fix: version check

Co-authored-by: zxhlyh <jasonapring2015@outlook.com>

.gitattributes

@@ -1,5 +1,5 @@
 # Ensure that .sh scripts use LF as line separator, even if they are checked out
-# to Windows(NTFS) file-system, by a user of Docker for Windows. 
+# to Windows(NTFS) file-system, by a user of Docker for Window. 
 # These .sh scripts will be run from the Container after `docker compose up -d`.
 # If they appear to be CRLF style, Dash from the Container will fail to execute
 # them.

.github/workflows/api-tests.yml

@@ -4,6 +4,7 @@ on:
   pull_request:
     branches:
       - main
+      - plugins/beta
     paths:
       - api/**
       - docker/**
@@ -26,9 +27,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Setup Poetry and Python ${{ matrix.python-version }}
         uses: ./.github/actions/setup-poetry

.github/workflows/build-push.yml

@@ -5,6 +5,7 @@ on:
     branches:
       - "main"
       - "deploy/dev"
+      - "plugins/beta"
   release:
     types: [published]
 
@@ -79,12 +80,10 @@ jobs:
           cache-to: type=gha,mode=max,scope=${{ matrix.service_name }}
 
       - name: Export digest
-        env:
-          DIGEST: ${{ steps.build.outputs.digest }}
         run: |
           mkdir -p /tmp/digests
-          sanitized_digest=${DIGEST#sha256:}
-          touch "/tmp/digests/${sanitized_digest}"
+          digest="${{ steps.build.outputs.digest }}"
+          touch "/tmp/digests/${digest#sha256:}"
 
       - name: Upload digest
         uses: actions/upload-artifact@v4
@@ -134,15 +133,10 @@ jobs:
 
       - name: Create manifest list and push
         working-directory: /tmp/digests
-        env:
-          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
         run: |
           docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
-            $(printf "$IMAGE_NAME@sha256:%s " *)
+            $(printf '${{ env[matrix.image_name_env] }}@sha256:%s ' *)
 
       - name: Inspect image
-        env:
-          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
-          IMAGE_VERSION: ${{ steps.meta.outputs.version }}
         run: |
-          docker buildx imagetools inspect "$IMAGE_NAME:$IMAGE_VERSION"
+          docker buildx imagetools inspect ${{ env[matrix.image_name_env] }}:${{ steps.meta.outputs.version }}

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

@@ -20,9 +20,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Setup Poetry and Python
         uses: ./.github/actions/setup-poetry

.github/workflows/expose_service_ports.sh

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

.github/workflows/style.yml

@@ -4,6 +4,7 @@ on:
   pull_request:
     branches:
       - main
+      - plugins/beta
 
 concurrency:
   group: style-${{ github.head_ref || github.run_id }}
@@ -17,9 +18,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -62,9 +60,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -92,7 +87,7 @@ jobs:
 
       - name: Web style check
         if: steps.changed-files.outputs.any_changed == 'true'
-        run: pnpm run lint
+        run: yarn run lint
 
   docker-compose-template:
     name: Docker Compose Template
@@ -101,9 +96,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -132,9 +124,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
@@ -152,7 +141,7 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         env:
           BASH_SEVERITY: warning
-          DEFAULT_BRANCH: main
+          DEFAULT_BRANCH: plugins/beta
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           IGNORE_GENERATED_FILES: true
           IGNORE_GITIGNORED_FILES: true

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

@@ -26,9 +26,6 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Use Node.js ${{ matrix.node-version }}
         uses: actions/setup-node@v4
@@ -38,7 +35,7 @@ jobs:
           cache-dependency-path: 'pnpm-lock.yaml'
 
       - name: Install Dependencies
-        run: pnpm install --frozen-lockfile
+        run: pnpm install
 
       - name: Test
         run: pnpm test

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

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

.github/workflows/vdb-tests.yml

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

.github/workflows/web-tests.yml

@@ -22,34 +22,25 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false
 
       - name: Check changed files
         id: changed-files
         uses: tj-actions/changed-files@v45
         with:
           files: web/**
-      # to run pnpm, should install package canvas, but it always install failed on amd64 under ubuntu-latest
-      # - name: Install pnpm
-      #   uses: pnpm/action-setup@v4
-      #   with:
-      #     version: 10
-      #     run_install: false
 
-      # - name: Setup Node.js
-      #   uses: actions/setup-node@v4
-      #   if: steps.changed-files.outputs.any_changed == 'true'
-      #   with:
-      #     node-version: 20
-      #     cache: pnpm
-      #     cache-dependency-path: ./web/package.json
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        if: steps.changed-files.outputs.any_changed == 'true'
+        with:
+          node-version: 20
+          cache: pnpm
+          cache-dependency-path: ./web/package.json
 
-      # - name: Install dependencies
-      #   if: steps.changed-files.outputs.any_changed == 'true'
-      #   run: pnpm install --frozen-lockfile
+      - name: Install dependencies
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: pnpm install --frozen-lockfile
 
-      # - name: Run tests
-      #   if: steps.changed-files.outputs.any_changed == 'true'
-      #   run: pnpm test
+      - name: Run tests
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: pnpm test

.gitignore

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

CONTRIBUTING.md

@@ -73,7 +73,7 @@ Dify requires the following dependencies to build, make sure they're installed o
 * [Docker](https://www.docker.com/)
 * [Docker Compose](https://docs.docker.com/compose/install/)
 * [Node.js v18.x (LTS)](http://nodejs.org)
-* [pnpm](https://pnpm.io/)
+* [npm](https://www.npmjs.com/) version 8.x.x or [Yarn](https://yarnpkg.com/)
 * [Python](https://www.python.org/) version 3.11.x or 3.12.x
 
 ### 4. Installations

CONTRIBUTING_CN.md

@@ -70,7 +70,7 @@ Dify 依赖以下工具和库：
 - [Docker](https://www.docker.com/)
 - [Docker Compose](https://docs.docker.com/compose/install/)
 - [Node.js v18.x (LTS)](http://nodejs.org)
-- [pnpm](https://pnpm.io/)
+- [npm](https://www.npmjs.com/) version 8.x.x or [Yarn](https://yarnpkg.com/)
 - [Python](https://www.python.org/) version 3.11.x or 3.12.x
 
 ### 4. 安装

CONTRIBUTING_DE.md

@@ -1,155 +0,0 @@
-# MITWIRKEN
-
-So, du möchtest zu Dify beitragen – das ist großartig, wir können es kaum erwarten, zu sehen, was du beisteuern wirst. Als ein Startup mit begrenzter Mitarbeiterzahl und Finanzierung haben wir große Ambitionen, den intuitivsten Workflow zum Aufbau und zur Verwaltung von LLM-Anwendungen zu entwickeln. Jede Unterstützung aus der Community zählt wirklich.
-
-Dieser Leitfaden, ebenso wie Dify selbst, ist ein ständig in Entwicklung befindliches Projekt. Wir schätzen Ihr Verständnis, falls er zeitweise hinter dem tatsächlichen Projekt zurückbleibt, und freuen uns über jegliches Feedback, das uns hilft, ihn zu verbessern.
-
-Bezüglich der Lizenzierung nehmen Sie sich bitte einen Moment Zeit, um unser kurzes [License and Contributor Agreement](./LICENSE) zu lesen. Die Community hält sich außerdem an den [Code of Conduct](https://github.com/langgenius/.github/blob/main/CODE_OF_CONDUCT.md).
-
-## Bevor Sie loslegen
-
-[Finde](https://github.com/langgenius/dify/issues?q=is:issue+is:open) ein bestehendes Issue, oder [öffne](https://github.com/langgenius/dify/issues/new/choose) ein neues. Wir kategorisieren Issues in zwei Typen:
-
-### Feature-Anfragen
-
-* Wenn Sie eine neue Feature-Anfrage stellen, bitten wir Sie zu erklären, was das vorgeschlagene Feature bewirken soll und so viel Kontext wie möglich bereitzustellen. [@perzeusss](https://github.com/perzeuss) hat einen soliden [Feature Request Copilot](https://udify.app/chat/MK2kVSnw1gakVwMX) entwickelt, der Ihnen dabei hilft, Ihre Anforderungen zu formulieren. Probieren Sie ihn gerne aus.
-
-* Wenn Sie eines der bestehenden Issues übernehmen möchten, hinterlassen Sie einfach einen Kommentar darunter, in dem Sie uns dies mitteilen.
-
-  Ein Teammitglied, das in der entsprechenden Richtung arbeitet, wird hinzugezogen. Wenn alles in Ordnung ist, gibt es das Okay, mit der Codierung zu beginnen. Wir bitten Sie, mit der Umsetzung des Features zu warten, damit keine Ihrer Arbeiten verloren gehen sollte unsererseits Änderungen vorgeschlagen werden.
-
-  Je nachdem, in welchen Bereich das vorgeschlagene Feature fällt, können Sie mit verschiedenen Teammitgliedern sprechen. Hier ist eine Übersicht der Bereiche, an denen unsere Teammitglieder derzeit arbeiten:
-
-  | Member                                                       | Scope                                                |
-  | ------------------------------------------------------------ | ---------------------------------------------------- |
-  | [@yeuoly](https://github.com/Yeuoly)                         | Architecting Agents                                  |
-  | [@jyong](https://github.com/JohnJyong)                       | RAG pipeline design                                  |
-  | [@GarfieldDai](https://github.com/GarfieldDai)               | Building workflow orchestrations                     |
-  | [@iamjoel](https://github.com/iamjoel) & [@zxhlyh](https://github.com/zxhlyh) | Making our frontend a breeze to use                  |
-  | [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | Developer experience, points of contact for anything |
-  | [@takatost](https://github.com/takatost)                     | Overall product direction and architecture           |
-
-  Wie wir Prioritäten setzen:
-
-  | Feature Type                                                 | Priority        |
-  | ------------------------------------------------------------ | --------------- |
-  | Funktionen mit hoher Priorität, wie sie von einem Teammitglied gekennzeichnet wurden     | High Priority   |
-  | Beliebte Funktionsanfragen von unserem [Community-Feedback-Board](https://github.com/langgenius/dify/discussions/categories/feedbacks) | Medium Priority |
-  | Nicht-Kernfunktionen und kleinere Verbesserungen                    | Low Priority    |
-  | Wertvoll, aber nicht unmittelbar                                  | Future-Feature  |
-
-### Sonstiges (e.g. bug report, performance optimization, typo correction)
-
-* Fangen Sie sofort an zu programmieren..
-
-  Wie wir Prioritäten setzen:
-
-  | Issue Type                                                   | Priority        |
-  | ------------------------------------------------------------ | --------------- |
-  | Fehler in Kernfunktionen (Anmeldung nicht möglich, Anwendungen funktionieren nicht, Sicherheitslücken) | Critical        |
-  | Nicht-kritische Fehler, Leistungsverbesserungen                     | Medium Priority |
-  | Kleinere Fehlerkorrekturen (Schreibfehler, verwirrende, aber funktionierende Benutzeroberfläche)                | Low Priority    |
-
-## Installieren
-
-Hier sind die Schritte, um Dify für die Entwicklung einzurichten:
-
-### 1. Fork dieses Repository
-
-### 2. Clone das Repo
-
- Klonen Sie das geforkte Repository von Ihrem Terminal aus:
-
-```shell
-git clone git@github.com:<github_username>/dify.git
-```
-
-### 3. Abhängigkeiten prüfen
-
-Dify benötigt die folgenden Abhängigkeiten zum Bauen – stellen Sie sicher, dass sie auf Ihrem System installiert sind:
-
-* [Docker](https://www.docker.com/)
-* [Docker Compose](https://docs.docker.com/compose/install/)
-* [Node.js v18.x (LTS)](http://nodejs.org)
-* [pnpm](https://pnpm.io/)
-* [Python](https://www.python.org/) version 3.11.x or 3.12.x
-
-### 4. Installationen
-
-Dify setzt sich aus einem Backend und einem Frontend zusammen. Wechseln Sie in das Backend-Verzeichnis mit `cd api/` und folgen Sie der [Backend README](api/README.md) zur Installation. Öffnen Sie in einem separaten Terminal das Frontend-Verzeichnis mit `cd web/` und folgen Sie der [Frontend README](web/README.md) zur Installation.
-
-Überprüfen Sie die [Installation FAQ](https://docs.dify.ai/learn-more/faq/install-faq) für eine Liste bekannter Probleme und Schritte zur Fehlerbehebung.
-
-### 5. Besuchen Sie dify in Ihrem Browser
-
-Um Ihre Einrichtung zu validieren, öffnen Sie Ihren Browser und navigieren Sie zu [http://localhost:3000](http://localhost:3000) (Standardwert oder Ihre selbst konfigurierte URL und Port). Sie sollten nun Dify im laufenden Betrieb sehen.
-
-## Entwickeln
-
-Wenn Sie einen Modellanbieter hinzufügen, ist [dieser Leitfaden](https://github.com/langgenius/dify/blob/main/api/core/model_runtime/README.md) für Sie.
-
-Wenn Sie einen Tool-Anbieter für Agent oder Workflow hinzufügen möchten, ist [dieser Leitfaden](./api/core/tools/README.md) für Sie.
-
-Um Ihnen eine schnelle Orientierung zu bieten, wo Ihr Beitrag passt, folgt eine kurze, kommentierte Übersicht des Backends und Frontends von Dify:
-
-### Backend
-
-Dify’s Backend ist in Python geschrieben und nutzt [Flask](https://flask.palletsprojects.com/en/3.0.x/) als Web-Framework. Es verwendet [SQLAlchemy](https://www.sqlalchemy.org/) für ORM und [Celery](https://docs.celeryq.dev/en/stable/getting-started/introduction.html) für Task-Queueing. Die Autorisierungslogik erfolgt über Flask-login.
-
-```text
-[api/]
-├── constants             // Konstante Einstellungen, die in der gesamten Codebasis verwendet werden.
-├── controllers           // API-Routendefinitionen und Logik zur Bearbeitung von Anfragen.
-├── core                  // Orchestrierung von Kernanwendungen, Modellintegrationen und Tools.
-├── docker                // Konfigurationen im Zusammenhang mit Docker und Containerisierung.
-├── events                // Ereignisbehandlung und -verarbeitung
-├── extensions            // Erweiterungen mit Frameworks/Plattformen von Drittanbietern.
-├── fields                // Felddefinitionen für die Serialisierung/Marshalling.
-├── libs                  // Wiederverwendbare Bibliotheken und Hilfsprogramme
-├── migrations            // Skripte für die Datenbankmigration.
-├── models                // Datenbankmodelle und Schemadefinitionen.
-├── services              // Gibt die Geschäftslogik an.
-├── storage               // Speicherung privater Schlüssel.   
-├── tasks                 // Handhabung von asynchronen Aufgaben und Hintergrundaufträgen.
-└── tests
-```
-
-### Frontend
-
-Die Website basiert auf einem [Next.js](https://nextjs.org/)-Boilerplate in TypeScript und verwendet [Tailwind CSS](https://tailwindcss.com/) für das Styling. [React-i18next](https://react.i18next.com/) wird für die Internationalisierung genutzt.
-
-```text
-[web/]
-├── app                   // Layouts, Seiten und Komponenten
-│   ├── (commonLayout)    // gemeinsames Layout für die gesamte Anwendung
-│   ├── (shareLayout)     // Layouts, die speziell für tokenspezifische Sitzungen gemeinsam genutzt werden 
-│   ├── activate          // Seite aufrufen
-│   ├── components        // gemeinsam genutzt von Seiten und Layouts
-│   ├── install           // Seite installieren
-│   ├── signin            // Anmeldeseite
-│   └── styles            // global geteilte Stile
-├── assets                // Statische Vermögenswerte
-├── bin                   // Skripte, die beim Build-Schritt ausgeführt werden
-├── config                // einstellbare Einstellungen und Optionen 
-├── context               // gemeinsame Kontexte, die von verschiedenen Teilen der Anwendung verwendet werden
-├── dictionaries          // Sprachspezifische Übersetzungsdateien 
-├── docker                // Container-Konfigurationen
-├── hooks                 // Wiederverwendbare Haken
-├── i18n                  // Konfiguration der Internationalisierung
-├── models                // beschreibt Datenmodelle und Formen von API-Antworten
-├── public                // Meta-Assets wie Favicon
-├── service               // legt Formen von API-Aktionen fest
-├── test                  
-├── types                 // Beschreibungen von Funktionsparametern und Rückgabewerten
-└── utils                 // Gemeinsame Nutzenfunktionen
-```
-
-## Einreichung Ihrer PR
-
-Am Ende ist es Zeit, einen Pull Request (PR) in unserem Repository zu eröffnen. Für wesentliche Features mergen wir diese zunächst in den `deploy/dev`-Branch zum Testen, bevor sie in den `main`-Branch übernommen werden. Falls Sie auf Probleme wie Merge-Konflikte stoßen oder nicht wissen, wie man einen Pull Request erstellt, schauen Sie sich [GitHub's Pull Request Tutorial](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests) an.
-
-Und das war's! Sobald Ihr PR gemerged wurde, werden Sie als Mitwirkender in unserem [README](https://github.com/langgenius/dify/blob/main/README.md) aufgeführt.
-
-## Hilfe bekommen
-
-Wenn Sie beim Beitragen jemals nicht weiter wissen oder eine brennende Frage haben, richten Sie Ihre Anfrage einfach über das entsprechende GitHub-Issue an uns oder besuchen Sie unseren [Discord](https://discord.gg/8Tpq4AcN9c) für ein kurzes Gespräch.

CONTRIBUTING_JA.md

@@ -73,7 +73,7 @@ Dify を構築するには次の依存関係が必要です。それらがシス
 - [Docker](https://www.docker.com/)
 - [Docker Compose](https://docs.docker.com/compose/install/)
 - [Node.js v18.x (LTS)](http://nodejs.org)
-- [pnpm](https://pnpm.io/)
+- [npm](https://www.npmjs.com/) version 8.x.x or [Yarn](https://yarnpkg.com/)
 - [Python](https://www.python.org/) version 3.11.x or 3.12.x
 
 ### 4. インストール

CONTRIBUTING_VI.md

@@ -72,7 +72,7 @@ Dify yêu cầu các phụ thuộc sau để build, hãy đảm bảo chúng đ
 - [Docker](https://www.docker.com/)
 - [Docker Compose](https://docs.docker.com/compose/install/)
 - [Node.js v18.x (LTS)](http://nodejs.org)
-- [pnpm](https://pnpm.io/)
+- [npm](https://www.npmjs.com/) phiên bản 8.x.x hoặc [Yarn](https://yarnpkg.com/)
 - [Python](https://www.python.org/) phiên bản 3.11.x hoặc 3.12.x
 
 ### 4. Cài đặt

LICENSE

@@ -1,12 +1,12 @@
 # Open Source License
 
-Dify is licensed under a modified version of the Apache License 2.0, with the following additional conditions:
+Dify is licensed under the Apache License 2.0, with the following additional conditions:
 
 1. Dify may be utilized commercially, including as a backend service for other applications or as an application development platform for enterprises. Should the conditions below be met, a commercial license must be obtained from the producer:
 
-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.
+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, 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.
 
@@ -21,4 +21,19 @@ Apart from the specific conditions mentioned above, all other rights and restric
 
 The interactive design of this product is protected by appearance patent.
 
-© 2025 LangGenius, Inc.
+© 2024 LangGenius, Inc.
+
+
+----------
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.

README.md

@@ -49,8 +49,6 @@
   <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>
-  <a href="./README_DE.md"><img alt="README in Deutsch" src="https://img.shields.io/badge/German-d9d9d9"></a>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 
@@ -110,72 +108,6 @@ Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-host
 **7. Backend-as-a-Service**: 
   All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.
 
-## Feature Comparison
-<table style="width: 100%;">
-  <tr>
-    <th align="center">Feature</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">Programming Approach</td>
-    <td align="center">API + App-oriented</td>
-    <td align="center">Python Code</td>
-    <td align="center">App-oriented</td>
-    <td align="center">API-oriented</td>
-  </tr>
-  <tr>
-    <td align="center">Supported LLMs</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">OpenAI-only</td>
-  </tr>
-  <tr>
-    <td align="center">RAG Engine</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Agent</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Workflow</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Observability</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Enterprise Feature (SSO/Access control)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Local Deployment</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>
 
 ## Using Dify
 

README_AR.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 <div style="text-align: right;">
@@ -54,7 +53,8 @@
 
 **1. سير العمل**:  قم ببناء واختبار سير عمل الذكاء الاصطناعي القوي على قماش بصري، مستفيدًا من جميع الميزات التالية وأكثر.
 
-  <https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa>
+  https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
+
 
 **2. الدعم الشامل للنماذج**: تكامل سلس مع مئات من LLMs الخاصة / مفتوحة المصدر من عشرات من موفري التحليل والحلول المستضافة ذاتيًا، مما يغطي GPT و Mistral و Llama3 وأي نماذج متوافقة مع واجهة OpenAI API. يمكن العثور على قائمة كاملة بمزودي النموذج المدعومين [هنا](https://docs.dify.ai/getting-started/readme/model-providers).
 
@@ -69,9 +69,7 @@
 **6. الـ LLMOps**: راقب وتحلل سجلات التطبيق والأداء على مر الزمن. يمكنك تحسين الأوامر والبيانات والنماذج باستمرار استنادًا إلى البيانات الإنتاجية والتعليقات.
 
 **7.الواجهة الخلفية (Backend) كخدمة**: تأتي جميع عروض Dify مع APIs مطابقة، حتى يمكنك دمج Dify بسهولة في منطق أعمالك الخاص.
-
 ## مقارنة الميزات
-
 <table style="width: 100%;">
   <tr>
     <th align="center">الميزة</th>
@@ -138,8 +136,8 @@
   </tr>
 </table>
 
-## استخدام Dify
 
+## استخدام Dify
 - **سحابة </br>**
 نحن نستضيف [خدمة Dify Cloud](https://dify.ai) لأي شخص لتجربتها بدون أي إعدادات. توفر كل قدرات النسخة التي تمت استضافتها ذاتيًا، وتتضمن 200 أمر GPT-4 مجانًا في خطة الصندوق الرملي.
 
@@ -149,19 +147,15 @@
 
 - **مشروع Dify للشركات / المؤسسات</br>**
 نحن نوفر ميزات إضافية مركزة على الشركات. [جدول اجتماع معنا](https://cal.com/guchenhe/30min) أو [أرسل لنا بريدًا إلكترونيًا](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) لمناقشة احتياجات الشركات. </br>
-
 > بالنسبة للشركات الناشئة والشركات الصغيرة التي تستخدم خدمات AWS، تحقق من [Dify Premium على AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) ونشرها في شبكتك الخاصة على AWS VPC بنقرة واحدة. إنها عرض AMI بأسعار معقولة مع خيار إنشاء تطبيقات بشعار وعلامة تجارية مخصصة.
->
 ## البقاء قدمًا
 
 قم بإضافة نجمة إلى Dify على GitHub وتلق تنبيهًا فوريًا بالإصدارات الجديدة.
 
 ![نجمنا](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
-
 ## البداية السريعة
->
 > قبل تثبيت Dify، تأكد من أن جهازك يلبي الحد الأدنى من متطلبات النظام التالية:
->
+> 
 >- معالج >= 2 نواة
 >- ذاكرة وصول عشوائي (RAM) >= 4 جيجابايت
 
@@ -194,26 +188,24 @@ docker compose up -d
 انشر Dify إلى منصة السحابة بنقرة واحدة باستخدام [terraform](https://www.terraform.io/)
 
 ##### Azure Global
-
 - [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)
 
 #### استخدام AWS CDK للنشر
 
 انشر Dify على AWS باستخدام [CDK](https://aws.amazon.com/cdk/)
 
-##### AWS
-
+##### AWS 
 - [AWS CDK بواسطة @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)
 
 ## المساهمة
 
-لأولئك الذين يرغبون في المساهمة، انظر إلى [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) لدينا.
+لأولئك الذين يرغبون في المساهمة، انظر إلى [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) لدينا. 
 في الوقت نفسه، يرجى النظر في دعم Dify عن طريق مشاركته على وسائل التواصل الاجتماعي وفي الفعاليات والمؤتمرات.
 
+
 > نحن نبحث عن مساهمين لمساعدة في ترجمة Dify إلى لغات أخرى غير اللغة الصينية المندرين أو الإنجليزية. إذا كنت مهتمًا بالمساعدة، يرجى الاطلاع على [README للترجمة](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) لمزيد من المعلومات، واترك لنا تعليقًا في قناة `global-users` على [خادم المجتمع على Discord](https://discord.gg/8Tpq4AcN9c).
 
 **المساهمون**
@@ -223,26 +215,26 @@ docker compose up -d
 </a>
 
 ## المجتمع والاتصال
-- [مناقشة Github](https://github.com/langgenius/dify/discussions). الأفضل لـ: مشاركة التعليقات وطرح الأسئلة.
-- [المشكلات على GitHub](https://github.com/langgenius/dify/issues). الأفضل لـ: الأخطاء التي تواجهها في استخدام Dify.AI، واقتراحات الميزات. انظر [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
-- [Discord](https://discord.gg/FngNHpbcY7). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
-- [تويتر](https://twitter.com/dify_ai). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
+* [مناقشة Github](https://github.com/langgenius/dify/discussions). الأفضل لـ: مشاركة التعليقات وطرح الأسئلة.
+* [المشكلات على GitHub](https://github.com/langgenius/dify/issues). الأفضل لـ: الأخطاء التي تواجهها في استخدام Dify.AI، واقتراحات الميزات. انظر [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
+* [Discord](https://discord.gg/FngNHpbcY7). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
+* [تويتر](https://twitter.com/dify_ai). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
 
 ## تاريخ النجمة
 
 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
 
+
 ## الكشف عن الأمان
 
-لحماية خصوصيتك، يرجى تجنب نشر مشكلات الأمان على GitHub. بدلاً من ذلك، أرسل أسئلتك إلى <security@dify.ai> وسنقدم لك إجابة أكثر تفصيلاً.
+لحماية خصوصيتك، يرجى تجنب نشر مشكلات الأمان على GitHub. بدلاً من ذلك، أرسل أسئلتك إلى security@dify.ai وسنقدم لك إجابة أكثر تفصيلاً.
 
 ## الرخصة
 
 هذا المستودع متاح تحت [رخصة البرنامج الحر Dify](LICENSE)، والتي تعتبر بشكل أساسي Apache 2.0 مع بعض القيود الإضافية.
-
 ## الكشف عن الأمان
 
-لحماية خصوصيتك، يرجى تجنب نشر مشكلات الأمان على GitHub. بدلاً من ذلك، أرسل أسئلتك إلى <security@dify.ai> وسنقدم لك إجابة أكثر تفصيلاً.
+لحماية خصوصيتك، يرجى تجنب نشر مشكلات الأمان على GitHub. بدلاً من ذلك، أرسل أسئلتك إلى security@dify.ai وسنقدم لك إجابة أكثر تفصيلاً.
 
 ## الرخصة
 

README_BN.md

@@ -1,258 +0,0 @@
-![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
-
-<p align="center">
-  📌 <a href="https://dify.ai/blog/introducing-dify-workflow-file-upload-a-demo-on-ai-podcast">ডিফাই ওয়ার্কফ্লো ফাইল আপলোড পরিচিতি: গুগল নোটবুক-এলএম পডকাস্ট পুনর্নির্মাণ</a>
-</p>
-
-<p align="center">
-  <a href="https://cloud.dify.ai">ডিফাই ক্লাউড</a> ·
-  <a href="https://docs.dify.ai/getting-started/install-self-hosted">সেল্ফ-হোস্টিং</a> ·
-  <a href="https://docs.dify.ai">ডকুমেন্টেশন</a> ·
-  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">ব্যাবসায়িক অনুসন্ধান</a>
-</p>
-
-<p align="center">
-    <a href="https://dify.ai" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a>
-    <a href="https://dify.ai/pricing" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a>
-    <a href="https://discord.gg/FngNHpbcY7" target="_blank">
-        <img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
-            alt="chat on Discord"></a>
-    <a href="https://reddit.com/r/difyai" target="_blank">  
-        <img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white" 
-            alt="join Reddit"></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 X(Twitter)"></a>
-    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
-        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
-            alt="follow on LinkedIn"></a>
-    <a href="https://hub.docker.com/u/langgenius" target="_blank">
-        <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
-    <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
-        <img alt="Commits last month" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
-    <a href="https://github.com/langgenius/dify/" target="_blank">
-        <img alt="Issues closed" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a>
-    <a href="https://github.com/langgenius/dify/discussions/" target="_blank">
-        <img alt="Discussion posts" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
-</p>
-
-<p align="center">
-  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
-  <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>
-  <a href="./README_DE.md"><img alt="README in Deutsch" src="https://img.shields.io/badge/German-d9d9d9"></a>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
-</p>
-
-ডিফাই একটি ওপেন-সোর্স LLM অ্যাপ ডেভেলপমেন্ট প্ল্যাটফর্ম। এটি ইন্টুইটিভ ইন্টারফেস, এজেন্টিক AI ওয়ার্কফ্লো, RAG পাইপলাইন, এজেন্ট ক্যাপাবিলিটি, মডেল ম্যানেজমেন্ট, মনিটরিং সুবিধা এবং আরও অনেক কিছু একত্রিত করে, যা দ্রুত প্রোটোটাইপ থেকে প্রোডাকশন পর্যন্ত নিয়ে যেতে সহায়তা করে।
-
-## কুইক স্টার্ট
->
->  ডিফাই ইনস্টল করার আগে, নিশ্চিত করুন যে আপনার মেশিন নিম্নলিখিত ন্যূনতম কনফিগারেশনের প্রয়োজনীয়তা পূরন করে :
->
->- সিপিউ >= 2 কোর
->- র‍্যাম >= 4 জিবি
-
-</br>
-
-ডিফাই সার্ভার চালু করার সবচেয়ে সহজ উপায় [docker compose](docker/docker-compose.yaml) মাধ্যমে। নিম্নলিখিত কমান্ডগুলো ব্যবহার করে ডিফাই চালানোর আগে, নিশ্চিত করুন যে আপনার মেশিনে [Docker](https://docs.docker.com/get-docker/) এবং [Docker Compose](https://docs.docker.com/compose/install/) ইনস্টল করা আছে :
-```bash
-cd dify
-cd docker
-cp .env.example .env
-docker compose up -d
-```
-চালানোর পর, আপনি আপনার ব্রাউজারে [http://localhost/install](http://localhost/install)-এ ডিফাই ড্যাশবোর্ডে অ্যাক্সেস করতে পারেন এবং ইনিশিয়ালাইজেশন প্রক্রিয়া শুরু করতে পারেন।
-
-#### সাহায্যের খোঁজে
-
-ডিফাই সেট আপ করতে সমস্যা হলে দয়া করে আমাদের [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) দেখুন। যদি তবুও সমস্যা থেকে থাকে, তাহলে [কমিউনিটি এবং আমাদের](#community--contact)  সাথে যোগাযোগ করুন।
-
-> যদি আপনি ডিফাইতে অবদান রাখতে বা অতিরিক্ত উন্নয়ন করতে চান, আমাদের [সোর্স কোড থেকে ডিপ্লয়মেন্টের গাইড](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code) দেখুন।
-
-## প্রধান ফিচারসমূহ
-
-**১. ওয়ার্কফ্লো**:
-    ভিজ্যুয়াল ক্যানভাসে  AI ওয়ার্কফ্লো তৈরি এবং পরীক্ষা করুন, নিম্নলিখিত সব ফিচার এবং  তার বাইরেও আরও অনেক কিছু ব্যবহার করে।
-
-  <https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa>
-
-**২.  মডেল সাপোর্ট**:
-  GPT, Mistral, Llama3, এবং যেকোনো OpenAI API-সামঞ্জস্যপূর্ণ মডেলসহ, কয়েক ডজন ইনফারেন্স প্রদানকারী এবং সেল্ফ-হোস্টেড সমাধান থেকে শুরু করে প্রোপ্রাইটরি/ওপেন-সোর্স LLM-এর সাথে সহজে ইন্টিগ্রেশন। সমর্থিত মডেল প্রদানকারীদের একটি সম্পূর্ণ তালিকা পাওয়া যাবে [এখানে](https://docs.dify.ai/getting-started/readme/model-providers)।
-
-![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
-
-**3.  প্রম্পট IDE**:
-      প্রম্পট তৈরি, মডেলের পারফরম্যান্স তুলনা এবং চ্যাট-বেজড অ্যাপে টেক্সট-টু-স্পিচের মতো  বৈশিষ্ট্য যুক্ত করার জন্য ইন্টুইটিভ ইন্টারফেস। 
-
-**4. RAG পাইপলাইন**:
-      ডকুমেন্ট ইনজেশন থেকে শুরু করে রিট্রিভ পর্যন্ত সবকিছুই বিস্তৃত RAG ক্যাপাবিলিটির আওতাভুক্ত।  PDF, PPT এবং অন্যান্য সাধারণ ডকুমেন্ট ফর্ম্যাট থেকে টেক্সট এক্সট্রাকশনের জন্য আউট-অফ-বক্স সাপোর্ট। 
-
-**5.  এজেন্ট ক্যাপাবিলিটি**:
-  LLM ফাংশন কলিং বা ReAct উপর ভিত্তি করে এজেন্ট ডিফাইন করতে পারেন এবং এজেন্টের জন্য পূর্ব-নির্মিত বা কাস্টম টুলস যুক্ত করতে পারেন। Dify AI এজেন্টদের জন্য 50+ বিল্ট-ইন টুলস সরবরাহ করে, যেমন Google Search, DALL·E, Stable Diffusion এবং WolframAlpha।
-
-**6.  এলএলএম-অপ্স**:
-      সময়ের সাথে সাথে অ্যাপ্লিকেশন লগ এবং পারফরম্যান্স মনিটর এবং বিশ্লেষণ করুন।  প্রডাকশন ডেটা এবং annotation এর উপর ভিত্তি করে প্রম্পট, ডেটাসেট এবং মডেলগুলিকে ক্রমাগত উন্নত করতে পারেন।
-
-**7. ব্যাকএন্ড-অ্যাজ-এ-সার্ভিস**:
-    ডিফাই-এর সমস্ত অফার সংশ্লিষ্ট API-সহ আছে, যাতে আপনি অনায়াসে ডিফাইকে আপনার নিজস্ব বিজনেস লজিকে ইন্টেগ্রেট করতে পারেন।
-
-## বৈশিষ্ট্য তুলনা
-
-<table style="width: 100%;">
-  <tr>
-    <th align="center">বৈশিষ্ট্য</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">প্রোগ্রামিং পদ্ধতি</td>
-    <td align="center">API + App-oriented</td>
-    <td align="center">Python Code</td>
-    <td align="center">App-oriented</td>
-    <td align="center">API-oriented</td>
-  </tr>
-  <tr>
-    <td align="center">সাপোর্টেড LLMs</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">OpenAI-only</td>
-  </tr>
-  <tr>
-    <td align="center">RAG ইঞ্জিন</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">এজেন্ট</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">ওয়ার্কফ্লো</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">অবজার্ভেবল</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">এন্টারপ্রাইজ ফিচার (SSO/Access control)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">লোকাল ডেপ্লয়মেন্ট</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>
-
-## ডিফাই-এর ব্যবহার 
-
-- **ক্লাউড </br>**
-জিরো সেটাপে ব্যবহার করতে আমাদের [Dify Cloud](https://dify.ai) সার্ভিসটি ব্যবহার করতে পারেন। এখানে সেল্ফহোস্টিং-এর সকল ফিচার ও ক্যাপাবিলিটিসহ স্যান্ডবক্সে ২০০ জিপিটি-৪ কল ফ্রি পাবেন।
-
-- **সেল্ফহোস্টিং ডিফাই কমিউনিটি সংস্করণ</br>**
-সেল্ফহোস্ট করতে এই [স্টার্টার গাইড](#quick-start) ব্যবহার করে দ্রুত আপনার এনভায়রনমেন্টে ডিফাই চালান।
-আরো ইন-ডেপথ রেফারেন্সের জন্য [ডকুমেন্টেশন](https://docs.dify.ai) দেখেন।
-
-- **এন্টারপ্রাইজ / প্রতিষ্ঠানের জন্য Dify</br>**
-আমরা এন্টারপ্রাইজ/প্রতিষ্ঠান-কেন্দ্রিক সেবা প্রদান করে থাকি  । [এই চ্যাটবটের মাধ্যমে আপনার প্রশ্নগুলি আমাদের জন্য লগ করুন।](https://udify.app/chat/22L1zSxg6yW1cWQg) অথবা [আমাদের ইমেল পাঠান](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) আপনার চাহিদা সম্পর্কে আলোচনা করার জন্য। </br>
-
-  > AWS ব্যবহারকারী স্টার্টআপ এবং ছোট ব্যবসার জন্য, [AWS মার্কেটপ্লেসে Dify Premium](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) দেখুন এবং এক-ক্লিকের মাধ্যমে এটি আপনার নিজস্ব AWS VPC-তে ডিপ্লয় করুন। এটি একটি সাশ্রয়ী মূল্যের AMI অফার, যাতে কাস্টম লোগো এবং ব্র্যান্ডিং সহ অ্যাপ তৈরির সুবিধা আছে।
-
-## এগিয়ে থাকুন
-
-GitHub-এ ডিফাইকে স্টার দিয়ে রাখুন এবং নতুন রিলিজের খবর তাৎক্ষণিকভাবে পান।
-
-![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
-
-## Advanced Setup
-
-যদি আপনার কনফিগারেশনটি কাস্টমাইজ করার প্রয়োজন হয়, তাহলে অনুগ্রহ করে আমাদের [.env.example](docker/.env.example) ফাইল দেখুন এবং আপনার `.env` ফাইলে সংশ্লিষ্ট মানগুলি আপডেট করুন। এছাড়াও, আপনার নির্দিষ্ট এনভায়রনমেন্ট এবং প্রয়োজনীয়তার উপর ভিত্তি করে আপনাকে `docker-compose.yaml` ফাইলে সমন্বয় করতে হতে পারে, যেমন ইমেজ ভার্সন পরিবর্তন করা, পোর্ট ম্যাপিং করা, অথবা ভলিউম মাউন্ট করা। 
-যেকোনো পরিবর্তন করার পর, অনুগ্রহ করে `docker-compose up -d` পুনরায় চালান। ভেরিয়েবলের সম্পূর্ণ তালিকা [এখানে] (https://docs.dify.ai/getting-started/install-self-hosted/environments) খুঁজে পেতে পারেন।
-
-যদি আপনি একটি হাইলি এভেইলেবল সেটআপ কনফিগার করতে চান, তাহলে কমিউনিটি  [Helm Charts](https://helm.sh/) এবং YAML ফাইল রয়েছে যা Dify কে Kubernetes-এ ডিপ্লয় করার প্রক্রিয়া বর্ণনা করে।
-
-- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
-- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
-- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
-
-#### টেরাফর্ম ব্যবহার করে ডিপ্লয়
-
-[terraform](https://www.terraform.io/) ব্যবহার করে এক ক্লিকেই ক্লাউড প্ল্যাটফর্মে Dify ডিপ্লয় করুন।
-
-##### অ্যাজুর গ্লোবাল
-
-- [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
-
-##### গুগল ক্লাউড
-
-- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
-
-#### AWS CDK ব্যবহার করে ডিপ্লয়
-
-[CDK](https://aws.amazon.com/cdk/) দিয়ে AWS-এ Dify ডিপ্লয় করুন
-
-##### AWS
-
-- [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)
-
-## Contributing
-
-যারা কোড অবদান রাখতে চান, তাদের জন্য আমাদের [অবদান নির্দেশিকা] দেখুন (https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)।
-একই সাথে, সোশ্যাল মিডিয়া এবং ইভেন্ট এবং কনফারেন্সে এটি শেয়ার করে Dify কে সমর্থন করুন।
-
-> আমরা ম্যান্ডারিন বা ইংরেজি ছাড়া অন্য ভাষায় Dify অনুবাদ করতে সাহায্য করার জন্য অবদানকারীদের খুঁজছি। আপনি যদি সাহায্য করতে আগ্রহী হন, তাহলে আরও তথ্যের জন্য [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) দেখুন এবং আমাদের [ডিসকর্ড কমিউনিটি সার্ভার](https://discord.gg/8Tpq4AcN9c) এর `গ্লোবাল-ইউজারস` চ্যানেলে আমাদের একটি মন্তব্য করুন।
-
-## কমিউনিটি এবং যোগাযোগ
-
-- [Github Discussion](https://github.com/langgenius/dify/discussions) ফিডব্যাক এবং প্রতিক্রিয়া জানানোর মাধ্যম।
-- [GitHub Issues](https://github.com/langgenius/dify/issues). Dify.AI ব্যবহার করে আপনি যেসব বাগের সম্মুখীন হন এবং ফিচার প্রস্তাবনা।  আমাদের [অবদান নির্দেশিকা](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) দেখুন।
-- [Discord](https://discord.gg/FngNHpbcY7) আপনার এপ্লিকেশন শেয়ার এবং কমিউনিটি আড্ডার মাধ্যম। 
-- [X(Twitter)](https://twitter.com/dify_ai) আপনার এপ্লিকেশন শেয়ার এবং কমিউনিটি আড্ডার মাধ্যম। 
-
-**অবদানকারীদের তালিকা**
-
-<a href="https://github.com/langgenius/dify/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=langgenius/dify" />
-</a>
-
-## স্টার হিস্ট্রি
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
-
-## নিরাপত্তা  বিষয়ক
-
-আপনার গোপনীয়তা রক্ষা করতে, অনুগ্রহ করে GitHub-এ নিরাপত্তা সংক্রান্ত সমস্যা পোস্ট করা এড়িয়ে চলুন। পরিবর্তে, আপনার প্রশ্নগুলি <security@dify.ai> ঠিকানায় পাঠান এবং আমরা আপনাকে আরও বিস্তারিত উত্তর প্রদান করব।
-
-## লাইসেন্স
-
-এই রিপোজিটরিটি [ডিফাই ওপেন সোর্স লাইসেন্স](LICENSE) এর অধিনে , যা মূলত অ্যাপাচি ২.০, তবে কিছু অতিরিক্ত বিধিনিষেধ রয়েছে।

README_CN.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </div>
 
 

README_DE.md

@@ -1,259 +0,0 @@
-![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
-
-<p align="center">
-  📌 <a href="https://dify.ai/blog/introducing-dify-workflow-file-upload-a-demo-on-ai-podcast">Einführung in Dify Workflow File Upload: Google NotebookLM Podcast nachbilden</a>
-</p>
-
-<p align="center">
-  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
-  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Selbstgehostetes</a> ·
-  <a href="https://docs.dify.ai">Dokumentation</a> ·
-  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Anfrage an Unternehmen</a>
-</p>
-
-<p align="center">
-    <a href="https://dify.ai" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a>
-    <a href="https://dify.ai/pricing" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a>
-    <a href="https://discord.gg/FngNHpbcY7" target="_blank">
-        <img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
-            alt="chat on Discord"></a>
-    <a href="https://reddit.com/r/difyai" target="_blank">  
-        <img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
-            alt="join Reddit"></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 X(Twitter)"></a>
-    <a href="https://www.linkedin.com/company/langgenius/" target="_blank">
-        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
-            alt="follow on LinkedIn"></a>
-    <a href="https://hub.docker.com/u/langgenius" target="_blank">
-        <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
-    <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
-        <img alt="Commits last month" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
-    <a href="https://github.com/langgenius/dify/" target="_blank">
-        <img alt="Issues closed" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a>
-    <a href="https://github.com/langgenius/dify/discussions/" target="_blank">
-        <img alt="Discussion posts" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
-</p>
-
-<p align="center">
-  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
-  <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>
-  <a href="./README_DE.md"><img alt="README in Deutsch" src="https://img.shields.io/badge/German-d9d9d9"></a>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
-</p>
-
-Dify ist eine Open-Source-Plattform zur Entwicklung von LLM-Anwendungen. Ihre intuitive Benutzeroberfläche vereint agentenbasierte KI-Workflows, RAG-Pipelines, Agentenfunktionen, Modellverwaltung, Überwachungsfunktionen und mehr, sodass Sie schnell von einem Prototyp in die Produktion übergehen können.
-
-## Schnellstart
-> Bevor Sie Dify installieren, stellen Sie sicher, dass Ihr System die folgenden Mindestanforderungen erfüllt:
-> 
->- CPU >= 2 Core
->- RAM >= 4 GiB
-
-</br>
-
-Der einfachste Weg, den Dify-Server zu starten, ist über [docker compose](docker/docker-compose.yaml). Stellen Sie vor dem Ausführen von Dify mit den folgenden Befehlen sicher, dass [Docker](https://docs.docker.com/get-docker/) und [Docker Compose](https://docs.docker.com/compose/install/) auf Ihrem System installiert sind:
-
-```bash
-cd dify
-cd docker
-cp .env.example .env
-docker compose up -d
-```
-
-Nachdem Sie den Server gestartet haben, können Sie über Ihren Browser auf das Dify Dashboard unter [http://localhost/install](http://localhost/install) zugreifen und den Initialisierungsprozess starten.
-
-#### Hilfe suchen
-Bitte beachten Sie unsere [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs), wenn Sie Probleme bei der Einrichtung von Dify haben. Wenden Sie sich an [die Community und uns](#community--contact), falls weiterhin Schwierigkeiten auftreten.
-
-> Wenn Sie zu Dify beitragen oder zusätzliche Entwicklungen durchführen möchten, lesen Sie bitte unseren [Leitfaden zur Bereitstellung aus dem Quellcode](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code).
-
-## Wesentliche Merkmale
-**1. Workflow**: 
-  Erstellen und testen Sie leistungsstarke KI-Workflows auf einer visuellen Oberfläche, wobei Sie alle der folgenden Funktionen und darüber hinaus nutzen können.
-
-
-  https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
-
-
-
-**2. Umfassende Modellunterstützung**: 
-  Nahtlose Integration mit Hunderten von proprietären und Open-Source-LLMs von Dutzenden Inferenzanbietern und selbstgehosteten Lösungen, die GPT, Mistral, Llama3 und alle mit der OpenAI API kompatiblen Modelle abdecken. Eine vollständige Liste der unterstützten Modellanbieter finden Sie [hier](https://docs.dify.ai/getting-started/readme/model-providers).
-
-
-![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
-
-
-**3. Prompt IDE**: 
-  Intuitive Benutzeroberfläche zum Erstellen von Prompts, zum Vergleichen der Modellleistung und zum Hinzufügen zusätzlicher Funktionen wie Text-to-Speech in einer chatbasierten Anwendung.
-
-**4. RAG Pipeline**: 
-  Umfassende RAG-Funktionalitäten, die alles von der Dokumenteneinlesung bis zur -abfrage abdecken, mit sofort einsatzbereiter Unterstützung für die Textextraktion aus PDFs, PPTs und anderen gängigen Dokumentformaten.
-
-**5. Fähigkeiten des Agenten**: 
-  Sie können Agenten basierend auf LLM Function Calling oder ReAct definieren und vorgefertigte oder benutzerdefinierte Tools für den Agenten hinzufügen. Dify stellt über 50 integrierte Tools für KI-Agenten bereit, wie zum Beispiel Google Search, DALL·E, Stable Diffusion und WolframAlpha.
-
-**6. LLMOps**: 
-  Überwachen und analysieren Sie Anwendungsprotokolle und die Leistung im Laufe der Zeit. Sie können kontinuierlich Prompts, Datensätze und Modelle basierend auf Produktionsdaten und Annotationen verbessern.
-
-**7. Backend-as-a-Service**: 
-  Alle Dify-Angebote kommen mit entsprechenden APIs, sodass Sie Dify mühelos in Ihre eigene Geschäftslogik integrieren können.
-
-## Vergleich der Merkmale
-<table style="width: 100%;">
-  <tr>
-    <th align="center">Feature</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">Programming Approach</td>
-    <td align="center">API + App-oriented</td>
-    <td align="center">Python Code</td>
-    <td align="center">App-oriented</td>
-    <td align="center">API-oriented</td>
-  </tr>
-  <tr>
-    <td align="center">Supported LLMs</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">OpenAI-only</td>
-  </tr>
-  <tr>
-    <td align="center">RAG Engine</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Agent</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Workflow</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Observability</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Enterprise Feature (SSO/Access control)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Local Deployment</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>
-
-## Dify verwenden
-
-- **Cloud </br>**
-Wir hosten einen [Dify Cloud](https://dify.ai)-Service, den jeder ohne Einrichtung ausprobieren kann. Er bietet alle Funktionen der selbstgehosteten Version und beinhaltet 200 kostenlose GPT-4-Aufrufe im Sandbox-Plan.
-
-- **Selbstgehostete Dify Community Edition</br>**
-Starten Sie Dify schnell in Ihrer Umgebung mit diesem [Schnellstart-Leitfaden](#quick-start). Nutzen Sie unsere [Dokumentation](https://docs.dify.ai) für weiterführende Informationen und detaillierte Anweisungen.
-
-- **Dify für Unternehmen / Organisationen</br>**
-Wir bieten zusätzliche, unternehmensspezifische Funktionen. [Über diesen Chatbot können Sie uns Ihre Fragen mitteilen](https://udify.app/chat/22L1zSxg6yW1cWQg) oder [senden Sie uns eine E-Mail](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry), um Ihre unternehmerischen Bedürfnisse zu besprechen. </br>
-  > Für Startups und kleine Unternehmen, die AWS nutzen, schauen Sie sich [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) an und stellen Sie es mit nur einem Klick in Ihrer eigenen AWS VPC bereit. Es handelt sich um ein erschwingliches AMI-Angebot mit der Option, Apps mit individuellem Logo und Branding zu erstellen.
-
-
-## Immer einen Schritt voraus
-
-Star Dify auf GitHub und lassen Sie sich sofort über neue Releases benachrichtigen.
-
-![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
-
-
-## Erweiterte Einstellungen
-
-Falls Sie die Konfiguration anpassen müssen, lesen Sie bitte die Kommentare in unserer [.env.example](docker/.env.example)-Datei und aktualisieren Sie die entsprechenden Werte in Ihrer `.env`-Datei. Zusätzlich müssen Sie eventuell Anpassungen an der `docker-compose.yaml`-Datei vornehmen, wie zum Beispiel das Ändern von Image-Versionen, Portzuordnungen oder Volumen-Mounts, je nach Ihrer spezifischen Einsatzumgebung und Ihren Anforderungen. Nachdem Sie Änderungen vorgenommen haben, starten Sie `docker-compose up -d` erneut. Eine vollständige Liste der verfügbaren Umgebungsvariablen finden Sie [hier](https://docs.dify.ai/getting-started/install-self-hosted/environments).
-
-Falls Sie eine hochverfügbare Konfiguration einrichten möchten, gibt es von der Community bereitgestellte [Helm Charts](https://helm.sh/) und YAML-Dateien, die es ermöglichen, Dify auf Kubernetes bereitzustellen.
-
-- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
-- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
-- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
-
-#### Terraform für die Bereitstellung verwenden
-
-Stellen Sie Dify mit nur einem Klick mithilfe von [terraform](https://www.terraform.io/) auf einer Cloud-Plattform bereit.
-
-##### Azure Global
-- [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)
-
-#### Verwendung von AWS CDK für die Bereitstellung
-
-Bereitstellung von Dify auf AWS mit [CDK](https://aws.amazon.com/cdk/)
-
-##### AWS 
-- [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)
-
-## Contributing
-
-Falls Sie Code beitragen möchten, lesen Sie bitte unseren [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). Gleichzeitig bitten wir Sie, Dify zu unterstützen, indem Sie es in den sozialen Medien teilen und auf Veranstaltungen und Konferenzen präsentieren.
-
-
-> Wir suchen Mitwirkende, die dabei helfen, Dify in weitere Sprachen zu übersetzen – außer Mandarin oder Englisch. Wenn Sie Interesse an einer Mitarbeit haben, lesen Sie bitte die [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) für weitere Informationen und hinterlassen Sie einen Kommentar im `global-users`-Kanal unseres [Discord Community Servers](https://discord.gg/8Tpq4AcN9c).
-
-## Gemeinschaft & Kontakt
-
-* [Github Discussion](https://github.com/langgenius/dify/discussions). Am besten geeignet für: den Austausch von Feedback und das Stellen von Fragen.
-* [GitHub Issues](https://github.com/langgenius/dify/issues). Am besten für: Fehler, auf die Sie bei der Verwendung von Dify.AI stoßen, und Funktionsvorschläge. Siehe unseren [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
-* [Discord](https://discord.gg/FngNHpbcY7).  Am besten geeignet für: den Austausch von Bewerbungen und den Austausch mit der Community.
-* [X(Twitter)](https://twitter.com/dify_ai). Am besten geeignet für: den Austausch von Bewerbungen und den Austausch mit der Community.
-
-**Mitwirkende**
-
-<a href="https://github.com/langgenius/dify/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=langgenius/dify" />
-</a>
-
-## Star-Geschichte
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
-
-
-## Offenlegung der Sicherheit
-
-Um Ihre Privatsphäre zu schützen, vermeiden Sie es bitte, Sicherheitsprobleme auf GitHub zu posten. Schicken Sie Ihre Fragen stattdessen an security@dify.ai und wir werden Ihnen eine ausführlichere Antwort geben.
-
-## Lizenz
-
-Dieses Repository steht unter der [Dify Open Source License](LICENSE), die im Wesentlichen Apache 2.0 mit einigen zusätzlichen Einschränkungen ist.
-

README_ES.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 #

README_FR.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 #
@@ -56,7 +55,7 @@
 Dify est une plateforme de développement d'applications LLM open source. Son interface intuitive combine un flux de travail d'IA, un pipeline RAG, des capacités d'agent, une gestion de modèles, des fonctionnalités d'observabilité, et plus encore, vous permettant de passer rapidement du prototype à la production. Voici une liste des fonctionnalités principales:
 </br> </br>
 
-**1. Flux de travail** : 
+**1. Flux de travail**: 
   Construisez et testez des flux de travail d'IA puissants sur un canevas visuel, en utilisant toutes les fonctionnalités suivantes et plus encore.
 
 
@@ -64,25 +63,27 @@ Dify est une plateforme de développement d'applications LLM open source. Son in
 
 
 
-**2. Prise en charge complète des modèles** : 
+**2. Prise en charge complète des modèles**: 
   Intégration transparente avec des centaines de LLM propriétaires / open source provenant de dizaines de fournisseurs d'inférence et de solutions auto-hébergées, couvrant GPT, Mistral, Llama3, et tous les modèles compatibles avec l'API OpenAI. Une liste complète des fournisseurs de modèles pris en charge se trouve [ici](https://docs.dify.ai/getting-started/readme/model-providers).
 
 ![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
 
 
-**3. IDE de prompt** : 
+**3. IDE de prompt**: 
   Interface intuitive pour créer des prompts, comparer les performances des modèles et ajouter des fonctionnalités supplémentaires telles que la synthèse vocale à une application basée sur des chats. 
 
-**4. Pipeline RAG** : 
+**4. Pipeline RAG**: 
   Des capacités RAG étendues qui couvrent tout, de l'ingestion de documents à la récupération, avec un support prêt à l'emploi pour l'extraction de texte à partir de PDF, PPT et autres formats de document courants.
 
-**5. Capacités d'agent** : 
+**5. Capac
+
+ités d'agent**: 
   Vous pouvez définir des agents basés sur l'appel de fonction LLM ou ReAct, et ajouter des outils pré-construits ou personnalisés pour l'agent. Dify fournit plus de 50 outils intégrés pour les agents d'IA, tels que la recherche Google, DALL·E, Stable Diffusion et WolframAlpha.
 
-**6. LLMOps** : 
+**6. LLMOps**: 
   Surveillez et analysez les journaux d'application et les performances au fil du temps. Vous pouvez continuellement améliorer les prompts, les ensembles de données et les modèles en fonction des données de production et des annotations.
 
-**7. Backend-as-a-Service** : 
+**7. Backend-as-a-Service**: 
   Toutes les offres de Dify sont accompagnées d'API correspondantes, vous permettant d'intégrer facilement Dify dans votre propre logique métier.
 
 

README_JA.md

@@ -15,7 +15,7 @@
     <a href="https://discord.gg/FngNHpbcY7" target="_blank">
         <img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
             alt="Discordでチャット"></a>
-    <a href="https://reddit.com/r/difyai" target="_blank">
+    <a href="https://reddit.com/r/difyai" target="_blank">  
         <img src="https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white"
             alt="Reddit"></a>
     <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 #
@@ -57,7 +56,7 @@
 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ォームです。直感的なインターフェイスには、AIワークフロー、RAGパイプライン、エージェント機能、モデル管理、観測機能などが組み合わさっており、プロトタイプから生産まで迅速に進めることができます。以下の機能が含まれます：
 </br> </br>
 
-**1. ワークフロー**:
+**1. ワークフロー**: 
   強力なAIワークフローをビジュアルキャンバス上で構築し、テストできます。すべての機能、および以下の機能を使用できます。
 
 
@@ -65,25 +64,25 @@ 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
 
 
 
-**2. 総合的なモデルサポート**:
+**2. 総合的なモデルサポート**: 
   数百ものプロプライエタリ/オープンソースのLLMと、数十もの推論プロバイダーおよびセルフホスティングソリューションとのシームレスな統合を提供します。GPT、Mistral、Llama3、OpenAI APIと互換性のあるすべてのモデルを統合されています。サポートされているモデルプロバイダーの完全なリストは[こちら](https://docs.dify.ai/getting-started/readme/model-providers)をご覧ください。
 
 ![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
 
 
-**3. プロンプトIDE**:
+**3. プロンプトIDE**: 
   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**:
+**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ポートも提供します。
 
-**5. エージェント機能**:
+**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。
 
-**6. LLMOps**:
+**6. LLMOps**: 
   アプリケーションのログやパフォーマンスを監視と分析し、生産のデータと注釈に基づいて、プロンプト、データセット、モデルを継続的に改善できます。
 
-**7. Backend-as-a-Service**:
+**7. Backend-as-a-Service**: 
   すべての機能はAPIを提供されており、Difyを自分のビジネスロジックに簡単に統合できます。
 
 
@@ -165,7 +164,7 @@ 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
 
 - **企業/組織向けのDify</br>**
 企業中心の機能を提供しています。[メールを送信](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)して企業のニーズについて相談してください。 </br>
-  > AWSを使用しているスタートアップ企業や中小企業の場合は、[AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)のDify Premiumをチェックして、ワンクリックで自分のAWS VPCにデプロイできます。さらに、手頃な価格のAMIオファリングとして、ロゴやブランディングをカスタマイズしてアプリケーションを作成するオプションがあります。
+  > AWSを使用しているスタートアップ企業や中小企業の場合は、[AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)のDify Premiumをチェックして、ワンクリックで自分のAWS VPCにデプロイできます。さらに、手頃な価格のAMIオファリングどして、ロゴやブランディングをカスタマイズしてアプリケーションを作成するオプションがあります。
 
 
 ## 最新の情報を入手
@@ -178,7 +177,7 @@ GitHub上でDifyにスターを付けることで、Difyに関する新しいニ
 
 ## クイックスタート
 > Difyをインストールする前に、お使いのマシンが以下の最小システム要件を満たしていることを確認してください：
->
+> 
 >- CPU >= 2コア
 >- RAM >= 4GB
 
@@ -220,7 +219,7 @@ docker compose up -d
 
 [CDK](https://aws.amazon.com/cdk/) を使用して、DifyをAWSにデプロイします
 
-##### AWS
+##### AWS 
 - [@KevinZhaoによるAWS CDK](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)
 
 ## 貢献

README_KL.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 #
@@ -88,7 +87,9 @@ Dify is an open-source LLM app development platform. Its intuitive interface com
 
 ## Feature Comparison
 <table style="width: 100%;">
-  <tr>
+  <tr
+
+>
     <th align="center">Feature</th>
     <th align="center">Dify.AI</th>
     <th align="center">LangChain</th>

README_KR.md

@@ -45,7 +45,6 @@
   <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>
-    <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 

README_PT.md

@@ -50,7 +50,6 @@
   <a href="./README_TR.md"><img alt="README em Turco" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
   <a href="./README_VI.md"><img alt="README em Vietnamita" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
   <a href="./README_PT.md"><img alt="README em Português - BR" src="https://img.shields.io/badge/Portugu%C3%AAs-BR?style=flat&label=BR&color=d9d9d9"></a>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 Dify é uma plataforma de desenvolvimento de aplicativos LLM de código aberto. Sua interface intuitiva combina workflow de IA, pipeline RAG, capacidades de agente, gerenciamento de modelos, recursos de observabilidade e muito mais, permitindo que você vá rapidamente do protótipo à produção. Aqui está uma lista das principais funcionalidades:

README_SI.md

@@ -47,7 +47,6 @@
   <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>
   <a href="./README_SI.md"><img alt="README Slovenščina" src="https://img.shields.io/badge/Sloven%C5%A1%C4%8Dina-d9d9d9"></a>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 
@@ -107,73 +106,6 @@ Prosimo, glejte naša pogosta vprašanja [FAQ](https://docs.dify.ai/getting-star
 **7. Backend-as-a-Service**: 
   AVse ponudbe Difyja so opremljene z ustreznimi API-ji, tako da lahko Dify brez težav integrirate v svojo poslovno logiko.
 
-## Primerjava Funkcij
-
-<table style="width: 100%;">
-  <tr>
-    <th align="center">Funkcija</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">Programski pristop</td>
-    <td align="center">API + usmerjeno v aplikacije</td>
-    <td align="center">Python koda</td>
-    <td align="center">Usmerjeno v aplikacije</td>
-    <td align="center">Usmerjeno v API</td>
-  </tr>
-  <tr>
-    <td align="center">Podprti LLM-ji</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Samo OpenAI</td>
-  </tr>
-  <tr>
-    <td align="center">RAG pogon</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Agent</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Potek dela</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Spremljanje</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Funkcija za podjetja (SSO/nadzor dostopa)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Lokalna namestitev</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>
 
 ## Uporaba Dify
 
@@ -255,4 +187,4 @@ Zaradi zaščite vaše zasebnosti se izogibajte objavljanju varnostnih vprašanj
 
 ## Licenca
 
-To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.
+To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.

README_TR.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 

README_VI.md

@@ -45,7 +45,6 @@
   <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>
-  <a href="./README_BN.md"><img alt="README in বাংলা" src="https://img.shields.io/badge/বাংলা-d9d9d9"></a>
 </p>
 
 

api/.env.example

@@ -427,6 +427,7 @@ PLUGIN_DAEMON_URL=http://127.0.0.1:5002
 PLUGIN_REMOTE_INSTALL_PORT=5003
 PLUGIN_REMOTE_INSTALL_HOST=localhost
 PLUGIN_MAX_PACKAGE_SIZE=15728640
+INNER_API_KEY=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1
 INNER_API_KEY_FOR_PLUGIN=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1
 
 # Marketplace configuration

api/.ruff.toml

@@ -7,7 +7,7 @@ line-length = 120
 quote-style = "double"
 
 [lint]
-preview = false
+preview = true
 select = [
     "B", # flake8-bugbear rules
     "C4", # flake8-comprehensions
@@ -18,6 +18,7 @@ select = [
     "N", # pep8-naming
     "PT", # flake8-pytest-style rules
     "PLC0208", # iteration-over-set
+    "PLC2801", # unnecessary-dunder-call
     "PLC0414", # useless-import-alias
     "PLE0604", # invalid-all-object
     "PLE0605", # invalid-all-format
@@ -45,6 +46,7 @@ ignore = [
     "E712", # true-false-comparison
     "E721", # type-comparison
     "E722", # bare-except
+    "E731", # lambda-assignment
     "F821", # undefined-name
     "F841", # unused-variable
     "FURB113", # repeated-append

api/Dockerfile

@@ -55,11 +55,9 @@ RUN \
         # basic environment
         curl nodejs libgmp-dev libmpfr-dev libmpc-dev \
         # For Security
-        expat libldap-2.5-0 perl libsqlite3-0 zlib1g \
+        # expat libldap-2.5-0 perl libsqlite3-0 zlib1g \
         # install a chinese font to support the use of tools like matplotlib
         fonts-noto-cjk \
-        # install a package to improve the accuracy of guessing mime type and file extension
-        media-types \
         # install libmagic to support the use of python-magic guess MIMETYPE
         libmagic1 \
     && apt-get autoremove -y \

api/README.md

@@ -37,13 +37,7 @@
 
 4. Create environment.
 
-   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. First, you need to add the poetry shell plugin, if you don't have it already, in order to run in a virtual environment. [Note: Poetry shell is no longer a native command so you need to install the poetry plugin beforehand]
-
-   ```bash
-   poetry self add poetry-plugin-shell
-   ```
-   
-   Then, You can execute `poetry shell` to activate the environment.
+   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. You can execute `poetry shell` to activate the environment.
 
 5. Install dependencies
 

api/app_factory.py

@@ -2,7 +2,6 @@ import logging
 import time
 
 from configs import dify_config
-from contexts.wrapper import RecyclableContextVar
 from dify_app import DifyApp
 
 
@@ -17,12 +16,6 @@ def create_flask_app_with_configs() -> DifyApp:
     dify_app = DifyApp(__name__)
     dify_app.config.from_mapping(dify_config.model_dump())
 
-    # add before request hook
-    @dify_app.before_request
-    def before_request():
-        # add an unique identifier to each request
-        RecyclableContextVar.increment_thread_recycles()
-
     return dify_app
 
 

api/commands.py

@@ -707,13 +707,12 @@ def extract_unique_plugins(output_file: str, input_file: str):
 @click.option(
     "--output_file", prompt=True, help="The file to store the installed plugins.", default="installed_plugins.jsonl"
 )
-@click.option("--workers", prompt=True, help="The number of workers to install plugins.", default=100)
-def install_plugins(input_file: str, output_file: str, workers: int):
+def install_plugins(input_file: str, output_file: str):
     """
     Install plugins.
     """
     click.echo(click.style("Starting install plugins.", fg="white"))
 
-    PluginMigration.install_plugins(input_file, output_file, workers)
+    PluginMigration.install_plugins(input_file, output_file)
 
     click.echo(click.style("Install plugins completed.", fg="green"))

api/configs/feature/__init__.py

@@ -373,8 +373,8 @@ class HttpConfig(BaseSettings):
     )
 
     RESPECT_XFORWARD_HEADERS_ENABLED: bool = Field(
-        description="Enable handling of X-Forwarded-For, X-Forwarded-Proto, and X-Forwarded-Port headers"
-        " when the app is behind a single trusted reverse proxy.",
+        description="Enable or disable the X-Forwarded-For Proxy Fix middleware from Werkzeug"
+        " to respect X-* headers to redirect clients",
         default=False,
     )
 
@@ -389,6 +389,11 @@ class InnerAPIConfig(BaseSettings):
         default=False,
     )
 
+    INNER_API_KEY: Optional[str] = Field(
+        description="API key for accessing the internal API",
+        default=None,
+    )
+
 
 class LoggingConfig(BaseSettings):
     """

api/configs/middleware/__init__.py

@@ -1,4 +1,3 @@
-import os
 from typing import Any, Literal, Optional
 from urllib.parse import quote_plus
 
@@ -167,11 +166,6 @@ class DatabaseConfig(BaseSettings):
         default=False,
     )
 
-    RETRIEVAL_SERVICE_EXECUTORS: NonNegativeInt = Field(
-        description="Number of processes for the retrieval service, default to CPU cores.",
-        default=os.cpu_count(),
-    )
-
     @computed_field
     def SQLALCHEMY_ENGINE_OPTIONS(self) -> dict[str, Any]:
         return {

api/configs/middleware/vdb/oracle_config.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from pydantic import Field
+from pydantic import Field, PositiveInt
 from pydantic_settings import BaseSettings
 
 
@@ -9,6 +9,16 @@ class OracleConfig(BaseSettings):
     Configuration settings for Oracle database
     """
 
+    ORACLE_HOST: Optional[str] = Field(
+        description="Hostname or IP address of the Oracle database server (e.g., 'localhost' or 'oracle.example.com')",
+        default=None,
+    )
+
+    ORACLE_PORT: PositiveInt = Field(
+        description="Port number on which the Oracle database server is listening (default is 1521)",
+        default=1521,
+    )
+
     ORACLE_USER: Optional[str] = Field(
         description="Username for authenticating with the Oracle database",
         default=None,
@@ -19,28 +29,7 @@ class OracleConfig(BaseSettings):
         default=None,
     )
 
-    ORACLE_DSN: Optional[str] = Field(
-        description="Oracle database connection string. For traditional database, use format 'host:port/service_name'. "
-        "For autonomous database, use the service name from tnsnames.ora in the wallet",
+    ORACLE_DATABASE: Optional[str] = Field(
+        description="Name of the Oracle database or service to connect to (e.g., 'ORCL' or 'pdborcl')",
         default=None,
     )
-
-    ORACLE_CONFIG_DIR: Optional[str] = Field(
-        description="Directory containing the tnsnames.ora configuration file. Only used in thin mode connection",
-        default=None,
-    )
-
-    ORACLE_WALLET_LOCATION: Optional[str] = Field(
-        description="Oracle wallet directory path containing the wallet files for secure connection",
-        default=None,
-    )
-
-    ORACLE_WALLET_PASSWORD: Optional[str] = Field(
-        description="Password to decrypt the Oracle wallet, if it is encrypted",
-        default=None,
-    )
-
-    ORACLE_IS_AUTONOMOUS: bool = Field(
-        description="Flag indicating whether connecting to Oracle Autonomous Database",
-        default=False,
-    )

api/constants/__init__.py

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

api/contexts/__init__.py

@@ -2,10 +2,7 @@ from contextvars import ContextVar
 from threading import Lock
 from typing import TYPE_CHECKING
 
-from contexts.wrapper import RecyclableContextVar
-
 if TYPE_CHECKING:
-    from core.model_runtime.entities.model_entities import AIModelEntity
     from core.plugin.entities.plugin_daemon import PluginModelProviderEntity
     from core.tools.plugin_tool.provider import PluginToolProviderController
     from core.workflow.entities.variable_pool import VariablePool
@@ -15,25 +12,8 @@ tenant_id: ContextVar[str] = ContextVar("tenant_id")
 
 workflow_variable_pool: ContextVar["VariablePool"] = ContextVar("workflow_variable_pool")
 
-"""
-To avoid race-conditions caused by gunicorn thread recycling, using RecyclableContextVar to replace with
-"""
-plugin_tool_providers: RecyclableContextVar[dict[str, "PluginToolProviderController"]] = RecyclableContextVar(
-    ContextVar("plugin_tool_providers")
-)
+plugin_tool_providers: ContextVar[dict[str, "PluginToolProviderController"]] = ContextVar("plugin_tool_providers")
+plugin_tool_providers_lock: ContextVar[Lock] = ContextVar("plugin_tool_providers_lock")
 
-plugin_tool_providers_lock: RecyclableContextVar[Lock] = RecyclableContextVar(ContextVar("plugin_tool_providers_lock"))
-
-plugin_model_providers: RecyclableContextVar[list["PluginModelProviderEntity"] | None] = RecyclableContextVar(
-    ContextVar("plugin_model_providers")
-)
-
-plugin_model_providers_lock: RecyclableContextVar[Lock] = RecyclableContextVar(
-    ContextVar("plugin_model_providers_lock")
-)
-
-plugin_model_schema_lock: RecyclableContextVar[Lock] = RecyclableContextVar(ContextVar("plugin_model_schema_lock"))
-
-plugin_model_schemas: RecyclableContextVar[dict[str, "AIModelEntity"]] = RecyclableContextVar(
-    ContextVar("plugin_model_schemas")
-)
+plugin_model_providers: ContextVar[list["PluginModelProviderEntity"] | None] = ContextVar("plugin_model_providers")
+plugin_model_providers_lock: ContextVar[Lock] = ContextVar("plugin_model_providers_lock")

api/contexts/wrapper.py

@@ -1,65 +0,0 @@
-from contextvars import ContextVar
-from typing import Generic, TypeVar
-
-T = TypeVar("T")
-
-
-class HiddenValue:
-    pass
-
-
-_default = HiddenValue()
-
-
-class RecyclableContextVar(Generic[T]):
-    """
-    RecyclableContextVar is a wrapper around ContextVar
-    It's safe to use in gunicorn with thread recycling, but features like `reset` are not available for now
-
-    NOTE: you need to call `increment_thread_recycles` before requests
-    """
-
-    _thread_recycles: ContextVar[int] = ContextVar("thread_recycles")
-
-    @classmethod
-    def increment_thread_recycles(cls):
-        try:
-            recycles = cls._thread_recycles.get()
-            cls._thread_recycles.set(recycles + 1)
-        except LookupError:
-            cls._thread_recycles.set(0)
-
-    def __init__(self, context_var: ContextVar[T]):
-        self._context_var = context_var
-        self._updates = ContextVar[int](context_var.name + "_updates", default=0)
-
-    def get(self, default: T | HiddenValue = _default) -> T:
-        thread_recycles = self._thread_recycles.get(0)
-        self_updates = self._updates.get()
-        if thread_recycles > self_updates:
-            self._updates.set(thread_recycles)
-
-        # check if thread is recycled and should be updated
-        if thread_recycles < self_updates:
-            return self._context_var.get()
-        else:
-            # thread_recycles >= self_updates, means current context is invalid
-            if isinstance(default, HiddenValue) or default is _default:
-                raise LookupError
-            else:
-                return default
-
-    def set(self, value: T):
-        # it leads to a situation that self.updates is less than cls.thread_recycles if `set` was never called before
-        # increase it manually
-        thread_recycles = self._thread_recycles.get(0)
-        self_updates = self._updates.get()
-        if thread_recycles > self_updates:
-            self._updates.set(thread_recycles)
-
-        if self._updates.get() == self._thread_recycles.get(0):
-            # after increment,
-            self._updates.set(self._updates.get() + 1)
-
-        # set the context
-        self._context_var.set(value)

api/controllers/console/app/site.py

@@ -2,6 +2,7 @@ from datetime import UTC, datetime
 
 from flask_login import current_user  # type: ignore
 from flask_restful import Resource, marshal_with, reqparse  # type: ignore
+from sqlalchemy.orm import Session
 from werkzeug.exceptions import Forbidden, NotFound
 
 from constants.languages import supported_language
@@ -50,35 +51,37 @@ class AppSite(Resource):
         if not current_user.is_editor:
             raise Forbidden()
 
-        site = db.session.query(Site).filter(Site.app_id == app_model.id).first()
-        if not site:
-            raise NotFound
+        with Session(db.engine) as session:
+            site = session.query(Site).filter(Site.app_id == app_model.id).first()
 
-        for attr_name in [
-            "title",
-            "icon_type",
-            "icon",
-            "icon_background",
-            "description",
-            "default_language",
-            "chat_color_theme",
-            "chat_color_theme_inverted",
-            "customize_domain",
-            "copyright",
-            "privacy_policy",
-            "custom_disclaimer",
-            "customize_token_strategy",
-            "prompt_public",
-            "show_workflow_steps",
-            "use_icon_as_answer_icon",
-        ]:
-            value = args.get(attr_name)
-            if value is not None:
-                setattr(site, attr_name, value)
+            if not site:
+                raise NotFound
 
-        site.updated_by = current_user.id
-        site.updated_at = datetime.now(UTC).replace(tzinfo=None)
-        db.session.commit()
+            for attr_name in [
+                "title",
+                "icon_type",
+                "icon",
+                "icon_background",
+                "description",
+                "default_language",
+                "chat_color_theme",
+                "chat_color_theme_inverted",
+                "customize_domain",
+                "copyright",
+                "privacy_policy",
+                "custom_disclaimer",
+                "customize_token_strategy",
+                "prompt_public",
+                "show_workflow_steps",
+                "use_icon_as_answer_icon",
+            ]:
+                value = args.get(attr_name)
+                if value is not None:
+                    setattr(site, attr_name, value)
+
+            site.updated_by = current_user.id
+            site.updated_at = datetime.now(UTC).replace(tzinfo=None)
+            session.commit()
 
         return site
 

api/controllers/console/datasets/datasets.py

@@ -623,6 +623,7 @@ class DatasetRetrievalSettingApi(Resource):
         match vector_type:
             case (
                 VectorType.RELYT
+                | VectorType.PGVECTOR
                 | VectorType.TIDB_VECTOR
                 | VectorType.CHROMA
                 | VectorType.TENCENT

api/controllers/files/image_preview.py

@@ -1,5 +1,3 @@
-from urllib.parse import quote
-
 from flask import Response, request
 from flask_restful import Resource, reqparse  # type: ignore
 from werkzeug.exceptions import NotFound
@@ -73,8 +71,7 @@ class FilePreviewApi(Resource):
         if upload_file.size > 0:
             response.headers["Content-Length"] = str(upload_file.size)
         if args["as_attachment"]:
-            encoded_filename = quote(upload_file.name)
-            response.headers["Content-Disposition"] = f"attachment; filename*=UTF-8''{encoded_filename}"
+            response.headers["Content-Disposition"] = f"attachment; filename={upload_file.name}"
 
         return response
 

api/controllers/inner_api/workspace/workspace.py

@@ -50,8 +50,8 @@ class EnterpriseWorkspaceNoOwnerEmail(Resource):
             "plan": tenant.plan,
             "status": tenant.status,
             "custom_config": json.loads(tenant.custom_config) if tenant.custom_config else {},
-            "created_at": tenant.created_at.isoformat() + "Z" if tenant.created_at else None,
-            "updated_at": tenant.updated_at.isoformat() + "Z" if tenant.updated_at else None,
+            "created_at": tenant.created_at.isoformat() if tenant.created_at else None,
+            "updated_at": tenant.updated_at.isoformat() if tenant.updated_at else None,
         }
 
         return {

api/controllers/service_api/app/message.py

@@ -10,7 +10,6 @@ from controllers.service_api.app.error import NotChatAppError
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.app.entities.app_invoke_entities import InvokeFrom
 from fields.conversation_fields import message_file_fields
-from fields.message_fields import feedback_fields, retriever_resource_fields
 from fields.raws import FilesContainedField
 from libs.helper import TimestampField, uuid_value
 from models.model import App, AppMode, EndUser
@@ -19,6 +18,26 @@ from services.message_service import MessageService
 
 
 class MessageListApi(Resource):
+    feedback_fields = {"rating": fields.String}
+    retriever_resource_fields = {
+        "id": fields.String,
+        "message_id": fields.String,
+        "position": fields.Integer,
+        "dataset_id": fields.String,
+        "dataset_name": fields.String,
+        "document_id": fields.String,
+        "document_name": fields.String,
+        "data_source_type": fields.String,
+        "segment_id": fields.String,
+        "score": fields.Float,
+        "hit_count": fields.Integer,
+        "word_count": fields.Integer,
+        "segment_position": fields.Integer,
+        "index_node_hash": fields.String,
+        "content": fields.String,
+        "created_at": TimestampField,
+    }
+
     agent_thought_fields = {
         "id": fields.String,
         "chain_id": fields.String,
@@ -70,7 +89,7 @@ class MessageListApi(Resource):
 
         try:
             return MessageService.pagination_by_first_id(
-                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
+                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"]
             )
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")

api/controllers/service_api/dataset/document.py

@@ -336,10 +336,6 @@ class DocumentUpdateByFileApi(DatasetApiResource):
 
         if not dataset:
             raise ValueError("Dataset is not exist.")
-
-        # indexing_technique is already set in dataset since this is an update
-        args["indexing_technique"] = dataset.indexing_technique
-
         if "file" in request.files:
             # save file info
             file = request.files["file"]

api/controllers/service_api/wraps.py

@@ -154,7 +154,7 @@ def validate_dataset_token(view=None):
             )  # TODO: only owner information is required, so only one is returned.
             if tenant_account_join:
                 tenant, ta = tenant_account_join
-                account = db.session.query(Account).filter(Account.id == ta.account_id).first()
+                account = Account.query.filter_by(id=ta.account_id).first()
                 # Login admin
                 if account:
                     account.current_tenant = tenant

api/controllers/web/message.py

@@ -21,7 +21,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from fields.conversation_fields import message_file_fields
-from fields.message_fields import agent_thought_fields, feedback_fields, retriever_resource_fields
+from fields.message_fields import agent_thought_fields
 from fields.raws import FilesContainedField
 from libs import helper
 from libs.helper import TimestampField, uuid_value
@@ -34,6 +34,27 @@ from services.message_service import MessageService
 
 
 class MessageListApi(WebApiResource):
+    feedback_fields = {"rating": fields.String}
+
+    retriever_resource_fields = {
+        "id": fields.String,
+        "message_id": fields.String,
+        "position": fields.Integer,
+        "dataset_id": fields.String,
+        "dataset_name": fields.String,
+        "document_id": fields.String,
+        "document_name": fields.String,
+        "data_source_type": fields.String,
+        "segment_id": fields.String,
+        "score": fields.Float,
+        "hit_count": fields.Integer,
+        "word_count": fields.Integer,
+        "segment_position": fields.Integer,
+        "index_node_hash": fields.String,
+        "content": fields.String,
+        "created_at": TimestampField,
+    }
+
     message_fields = {
         "id": fields.String,
         "conversation_id": fields.String,

api/core/agent/entities.py

@@ -1,7 +1,7 @@
 from enum import StrEnum
 from typing import Any, Optional, Union
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
 
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType
 
@@ -14,7 +14,7 @@ class AgentToolEntity(BaseModel):
     provider_type: ToolProviderType
     provider_id: str
     tool_name: str
-    tool_parameters: dict[str, Any] = Field(default_factory=dict)
+    tool_parameters: dict[str, Any] = {}
     plugin_unique_identifier: str | None = None
 
 

api/core/app/app_config/easy_ui_based_app/model_config/manager.py

@@ -2,9 +2,9 @@ from collections.abc import Mapping
 from typing import Any
 
 from core.app.app_config.entities import ModelConfigEntity
+from core.entities import DEFAULT_PLUGIN_ID
 from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType
 from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
-from core.plugin.entities.plugin import ModelProviderID
 from core.provider_manager import ProviderManager
 
 
@@ -61,7 +61,9 @@ class ModelConfigManager:
             raise ValueError(f"model.provider is required and must be in {str(model_provider_names)}")
 
         if "/" not in config["model"]["provider"]:
-            config["model"]["provider"] = str(ModelProviderID(config["model"]["provider"]))
+            config["model"]["provider"] = (
+                f"{DEFAULT_PLUGIN_ID}/{config['model']['provider']}/{config['model']['provider']}"
+            )
 
         if config["model"]["provider"] not in model_provider_names:
             raise ValueError(f"model.provider is required and must be in {str(model_provider_names)}")

api/core/app/app_config/entities.py

@@ -17,8 +17,8 @@ class ModelConfigEntity(BaseModel):
     provider: str
     model: str
     mode: Optional[str] = None
-    parameters: dict[str, Any] = Field(default_factory=dict)
-    stop: list[str] = Field(default_factory=list)
+    parameters: dict[str, Any] = {}
+    stop: list[str] = []
 
 
 class AdvancedChatMessageEntity(BaseModel):
@@ -132,7 +132,7 @@ class ExternalDataVariableEntity(BaseModel):
 
     variable: str
     type: str
-    config: dict[str, Any] = Field(default_factory=dict)
+    config: dict[str, Any] = {}
 
 
 class DatasetRetrieveConfigEntity(BaseModel):
@@ -188,7 +188,7 @@ class SensitiveWordAvoidanceEntity(BaseModel):
     """
 
     type: str
-    config: dict[str, Any] = Field(default_factory=dict)
+    config: dict[str, Any] = {}
 
 
 class TextToSpeechEntity(BaseModel):

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

@@ -140,7 +140,9 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             app_config=app_config,
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,

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

@@ -582,15 +582,6 @@ class AdvancedChatAppGenerateTaskPipeline:
                         session.commit()
 
                     yield workflow_finish_resp
-                elif event.stopped_by in (
-                    QueueStopEvent.StopBy.INPUT_MODERATION,
-                    QueueStopEvent.StopBy.ANNOTATION_REPLY,
-                ):
-                    # When hitting input-moderation or annotation-reply, the workflow will not start
-                    with Session(db.engine, expire_on_commit=False) as session:
-                        # Save message
-                        self._save_message(session=session)
-                        session.commit()
 
                 yield self._message_end_to_stream_response()
                 break

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

@@ -149,7 +149,9 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             model_conf=ModelConfigConverter.convert(app_config),
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,

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

@@ -141,7 +141,9 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             model_conf=ModelConfigConverter.convert(app_config),
             file_upload_config=file_extra_config,
             conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                 user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
             ),
             query=query,

api/core/app/apps/message_based_app_generator.py

@@ -42,6 +42,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
             ChatAppGenerateEntity,
             CompletionAppGenerateEntity,
             AgentChatAppGenerateEntity,
+            AgentChatAppGenerateEntity,
         ],
         queue_manager: AppQueueManager,
         conversation: Conversation,

api/core/app/entities/app_invoke_entities.py

@@ -63,9 +63,9 @@ class ModelConfigWithCredentialsEntity(BaseModel):
     model_schema: AIModelEntity
     mode: str
     provider_model_bundle: ProviderModelBundle
-    credentials: dict[str, Any] = Field(default_factory=dict)
-    parameters: dict[str, Any] = Field(default_factory=dict)
-    stop: list[str] = Field(default_factory=list)
+    credentials: dict[str, Any] = {}
+    parameters: dict[str, Any] = {}
+    stop: list[str] = []
 
     # pydantic configs
     model_config = ConfigDict(protected_namespaces=())
@@ -94,7 +94,7 @@ class AppGenerateEntity(BaseModel):
     call_depth: int = 0
 
     # extra parameters, like: auto_generate_conversation_name
-    extras: dict[str, Any] = Field(default_factory=dict)
+    extras: dict[str, Any] = {}
 
     # tracing instance
     trace_manager: Optional[TraceQueueManager] = None

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -844,7 +844,7 @@ class WorkflowCycleManage:
         if node_execution_id not in self._workflow_node_executions:
             raise ValueError(f"Workflow node execution not found: {node_execution_id}")
         cached_workflow_node_execution = self._workflow_node_executions[node_execution_id]
-        return session.merge(cached_workflow_node_execution)
+        return cached_workflow_node_execution
 
     def _handle_agent_log(self, task_id: str, event: QueueAgentLogEvent) -> AgentLogStreamResponse:
         """

api/core/entities/provider_configuration.py

@@ -6,10 +6,10 @@ from collections.abc import Iterator, Sequence
 from json import JSONDecodeError
 from typing import Optional
 
-from pydantic import BaseModel, ConfigDict, Field
-from sqlalchemy import or_
+from pydantic import BaseModel, ConfigDict
 
 from constants import HIDDEN_VALUE
+from core.entities import DEFAULT_PLUGIN_ID
 from core.entities.model_entities import ModelStatus, ModelWithProviderEntity, SimpleModelProviderEntity
 from core.entities.provider_entities import (
     CustomConfiguration,
@@ -28,7 +28,6 @@ from core.model_runtime.entities.provider_entities import (
 )
 from core.model_runtime.model_providers.__base.ai_model import AIModel
 from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
-from core.plugin.entities.plugin import ModelProviderID
 from extensions.ext_database import db
 from models.provider import (
     LoadBalancingModelConfig,
@@ -191,11 +190,8 @@ class ProviderConfiguration(BaseModel):
             db.session.query(Provider)
             .filter(
                 Provider.tenant_id == self.tenant_id,
+                Provider.provider_name == self.provider.provider,
                 Provider.provider_type == ProviderType.CUSTOM.value,
-                or_(
-                    Provider.provider_name == ModelProviderID(self.provider.provider).plugin_name,
-                    Provider.provider_name == self.provider.provider,
-                ),
             )
             .first()
         )
@@ -283,10 +279,7 @@ class ProviderConfiguration(BaseModel):
             db.session.query(Provider)
             .filter(
                 Provider.tenant_id == self.tenant_id,
-                or_(
-                    Provider.provider_name == ModelProviderID(self.provider.provider).plugin_name,
-                    Provider.provider_name == self.provider.provider,
-                ),
+                Provider.provider_name == self.provider.provider,
                 Provider.provider_type == ProviderType.CUSTOM.value,
             )
             .first()
@@ -1003,7 +996,7 @@ class ProviderConfigurations(BaseModel):
     """
 
     tenant_id: str
-    configurations: dict[str, ProviderConfiguration] = Field(default_factory=dict)
+    configurations: dict[str, ProviderConfiguration] = {}
 
     def __init__(self, tenant_id: str):
         super().__init__(tenant_id=tenant_id)
@@ -1059,7 +1052,7 @@ class ProviderConfigurations(BaseModel):
 
     def __getitem__(self, key):
         if "/" not in key:
-            key = str(ModelProviderID(key))
+            key = f"{DEFAULT_PLUGIN_ID}/{key}/{key}"
 
         return self.configurations[key]
 
@@ -1074,7 +1067,7 @@ class ProviderConfigurations(BaseModel):
 
     def get(self, key, default=None) -> ProviderConfiguration | None:
         if "/" not in key:
-            key = str(ModelProviderID(key))
+            key = f"{DEFAULT_PLUGIN_ID}/{key}/{key}"
 
         return self.configurations.get(key, default)  # type: ignore
 

api/core/hosting_configuration.py

@@ -41,13 +41,9 @@ class HostedModerationConfig(BaseModel):
 
 
 class HostingConfiguration:
-    provider_map: dict[str, HostingProvider]
+    provider_map: dict[str, HostingProvider] = {}
     moderation_config: Optional[HostedModerationConfig] = None
 
-    def __init__(self) -> None:
-        self.provider_map = {}
-        self.moderation_config = None
-
     def init_app(self, app: Flask) -> None:
         if dify_config.EDITION != "CLOUD":
             return

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

@@ -1,11 +1,8 @@
 import decimal
-import hashlib
-from threading import Lock
 from typing import Optional
 
 from pydantic import BaseModel, ConfigDict, Field
 
-import contexts
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE
 from core.model_runtime.entities.model_entities import (
@@ -142,35 +139,15 @@ class AIModel(BaseModel):
         :return: model schema
         """
         plugin_model_manager = PluginModelManager()
-        cache_key = f"{self.tenant_id}:{self.plugin_id}:{self.provider_name}:{self.model_type.value}:{model}"
-        # sort credentials
-        sorted_credentials = sorted(credentials.items()) if credentials else []
-        cache_key += ":".join([hashlib.md5(f"{k}:{v}".encode()).hexdigest() for k, v in sorted_credentials])
-
-        try:
-            contexts.plugin_model_schemas.get()
-        except LookupError:
-            contexts.plugin_model_schemas.set({})
-            contexts.plugin_model_schema_lock.set(Lock())
-
-        with contexts.plugin_model_schema_lock.get():
-            if cache_key in contexts.plugin_model_schemas.get():
-                return contexts.plugin_model_schemas.get()[cache_key]
-
-            schema = plugin_model_manager.get_model_schema(
-                tenant_id=self.tenant_id,
-                user_id="unknown",
-                plugin_id=self.plugin_id,
-                provider=self.provider_name,
-                model_type=self.model_type.value,
-                model=model,
-                credentials=credentials or {},
-            )
-
-            if schema:
-                contexts.plugin_model_schemas.get()[cache_key] = schema
-
-            return schema
+        return plugin_model_manager.get_model_schema(
+            tenant_id=self.tenant_id,
+            user_id="unknown",
+            plugin_id=self.plugin_id,
+            provider=self.provider_name,
+            model_type=self.model_type.value,
+            model=model,
+            credentials=credentials or {},
+        )
 
     def get_customizable_model_schema_from_credentials(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
         """
@@ -180,9 +157,14 @@ class AIModel(BaseModel):
         :param credentials: model credentials
         :return: model schema
         """
+        return self._get_customizable_model_schema(model, credentials)
 
-        # get customizable model schema
+    def _get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
+        """
+        Get customizable model schema and fill in the template
+        """
         schema = self.get_customizable_model_schema(model, credentials)
+
         if not schema:
             return None
 

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

@@ -228,7 +228,7 @@ class LargeLanguageModel(AIModel):
         :return: result generator
         """
         callbacks = callbacks or []
-        assistant_message = AssistantPromptMessage(content="")
+        prompt_message = AssistantPromptMessage(content="")
         usage = None
         system_fingerprint = None
         real_model = model
@@ -250,7 +250,7 @@ class LargeLanguageModel(AIModel):
                     callbacks=callbacks,
                 )
 
-                assistant_message.content += chunk.delta.message.content
+                prompt_message.content += chunk.delta.message.content
                 real_model = chunk.model
                 if chunk.delta.usage:
                     usage = chunk.delta.usage
@@ -265,7 +265,7 @@ class LargeLanguageModel(AIModel):
             result=LLMResult(
                 model=real_model,
                 prompt_messages=prompt_messages,
-                message=assistant_message,
+                message=prompt_message,
                 usage=usage or LLMUsage.empty_usage(),
                 system_fingerprint=system_fingerprint,
             ),

api/core/model_runtime/model_providers/model_provider_factory.py

@@ -1,4 +1,3 @@
-import hashlib
 import logging
 import os
 from collections.abc import Sequence
@@ -8,6 +7,7 @@ from typing import Optional
 from pydantic import BaseModel
 
 import contexts
+from core.entities import DEFAULT_PLUGIN_ID
 from core.helper.position_helper import get_provider_position_map, sort_to_dict_by_position_map
 from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
 from core.model_runtime.entities.provider_entities import ProviderConfig, ProviderEntity, SimpleProviderEntity
@@ -34,11 +34,9 @@ class ModelProviderExtension(BaseModel):
 
 
 class ModelProviderFactory:
-    provider_position_map: dict[str, int]
+    provider_position_map: dict[str, int] = {}
 
     def __init__(self, tenant_id: str) -> None:
-        self.provider_position_map = {}
-
         self.tenant_id = tenant_id
         self.plugin_model_manager = PluginModelManager()
 
@@ -207,35 +205,17 @@ class ModelProviderFactory:
         Get model schema
         """
         plugin_id, provider_name = self.get_plugin_id_and_provider_name_from_provider(provider)
-        cache_key = f"{self.tenant_id}:{plugin_id}:{provider_name}:{model_type.value}:{model}"
-        # sort credentials
-        sorted_credentials = sorted(credentials.items()) if credentials else []
-        cache_key += ":".join([hashlib.md5(f"{k}:{v}".encode()).hexdigest() for k, v in sorted_credentials])
+        model_schema = self.plugin_model_manager.get_model_schema(
+            tenant_id=self.tenant_id,
+            user_id="unknown",
+            plugin_id=plugin_id,
+            provider=provider_name,
+            model_type=model_type.value,
+            model=model,
+            credentials=credentials,
+        )
 
-        try:
-            contexts.plugin_model_schemas.get()
-        except LookupError:
-            contexts.plugin_model_schemas.set({})
-            contexts.plugin_model_schema_lock.set(Lock())
-
-        with contexts.plugin_model_schema_lock.get():
-            if cache_key in contexts.plugin_model_schemas.get():
-                return contexts.plugin_model_schemas.get()[cache_key]
-
-            schema = self.plugin_model_manager.get_model_schema(
-                tenant_id=self.tenant_id,
-                user_id="unknown",
-                plugin_id=plugin_id,
-                provider=provider_name,
-                model_type=model_type.value,
-                model=model,
-                credentials=credentials or {},
-            )
-
-            if schema:
-                contexts.plugin_model_schemas.get()[cache_key] = schema
-
-            return schema
+        return model_schema
 
     def get_models(
         self,
@@ -380,5 +360,11 @@ class ModelProviderFactory:
         :param provider: provider name
         :return: plugin id and provider name
         """
-        provider_id = ModelProviderID(provider)
-        return provider_id.plugin_id, provider_id.provider_name
+        plugin_id = DEFAULT_PLUGIN_ID
+        provider_name = provider
+        if "/" in provider:
+            # get the plugin_id before provider
+            plugin_id = "/".join(provider.split("/")[:-1])
+            provider_name = provider.split("/")[-1]
+
+        return str(plugin_id), provider_name

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

@@ -1,22 +0,0 @@
-- claude-3-haiku@20240307
-- claude-3-opus@20240229
-- claude-3-sonnet@20240229
-- claude-3-5-sonnet-v2@20241022
-- claude-3-5-sonnet@20240620
-- gemini-1.0-pro-vision-001
-- gemini-1.0-pro-002
-- gemini-1.5-flash-001
-- gemini-1.5-flash-002
-- gemini-1.5-pro-001
-- gemini-1.5-pro-002
-- gemini-2.0-flash-001
-- gemini-2.0-flash-exp
-- gemini-2.0-flash-lite-preview-02-05
-- gemini-2.0-flash-thinking-exp-01-21
-- gemini-2.0-flash-thinking-exp-1219
-- gemini-2.0-pro-exp-02-05
-- gemini-exp-1114
-- gemini-exp-1121
-- gemini-exp-1206
-- gemini-flash-experimental
-- gemini-pro-experimental

api/core/plugin/entities/plugin.py

@@ -159,7 +159,7 @@ class GenericProviderID:
             if re.match(r"^[a-z0-9_-]+$", value):
                 value = f"langgenius/{value}/{value}"
             else:
-                raise ValueError(f"Invalid plugin id {value}")
+                raise ValueError("Invalid plugin id")
 
         self.organization, self.plugin_name, self.provider_name = value.split("/")
         self.is_hardcoded = is_hardcoded
@@ -180,7 +180,7 @@ class ToolProviderID(GenericProviderID):
     def __init__(self, value: str, is_hardcoded: bool = False) -> None:
         super().__init__(value, is_hardcoded)
         if self.organization == "langgenius":
-            if self.provider_name in ["jina", "siliconflow", "stepfun", "gitee_ai"]:
+            if self.provider_name in ["jina", "siliconflow"]:
                 self.plugin_name = f"{self.provider_name}_tool"
 
 
@@ -212,9 +212,3 @@ class PluginDependency(BaseModel):
 
     type: Type
     value: Github | Marketplace | Package
-    current_identifier: Optional[str] = None
-
-
-class MissingPluginDependency(BaseModel):
-    plugin_unique_identifier: str
-    current_identifier: Optional[str] = None

api/core/plugin/manager/plugin.py

@@ -3,7 +3,6 @@ from collections.abc import Sequence
 from core.plugin.entities.bundle import PluginBundleDependency
 from core.plugin.entities.plugin import (
     GenericProviderID,
-    MissingPluginDependency,
     PluginDeclaration,
     PluginEntity,
     PluginInstallation,
@@ -176,16 +175,14 @@ class PluginInstallationManager(BasePluginManager):
             headers={"Content-Type": "application/json"},
         )
 
-    def fetch_missing_dependencies(
-        self, tenant_id: str, plugin_unique_identifiers: list[str]
-    ) -> list[MissingPluginDependency]:
+    def fetch_missing_dependencies(self, tenant_id: str, plugin_unique_identifiers: list[str]) -> list[str]:
         """
         Fetch missing dependencies
         """
         return self._request_with_plugin_daemon_response(
             "POST",
             f"plugin/{tenant_id}/management/installation/missing",
-            list[MissingPluginDependency],
+            list[str],
             data={"plugin_unique_identifiers": plugin_unique_identifiers},
             headers={"Content-Type": "application/json"},
         )

api/core/plugin/manager/tool.py

@@ -3,7 +3,7 @@ from typing import Any, Optional
 
 from pydantic import BaseModel
 
-from core.plugin.entities.plugin import GenericProviderID, ToolProviderID
+from core.plugin.entities.plugin import GenericProviderID
 from core.plugin.entities.plugin_daemon import PluginBasicBooleanResponse, PluginToolProviderEntity
 from core.plugin.manager.base import BasePluginManager
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
@@ -45,7 +45,7 @@ class PluginToolManager(BasePluginManager):
         """
         Fetch tool provider for the given tenant and plugin.
         """
-        tool_provider_id = ToolProviderID(provider)
+        tool_provider_id = GenericProviderID(provider)
 
         def transformer(json_response: dict[str, Any]) -> dict:
             data = json_response.get("data")

api/core/provider_manager.py

@@ -100,23 +100,8 @@ class ProviderManager:
             tenant_id, provider_name_to_provider_records_dict
         )
 
-        # append providers with langgenius/openai/openai
-        provider_name_list = list(provider_name_to_provider_records_dict.keys())
-        for provider_name in provider_name_list:
-            provider_id = ModelProviderID(provider_name)
-            if str(provider_id) not in provider_name_list:
-                provider_name_to_provider_records_dict[str(provider_id)] = provider_name_to_provider_records_dict[
-                    provider_name
-                ]
-
         # Get all provider model records of the workspace
         provider_name_to_provider_model_records_dict = self._get_all_provider_models(tenant_id)
-        for provider_name in list(provider_name_to_provider_model_records_dict.keys()):
-            provider_id = ModelProviderID(provider_name)
-            if str(provider_id) not in provider_name_to_provider_model_records_dict:
-                provider_name_to_provider_model_records_dict[str(provider_id)] = (
-                    provider_name_to_provider_model_records_dict[provider_name]
-                )
 
         # Get all provider entities
         model_provider_factory = ModelProviderFactory(tenant_id)
@@ -375,8 +360,7 @@ class ProviderManager:
 
         provider_name_to_provider_records_dict = defaultdict(list)
         for provider in providers:
-            # TODO: Use provider name with prefix after the data migration
-            provider_name_to_provider_records_dict[str(ModelProviderID(provider.provider_name))].append(provider)
+            provider_name_to_provider_records_dict[provider.provider_name].append(provider)
 
         return provider_name_to_provider_records_dict
 
@@ -470,9 +454,11 @@ class ProviderManager:
 
         provider_name_to_provider_load_balancing_model_configs_dict = defaultdict(list)
         for provider_load_balancing_config in provider_load_balancing_configs:
-            provider_name_to_provider_load_balancing_model_configs_dict[
-                provider_load_balancing_config.provider_name
-            ].append(provider_load_balancing_config)
+            (
+                provider_name_to_provider_load_balancing_model_configs_dict[
+                    provider_load_balancing_config.provider_name
+                ].append(provider_load_balancing_config)
+            )
 
         return provider_name_to_provider_load_balancing_model_configs_dict
 
@@ -515,8 +501,7 @@ class ProviderManager:
                             # FIXME ignore the type errork, onyl TrialHostingQuota has limit need to change the logic
                             provider_record = Provider(
                                 tenant_id=tenant_id,
-                                # TODO: Use provider name with prefix after the data migration.
-                                provider_name=ModelProviderID(provider_name).provider_name,
+                                provider_name=provider_name,
                                 provider_type=ProviderType.SYSTEM.value,
                                 quota_type=ProviderQuotaType.TRIAL.value,
                                 quota_limit=quota.quota_limit,  # type: ignore
@@ -531,12 +516,13 @@ class ProviderManager:
                                 db.session.query(Provider)
                                 .filter(
                                     Provider.tenant_id == tenant_id,
-                                    Provider.provider_name == ModelProviderID(provider_name).provider_name,
+                                    Provider.provider_name == provider_name,
                                     Provider.provider_type == ProviderType.SYSTEM.value,
                                     Provider.quota_type == ProviderQuotaType.TRIAL.value,
                                 )
                                 .first()
                             )
+
                             if provider_record and not provider_record.is_valid:
                                 provider_record.is_valid = True
                                 db.session.commit()

api/core/rag/datasource/retrieval_service.py

@@ -1,12 +1,8 @@
-import concurrent.futures
-import json
-from concurrent.futures import ThreadPoolExecutor
+import threading
 from typing import Optional
 
 from flask import Flask, current_app
-from sqlalchemy.orm import load_only
 
-from configs import dify_config
 from core.rag.data_post_processor.data_post_processor import DataPostProcessor
 from core.rag.datasource.keyword.keyword_factory import Keyword
 from core.rag.datasource.vdb.vector_factory import Vector
@@ -30,7 +26,6 @@ default_retrieval_model = {
 
 
 class RetrievalService:
-    # Cache precompiled regular expressions to avoid repeated compilation
     @classmethod
     def retrieve(
         cls,
@@ -45,62 +40,74 @@ class RetrievalService:
     ):
         if not query:
             return []
-        dataset = cls._get_dataset(dataset_id)
-        if not dataset or dataset.available_document_count == 0 or dataset.available_segment_count == 0:
+        dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
+        if not dataset:
             return []
 
+        if not dataset or dataset.available_document_count == 0 or dataset.available_segment_count == 0:
+            return []
         all_documents: list[Document] = []
+        threads: list[threading.Thread] = []
         exceptions: list[str] = []
+        # retrieval_model source with keyword
+        if retrieval_method == "keyword_search":
+            keyword_thread = threading.Thread(
+                target=RetrievalService.keyword_search,
+                kwargs={
+                    "flask_app": current_app._get_current_object(),  # type: ignore
+                    "dataset_id": dataset_id,
+                    "query": query,
+                    "top_k": top_k,
+                    "all_documents": all_documents,
+                    "exceptions": exceptions,
+                },
+            )
+            threads.append(keyword_thread)
+            keyword_thread.start()
+        # retrieval_model source with semantic
+        if RetrievalMethod.is_support_semantic_search(retrieval_method):
+            embedding_thread = threading.Thread(
+                target=RetrievalService.embedding_search,
+                kwargs={
+                    "flask_app": current_app._get_current_object(),  # type: ignore
+                    "dataset_id": dataset_id,
+                    "query": query,
+                    "top_k": top_k,
+                    "score_threshold": score_threshold,
+                    "reranking_model": reranking_model,
+                    "all_documents": all_documents,
+                    "retrieval_method": retrieval_method,
+                    "exceptions": exceptions,
+                },
+            )
+            threads.append(embedding_thread)
+            embedding_thread.start()
 
-        # Optimize multithreading with thread pools
-        with ThreadPoolExecutor(max_workers=dify_config.RETRIEVAL_SERVICE_EXECUTORS) as executor:  # type: ignore
-            futures = []
-            if retrieval_method == "keyword_search":
-                futures.append(
-                    executor.submit(
-                        cls.keyword_search,
-                        flask_app=current_app._get_current_object(),  # type: ignore
-                        dataset_id=dataset_id,
-                        query=query,
-                        top_k=top_k,
-                        all_documents=all_documents,
-                        exceptions=exceptions,
-                    )
-                )
-            if RetrievalMethod.is_support_semantic_search(retrieval_method):
-                futures.append(
-                    executor.submit(
-                        cls.embedding_search,
-                        flask_app=current_app._get_current_object(),  # type: ignore
-                        dataset_id=dataset_id,
-                        query=query,
-                        top_k=top_k,
-                        score_threshold=score_threshold,
-                        reranking_model=reranking_model,
-                        all_documents=all_documents,
-                        retrieval_method=retrieval_method,
-                        exceptions=exceptions,
-                    )
-                )
-            if RetrievalMethod.is_support_fulltext_search(retrieval_method):
-                futures.append(
-                    executor.submit(
-                        cls.full_text_index_search,
-                        flask_app=current_app._get_current_object(),  # type: ignore
-                        dataset_id=dataset_id,
-                        query=query,
-                        top_k=top_k,
-                        score_threshold=score_threshold,
-                        reranking_model=reranking_model,
-                        all_documents=all_documents,
-                        retrieval_method=retrieval_method,
-                        exceptions=exceptions,
-                    )
-                )
-            concurrent.futures.wait(futures, timeout=30, return_when=concurrent.futures.ALL_COMPLETED)
+        # retrieval source with full text
+        if RetrievalMethod.is_support_fulltext_search(retrieval_method):
+            full_text_index_thread = threading.Thread(
+                target=RetrievalService.full_text_index_search,
+                kwargs={
+                    "flask_app": current_app._get_current_object(),  # type: ignore
+                    "dataset_id": dataset_id,
+                    "query": query,
+                    "retrieval_method": retrieval_method,
+                    "score_threshold": score_threshold,
+                    "top_k": top_k,
+                    "reranking_model": reranking_model,
+                    "all_documents": all_documents,
+                    "exceptions": exceptions,
+                },
+            )
+            threads.append(full_text_index_thread)
+            full_text_index_thread.start()
+
+        for thread in threads:
+            thread.join()
 
         if exceptions:
-            raise ValueError(";\n".join(exceptions))
+            exception_message = ";\n".join(exceptions)
+            raise ValueError(exception_message)
 
         if retrieval_method == RetrievalMethod.HYBRID_SEARCH.value:
             data_post_processor = DataPostProcessor(
@@ -125,21 +132,18 @@ class RetrievalService:
         )
         return all_documents
 
-    @classmethod
-    def _get_dataset(cls, dataset_id: str) -> Optional[Dataset]:
-        return db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
-
     @classmethod
     def keyword_search(
         cls, flask_app: Flask, dataset_id: str, query: str, top_k: int, all_documents: list, exceptions: list
     ):
         with flask_app.app_context():
             try:
-                dataset = cls._get_dataset(dataset_id)
+                dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
                 if not dataset:
                     raise ValueError("dataset not found")
 
                 keyword = Keyword(dataset=dataset)
+
                 documents = keyword.search(cls.escape_query_for_search(query), top_k=top_k)
                 all_documents.extend(documents)
             except Exception as e:
@@ -160,13 +164,14 @@ class RetrievalService:
     ):
         with flask_app.app_context():
             try:
-                dataset = cls._get_dataset(dataset_id)
+                dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
                 if not dataset:
                     raise ValueError("dataset not found")
 
                 vector = Vector(dataset=dataset)
+
                 documents = vector.search_by_vector(
-                    query,
+                    cls.escape_query_for_search(query),
                     search_type="similarity_score_threshold",
                     top_k=top_k,
                     score_threshold=score_threshold,
@@ -181,7 +186,7 @@ class RetrievalService:
                         and retrieval_method == RetrievalMethod.SEMANTIC_SEARCH.value
                     ):
                         data_post_processor = DataPostProcessor(
-                            str(dataset.tenant_id), str(RerankMode.RERANKING_MODEL.value), reranking_model, None, False
+                            str(dataset.tenant_id), RerankMode.RERANKING_MODEL.value, reranking_model, None, False
                         )
                         all_documents.extend(
                             data_post_processor.invoke(
@@ -211,11 +216,13 @@ class RetrievalService:
     ):
         with flask_app.app_context():
             try:
-                dataset = cls._get_dataset(dataset_id)
+                dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
                 if not dataset:
                     raise ValueError("dataset not found")
 
-                vector_processor = Vector(dataset=dataset)
+                vector_processor = Vector(
+                    dataset=dataset,
+                )
 
                 documents = vector_processor.search_by_full_text(cls.escape_query_for_search(query), top_k=top_k)
                 if documents:
@@ -226,7 +233,7 @@ class RetrievalService:
                         and retrieval_method == RetrievalMethod.FULL_TEXT_SEARCH.value
                     ):
                         data_post_processor = DataPostProcessor(
-                            str(dataset.tenant_id), str(RerankMode.RERANKING_MODEL.value), reranking_model, None, False
+                            str(dataset.tenant_id), RerankMode.RERANKING_MODEL.value, reranking_model, None, False
                         )
                         all_documents.extend(
                             data_post_processor.invoke(
@@ -243,106 +250,66 @@ class RetrievalService:
 
     @staticmethod
     def escape_query_for_search(query: str) -> str:
-        return json.dumps(query).strip('"')
-
-    @classmethod
-    def format_retrieval_documents(cls, documents: list[Document]) -> list[RetrievalSegments]:
-        """Format retrieval documents with optimized batch processing"""
-        if not documents:
-            return []
-
-        try:
-            # Collect document IDs
-            document_ids = {doc.metadata.get("document_id") for doc in documents if "document_id" in doc.metadata}
-            if not document_ids:
-                return []
-
-            # Batch query dataset documents
-            dataset_documents = {
-                doc.id: doc
-                for doc in db.session.query(DatasetDocument)
-                .filter(DatasetDocument.id.in_(document_ids))
-                .options(load_only(DatasetDocument.id, DatasetDocument.doc_form, DatasetDocument.dataset_id))
-                .all()
-            }
-
-            records = []
-            include_segment_ids = set()
-            segment_child_map = {}
-
-            # Process documents
-            for document in documents:
-                document_id = document.metadata.get("document_id")
-                if document_id not in dataset_documents:
-                    continue
-
-                dataset_document = dataset_documents[document_id]
+        return query.replace('"', '\\"')
 
+    @staticmethod
+    def format_retrieval_documents(documents: list[Document]) -> list[RetrievalSegments]:
+        records = []
+        include_segment_ids = []
+        segment_child_map = {}
+        for document in documents:
+            document_id = document.metadata.get("document_id")
+            dataset_document = db.session.query(DatasetDocument).filter(DatasetDocument.id == document_id).first()
+            if dataset_document:
                 if dataset_document.doc_form == IndexType.PARENT_CHILD_INDEX:
-                    # Handle parent-child documents
                     child_index_node_id = document.metadata.get("doc_id")
-
-                    child_chunk = (
-                        db.session.query(ChildChunk).filter(ChildChunk.index_node_id == child_index_node_id).first()
-                    )
-
-                    if not child_chunk:
-                        continue
-
-                    segment = (
-                        db.session.query(DocumentSegment)
+                    result = (
+                        db.session.query(ChildChunk, DocumentSegment)
+                        .join(DocumentSegment, ChildChunk.segment_id == DocumentSegment.id)
                         .filter(
+                            ChildChunk.index_node_id == child_index_node_id,
                             DocumentSegment.dataset_id == dataset_document.dataset_id,
                             DocumentSegment.enabled == True,
                             DocumentSegment.status == "completed",
-                            DocumentSegment.id == child_chunk.segment_id,
-                        )
-                        .options(
-                            load_only(
-                                DocumentSegment.id,
-                                DocumentSegment.content,
-                                DocumentSegment.answer,
-                            )
                         )
                         .first()
                     )
-
-                    if not segment:
-                        continue
-
-                    if segment.id not in include_segment_ids:
-                        include_segment_ids.add(segment.id)
-                        child_chunk_detail = {
-                            "id": child_chunk.id,
-                            "content": child_chunk.content,
-                            "position": child_chunk.position,
-                            "score": document.metadata.get("score", 0.0),
-                        }
-                        map_detail = {
-                            "max_score": document.metadata.get("score", 0.0),
-                            "child_chunks": [child_chunk_detail],
-                        }
-                        segment_child_map[segment.id] = map_detail
-                        record = {
-                            "segment": segment,
-                        }
-                        records.append(record)
+                    if result:
+                        child_chunk, segment = result
+                        if not segment:
+                            continue
+                        if segment.id not in include_segment_ids:
+                            include_segment_ids.append(segment.id)
+                            child_chunk_detail = {
+                                "id": child_chunk.id,
+                                "content": child_chunk.content,
+                                "position": child_chunk.position,
+                                "score": document.metadata.get("score", 0.0),
+                            }
+                            map_detail = {
+                                "max_score": document.metadata.get("score", 0.0),
+                                "child_chunks": [child_chunk_detail],
+                            }
+                            segment_child_map[segment.id] = map_detail
+                            record = {
+                                "segment": segment,
+                            }
+                            records.append(record)
+                        else:
+                            child_chunk_detail = {
+                                "id": child_chunk.id,
+                                "content": child_chunk.content,
+                                "position": child_chunk.position,
+                                "score": document.metadata.get("score", 0.0),
+                            }
+                            segment_child_map[segment.id]["child_chunks"].append(child_chunk_detail)
+                            segment_child_map[segment.id]["max_score"] = max(
+                                segment_child_map[segment.id]["max_score"], document.metadata.get("score", 0.0)
+                            )
                     else:
-                        child_chunk_detail = {
-                            "id": child_chunk.id,
-                            "content": child_chunk.content,
-                            "position": child_chunk.position,
-                            "score": document.metadata.get("score", 0.0),
-                        }
-                        segment_child_map[segment.id]["child_chunks"].append(child_chunk_detail)
-                        segment_child_map[segment.id]["max_score"] = max(
-                            segment_child_map[segment.id]["max_score"], document.metadata.get("score", 0.0)
-                        )
-                else:
-                    # Handle normal documents
-                    index_node_id = document.metadata.get("doc_id")
-                    if not index_node_id:
                         continue
+                else:
+                    index_node_id = document.metadata["doc_id"]
 
                     segment = (
                         db.session.query(DocumentSegment)
@@ -357,21 +324,16 @@ class RetrievalService:
 
                     if not segment:
                         continue
-
-                    include_segment_ids.add(segment.id)
+                    include_segment_ids.append(segment.id)
                     record = {
                         "segment": segment,
-                        "score": document.metadata.get("score"),  # type: ignore
+                        "score": document.metadata.get("score", None),
                     }
-                    records.append(record)
 
-            # Add child chunks information to records
+                    records.append(record)
             for record in records:
                 if record["segment"].id in segment_child_map:
-                    record["child_chunks"] = segment_child_map[record["segment"].id].get("child_chunks")  # type: ignore
+                    record["child_chunks"] = segment_child_map[record["segment"].id].get("child_chunks", None)
                     record["score"] = segment_child_map[record["segment"].id]["max_score"]
 
-            return [RetrievalSegments(**record) for record in records]
-        except Exception as e:
-            db.session.rollback()
-            raise e
+        return [RetrievalSegments(**record) for record in records]

api/core/rag/datasource/vdb/chroma/chroma_vector.py

@@ -111,9 +111,8 @@ class ChromaVector(BaseVector):
         for index in range(len(ids)):
             distance = distances[index]
             metadata = dict(metadatas[index])
-            score = 1 - distance
-            if score > score_threshold:
-                metadata["score"] = score
+            if distance >= score_threshold:
+                metadata["score"] = distance
                 doc = Document(
                     page_content=documents[index],
                     metadata=metadata,

api/core/rag/datasource/vdb/milvus/milvus_vector.py

@@ -72,18 +72,8 @@ class MilvusVector(BaseVector):
         self._client = self._init_client(config)
         self._consistency_level = "Session"  # Consistency level for Milvus operations
         self._fields: list[str] = []  # List of fields in the collection
-        if self._client.has_collection(collection_name):
-            self._load_collection_fields()
         self._hybrid_search_enabled = self._check_hybrid_search_support()  # Check if hybrid search is supported
 
-    def _load_collection_fields(self, fields: Optional[list[str]] = None) -> None:
-        if fields is None:
-            # Load collection fields from remote server
-            collection_info = self._client.describe_collection(self._collection_name)
-            fields = [field["name"] for field in collection_info["fields"]]
-        # Since primary field is auto-id, no need to track it
-        self._fields = [f for f in fields if f != Field.PRIMARY_KEY.value]
-
     def _check_hybrid_search_support(self) -> bool:
         """
         Check if the current Milvus version supports hybrid search.
@@ -316,7 +306,10 @@ class MilvusVector(BaseVector):
                     )
                     schema.add_function(bm25_function)
 
-                self._load_collection_fields([f.name for f in schema.fields])
+                for x in schema.fields:
+                    self._fields.append(x.name)
+                # Since primary field is auto-id, no need to track it
+                self._fields.remove(Field.PRIMARY_KEY.value)
 
                 # Create Index params for the collection
                 index_params_obj = IndexParams()

api/core/rag/datasource/vdb/oracle/oraclevector.py

@@ -23,30 +23,25 @@ oracledb.defaults.fetch_lobs = False
 
 
 class OracleVectorConfig(BaseModel):
+    host: str
+    port: int
     user: str
     password: str
-    dsn: str
-    config_dir: str | None = None
-    wallet_location: str | None = None
-    wallet_password: str | None = None
-    is_autonomous: bool = False
+    database: str
 
     @model_validator(mode="before")
     @classmethod
     def validate_config(cls, values: dict) -> dict:
+        if not values["host"]:
+            raise ValueError("config ORACLE_HOST is required")
+        if not values["port"]:
+            raise ValueError("config ORACLE_PORT is required")
         if not values["user"]:
             raise ValueError("config ORACLE_USER is required")
         if not values["password"]:
             raise ValueError("config ORACLE_PASSWORD is required")
-        if not values["dsn"]:
-            raise ValueError("config ORACLE_DSN is required")
-        if values.get("is_autonomous", False):
-            if not values.get("config_dir"):
-                raise ValueError("config_dir is required for autonomous database")
-            if not values.get("wallet_location"):
-                raise ValueError("wallet_location is required for autonomous database")
-            if not values.get("wallet_password"):
-                raise ValueError("wallet_password is required for autonomous database")
+        if not values["database"]:
+            raise ValueError("config ORACLE_DB is required")
         return values
 
 
@@ -61,7 +56,7 @@ CREATE TABLE IF NOT EXISTS {table_name} (
 SQL_CREATE_INDEX = """
 CREATE INDEX IF NOT EXISTS idx_docs_{table_name} ON {table_name}(text) 
 INDEXTYPE IS CTXSYS.CONTEXT PARAMETERS 
-('FILTER CTXSYS.NULL_FILTER SECTION GROUP CTXSYS.HTML_SECTION_GROUP LEXER multilingual_lexer')
+('FILTER CTXSYS.NULL_FILTER SECTION GROUP CTXSYS.HTML_SECTION_GROUP LEXER sys.my_chinese_vgram_lexer')
 """
 
 
@@ -108,25 +103,14 @@ class OracleVector(BaseVector):
             )
 
     def _create_connection_pool(self, config: OracleVectorConfig):
-        pool_params = {
-            "user": config.user,
-            "password": config.password,
-            "dsn": config.dsn,
-            "min": 1,
-            "max": 50,
-            "increment": 1,
-        }
-
-        if config.is_autonomous:
-            pool_params.update(
-                {
-                    "config_dir": config.config_dir,
-                    "wallet_location": config.wallet_location,
-                    "wallet_password": config.wallet_password,
-                }
-            )
-
-        return oracledb.create_pool(**pool_params)
+        return oracledb.create_pool(
+            user=config.user,
+            password=config.password,
+            dsn="{}:{}/{}".format(config.host, config.port, config.database),
+            min=1,
+            max=50,
+            increment=1,
+        )
 
     @contextmanager
     def _get_cursor(self):
@@ -303,12 +287,10 @@ class OracleVectorFactory(AbstractVectorFactory):
         return OracleVector(
             collection_name=collection_name,
             config=OracleVectorConfig(
+                host=dify_config.ORACLE_HOST or "localhost",
+                port=dify_config.ORACLE_PORT,
                 user=dify_config.ORACLE_USER or "system",
                 password=dify_config.ORACLE_PASSWORD or "oracle",
-                dsn=dify_config.ORACLE_DSN or "oracle:1521/freepdb1",
-                config_dir=dify_config.ORACLE_CONFIG_DIR,
-                wallet_location=dify_config.ORACLE_WALLET_LOCATION,
-                wallet_password=dify_config.ORACLE_WALLET_PASSWORD,
-                is_autonomous=dify_config.ORACLE_IS_AUTONOMOUS,
+                database=dify_config.ORACLE_DATABASE or "orcl",
             ),
         )

api/core/rag/datasource/vdb/tidb_vector/tidb_vector.py

@@ -9,7 +9,6 @@ from sqlalchemy import text as sql_text
 from sqlalchemy.orm import Session, declarative_base
 
 from configs import dify_config
-from core.rag.datasource.vdb.field import Field
 from core.rag.datasource.vdb.vector_base import BaseVector
 from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
 from core.rag.datasource.vdb.vector_type import VectorType
@@ -55,13 +54,14 @@ class TiDBVector(BaseVector):
         return Table(
             self._collection_name,
             self._orm_base.metadata,
-            Column(Field.PRIMARY_KEY.value, String(36), primary_key=True, nullable=False),
+            Column("id", String(36), primary_key=True, nullable=False),
             Column(
-                Field.VECTOR.value,
+                "vector",
                 VectorType(dim),
                 nullable=False,
+                comment="" if self._distance_func is None else f"hnsw(distance={self._distance_func})",
             ),
-            Column(Field.TEXT_KEY.value, TEXT, nullable=False),
+            Column("text", TEXT, nullable=False),
             Column("meta", JSON, nullable=False),
             Column("create_time", DateTime, server_default=sqlalchemy.text("CURRENT_TIMESTAMP")),
             Column(
@@ -96,7 +96,6 @@ class TiDBVector(BaseVector):
             collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
             if redis_client.get(collection_exist_cache_key):
                 return
-            tidb_dist_func = self._get_distance_func()
             with Session(self._engine) as session:
                 session.begin()
                 create_statement = sql_text(f"""
@@ -105,14 +104,14 @@ class TiDBVector(BaseVector):
                         text TEXT NOT NULL,
                         meta JSON NOT NULL,
                         doc_id VARCHAR(64) AS (JSON_UNQUOTE(JSON_EXTRACT(meta, '$.doc_id'))) STORED,
-                        vector VECTOR<FLOAT>({dimension}) NOT NULL,
-                        create_time DATETIME DEFAULT CURRENT_TIMESTAMP,
-                        update_time DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
                         KEY (doc_id),
-                        VECTOR INDEX idx_vector (({tidb_dist_func}(vector))) USING HNSW
+                        vector VECTOR<FLOAT>({dimension}) NOT NULL COMMENT "hnsw(distance={self._distance_func})",
+                        create_time DATETIME DEFAULT CURRENT_TIMESTAMP,
+                        update_time DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
                     );
                 """)
                 session.execute(create_statement)
+                # tidb vector not support 'CREATE/ADD INDEX' now
                 session.commit()
             redis_client.set(collection_exist_cache_key, 1, ex=3600)
 
@@ -195,30 +194,23 @@ class TiDBVector(BaseVector):
         )
 
         docs = []
-        tidb_dist_func = self._get_distance_func()
+        if self._distance_func == "l2":
+            tidb_func = "Vec_l2_distance"
+        elif self._distance_func == "cosine":
+            tidb_func = "Vec_Cosine_distance"
+        else:
+            tidb_func = "Vec_Cosine_distance"
 
         with Session(self._engine) as session:
-            select_statement = sql_text(f"""
-                SELECT meta, text, distance 
-                FROM (
-                  SELECT 
-                    meta,
-                    text,
-                    {tidb_dist_func}(vector, :query_vector_str) AS distance
-                  FROM {self._collection_name}
-                  ORDER BY distance ASC
-                  LIMIT :top_k
-                ) t
-                WHERE distance <= :distance
-                """)
-            res = session.execute(
-                select_statement,
-                params={
-                    "query_vector_str": query_vector_str,
-                    "distance": distance,
-                    "top_k": top_k,
-                },
+            select_statement = sql_text(
+                f"""SELECT meta, text, distance FROM (
+                        SELECT meta, text, {tidb_func}(vector, "{query_vector_str}")  as distance
+                        FROM {self._collection_name}
+                        ORDER BY distance
+                        LIMIT {top_k}
+                    ) t WHERE distance < {distance};"""
             )
+            res = session.execute(select_statement)
             results = [(row[0], row[1], row[2]) for row in res]
             for meta, text, distance in results:
                 metadata = json.loads(meta)
@@ -235,16 +227,6 @@ class TiDBVector(BaseVector):
             session.execute(sql_text(f"""DROP TABLE IF EXISTS {self._collection_name};"""))
             session.commit()
 
-    def _get_distance_func(self) -> str:
-        match self._distance_func:
-            case "l2":
-                tidb_dist_func = "VEC_L2_DISTANCE"
-            case "cosine":
-                tidb_dist_func = "VEC_COSINE_DISTANCE"
-            case _:
-                tidb_dist_func = "VEC_COSINE_DISTANCE"
-        return tidb_dist_func
-
 
 class TiDBVectorFactory(AbstractVectorFactory):
     def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> TiDBVector:

api/core/rag/retrieval/dataset_retrieval.py

@@ -203,7 +203,6 @@ class DatasetRetrieval:
                                 "segment_id": segment.id,
                                 "retriever_from": invoke_from.to_source(),
                                 "score": record.score or 0.0,
-                                "doc_metadata": document.doc_metadata,
                             }
 
                             if invoke_from.to_source() == "dev":

api/core/tools/custom_tool/tool.py

@@ -105,10 +105,10 @@ class ApiTool(Tool):
         needed_parameters = [parameter for parameter in (self.api_bundle.parameters or []) if parameter.required]
         for parameter in needed_parameters:
             if parameter.required and parameter.name not in parameters:
-                if parameter.default is not None:
-                    parameters[parameter.name] = parameter.default
-                else:
-                    raise ToolParameterValidationError(f"Missing required parameter {parameter.name}")
+                raise ToolParameterValidationError(f"Missing required parameter {parameter.name}")
+
+            if parameter.default is not None and parameter.name not in parameters:
+                parameters[parameter.name] = parameter.default
 
         return headers
 

api/core/tools/entities/tool_entities.py

@@ -185,7 +185,7 @@ class ToolInvokeMessage(BaseModel):
     """
         plain text, image url or link url
     """
-    message: JsonMessage | TextMessage | BlobMessage | LogMessage | FileMessage | None | VariableMessage
+    message: JsonMessage | TextMessage | BlobMessage | VariableMessage | FileMessage | LogMessage | None
     meta: dict[str, Any] | None = None
 
     @field_validator("message", mode="before")

api/core/tools/tool_engine.py

@@ -246,11 +246,10 @@ class ToolEngine:
                     + "you do not need to create it, just tell the user to check it now."
                 )
             elif response.type == ToolInvokeMessage.MessageType.JSON:
-                result = json.dumps(
-                    cast(ToolInvokeMessage.JsonMessage, response.message).json_object, ensure_ascii=False
-                )
+                text = json.dumps(cast(ToolInvokeMessage.JsonMessage, response.message).json_object, ensure_ascii=False)
+                result += f"tool response: {text}."
             else:
-                result += str(response.message)
+                result += f"tool response: {response.message!r}."
 
         return result
 

api/core/tools/tool_manager.py

@@ -9,7 +9,7 @@ from typing import TYPE_CHECKING, Any, Union, cast
 from yarl import URL
 
 import contexts
-from core.plugin.entities.plugin import ToolProviderID
+from core.plugin.entities.plugin import GenericProviderID
 from core.plugin.manager.tool import PluginToolManager
 from core.tools.__base.tool_provider import ToolProviderController
 from core.tools.__base.tool_runtime import ToolRuntime
@@ -188,13 +188,13 @@ class ToolManager:
                 )
 
             if isinstance(provider_controller, PluginToolProviderController):
-                provider_id_entity = ToolProviderID(provider_id)
+                provider_id_entity = GenericProviderID(provider_id)
                 # get credentials
                 builtin_provider: BuiltinToolProvider | None = (
                     db.session.query(BuiltinToolProvider)
                     .filter(
                         BuiltinToolProvider.tenant_id == tenant_id,
-                        (BuiltinToolProvider.provider == str(provider_id_entity))
+                        (BuiltinToolProvider.provider == provider_id)
                         | (BuiltinToolProvider.provider == provider_id_entity.provider_name),
                     )
                     .first()
@@ -572,96 +572,95 @@ class ToolManager:
         else:
             filters.append(typ)
 
-        with db.session.no_autoflush:
-            if "builtin" in filters:
-                # get builtin providers
-                builtin_providers = cls.list_builtin_providers(tenant_id)
+        if "builtin" in filters:
+            # get builtin providers
+            builtin_providers = cls.list_builtin_providers(tenant_id)
 
-                # get db builtin providers
-                db_builtin_providers: list[BuiltinToolProvider] = (
-                    db.session.query(BuiltinToolProvider).filter(BuiltinToolProvider.tenant_id == tenant_id).all()
+            # get db builtin providers
+            db_builtin_providers: list[BuiltinToolProvider] = (
+                db.session.query(BuiltinToolProvider).filter(BuiltinToolProvider.tenant_id == tenant_id).all()
+            )
+
+            # rewrite db_builtin_providers
+            for db_provider in db_builtin_providers:
+                tool_provider_id = GenericProviderID(db_provider.provider)
+                db_provider.provider = tool_provider_id.to_string()
+
+            def find_db_builtin_provider(provider):
+                return next((x for x in db_builtin_providers if x.provider == provider), None)
+
+            # append builtin providers
+            for provider in builtin_providers:
+                # handle include, exclude
+                if is_filtered(
+                    include_set=cast(set[str], dify_config.POSITION_TOOL_INCLUDES_SET),
+                    exclude_set=cast(set[str], dify_config.POSITION_TOOL_EXCLUDES_SET),
+                    data=provider,
+                    name_func=lambda x: x.identity.name,
+                ):
+                    continue
+
+                user_provider = ToolTransformService.builtin_provider_to_user_provider(
+                    provider_controller=provider,
+                    db_provider=find_db_builtin_provider(provider.entity.identity.name),
+                    decrypt_credentials=False,
                 )
 
-                # rewrite db_builtin_providers
-                for db_provider in db_builtin_providers:
-                    tool_provider_id = str(ToolProviderID(db_provider.provider))
-                    db_provider.provider = tool_provider_id
+                if isinstance(provider, PluginToolProviderController):
+                    result_providers[f"plugin_provider.{user_provider.name}"] = user_provider
+                else:
+                    result_providers[f"builtin_provider.{user_provider.name}"] = user_provider
 
-                def find_db_builtin_provider(provider):
-                    return next((x for x in db_builtin_providers if x.provider == provider), None)
+        # get db api providers
 
-                # append builtin providers
-                for provider in builtin_providers:
-                    # handle include, exclude
-                    if is_filtered(
-                        include_set=cast(set[str], dify_config.POSITION_TOOL_INCLUDES_SET),
-                        exclude_set=cast(set[str], dify_config.POSITION_TOOL_EXCLUDES_SET),
-                        data=provider,
-                        name_func=lambda x: x.identity.name,
-                    ):
-                        continue
+        if "api" in filters:
+            db_api_providers: list[ApiToolProvider] = (
+                db.session.query(ApiToolProvider).filter(ApiToolProvider.tenant_id == tenant_id).all()
+            )
 
-                    user_provider = ToolTransformService.builtin_provider_to_user_provider(
-                        provider_controller=provider,
-                        db_provider=find_db_builtin_provider(provider.entity.identity.name),
-                        decrypt_credentials=False,
+            api_provider_controllers: list[dict[str, Any]] = [
+                {"provider": provider, "controller": ToolTransformService.api_provider_to_controller(provider)}
+                for provider in db_api_providers
+            ]
+
+            # get labels
+            labels = ToolLabelManager.get_tools_labels([x["controller"] for x in api_provider_controllers])
+
+            for api_provider_controller in api_provider_controllers:
+                user_provider = ToolTransformService.api_provider_to_user_provider(
+                    provider_controller=api_provider_controller["controller"],
+                    db_provider=api_provider_controller["provider"],
+                    decrypt_credentials=False,
+                    labels=labels.get(api_provider_controller["controller"].provider_id, []),
+                )
+                result_providers[f"api_provider.{user_provider.name}"] = user_provider
+
+        if "workflow" in filters:
+            # get workflow providers
+            workflow_providers: list[WorkflowToolProvider] = (
+                db.session.query(WorkflowToolProvider).filter(WorkflowToolProvider.tenant_id == tenant_id).all()
+            )
+
+            workflow_provider_controllers: list[WorkflowToolProviderController] = []
+            for provider in workflow_providers:
+                try:
+                    workflow_provider_controllers.append(
+                        ToolTransformService.workflow_provider_to_controller(db_provider=provider)
                     )
+                except Exception:
+                    # app has been deleted
+                    pass
 
-                    if isinstance(provider, PluginToolProviderController):
-                        result_providers[f"plugin_provider.{user_provider.name}"] = user_provider
-                    else:
-                        result_providers[f"builtin_provider.{user_provider.name}"] = user_provider
+            labels = ToolLabelManager.get_tools_labels(
+                [cast(ToolProviderController, controller) for controller in workflow_provider_controllers]
+            )
 
-            # get db api providers
-
-            if "api" in filters:
-                db_api_providers: list[ApiToolProvider] = (
-                    db.session.query(ApiToolProvider).filter(ApiToolProvider.tenant_id == tenant_id).all()
+            for provider_controller in workflow_provider_controllers:
+                user_provider = ToolTransformService.workflow_provider_to_user_provider(
+                    provider_controller=provider_controller,
+                    labels=labels.get(provider_controller.provider_id, []),
                 )
-
-                api_provider_controllers: list[dict[str, Any]] = [
-                    {"provider": provider, "controller": ToolTransformService.api_provider_to_controller(provider)}
-                    for provider in db_api_providers
-                ]
-
-                # get labels
-                labels = ToolLabelManager.get_tools_labels([x["controller"] for x in api_provider_controllers])
-
-                for api_provider_controller in api_provider_controllers:
-                    user_provider = ToolTransformService.api_provider_to_user_provider(
-                        provider_controller=api_provider_controller["controller"],
-                        db_provider=api_provider_controller["provider"],
-                        decrypt_credentials=False,
-                        labels=labels.get(api_provider_controller["controller"].provider_id, []),
-                    )
-                    result_providers[f"api_provider.{user_provider.name}"] = user_provider
-
-            if "workflow" in filters:
-                # get workflow providers
-                workflow_providers: list[WorkflowToolProvider] = (
-                    db.session.query(WorkflowToolProvider).filter(WorkflowToolProvider.tenant_id == tenant_id).all()
-                )
-
-                workflow_provider_controllers: list[WorkflowToolProviderController] = []
-                for provider in workflow_providers:
-                    try:
-                        workflow_provider_controllers.append(
-                            ToolTransformService.workflow_provider_to_controller(db_provider=provider)
-                        )
-                    except Exception:
-                        # app has been deleted
-                        pass
-
-                labels = ToolLabelManager.get_tools_labels(
-                    [cast(ToolProviderController, controller) for controller in workflow_provider_controllers]
-                )
-
-                for provider_controller in workflow_provider_controllers:
-                    user_provider = ToolTransformService.workflow_provider_to_user_provider(
-                        provider_controller=provider_controller,
-                        labels=labels.get(provider_controller.provider_id, []),
-                    )
-                    result_providers[f"workflow_provider.{user_provider.name}"] = user_provider
+                result_providers[f"workflow_provider.{user_provider.name}"] = user_provider
 
         return BuiltinToolProviderSort.sort(list(result_providers.values()))
 

api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py

@@ -123,7 +123,6 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
                             "segment_id": segment.id,
                             "retriever_from": self.retriever_from,
                             "score": document_score_list.get(segment.index_node_id, None),
-                            "doc_metadata": document.doc_metadata,
                         }
 
                         if self.retriever_from == "dev":

api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py

@@ -3,13 +3,11 @@ from typing import Any
 from pydantic import BaseModel, Field
 
 from core.rag.datasource.retrieval_service import RetrievalService
-from core.rag.entities.context_entities import DocumentContext
 from core.rag.models.document import Document as RetrievalDocument
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.tools.utils.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
-from models.dataset import Dataset
-from models.dataset import Document as DatasetDocument
+from models.dataset import Dataset, Document, DocumentSegment
 from services.external_knowledge_service import ExternalDatasetService
 
 default_retrieval_model = {
@@ -56,6 +54,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
 
         if not dataset:
             return ""
+
         for hit_callback in self.hit_callbacks:
             hit_callback.on_query(query, dataset.id)
         if dataset.provider == "external":
@@ -126,6 +125,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
                     )
                 else:
                     documents = []
+
                 for hit_callback in self.hit_callbacks:
                     hit_callback.on_tool_end(documents)
                 document_score_list = {}
@@ -134,47 +134,50 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
                         if item.metadata is not None and item.metadata.get("score"):
                             document_score_list[item.metadata["doc_id"]] = item.metadata["score"]
                 document_context_list = []
-                records = RetrievalService.format_retrieval_documents(documents)
-                if records:
-                    for record in records:
-                        segment = record.segment
+                index_node_ids = [document.metadata["doc_id"] for document in documents]
+                segments = DocumentSegment.query.filter(
+                    DocumentSegment.dataset_id == self.dataset_id,
+                    DocumentSegment.completed_at.isnot(None),
+                    DocumentSegment.status == "completed",
+                    DocumentSegment.enabled == True,
+                    DocumentSegment.index_node_id.in_(index_node_ids),
+                ).all()
+
+                if segments:
+                    index_node_id_to_position = {id: position for position, id in enumerate(index_node_ids)}
+                    sorted_segments = sorted(
+                        segments, key=lambda segment: index_node_id_to_position.get(segment.index_node_id, float("inf"))
+                    )
+                    for segment in sorted_segments:
                         if segment.answer:
                             document_context_list.append(
-                                DocumentContext(
-                                    content=f"question:{segment.get_sign_content()} answer:{segment.answer}",
-                                    score=record.score,
-                                )
+                                f"question:{segment.get_sign_content()} answer:{segment.answer}"
                             )
                         else:
-                            document_context_list.append(
-                                DocumentContext(
-                                    content=segment.get_sign_content(),
-                                    score=record.score,
-                                )
-                            )
-                    retrieval_resource_list = []
+                            document_context_list.append(segment.get_sign_content())
                     if self.return_resource:
-                        for record in records:
-                            segment = record.segment
-                            dataset = Dataset.query.filter_by(id=segment.dataset_id).first()
-                            document = DatasetDocument.query.filter(
-                                DatasetDocument.id == segment.document_id,
-                                DatasetDocument.enabled == True,
-                                DatasetDocument.archived == False,
+                        context_list = []
+                        resource_number = 1
+                        for segment in sorted_segments:
+                            document_segment = Document.query.filter(
+                                Document.id == segment.document_id,
+                                Document.enabled == True,
+                                Document.archived == False,
                             ).first()
-                            if dataset and document:
+                            if not document_segment:
+                                continue
+                            if dataset and document_segment:
                                 source = {
+                                    "position": resource_number,
                                     "dataset_id": dataset.id,
                                     "dataset_name": dataset.name,
-                                    "document_id": document.id,  # type: ignore
-                                    "document_name": document.name,  # type: ignore
-                                    "data_source_type": document.data_source_type,  # type: ignore
+                                    "document_id": document_segment.id,
+                                    "document_name": document_segment.name,
+                                    "data_source_type": document_segment.data_source_type,
                                     "segment_id": segment.id,
                                     "retriever_from": self.retriever_from,
-                                    "score": record.score or 0.0,
-                                    "doc_metadata": document.doc_metadata,  # type: ignore
+                                    "score": document_score_list.get(segment.index_node_id, None),
                                 }
-
                                 if self.retriever_from == "dev":
                                     source["hit_count"] = segment.hit_count
                                     source["word_count"] = segment.word_count
@@ -184,19 +187,10 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
                                     source["content"] = f"question:{segment.content} \nanswer:{segment.answer}"
                                 else:
                                     source["content"] = segment.content
-                                retrieval_resource_list.append(source)
+                                context_list.append(source)
+                            resource_number += 1
 
-            if self.return_resource and retrieval_resource_list:
-                retrieval_resource_list = sorted(
-                    retrieval_resource_list,
-                    key=lambda x: x.get("score") or 0.0,
-                    reverse=True,
-                )
-                for position, item in enumerate(retrieval_resource_list, start=1):  # type: ignore
-                    item["position"] = position  # type: ignore
-                for hit_callback in self.hit_callbacks:
-                    hit_callback.return_retriever_resource_info(retrieval_resource_list)
-            if document_context_list:
-                document_context_list = sorted(document_context_list, key=lambda x: x.score or 0.0, reverse=True)
-                return str("\n".join([document_context.content for document_context in document_context_list]))
-            return ""
+                        for hit_callback in self.hit_callbacks:
+                            hit_callback.return_retriever_resource_info(context_list)
+
+                return str("\n".join(document_context_list))

api/core/workflow/graph_engine/entities/graph.py

@@ -590,6 +590,8 @@ class Graph(BaseModel):
                             start_node_id=node_id,
                             routes_node_ids=routes_node_ids,
                         )
+                        # Exclude conditional branch nodes
+                        and all(edge.run_condition is None for edge in reverse_edge_mapping.get(node_id, []))
                     ):
                         if node_id not in merge_branch_node_ids:
                             merge_branch_node_ids[node_id] = []

api/core/workflow/graph_engine/graph_engine.py

@@ -665,7 +665,7 @@ class GraphEngine:
                                     retries += 1
                                     route_node_state.node_run_result = run_result
                                     yield NodeRunRetryEvent(
-                                        id=str(uuid.uuid4()),
+                                        id=node_instance.id,
                                         node_id=node_instance.node_id,
                                         node_type=node_instance.node_type,
                                         node_data=node_instance.node_data,
@@ -680,7 +680,7 @@ class GraphEngine:
                                         start_at=retry_start_at,
                                     )
                                     time.sleep(retry_interval)
-                                    break
+                                    continue
                             route_node_state.set_finished(run_result=run_result)
 
                             if run_result.status == WorkflowNodeExecutionStatus.FAILED:

api/core/workflow/nodes/agent/agent_node.py

@@ -8,12 +8,12 @@ from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.plugin.manager.exc import PluginDaemonClientSideError
 from core.plugin.manager.plugin import PluginInstallationManager
-from core.tools.entities.tool_entities import ToolParameter, ToolProviderType
+from core.tools.entities.tool_entities import ToolProviderType
 from core.tools.tool_manager import ToolManager
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.enums import SystemVariableKey
-from core.workflow.nodes.agent.entities import AgentNodeData, ParamsAutoGenerated
+from core.workflow.nodes.agent.entities import AgentNodeData
 from core.workflow.nodes.base.entities import BaseNodeData
 from core.workflow.nodes.enums import NodeType
 from core.workflow.nodes.event.event import RunCompletedEvent
@@ -156,38 +156,16 @@ class AgentNode(ToolNode):
                 value = cast(list[dict[str, Any]], value)
                 value = [tool for tool in value if tool.get("enabled", False)]
 
-                for tool in value:
-                    if "schemas" in tool:
-                        tool.pop("schemas")
-                    parameters = tool.get("parameters", {})
-                    if all(isinstance(v, dict) for _, v in parameters.items()):
-                        params = {}
-                        for key, param in parameters.items():
-                            if param.get("auto", ParamsAutoGenerated.OPEN.value) == ParamsAutoGenerated.CLOSE.value:
-                                value_param = param.get("value", {})
-                                params[key] = value_param.get("value", "") if value_param is not None else None
-                            else:
-                                params[key] = None
-                        parameters = params
-                    tool["settings"] = {k: v.get("value", None) for k, v in tool.get("settings", {}).items()}
-                    tool["parameters"] = parameters
-
             if not for_log:
                 if parameter.type == "array[tools]":
                     value = cast(list[dict[str, Any]], value)
                     tool_value = []
                     for tool in value:
-                        provider_type = ToolProviderType(tool.get("type", ToolProviderType.BUILT_IN.value))
-                        setting_params = tool.get("settings", {})
-                        parameters = tool.get("parameters", {})
-                        manual_input_params = [key for key, value in parameters.items() if value is not None]
-
-                        parameters = {**parameters, **setting_params}
                         entity = AgentToolEntity(
                             provider_id=tool.get("provider_name", ""),
-                            provider_type=provider_type,
+                            provider_type=ToolProviderType.BUILT_IN,
                             tool_name=tool.get("tool_name", ""),
-                            tool_parameters=parameters,
+                            tool_parameters=tool.get("parameters", {}),
                             plugin_unique_identifier=tool.get("plugin_unique_identifier", None),
                         )
 
@@ -200,26 +178,11 @@ class AgentNode(ToolNode):
                             tool_runtime.entity.description.llm = (
                                 extra.get("descrption", "") or tool_runtime.entity.description.llm
                             )
-                        for tool_runtime_params in tool_runtime.entity.parameters:
-                            tool_runtime_params.form = (
-                                ToolParameter.ToolParameterForm.FORM
-                                if tool_runtime_params.name in manual_input_params
-                                else tool_runtime_params.form
-                            )
-                        manual_input_value = {}
-                        if tool_runtime.entity.parameters:
-                            manual_input_value = {
-                                key: value for key, value in parameters.items() if key in manual_input_params
-                            }
-                        runtime_parameters = {
-                            **tool_runtime.runtime.runtime_parameters,
-                            **manual_input_value,
-                        }
+
                         tool_value.append(
                             {
                                 **tool_runtime.entity.model_dump(mode="json"),
-                                "runtime_parameters": runtime_parameters,
-                                "provider_type": provider_type.value,
+                                "runtime_parameters": tool_runtime.runtime.runtime_parameters,
                             }
                         )
                     value = tool_value

api/core/workflow/nodes/agent/entities.py

@@ -1,4 +1,3 @@
-from enum import Enum
 from typing import Any, Literal, Union
 
 from pydantic import BaseModel
@@ -17,8 +16,3 @@ class AgentNodeData(BaseNodeData):
         type: Literal["mixed", "variable", "constant"]
 
     agent_parameters: dict[str, AgentInput]
-
-
-class ParamsAutoGenerated(Enum):
-    CLOSE = 0
-    OPEN = 1

api/core/workflow/nodes/document_extractor/node.py

@@ -107,10 +107,8 @@ def _extract_text_by_mime_type(*, file_content: bytes, mime_type: str) -> str:
             return _extract_text_from_plain_text(file_content)
         case "application/pdf":
             return _extract_text_from_pdf(file_content)
-        case "application/msword":
+        case "application/vnd.openxmlformats-officedocument.wordprocessingml.document" | "application/msword":
             return _extract_text_from_doc(file_content)
-        case "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-            return _extract_text_from_docx(file_content)
         case "text/csv":
             return _extract_text_from_csv(file_content)
         case "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" | "application/vnd.ms-excel":
@@ -144,10 +142,8 @@ def _extract_text_by_file_extension(*, file_content: bytes, file_extension: str)
             return _extract_text_from_yaml(file_content)
         case ".pdf":
             return _extract_text_from_pdf(file_content)
-        case ".doc":
+        case ".doc" | ".docx":
             return _extract_text_from_doc(file_content)
-        case ".docx":
-            return _extract_text_from_docx(file_content)
         case ".csv":
             return _extract_text_from_csv(file_content)
         case ".xls" | ".xlsx":
@@ -207,33 +203,7 @@ def _extract_text_from_pdf(file_content: bytes) -> str:
 
 def _extract_text_from_doc(file_content: bytes) -> str:
     """
-    Extract text from a DOC file.
-    """
-    from unstructured.partition.api import partition_via_api
-
-    if not (dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY):
-        raise TextExtractionError("UNSTRUCTURED_API_URL and UNSTRUCTURED_API_KEY must be set")
-
-    try:
-        with tempfile.NamedTemporaryFile(suffix=".doc", delete=False) as temp_file:
-            temp_file.write(file_content)
-            temp_file.flush()
-            with open(temp_file.name, "rb") as file:
-                elements = partition_via_api(
-                    file=file,
-                    metadata_filename=temp_file.name,
-                    api_url=dify_config.UNSTRUCTURED_API_URL,
-                    api_key=dify_config.UNSTRUCTURED_API_KEY,
-                )
-            os.unlink(temp_file.name)
-        return "\n".join([getattr(element, "text", "") for element in elements])
-    except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from DOC: {str(e)}") from e
-
-
-def _extract_text_from_docx(file_content: bytes) -> str:
-    """
-    Extract text from a DOCX file.
+    Extract text from a DOC/DOCX file.
     For now support only paragraph and table add more if needed
     """
     try:
@@ -285,13 +255,13 @@ def _extract_text_from_docx(file_content: bytes) -> str:
 
                         text.append(markdown_table)
                 except Exception as e:
-                    logger.warning(f"Failed to extract table from DOC: {e}")
+                    logger.warning(f"Failed to extract table from DOC/DOCX: {e}")
                     continue
 
         return "\n".join(text)
 
     except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from DOCX: {str(e)}") from e
+        raise TextExtractionError(f"Failed to extract text from DOC/DOCX: {str(e)}") from e
 
 
 def _download_file_content(file: File) -> bytes:
@@ -359,29 +329,14 @@ def _extract_text_from_excel(file_content: bytes) -> str:
 
 
 def _extract_text_from_ppt(file_content: bytes) -> str:
-    from unstructured.partition.api import partition_via_api
     from unstructured.partition.ppt import partition_ppt
 
     try:
-        if dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY:
-            with tempfile.NamedTemporaryFile(suffix=".ppt", delete=False) as temp_file:
-                temp_file.write(file_content)
-                temp_file.flush()
-                with open(temp_file.name, "rb") as file:
-                    elements = partition_via_api(
-                        file=file,
-                        metadata_filename=temp_file.name,
-                        api_url=dify_config.UNSTRUCTURED_API_URL,
-                        api_key=dify_config.UNSTRUCTURED_API_KEY,
-                    )
-                os.unlink(temp_file.name)
-        else:
-            with io.BytesIO(file_content) as file:
-                elements = partition_ppt(file=file)
+        with io.BytesIO(file_content) as file:
+            elements = partition_ppt(file=file)
         return "\n".join([getattr(element, "text", "") for element in elements])
-
     except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from PPTX: {str(e)}") from e
+        raise TextExtractionError(f"Failed to extract text from PPT: {str(e)}") from e
 
 
 def _extract_text_from_pptx(file_content: bytes) -> str:

api/core/workflow/nodes/end/end_node.py

@@ -1,3 +1,6 @@
+from collections.abc import Mapping, Sequence
+from typing import Any
+
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.nodes.base import BaseNode
 from core.workflow.nodes.end.entities import EndNodeData
@@ -27,3 +30,20 @@ class EndNode(BaseNode[EndNodeData]):
             inputs=outputs,
             outputs=outputs,
         )
+
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls,
+        *,
+        graph_config: Mapping[str, Any],
+        node_id: str,
+        node_data: EndNodeData,
+    ) -> Mapping[str, Sequence[str]]:
+        """
+        Extract variable selector to variable mapping
+        :param graph_config: graph config
+        :param node_id: node id
+        :param node_data: node data
+        :return:
+        """
+        return {}

api/core/workflow/nodes/if_else/if_else_node.py

@@ -1,4 +1,5 @@
-from typing import Literal
+from collections.abc import Mapping, Sequence
+from typing import Any, Literal
 
 from typing_extensions import deprecated
 
@@ -87,6 +88,23 @@ class IfElseNode(BaseNode[IfElseNodeData]):
 
         return data
 
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls,
+        *,
+        graph_config: Mapping[str, Any],
+        node_id: str,
+        node_data: IfElseNodeData,
+    ) -> Mapping[str, Sequence[str]]:
+        """
+        Extract variable selector to variable mapping
+        :param graph_config: graph config
+        :param node_id: node id
+        :param node_data: node data
+        :return:
+        """
+        return {}
+
 
 @deprecated("This function is deprecated. You should use the new cases structure.")
 def _should_not_use_old_function(

api/core/workflow/nodes/iteration/iteration_node.py

@@ -590,7 +590,6 @@ class IterationNode(BaseNode[IterationNodeData]):
         with flask_app.app_context():
             parallel_mode_run_id = uuid.uuid4().hex
             graph_engine_copy = graph_engine.create_copy()
-            graph_engine_copy.graph_runtime_state.total_tokens = 0
             variable_pool_copy = graph_engine_copy.graph_runtime_state.variable_pool
             variable_pool_copy.add([self.node_id, "index"], index)
             variable_pool_copy.add([self.node_id, "item"], item)

api/core/workflow/nodes/iteration/iteration_start_node.py

@@ -1,7 +1,10 @@
+from collections.abc import Mapping, Sequence
+from typing import Any
+
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.nodes.base import BaseNode
 from core.workflow.nodes.enums import NodeType
-from core.workflow.nodes.iteration.entities import IterationStartNodeData
+from core.workflow.nodes.iteration.entities import IterationNodeData, IterationStartNodeData
 from models.workflow import WorkflowNodeExecutionStatus
 
 
@@ -18,3 +21,16 @@ class IterationStartNode(BaseNode):
         Run the node.
         """
         return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED)
+
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls, graph_config: Mapping[str, Any], node_id: str, node_data: IterationNodeData
+    ) -> Mapping[str, Sequence[str]]:
+        """
+        Extract variable selector to variable mapping
+        :param graph_config: graph config
+        :param node_id: node id
+        :param node_data: node data
+        :return:
+        """
+        return {}

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -240,7 +240,6 @@ class KnowledgeRetrievalNode(BaseNode[KnowledgeRetrievalNodeData]):
                                 "segment_word_count": segment.word_count,
                                 "segment_position": segment.position,
                                 "segment_index_node_hash": segment.index_node_hash,
-                                "doc_metadata": document.doc_metadata,
                             },
                             "title": document.name,
                         }

api/core/workflow/nodes/llm/node.py

@@ -1,7 +1,6 @@
 import json
 import logging
 from collections.abc import Generator, Mapping, Sequence
-from datetime import UTC, datetime
 from typing import TYPE_CHECKING, Any, Optional, cast
 
 from configs import dify_config
@@ -30,7 +29,6 @@ from core.model_runtime.entities.message_entities import (
 from core.model_runtime.entities.model_entities import ModelFeature, ModelPropertyKey, ModelType
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.plugin.entities.plugin import ModelProviderID
 from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.variables import (
@@ -191,22 +189,6 @@ class LLMNode(BaseNode[LLMNodeData]):
                     # deduct quota
                     self.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage)
                     break
-            outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason}
-
-            yield RunCompletedEvent(
-                run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                    inputs=node_inputs,
-                    process_data=process_data,
-                    outputs=outputs,
-                    metadata={
-                        NodeRunMetadataKey.TOTAL_TOKENS: usage.total_tokens,
-                        NodeRunMetadataKey.TOTAL_PRICE: usage.total_price,
-                        NodeRunMetadataKey.CURRENCY: usage.currency,
-                    },
-                    llm_usage=usage,
-                )
-            )
         except LLMNodeError as e:
             yield RunCompletedEvent(
                 run_result=NodeRunResult(
@@ -227,6 +209,23 @@ class LLMNode(BaseNode[LLMNodeData]):
                 )
             )
 
+        outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason}
+
+        yield RunCompletedEvent(
+            run_result=NodeRunResult(
+                status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                inputs=node_inputs,
+                process_data=process_data,
+                outputs=outputs,
+                metadata={
+                    NodeRunMetadataKey.TOTAL_TOKENS: usage.total_tokens,
+                    NodeRunMetadataKey.TOTAL_PRICE: usage.total_price,
+                    NodeRunMetadataKey.CURRENCY: usage.currency,
+                },
+                llm_usage=usage,
+            )
+        )
+
     def _invoke_llm(
         self,
         node_data_model: ModelConfig,
@@ -248,24 +247,6 @@ class LLMNode(BaseNode[LLMNodeData]):
 
     def _handle_invoke_result(self, invoke_result: LLMResult | Generator) -> Generator[NodeEvent, None, None]:
         if isinstance(invoke_result, LLMResult):
-            content = invoke_result.message.content
-            if content is None:
-                message_text = ""
-            elif isinstance(content, str):
-                message_text = content
-            elif isinstance(content, list):
-                # Assuming the list contains PromptMessageContent objects with a "data" attribute
-                message_text = "".join(
-                    item.data if hasattr(item, "data") and isinstance(item.data, str) else str(item) for item in content
-                )
-            else:
-                message_text = str(content)
-
-            yield ModelInvokeCompletedEvent(
-                text=message_text,
-                usage=invoke_result.usage,
-                finish_reason=None,
-            )
             return
 
         model = None
@@ -458,7 +439,6 @@ class LLMNode(BaseNode[LLMNodeData]):
                 "index_node_hash": metadata.get("segment_index_node_hash"),
                 "content": context_dict.get("content"),
                 "page": metadata.get("page"),
-                "doc_metadata": metadata.get("doc_metadata"),
             }
 
             return source
@@ -760,17 +740,11 @@ class LLMNode(BaseNode[LLMNodeData]):
         if used_quota is not None and system_configuration.current_quota_type is not None:
             db.session.query(Provider).filter(
                 Provider.tenant_id == tenant_id,
-                # TODO: Use provider name with prefix after the data migration.
-                Provider.provider_name == ModelProviderID(model_instance.provider).provider_name,
+                Provider.provider_name == model_instance.provider,
                 Provider.provider_type == ProviderType.SYSTEM.value,
                 Provider.quota_type == system_configuration.current_quota_type.value,
                 Provider.quota_limit > Provider.quota_used,
-            ).update(
-                {
-                    "quota_used": Provider.quota_used + used_quota,
-                    "last_used": datetime.now(tz=UTC).replace(tzinfo=None),
-                }
-            )
+            ).update({"quota_used": Provider.quota_used + used_quota})
             db.session.commit()
 
     @classmethod

api/core/workflow/nodes/start/start_node.py

@@ -1,3 +1,6 @@
+from collections.abc import Mapping, Sequence
+from typing import Any
+
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.nodes.base import BaseNode
@@ -20,3 +23,13 @@ class StartNode(BaseNode[StartNodeData]):
             node_inputs[SYSTEM_VARIABLE_NODE_ID + "." + var] = system_inputs[var]
 
         return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=node_inputs, outputs=node_inputs)
+
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls,
+        *,
+        graph_config: Mapping[str, Any],
+        node_id: str,
+        node_data: StartNodeData,
+    ) -> Mapping[str, Sequence[str]]:
+        return {}

api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py

@@ -1,3 +1,6 @@
+from collections.abc import Mapping, Sequence
+from typing import Any
+
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.nodes.base import BaseNode
 from core.workflow.nodes.enums import NodeType
@@ -33,3 +36,16 @@ class VariableAggregatorNode(BaseNode[VariableAssignerNodeData]):
                         break
 
         return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, outputs=outputs, inputs=inputs)
+
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls, *, graph_config: Mapping[str, Any], node_id: str, node_data: VariableAssignerNodeData
+    ) -> Mapping[str, Sequence[str]]:
+        """
+        Extract variable selector to variable mapping
+        :param graph_config: graph config
+        :param node_id: node id
+        :param node_data: node data
+        :return:
+        """
+        return {}

api/core/workflow/utils/condition/processor.py

@@ -64,10 +64,6 @@ class ConditionProcessor:
                     expected=expected_value,
                 )
             group_results.append(result)
-            # Implemented short-circuit evaluation for logical conditions
-            if (operator == "and" and not result) or (operator == "or" and result):
-                final_result = result
-                return input_conditions, group_results, final_result
 
         final_result = all(group_results) if operator == "and" else any(group_results)
         return input_conditions, group_results, final_result

api/events/event_handlers/deduct_quota_when_message_created.py

@@ -1,9 +1,6 @@
-from datetime import UTC, datetime
-
 from configs import dify_config
 from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, ChatAppGenerateEntity
 from core.entities.provider_entities import QuotaUnit
-from core.plugin.entities.plugin import ModelProviderID
 from events.message_event import message_was_created
 from extensions.ext_database import db
 from models.provider import Provider, ProviderType
@@ -51,15 +48,9 @@ def handle(sender, **kwargs):
     if used_quota is not None and system_configuration.current_quota_type is not None:
         db.session.query(Provider).filter(
             Provider.tenant_id == application_generate_entity.app_config.tenant_id,
-            # TODO: Use provider name with prefix after the data migration.
-            Provider.provider_name == ModelProviderID(model_config.provider).provider_name,
+            Provider.provider_name == model_config.provider,
             Provider.provider_type == ProviderType.SYSTEM.value,
             Provider.quota_type == system_configuration.current_quota_type.value,
             Provider.quota_limit > Provider.quota_used,
-        ).update(
-            {
-                "quota_used": Provider.quota_used + used_quota,
-                "last_used": datetime.now(tz=UTC).replace(tzinfo=None),
-            }
-        )
+        ).update({"quota_used": Provider.quota_used + used_quota})
         db.session.commit()

api/extensions/ext_proxy_fix.py

@@ -6,4 +6,4 @@ def init_app(app: DifyApp):
     if dify_config.RESPECT_XFORWARD_HEADERS_ENABLED:
         from werkzeug.middleware.proxy_fix import ProxyFix
 
-        app.wsgi_app = ProxyFix(app.wsgi_app, x_port=1)  # type: ignore
+        app.wsgi_app = ProxyFix(app.wsgi_app)  # type: ignore

api/fields/app_fields.py

@@ -198,7 +198,7 @@ app_site_fields = {
     "use_icon_as_answer_icon": fields.Boolean,
 }
 
-leaked_dependency_fields = {"type": fields.String, "value": fields.Raw, "current_identifier": fields.String}
+leaked_dependency_fields = {"type": fields.String, "value": fields.Raw}
 
 app_import_fields = {
     "id": fields.String,