically call the corresponding model layer's validate_credentials to validate the credentials based on the model type and name selected by the user.
+
+### Writing the Vendor YAML
+
+First, we need to identify the types of models supported by the vendor we are integrating.
+
+Currently supported model types are as follows:
+
+- `llm` Text Generation Models
+
+- `text_embedding` Text Embedding Models
+
+- `rerank` Rerank Models
+
+- `speech2text` Speech-to-Text
+
+- `tts` Text-to-Speech
+
+- `moderation` Moderation
+
+Xinference supports LLM, Text Embedding, and Rerank. So we will start by writing xinference.yaml.
+
+```yaml
+provider: xinference #Define the vendor identifier
+label: # Vendor display name, supports both en_US (English) and zh_Hans (Simplified Chinese). If zh_Hans is not set, it will use en_US by default.
+  en_US: Xorbits Inference
+icon_small: # Small icon, refer to other vendors' icons stored in the _assets directory within the vendor implementation directory; follows the same language policy as the label
+  en_US: icon_s_en.svg
+icon_large: # Large icon
+  en_US: icon_l_en.svg
+help: # Help information
+  title:
+    en_US: How to deploy Xinference
+    zh_Hans: 如何部署 Xinference
+  url:
+    en_US: https://github.com/xorbitsai/inference
+supported_model_types: # Supported model types. Xinference supports LLM, Text Embedding, and Rerank
+- llm
+- text-embedding
+- rerank
+configurate_methods: # Since Xinference is a locally deployed vendor with no predefined models, users need to deploy whatever models they need according to Xinference documentation. Thus, it only supports custom models.
+- customizable-model
+provider_credential_schema:
+  credential_form_schemas:
+```
+
+
+Then, we need to determine what credentials are required to define a model in Xinference.
+
+- Since it supports three different types of models, we need to specify the model_type to denote the model type. Here is how we can define it:
+
+```yaml
+provider_credential_schema:
+  credential_form_schemas:
+  - variable: model_type
+    type: select
+    label:
+      en_US: Model type
+      zh_Hans: 模型类型
+    required: true
+    options:
+    - value: text-generation
+      label:
+        en_US: Language Model
+        zh_Hans: 语言模型
+    - value: embeddings
+      label:
+        en_US: Text Embedding
+    - value: reranking
+      label:
+        en_US: Rerank
+```
+
+- Next, each model has its own model_name, so we need to define that here:
+
+```yaml
+  - variable: model_name
+    type: text-input
+    label:
+      en_US: Model name
+      zh_Hans: 模型名称
+    required: true
+    placeholder:
+      zh_Hans: 填写模型名称
+      en_US: Input model name
+```
+
+- Specify the Xinference local deployment address:
+
+```yaml
+  - variable: server_url
+    label:
+      zh_Hans: 服务器URL
+      en_US: Server url
+    type: text-input
+    required: true
+    placeholder:
+      zh_Hans: 在此输入Xinference的服务器地址，如 https://example.com/xxx
+      en_US: Enter the url of your Xinference, for example https://example.com/xxx
+```
+
+- Each model has a unique model_uid, so we also need to define that here:
+
+```yaml
+  - variable: model_uid
+    label:
+      zh_Hans: 模型UID
+      en_US: Model uid
+    type: text-input
+    required: true
+    placeholder:
+      zh_Hans: 在此输入您的Model UID
+      en_US: Enter the model uid
+```
+
+Now, we have completed the basic definition of the vendor.
+
+### Writing the Model Code
+
+Next, let's take the `llm` type as an example and write `xinference.llm.llm.py`.
+
+In `llm.py`, create a Xinference LLM class, we name it `XinferenceAILargeLanguageModel` (this can be arbitrary), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
+
+- LLM Invocation
+
+Implement the core method for LLM invocation, supporting both stream and synchronous responses.
+
+```python
+def _invoke(self, model: str, credentials: dict,
+            prompt_messages: list[PromptMessage], model_parameters: dict,
+            tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
+            stream: bool = True, user: Optional[str] = None) \
+        -> Union[LLMResult, Generator]:
+    """
+    Invoke large language model
+    
+    :param model: model name
+	:param credentials: model credentials
+	:param prompt_messages: prompt messages
+	:param model_parameters: model parameters
+	:param tools: tools for tool usage
+	:param stop: stop words
+	:param stream: is the response a stream
+	:param user: unique user id
+	:return: full response or stream response chunk generator result
+	"""
+```
+
+When implementing, ensure to use two functions to return data separately for synchronous and stream responses. This is important because Python treats functions containing the `yield` keyword as generator functions, mandating them to return `Generator` types. Here’s an example (note that the example uses simplified parameters; in real implementation, use the parameter list as defined above):
+
+```python
+def _invoke(self, stream: bool, **kwargs) \
+        -> Union[LLMResult, Generator]:
+    if stream:
+          return self._handle_stream_response(**kwargs)
+    return self._handle_sync_response(**kwargs)
+
+def _handle_stream_response(self, **kwargs) -> Generator:
+    for chunk in response:
+          yield chunk
+def _handle_sync_response(self, **kwargs) -> LLMResult:
+    return LLMResult(**response)
+```
+
+- Pre-compute Input Tokens
+
+If the model does not provide an interface for pre-computing tokens, you can return 0 directly.
+
+```python
+def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],tools: Optional[list[PromptMessageTool]] = None) -> int:
+  """
+  Get number of tokens for given prompt messages
+
+  :param model: model name
+  :param credentials: model credentials
+  :param prompt_messages: prompt messages
+  :param tools: tools for tool usage
+  :return: token count
+  """
+```
+
+
+Sometimes, you might not want to return 0 directly. In such cases, you can use `self._get_num_tokens_by_gpt2(text: str)` to get pre-computed tokens. This method is provided by the `AIModel` base class, and it uses GPT2's Tokenizer for calculation. However, it should be noted that this is only a substitute and may not be fully accurate.
+
+- Model Credentials Validation
+
+Similar to vendor credentials validation, this method validates individual model credentials.
+
+```python
+def validate_credentials(self, model: str, credentials: dict) -> None:
+    """
+    Validate model credentials
+    
+    :param model: model name
+	:param credentials: model credentials
+	:return: None
+	"""
+```
+
+- Model Parameter Schema
+
+Unlike custom types, since the YAML file does not define which parameters a model supports, we need to dynamically generate the model parameter schema.
+
+For instance, Xinference supports `max_tokens`, `temperature`, and `top_p` parameters.
+
+However, some vendors may support different parameters for different models. For example, the `OpenLLM` vendor supports `top_k`, but not all models provided by this vendor support `top_k`. Let's say model A supports `top_k` but model B does not. In such cases, we need to dynamically generate the model parameter schema, as illustrated below:
+
+```python
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+            used to define customizable model schema
+        """
+        rules = [
+            ParameterRule(
+                name='temperature', type=ParameterType.FLOAT,
+                use_template='temperature',
+                label=I18nObject(
+                    zh_Hans='温度', en_US='Temperature'
+                )
+            ),
+            ParameterRule(
+                name='top_p', type=ParameterType.FLOAT,
+                use_template='top_p',
+                label=I18nObject(
+                    zh_Hans='Top P', en_US='Top P'
+                )
+            ),
+            ParameterRule(
+                name='max_tokens', type=ParameterType.INT,
+                use_template='max_tokens',
+                min=1,
+                default=512,
+                label=I18nObject(
+                    zh_Hans='最大生成长度', en_US='Max Tokens'
+                )
+            )
+        ]
+
+        # if model is A, add top_k to rules
+        if model == 'A':
+            rules.append(
+                ParameterRule(
+                    name='top_k', type=ParameterType.INT,
+                    use_template='top_k',
+                    min=1,
+                    default=50,
+                    label=I18nObject(
+                        zh_Hans='Top K', en_US='Top K'
+                    )
+                )
+            )
+
+        """
+            some NOT IMPORTANT code here
+        """
+
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(
+                en_US=model
+            ),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=model_type,
+            model_properties={ 
+                ModelPropertyKey.MODE:  ModelType.LLM,
+            },
+            parameter_rules=rules
+        )
+
+        return entity
+```
+
+- Exception Error Mapping
+
+When a model invocation error occurs, it should be mapped to the runtime's specified `InvokeError` type, enabling Dify to handle different errors appropriately.
+
+Runtime Errors:
+
+- `InvokeConnectionError` Connection error during invocation
+- `InvokeServerUnavailableError` Service provider unavailable
+- `InvokeRateLimitError` Rate limit reached
+- `InvokeAuthorizationError` Authorization failure
+- `InvokeBadRequestError` Invalid request parameters
+
+```python
+  @property
+  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+      """
+      Map model invoke error to unified error
+      The key is the error type thrown to the caller
+      The value is the error type thrown by the model,
+      which needs to be converted into a unified error type for the caller.
+  
+      :return: Invoke error mapping
+      """
+```
+
+For interface method details, see: [Interfaces](./interfaces.md). For specific implementations, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/predefined_model_scale_out.md

@@ -0,0 +1,173 @@
+## Predefined Model Integration
+
+After completing the vendor integration, the next step is to integrate the models from the vendor.
+
+First, we need to determine the type of model to be integrated and create the corresponding model type `module` under the respective vendor's directory.
+
+Currently supported model types are:
+
+- `llm` Text Generation Model
+- `text_embedding` Text Embedding Model
+- `rerank` Rerank Model
+- `speech2text` Speech-to-Text
+- `tts` Text-to-Speech
+- `moderation` Moderation
+
+Continuing with `Anthropic` as an example, `Anthropic` only supports LLM, so create a `module` named `llm` under `model_providers.anthropic`.
+
+For predefined models, we first need to create a YAML file named after the model under the `llm` `module`, such as `claude-2.1.yaml`.
+
+### Prepare Model YAML
+
+```yaml
+model: claude-2.1  # Model identifier
+# Display name of the model, which can be set to en_US English or zh_Hans Chinese. If zh_Hans is not set, it will default to en_US.
+# This can also be omitted, in which case the model identifier will be used as the label
+label:
+  en_US: claude-2.1
+model_type: llm  # Model type, claude-2.1 is an LLM
+features:  # Supported features, agent-thought supports Agent reasoning, vision supports image understanding
+- agent-thought
+model_properties:  # Model properties
+  mode: chat  # LLM mode, complete for text completion models, chat for conversation models
+  context_size: 200000  # Maximum context size
+parameter_rules:  # Parameter rules for the model call; only LLM requires this
+- name: temperature  # Parameter variable name
+  # Five default configuration templates are provided: temperature/top_p/max_tokens/presence_penalty/frequency_penalty
+  # The template variable name can be set directly in use_template, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE
+  # Additional configuration parameters will override the default configuration if set
+  use_template: temperature
+- name: top_p
+  use_template: top_p
+- name: top_k
+  label:  # Display name of the parameter
+    zh_Hans: 取样数量
+    en_US: Top k
+  type: int  # Parameter type, supports float/int/string/boolean
+  help:  # Help information, describing the parameter's function
+    zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+    en_US: Only sample from the top K options for each subsequent token.
+  required: false  # Whether the parameter is mandatory; can be omitted
+- name: max_tokens_to_sample
+  use_template: max_tokens
+  default: 4096  # Default value of the parameter
+  min: 1  # Minimum value of the parameter, applicable to float/int only
+  max: 4096  # Maximum value of the parameter, applicable to float/int only
+pricing:  # Pricing information
+  input: '8.00'  # Input unit price, i.e., prompt price
+  output: '24.00'  # Output unit price, i.e., response content price
+  unit: '0.000001'  # Price unit, meaning the above prices are per 100K
+  currency: USD  # Price currency
+```
+
+It is recommended to prepare all model configurations before starting the implementation of the model code.
+
+You can also refer to the YAML configuration information under the corresponding model type directories of other vendors in the `model_providers` directory. For the complete YAML rules, refer to: [Schema](schema.md#aimodelentity).
+
+### Implement the Model Call Code
+
+Next, create a Python file named `llm.py` under the `llm` `module` to write the implementation code.
+
+Create an Anthropic LLM class named `AnthropicLargeLanguageModel` (or any other name), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
+
+- LLM Call
+
+Implement the core method for calling the LLM, supporting both streaming and synchronous responses.
+
+```python
+  def _invoke(self, model: str, credentials: dict,
+              prompt_messages: list[PromptMessage], model_parameters: dict,
+              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
+              stream: bool = True, user: Optional[str] = None) \
+          -> Union[LLMResult, Generator]:
+      """
+      Invoke large language model
+  
+      :param model: model name
+      :param credentials: model credentials
+      :param prompt_messages: prompt messages
+      :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
+      :return: full response or stream response chunk generator result
+      """
+```
+
+Ensure to use two functions for returning data, one for synchronous returns and the other for streaming returns, because Python identifies functions containing the `yield` keyword as generator functions, fixing the return type to `Generator`. Thus, synchronous and streaming returns need to be implemented separately, as shown below (note that the example uses simplified parameters, for actual implementation follow the above parameter list):
+
+```python
+  def _invoke(self, stream: bool, **kwargs) \
+          -> Union[LLMResult, Generator]:
+      if stream:
+            return self._handle_stream_response(**kwargs)
+      return self._handle_sync_response(**kwargs)
+
+  def _handle_stream_response(self, **kwargs) -> Generator:
+      for chunk in response:
+            yield chunk
+  def _handle_sync_response(self, **kwargs) -> LLMResult:
+      return LLMResult(**response)
+```
+
+- Pre-compute Input Tokens
+
+If the model does not provide an interface to precompute tokens, return 0 directly.
+
+```python
+  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
+                     tools: Optional[list[PromptMessageTool]] = None) -> int:
+      """
+      Get number of tokens for given prompt messages
+
+      :param model: model name
+      :param credentials: model credentials
+      :param prompt_messages: prompt messages
+      :param tools: tools for tool calling
+      :return:
+      """
+```
+
+- Validate Model Credentials
+
+Similar to vendor credential validation, but specific to a single model.
+
+```python
+  def validate_credentials(self, model: str, credentials: dict) -> None:
+      """
+      Validate model credentials
+  
+      :param model: model name
+      :param credentials: model credentials
+      :return:
+      """
+```
+
+- Map Invoke Errors
+
+When a model call fails, map it to a specific `InvokeError` type as required by Runtime, allowing Dify to handle different errors accordingly.
+
+Runtime Errors:
+
+- `InvokeConnectionError` Connection error
+
+- `InvokeServerUnavailableError` Service provider unavailable
+- `InvokeRateLimitError` Rate limit reached
+- `InvokeAuthorizationError` Authorization failed
+- `InvokeBadRequestError` Parameter error
+
+```python
+  @property
+  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+      """
+      Map model invoke error to unified error
+      The key is the error type thrown to the caller
+      The value is the error type thrown by the model,
+      which needs to be converted into a unified error type for the caller.
+  
+      :return: Invoke error mapping
+      """
+```
+
+For interface method explanations, see: [Interfaces](./interfaces.md). For detailed implementation, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/provider_scale_out.md

@@ -58,7 +58,7 @@ provider_credential_schema:  # Provider credential rules, as Anthropic only supp
       en_US: Enter your API URL
 ```
 
-You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#Provider).
+You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#provider).
 
 ### Implementing Provider Code
 

api/core/model_runtime/docs/zh_Hans/provider_scale_out.md

@@ -117,7 +117,7 @@ model_credential_schema:
       en_US: Enter your API Base
 ```
 
-也可以参考  `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#Provider)。
+也可以参考  `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#provider)。
 
 #### 实现供应商代码
 

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

@@ -94,7 +94,7 @@ class LargeLanguageModel(AIModel):
         )
 
         try:
-            if "response_format" in model_parameters:
+            if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}:
                 result = self._code_block_mode_wrapper(
                     model=model,
                     credentials=credentials,

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

@@ -4,7 +4,7 @@ from typing import Optional
 
 from pydantic import ConfigDict
 
-from core.embedding.embedding_constant import EmbeddingInputType
+from core.entities.embedding_type import EmbeddingInputType
 from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType
 from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
 from core.model_runtime.model_providers.__base.ai_model import AIModel

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

@@ -1,7 +1,7 @@
 import logging
 import re
 from abc import abstractmethod
-from typing import Optional
+from typing import Any, Optional
 
 from pydantic import ConfigDict
 
@@ -88,7 +88,7 @@ class TTSModel(AIModel):
             else:
                 return [{"name": d["name"], "value": d["mode"]} for d in voices]
 
-    def _get_model_default_voice(self, model: str, credentials: dict) -> any:
+    def _get_model_default_voice(self, model: str, credentials: dict) -> Any:
         """
         Get voice for given tts model
 

api/core/model_runtime/model_providers/_position.yaml

@@ -40,3 +40,4 @@
 - fireworks
 - mixedbread
 - nomic
+- voyage

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

@@ -169,7 +169,7 @@ class AnthropicLargeLanguageModel(LargeLanguageModel):
         stop: Optional[list[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-        callbacks: list[Callback] = None,
+        callbacks: Optional[list[Callback]] = None,
     ) -> Union[LLMResult, Generator]:
         """
         Code block mode wrapper for invoking large language model

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

@@ -1081,8 +1081,97 @@ LLM_BASE_MODELS = [
             ),
         ),
     ),
+    AzureBaseModel(
+        base_model_name="o1-preview",
+        entity=AIModelEntity(
+            model="fake-deployment-name",
+            label=I18nObject(
+                en_US="fake-deployment-name-label",
+            ),
+            model_type=ModelType.LLM,
+            features=[
+                ModelFeature.AGENT_THOUGHT,
+            ],
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={
+                ModelPropertyKey.MODE: LLMMode.CHAT.value,
+                ModelPropertyKey.CONTEXT_SIZE: 128000,
+            },
+            parameter_rules=[
+                ParameterRule(
+                    name="temperature",
+                    **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE],
+                ),
+                ParameterRule(
+                    name="top_p",
+                    **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P],
+                ),
+                ParameterRule(
+                    name="response_format",
+                    label=I18nObject(zh_Hans="回复格式", en_US="response_format"),
+                    type="string",
+                    help=I18nObject(
+                        zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output"
+                    ),
+                    required=False,
+                    options=["text", "json_object"],
+                ),
+                _get_max_tokens(default=512, min_val=1, max_val=32768),
+            ],
+            pricing=PriceConfig(
+                input=15.00,
+                output=60.00,
+                unit=0.000001,
+                currency="USD",
+            ),
+        ),
+    ),
+    AzureBaseModel(
+        base_model_name="o1-mini",
+        entity=AIModelEntity(
+            model="fake-deployment-name",
+            label=I18nObject(
+                en_US="fake-deployment-name-label",
+            ),
+            model_type=ModelType.LLM,
+            features=[
+                ModelFeature.AGENT_THOUGHT,
+            ],
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={
+                ModelPropertyKey.MODE: LLMMode.CHAT.value,
+                ModelPropertyKey.CONTEXT_SIZE: 128000,
+            },
+            parameter_rules=[
+                ParameterRule(
+                    name="temperature",
+                    **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE],
+                ),
+                ParameterRule(
+                    name="top_p",
+                    **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P],
+                ),
+                ParameterRule(
+                    name="response_format",
+                    label=I18nObject(zh_Hans="回复格式", en_US="response_format"),
+                    type="string",
+                    help=I18nObject(
+                        zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output"
+                    ),
+                    required=False,
+                    options=["text", "json_object"],
+                ),
+                _get_max_tokens(default=512, min_val=1, max_val=65536),
+            ],
+            pricing=PriceConfig(
+                input=3.00,
+                output=12.00,
+                unit=0.000001,
+                currency="USD",
+            ),
+        ),
+    ),
 ]
-
 EMBEDDING_BASE_MODELS = [
     AzureBaseModel(
         base_model_name="text-embedding-ada-002",

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

@@ -53,6 +53,9 @@ model_credential_schema:
       type: select
       required: true
       options:
+        - label:
+            en_US: 2024-09-01-preview
+          value: 2024-09-01-preview
         - label:
             en_US: 2024-08-01-preview
           value: 2024-08-01-preview
@@ -120,6 +123,18 @@ model_credential_schema:
           show_on:
             - variable: __model_type
               value: llm
+        - label:
+            en_US: o1-mini
+          value: o1-mini
+          show_on:
+            - variable: __model_type
+              value: llm
+        - label:
+            en_US: o1-preview
+          value: o1-preview
+          show_on:
+            - variable: __model_type
+              value: llm
         - label:
             en_US: gpt-4o-mini
           value: gpt-4o-mini

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

@@ -119,7 +119,15 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         try:
             client = AzureOpenAI(**self._to_credential_kwargs(credentials))
 
-            if ai_model_entity.entity.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value:
+            if model.startswith("o1"):
+                client.chat.completions.create(
+                    messages=[{"role": "user", "content": "ping"}],
+                    model=model,
+                    temperature=1,
+                    max_completion_tokens=20,
+                    stream=False,
+                )
+            elif ai_model_entity.entity.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value:
                 # chat model
                 client.chat.completions.create(
                     messages=[{"role": "user", "content": "ping"}],
@@ -312,10 +320,24 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         if user:
             extra_model_kwargs["user"] = user
 
+        # clear illegal prompt messages
+        prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages)
+
+        block_as_stream = False
+        if model.startswith("o1"):
+            if stream:
+                block_as_stream = True
+                stream = False
+
+                if "stream_options" in extra_model_kwargs:
+                    del extra_model_kwargs["stream_options"]
+
+            if "stop" in extra_model_kwargs:
+                del extra_model_kwargs["stop"]
+
         # chat model
-        messages = [self._convert_prompt_message_to_dict(m) for m in prompt_messages]
         response = client.chat.completions.create(
-            messages=messages,
+            messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages],
             model=model,
             stream=stream,
             **model_parameters,
@@ -325,7 +347,91 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         if stream:
             return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools)
 
-        return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
+        block_result = self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
+
+        if block_as_stream:
+            return self._handle_chat_block_as_stream_response(block_result, prompt_messages, stop)
+
+        return block_result
+
+    def _handle_chat_block_as_stream_response(
+        self,
+        block_result: LLMResult,
+        prompt_messages: list[PromptMessage],
+        stop: Optional[list[str]] = None,
+    ) -> Generator[LLMResultChunk, None, None]:
+        """
+        Handle llm chat response
+
+        :param model: model name
+        :param credentials: credentials
+        :param response: response
+        :param prompt_messages: prompt messages
+        :param tools: tools for tool calling
+        :param stop: stop words
+        :return: llm response chunk generator
+        """
+        text = block_result.message.content
+        text = cast(str, text)
+
+        if stop:
+            text = self.enforce_stop_tokens(text, stop)
+
+        yield LLMResultChunk(
+            model=block_result.model,
+            prompt_messages=prompt_messages,
+            system_fingerprint=block_result.system_fingerprint,
+            delta=LLMResultChunkDelta(
+                index=0,
+                message=AssistantPromptMessage(content=text),
+                finish_reason="stop",
+                usage=block_result.usage,
+            ),
+        )
+
+    def _clear_illegal_prompt_messages(self, model: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
+        """
+        Clear illegal prompt messages for OpenAI API
+
+        :param model: model name
+        :param prompt_messages: prompt messages
+        :return: cleaned prompt messages
+        """
+        checklist = ["gpt-4-turbo", "gpt-4-turbo-2024-04-09"]
+
+        if model in checklist:
+            # count how many user messages are there
+            user_message_count = len([m for m in prompt_messages if isinstance(m, UserPromptMessage)])
+            if user_message_count > 1:
+                for prompt_message in prompt_messages:
+                    if isinstance(prompt_message, UserPromptMessage):
+                        if isinstance(prompt_message.content, list):
+                            prompt_message.content = "\n".join(
+                                [
+                                    item.data
+                                    if item.type == PromptMessageContentType.TEXT
+                                    else "[IMAGE]"
+                                    if item.type == PromptMessageContentType.IMAGE
+                                    else ""
+                                    for item in prompt_message.content
+                                ]
+                            )
+
+        if model.startswith("o1"):
+            system_message_count = len([m for m in prompt_messages if isinstance(m, SystemPromptMessage)])
+            if system_message_count > 0:
+                new_prompt_messages = []
+                for prompt_message in prompt_messages:
+                    if isinstance(prompt_message, SystemPromptMessage):
+                        prompt_message = UserPromptMessage(
+                            content=prompt_message.content,
+                            name=prompt_message.name,
+                        )
+
+                    new_prompt_messages.append(prompt_message)
+                prompt_messages = new_prompt_messages
+
+        return prompt_messages
 
     def _handle_chat_generate_response(
         self,
@@ -560,7 +666,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
             tokens_per_message = 4
             # if there's a name, the role is omitted
             tokens_per_name = -1
-        elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4"):
+        elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4") or model.startswith("o1"):
             tokens_per_message = 3
             tokens_per_name = 1
         else:

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

@@ -7,7 +7,7 @@ import numpy as np
 import tiktoken
 from openai import AzureOpenAI
 
-from core.embedding.embedding_constant import EmbeddingInputType
+from core.entities.embedding_type import EmbeddingInputType
 from core.model_runtime.entities.model_entities import AIModelEntity, PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError

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

@@ -1,6 +1,6 @@
 import concurrent.futures
 import copy
-from typing import Optional
+from typing import Any, Optional
 
 from openai import AzureOpenAI
 
@@ -19,7 +19,7 @@ class AzureOpenAIText2SpeechModel(_CommonAzureOpenAI, TTSModel):
 
     def _invoke(
         self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None
-    ) -> any:
+    ) -> Any:
         """
         _invoke text2speech model
 
@@ -56,7 +56,7 @@ class AzureOpenAIText2SpeechModel(_CommonAzureOpenAI, TTSModel):
         except Exception as ex:
             raise CredentialsValidateFailedError(str(ex))
 
-    def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any:
+    def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> Any:
         """
         _tts_invoke_streaming text2speech model
         :param model: model name

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

@@ -4,7 +4,7 @@ from typing import Optional
 
 from requests import post
 
-from core.embedding.embedding_constant import EmbeddingInputType
+from core.entities.embedding_type import EmbeddingInputType
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.invoke import (

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

@@ -50,34 +50,62 @@ provider_credential_schema:
           label:
             en_US: US East (N. Virginia)
             zh_Hans: 美国东部 (弗吉尼亚北部)
+        - value: us-east-2
+          label:
+            en_US: US East (Ohio)
+            zh_Hans: 美国东部 (弗吉尼亚北部)
         - value: us-west-2
           label:
             en_US: US West (Oregon)
             zh_Hans: 美国西部 (俄勒冈州)
+        - value: ap-south-1
+          label:
+            en_US: Asia Pacific (Mumbai)
+            zh_Hans: 亚太地区（孟买）
         - value: ap-southeast-1
           label:
             en_US: Asia Pacific (Singapore)
             zh_Hans: 亚太地区 (新加坡)
-        - value: ap-northeast-1
-          label:
-            en_US: Asia Pacific (Tokyo)
-            zh_Hans: 亚太地区 (东京)
-        - value: eu-central-1
-          label:
-            en_US: Europe (Frankfurt)
-            zh_Hans: 欧洲 (法兰克福)
-        - value: eu-west-2
-          label:
-            en_US: Eu west London (London)
-            zh_Hans: 欧洲西部 (伦敦)
-        - value: us-gov-west-1
-          label:
-            en_US: AWS GovCloud (US-West)
-            zh_Hans: AWS GovCloud (US-West)
         - value: ap-southeast-2
           label:
             en_US: Asia Pacific (Sydney)
             zh_Hans: 亚太地区 (悉尼)
+        - value: ap-northeast-1
+          label:
+            en_US: Asia Pacific (Tokyo)
+            zh_Hans: 亚太地区 (东京)
+        - value: ap-northeast-2
+          label:
+            en_US: Asia Pacific (Seoul)
+            zh_Hans: 亚太地区（首尔）
+        - value: ca-central-1
+          label:
+            en_US: Canada (Central)
+            zh_Hans: 加拿大（中部）
+        - value: eu-central-1
+          label:
+            en_US: Europe (Frankfurt)
+            zh_Hans: 欧洲 (法兰克福)
+        - value: eu-west-1
+          label:
+            en_US: Europe (Ireland)
+            zh_Hans: 欧洲（爱尔兰）
+        - value: eu-west-2
+          label:
+            en_US: Europe (London)
+            zh_Hans: 欧洲西部 (伦敦)
+        - value: eu-west-3
+          label:
+            en_US: Europe (Paris)
+            zh_Hans: 欧洲（巴黎）
+        - value: sa-east-1
+          label:
+            en_US: South America (São Paulo)
+            zh_Hans: 南美洲（圣保罗）
+        - value: us-gov-west-1
+          label:
+            en_US: AWS GovCloud (US-West)
+            zh_Hans: AWS GovCloud (US-West)
     - variable: model_for_validation
       required: false
       label: