fix: yarn install extract package err when using GitHub Cache in amd6… (#3383)

Co-authored-by: lbm21 <313338264@qq.com>
Co-authored-by: akou <beiming1201@gmail.com>

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -8,6 +8,8 @@ body:
       label: Self Checks
       description: "To make sure we get to you in time, please check the following :)"
       options:
+        - label: This is only for bug report, if you would like to ask a quesion, please head to [Discussions](https://github.com/langgenius/dify/discussions/categories/general).
+          required: true
         - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
           required: true
         - label: I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).

.github/ISSUE_TEMPLATE/config.yml

@@ -1,8 +1,5 @@
 blank_issues_enabled: false
 contact_links:
-  - name: "\U0001F4DA Dify user documentation"
-    url: https://docs.dify.ai/getting-started/readme
-    about: Documentation for users of Dify
-  - name: "\U0001F4DA Dify dev documentation"
-    url: https://docs.dify.ai/getting-started/install-self-hosted
-    about: Documentation for people interested in developing and contributing for Dify
+  - name: "\U0001F4E7 Discussions"
+    url: https://github.com/langgenius/dify/discussions/categories/general
+    about: General discussions and request help from the community

.github/ISSUE_TEMPLATE/help_wanted.yml

@@ -1,22 +0,0 @@
-name: "🤝 Help Wanted"
-description: "Request help from the community [please use English :）]"
-labels:
-  - help-wanted
-body:
-  - type: checkboxes
-    attributes:
-      label: Self Checks
-      description: "To make sure we get to you in time, please check the following :)"
-      options:
-        - label: I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
-          required: true
-        - label: I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)).
-          required: true
-        - label: "Pleas do not modify this template :) and fill in all the required fields."
-          required: true
-  - type: textarea
-    attributes:
-      label: Provide a description of the help you need
-      placeholder: Briefly describe what you need help with.
-    validations:
-      required: true

.github/pull_request_template.md

@@ -12,6 +12,8 @@ Please delete options that are not relevant.
 - [ ] New feature (non-breaking change which adds functionality)
 - [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
 - [ ] This change requires a documentation update, included: [Dify Document](https://github.com/langgenius/dify-docs)
+- [ ] Improvement, including but not limited to code refactoring, performance optimization, and UI/UX improvement
+- [ ] Dependency upgrade
 
 # How Has This Been Tested?
 

.github/workflows/api-tests.yml

@@ -26,6 +26,7 @@ jobs:
       HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL: b
       HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL: c
       MOCK_SWITCH: true
+      CODE_MAX_STRING_LENGTH: 80000
 
     steps:
       - name: Checkout code
@@ -41,5 +42,11 @@ jobs:
       - name: Install dependencies
         run: pip install -r ./api/requirements.txt
 
-      - name: Run pytest
+      - name: Run ModelRuntime
         run: pytest api/tests/integration_tests/model_runtime/anthropic api/tests/integration_tests/model_runtime/azure_openai api/tests/integration_tests/model_runtime/openai api/tests/integration_tests/model_runtime/chatglm api/tests/integration_tests/model_runtime/google api/tests/integration_tests/model_runtime/xinference api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py
+
+      - name: Run Tool
+        run: pytest api/tests/integration_tests/tools/test_all_provider.py
+
+      - name: Run Workflow
+        run: pytest api/tests/integration_tests/workflow

.github/workflows/build-push.yml

@@ -1,17 +1,32 @@
-name: Build and Push API Image
+name: Build and Push API & Web
 
 on:
   push:
     branches:
-      - 'main'
-      - 'deploy/dev'
+      - "main"
+      - "deploy/dev"
   release:
-    types: [ published ]
+    types: [published]
+
+env:
+  DOCKERHUB_USER: ${{ secrets.DOCKERHUB_USER }}
+  DOCKERHUB_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}
+  DIFY_WEB_IMAGE_NAME: ${{ vars.DIFY_WEB_IMAGE_NAME || 'langgenius/dify-web' }}
+  DIFY_API_IMAGE_NAME: ${{ vars.DIFY_API_IMAGE_NAME || 'langgenius/dify-api' }}
 
 jobs:
   build-and-push:
     runs-on: ubuntu-latest
     if: github.event.pull_request.draft == false
+    strategy:
+      matrix:
+        include:
+          - service_name: "web"
+            image_name_env: "DIFY_WEB_IMAGE_NAME"
+            context: "web"
+          - service_name: "api"
+            image_name_env: "DIFY_API_IMAGE_NAME"
+            context: "api"
     steps:
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v3
@@ -22,14 +37,14 @@ jobs:
       - name: Login to Docker Hub
         uses: docker/login-action@v2
         with:
-          username: ${{ secrets.DOCKERHUB_USER }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
+          username: ${{ env.DOCKERHUB_USER }}
+          password: ${{ env.DOCKERHUB_TOKEN }}
 
       - name: Extract metadata (tags, labels) for Docker
         id: meta
         uses: docker/metadata-action@v5
         with:
-          images: langgenius/dify-api
+          images: ${{ env[matrix.image_name_env] }}
           tags: |
             type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') }}
             type=ref,event=branch
@@ -39,22 +54,11 @@ jobs:
       - name: Build and push
         uses: docker/build-push-action@v5
         with:
-          context: "{{defaultContext}}:api"
+          context: "{{defaultContext}}:${{ matrix.context }}"
           platforms: ${{ startsWith(github.ref, 'refs/tags/') && 'linux/amd64,linux/arm64' || 'linux/amd64' }}
-          build-args: |
-            COMMIT_SHA=${{ fromJSON(steps.meta.outputs.json).labels['org.opencontainers.image.revision'] }}
+          build-args: COMMIT_SHA=${{ fromJSON(steps.meta.outputs.json).labels['org.opencontainers.image.revision'] }}
           push: true
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
           cache-from: type=gha
           cache-to: type=gha,mode=max
-
-      - name: Deploy to server
-        if: github.ref == 'refs/heads/deploy/dev'
-        uses: appleboy/ssh-action@v0.1.8
-        with:
-          host: ${{ secrets.SSH_HOST }}
-          username: ${{ secrets.SSH_USER }}
-          key: ${{ secrets.SSH_PRIVATE_KEY }}
-          script: |
-            ${{ secrets.SSH_SCRIPT }}

.github/workflows/build-web-image.yml

@@ -1,60 +0,0 @@
-name: Build and Push WEB Image
-
-on:
-  push:
-    branches:
-      - 'main'
-      - 'deploy/dev'
-  release:
-    types: [ published ]
-
-jobs:
-  build-and-push:
-    runs-on: ubuntu-latest
-    if: github.event.pull_request.draft == false
-    steps:
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v3
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-
-      - name: Login to Docker Hub
-        uses: docker/login-action@v2
-        with:
-          username: ${{ secrets.DOCKERHUB_USER }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
-
-      - name: Extract metadata (tags, labels) for Docker
-        id: meta
-        uses: docker/metadata-action@v5
-        with:
-          images: langgenius/dify-web
-          tags: |
-            type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') }}
-            type=ref,event=branch
-            type=sha,enable=true,priority=100,prefix=,suffix=,format=long
-            type=raw,value=${{ github.ref_name }},enable=${{ startsWith(github.ref, 'refs/tags/') }}
-
-      - name: Build and push
-        uses: docker/build-push-action@v5
-        with:
-          context: "{{defaultContext}}:web"
-          platforms: ${{ startsWith(github.ref, 'refs/tags/') && 'linux/amd64,linux/arm64' || 'linux/amd64' }}
-          build-args: |
-            COMMIT_SHA=${{ fromJSON(steps.meta.outputs.json).labels['org.opencontainers.image.revision'] }}
-          push: true
-          tags: ${{ steps.meta.outputs.tags }}
-          labels: ${{ steps.meta.outputs.labels }}
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
-
-      - name: Deploy to server
-        if: github.ref == 'refs/heads/deploy/dev'
-        uses: appleboy/ssh-action@v0.1.8
-        with:
-          host: ${{ secrets.SSH_HOST }}
-          username: ${{ secrets.SSH_USER }}
-          key: ${{ secrets.SSH_PRIVATE_KEY }}
-          script: |
-            ${{ secrets.SSH_SCRIPT }}

.github/workflows/deploy-dev.yml

@@ -0,0 +1,24 @@
+name: Deploy Dev
+
+on:
+  workflow_run:
+    workflows: ["Build and Push API & Web"]
+    branches:
+      - "deploy/dev"
+    types:
+      - completed
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    if: |
+      github.event.workflow_run.conclusion == 'success'
+    steps:
+      - name: Deploy to server
+        uses: appleboy/ssh-action@v0.1.8
+        with:
+          host: ${{ secrets.SSH_HOST }}
+          username: ${{ secrets.SSH_USER }}
+          key: ${{ secrets.SSH_PRIVATE_KEY }}
+          script: |
+            ${{ vars.SSH_SCRIPT || secrets.SSH_SCRIPT }}

.github/workflows/tool-tests.yaml

@@ -1,26 +0,0 @@
-name: Run Tool Pytest
-
-on:
-  pull_request:
-    branches:
-      - main
-
-jobs:
-  test:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.10'
-          cache: 'pip'
-          cache-dependency-path: ./api/requirements.txt
-
-      - name: Install dependencies
-        run: pip install -r ./api/requirements.txt
-
-      - name: Run pytest
-        run: pytest ./api/tests/integration_tests/tools/test_all_provider.py

.gitignore

@@ -145,10 +145,14 @@ docker/volumes/db/data/*
 docker/volumes/redis/data/*
 docker/volumes/weaviate/*
 docker/volumes/qdrant/*
+docker/volumes/etcd/*
+docker/volumes/minio/*
+docker/volumes/milvus/*
 
 sdks/python-client/build
 sdks/python-client/dist
 sdks/python-client/dify_client.egg-info
 
 .vscode/*
-!.vscode/launch.json
+!.vscode/launch.json
+pyrightconfig.json

CONTRIBUTING.md

@@ -36,7 +36,7 @@ In terms of licensing, please take a minute to read our short [License and Contr
   | Feature Type                                                 | Priority        |
   | ------------------------------------------------------------ | --------------- |
   | High-Priority Features as being labeled by a team member     | High Priority   |
-  | Popular feature requests from our [community feedback board](https://feedback.dify.ai/) | Medium Priority |
+  | Popular feature requests from our [community feedback board](https://github.com/langgenius/dify/discussions/categories/feedbacks) | Medium Priority |
   | Non-core features and minor enhancements                     | Low Priority    |
   | Valuable but not immediate                                   | Future-Feature  |
 
@@ -155,4 +155,4 @@ And that's it! Once your PR is merged, you will be featured as a contributor in
 
 ## Getting Help
 
-If you ever get stuck or got a burning question while contributing, simply shoot your queries our way via the related GitHub issue, or hop onto our [Discord](https://discord.gg/AhzKf7dNgk) for a quick chat. 
+If you ever get stuck or got a burning question while contributing, simply shoot your queries our way via the related GitHub issue, or hop onto our [Discord](https://discord.gg/8Tpq4AcN9c) for a quick chat. 

CONTRIBUTING_CN.md

@@ -34,7 +34,7 @@
   | Feature Type                                                 | Priority        |
   | ------------------------------------------------------------ | --------------- |
   | High-Priority Features as being labeled by a team member     | High Priority   |
-  | Popular feature requests from our [community feedback board](https://feedback.dify.ai/) | Medium Priority |
+  | Popular feature requests from our [community feedback board](https://github.com/langgenius/dify/discussions/categories/feedbacks) | Medium Priority |
   | Non-core features and minor enhancements                     | Low Priority    |
   | Valuable but not immediate                                   | Future-Feature  |
 
@@ -152,4 +152,4 @@ Dify的后端使用Python编写，使用[Flask](https://flask.palletsprojects.co
 
 ## 获取帮助
 
-如果你在贡献过程中遇到困难或者有任何问题，可以通过相关的 GitHub 问题提出你的疑问，或者加入我们的 [Discord](https://discord.gg/AhzKf7dNgk) 进行快速交流。
+如果你在贡献过程中遇到困难或者有任何问题，可以通过相关的 GitHub 问题提出你的疑问，或者加入我们的 [Discord](https://discord.gg/8Tpq4AcN9c) 进行快速交流。

Makefile

@@ -0,0 +1,43 @@
+# Variables
+DOCKER_REGISTRY=langgenius
+WEB_IMAGE=$(DOCKER_REGISTRY)/dify-web
+API_IMAGE=$(DOCKER_REGISTRY)/dify-api
+VERSION=latest
+
+# Build Docker images
+build-web:
+	@echo "Building web Docker image: $(WEB_IMAGE):$(VERSION)..."
+	docker build -t $(WEB_IMAGE):$(VERSION) ./web
+	@echo "Web Docker image built successfully: $(WEB_IMAGE):$(VERSION)"
+
+build-api:
+	@echo "Building API Docker image: $(API_IMAGE):$(VERSION)..."
+	docker build -t $(API_IMAGE):$(VERSION) ./api
+	@echo "API Docker image built successfully: $(API_IMAGE):$(VERSION)"
+
+# Push Docker images
+push-web:
+	@echo "Pushing web Docker image: $(WEB_IMAGE):$(VERSION)..."
+	docker push $(WEB_IMAGE):$(VERSION)
+	@echo "Web Docker image pushed successfully: $(WEB_IMAGE):$(VERSION)"
+
+push-api:
+	@echo "Pushing API Docker image: $(API_IMAGE):$(VERSION)..."
+	docker push $(API_IMAGE):$(VERSION)
+	@echo "API Docker image pushed successfully: $(API_IMAGE):$(VERSION)"
+
+# Build all images
+build-all: build-web build-api
+
+# Push all images
+push-all: push-web push-api
+
+build-push-api: build-api push-api
+build-push-web: build-web push-web
+
+# Build and push all images
+build-push-all: build-all push-all
+	@echo "All Docker images have been built and pushed."
+
+# Phony targets
+.PHONY: build-web build-api push-web push-api build-all push-all build-push-all

README.md

@@ -1,103 +1,176 @@
-[![](./images/describe.png)](https://dify.ai)
+![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
+
 <p align="center">
-  <a href="./README.md">English</a> |
-  <a href="./README_CN.md">简体中文</a> |
-  <a href="./README_JA.md">日本語</a> |
-  <a href="./README_ES.md">Español</a> |
-  <a href="./README_KL.md">Klingon</a> |
-  <a href="./README_FR.md">Français</a>
+  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
+  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> ·
+  <a href="https://docs.dify.ai">Documentation</a> ·
+  <a href="https://cal.com/guchenhe/30min">Commercial inquiry</a>
 </p>
 
 <p align="center">
     <a href="https://dify.ai" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/AI-Dify?logo=AI&logoColor=%20%23f5f5f5&label=Dify&labelColor=%20%23155EEF&color=%23EAECF0"></a>
+        <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"
+        <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://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
-        <img src="https://img.shields.io/twitter/follow/dify_ai?style=social&logo=X"
+        <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
             alt="follow on Twitter"></a>
     <a href="https://hub.docker.com/u/langgenius" target="_blank">
-        <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web"></a>
+        <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="https://discord.com/events/1082486657678311454/1211724120996188220" target="_blank">
-   Dify.AI Upcoming Meetup Event [👉 Click to Join the Event Here 👈]
-  </a>
-   <ul align="center" style="text-decoration: none; list-style: none;">
-      <li> US EST: 09:00 (9:00 AM)</li>
-      <li> CET: 15:00 (3:00 PM)</li>
-      <li> CST:  22:00 (10:00 PM)</li>
-   </ul>
+  <a href="./README.md"><img alt="Commits last month" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="Commits last month" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="Commits last month" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="Commits last month" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="Commits last month" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="Commits last month" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
 </p>
 
+#
+
 <p align="center">
-   <a href="https://dify.ai/blog/dify-ai-unveils-ai-agent-creating-gpts-and-assistants-with-various-llms" target="_blank">
-   Dify.AI Unveils AI Agent: Creating GPTs and Assistants with Various LLMs
-  </a>
+  <a href="https://trendshift.io/repositories/2152" target="_blank"><img src="https://trendshift.io/api/badge/repositories/2152" alt="langgenius%2Fdify | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 </p>
+Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production. Here's a list of the core features:
+</br> </br>
 
-**Dify** is an LLM application development platform that has helped built over **100,000** applications. It integrates BaaS and LLMOps, covering the essential tech stack for building generative AI-native applications, including a built-in RAG engine. Dify allows you to **deploy your own version of Assistants API and GPTs, based on any LLMs.**
+**1. Workflow**: 
+  Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.
 
-![](./images/demo.png)
+
+  https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
 
 
 
-## Using our Cloud Services
+**2. Comprehensive model support**: 
+  Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama2, and any OpenAI API-compatible models. A full list of supported model providers can be found [here](https://docs.dify.ai/getting-started/readme/model-providers).
 
-You can try out [Dify.AI Cloud](https://dify.ai) now. It provides all the capabilities of the self-deployed version, and includes 200 free requests to OpenAI GPT-3.5.
+![providers-v3](https://github.com/langgenius/dify/assets/13230914/55fab860-d818-4c95-95a2-7ac39f6aea83)
 
-## Dify vs. LangChain vs. Assistants API
 
-| Feature | Dify.AI | Assistants API | LangChain |
-|---------|---------|----------------|-----------|
-| **Programming Approach** | API-oriented | API-oriented | Python Code-oriented |
-| **Ecosystem Strategy** | Open Source | Close Source | Open Source |
-| **RAG Engine** | Supported | Supported | Not Supported |
-| **Prompt IDE** | Included | Included | None |
-| **Supported LLMs** | Rich Variety | OpenAI-only | Rich Variety |
-| **Local Deployment** | Supported | Not Supported | Not Applicable |
+**3. Prompt IDE**: 
+  Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app. 
+
+**4. RAG Pipeline**: 
+  Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.
+
+**5. Agent capabilities**: 
+  You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DELL·E, Stable Diffusion and WolframAlpha.
+
+**6. LLMOps**: 
+  Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.
+
+**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
+
+- **Cloud </br>**
+We host a [Dify Cloud](https://dify.ai) service for anyone to try with zero setup. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls in the sandbox plan.
+
+- **Self-hosting Dify Community Edition</br>**
+Quickly get Dify running in your environment with this [starter guide](#quick-start).
+Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions.
+
+- **Dify for Enterprise / Organizations</br>**
+We provide additional enterprise-centric features. [Schedule a meeting with us](https://cal.com/guchenhe/30min) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
+  > For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click. It's an affordable AMI offering with the option to create apps with custom logo and branding.
+
+
+## Staying ahead
+
+Star Dify on GitHub and be instantly notified of new releases.
+
+![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
 
 
 
-## Features
+## Quick Start
+> Before installing Dify, make sure your machine meets the following minimum system requirements:
+> 
+>- CPU >= 2 Core
+>- RAM >= 4GB
 
-![](./images/models.png)
-
-**1. LLM Support**: Integration with OpenAI's GPT family of models, or the open-source Llama2 family models. In fact, Dify supports mainstream commercial models and open-source models (locally deployed or based on MaaS).
-
-**2. Prompt IDE**: Visual orchestration of applications and services based on LLMs with your team.
-
-**3. RAG Engine**: Includes various RAG capabilities based on full-text indexing or vector database embeddings, allowing direct upload of PDFs, TXTs, and other text formats.
-
-**4. AI Agent**: Based on Function Calling and ReAct, the Agent inference framework allows users to customize tools, what you see is what you get. Dify provides more than a dozen built-in tool calling capabilities, such as Google Search, DELL·E, Stable Diffusion, WolframAlpha, etc.
-
-
-**5. Continuous Operations**: Monitor and analyze application logs and performance, continuously improving Prompts, datasets, or models using production data.
-
-## Before You Start
-
-**Star us on GitHub, and be instantly notified for new releases!**
-
-![star-us](https://github.com/langgenius/dify/assets/100913391/95f37259-7370-4456-a9f0-0bc01ef8642f)
-
-- [Website](https://dify.ai)
-- [Docs](https://docs.dify.ai)
-- [Deployment Docs](https://docs.dify.ai/getting-started/install-self-hosted)
-- [FAQ](https://docs.dify.ai/getting-started/faq) 
-
-
-## Install the Community Edition
-
-### System Requirements
-
-Before installing Dify, make sure your machine meets the following minimum system requirements:
-
-- CPU >= 2 Core
-- RAM >= 4GB
-
-### Quick Start
+</br>
 
 The easiest way to start the Dify server is to run our [docker-compose.yml](docker/docker-compose.yaml) file. Before running the installation command, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:
 
@@ -106,55 +179,63 @@ cd docker
 docker compose up -d
 ```
 
-After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization installation process.
+After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization process.
 
-### Helm Chart
+> If you'd like to contribute to Dify or do additional development, refer to our [guide to deploying from source code](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
 
-Big thanks to @BorisPolonsky for providing us with a [Helm Chart](https://helm.sh/) version, which allows Dify to be deployed on Kubernetes.
-You can go to https://github.com/BorisPolonsky/dify-helm for deployment information.
+## Next steps
 
-### Configuration
+If you need to customize the configuration, please refer to the comments in our [docker-compose.yml](docker/docker-compose.yaml) file and manually set the environment configuration. After making the changes, please run `docker-compose up -d` again. You can see the full list of environment variables [here](https://docs.dify.ai/getting-started/install-self-hosted/environments).
 
-If you need to customize the configuration, please refer to the comments in our [docker-compose.yml](docker/docker-compose.yaml) file and manually set the environment configuration. After making the changes, please run `docker-compose up -d` again. You can see the full list of environment variables in our [docs](https://docs.dify.ai/getting-started/install-self-hosted/environments).
+If you'd like to configure a highly-available setup, there are community-contributed [Helm Charts](https://helm.sh/) which allow Dify to be deployed on Kubernetes.
 
+- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
+- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
 
-## Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
 
 ## Contributing
 
 For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). 
-
 At the same time, please consider supporting Dify by sharing it on social media and at events and conferences.
 
-### Contributors
+
+> We are looking for contributors to help with translating Dify to languages other than Mandarin or English. If you are interested in helping, please see the [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).
+
+**Contributors**
 
 <a href="https://github.com/langgenius/dify/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langgenius/dify" />
 </a>
 
-### Translations
+## Community & Contact
 
-We are looking for contributors to help with translating Dify to languages other than Mandarin or English. If you are interested in helping, please see the [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README_EN.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/AhzKf7dNgk).
-
-## Community & Support
-
-* [Canny](https://feedback.dify.ai/). Best for: sharing feedback and checking out our feature roadmap.
+* [Github Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
-* [Email Support](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify). Best for: questions you have about using Dify.AI.
+* [Email](mailto:support@dify.ai?subject=[GitHub]Questions%20About%20Dify). Best for: questions you have about using Dify.AI.
 * [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
 * [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.
-* [Business Contact](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry). Best for: business inquiries of licensing Dify.AI for commercial use.
 
-### Direct Meetings
+Or, schedule a meeting directly with a team member:
 
-**Help us make Dify better. Reach out directly to us**.
+<table>
+  <tr>
+    <th>Point of Contact</th>
+    <th>Purpose</th>
+  </tr>
+  <tr>
+    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
+    <td>Business enquiries & product feedback</td>
+  </tr>
+  <tr>
+    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
+    <td>Contributions, issues & feature requests</td>
+  </tr>
+</table>
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
 
-|                       Point of Contact                       |                           Purpose                            |
-| :----------------------------------------------------------: | :----------------------------------------------------------: |
-| <a href='https://cal.com/guchenhe/15min' target='_blank'><img src='https://i.postimg.cc/fWBqSmjP/Git-Hub-README-Button-3x.png' border='0' alt='Git-Hub-README-Button-3x' height="60" width="214"/></a> | Product design feedback, user experience discussions, feature planning and roadmaps. |
-| <a href='https://cal.com/pinkbanana' target='_blank'><img src='https://i.postimg.cc/LsRTh87D/Git-Hub-README-Button-2x.png' border='0' alt='Git-Hub-README-Button-2x' height="60" width="225"/></a> |        Technical support, issues, or feature requests        |
 
 ## Security Disclosure
 

README_CN.md

@@ -21,6 +21,10 @@
         <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web"></a>
 </p>
 
+<p align="center">
+<a href="https://trendshift.io/repositories/2152" target="_blank"><img src="https://trendshift.io/api/badge/repositories/2152" alt="langgenius%2Fdify | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
 <p align="center">
    <a href="https://mp.weixin.qq.com/s/TnyfIuH-tPi9o1KNjwVArw" target="_blank">
    Dify 发布 AI Agent 能力：基于不同的大型语言模型构建 GPTs 和 Assistants
@@ -94,10 +98,12 @@ docker compose up -d
 
 运行后，可以在浏览器上访问 [http://localhost/install](http://localhost/install) 进入 Dify 控制台并开始初始化安装操作。
 
-### Helm Chart
+#### 使用 Helm Chart 部署
 
-非常感谢 @BorisPolonsky 为我们提供了一个 [Helm Chart](https://helm.sh/) 版本，可以在 Kubernetes 上部署 Dify。
-您可以前往 https://github.com/BorisPolonsky/dify-helm 来获取部署信息。
+使用 [Helm Chart](https://helm.sh/) 版本，可以在 Kubernetes 上部署 Dify。
+
+- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
+- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
 
 ### 配置
 
@@ -112,6 +118,7 @@ docker compose up -d
 
 我们欢迎您为 Dify 做出贡献，以帮助改善 Dify。包括：提交代码、问题、新想法，或分享您基于 Dify 创建的有趣且有用的 AI 应用程序。同时，我们也欢迎您在不同的活动、会议和社交媒体上分享 Dify。
 
+- [Github Discussion](https://github.com/langgenius/dify/discussions). 👉：分享您的应用程序并与社区交流。
 - [GitHub Issues](https://github.com/langgenius/dify/issues)。👉：使用 Dify.AI 时遇到的错误和问题，请参阅[贡献指南](CONTRIBUTING.md)。
 - [电子邮件支持](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify)。👉：关于使用 Dify.AI 的问题。
 - [Discord](https://discord.gg/FngNHpbcY7)。👉：分享您的应用程序并与社区交流。

README_JA.md

@@ -115,6 +115,7 @@ docker compose up -d
 
 Difyに貢献していただき、コードの提出、問題の報告、新しいアイデアの提供、またはDifyを基に作成した興味深く有用なAIアプリケーションの共有により、Difyをより良いものにするお手伝いを歓迎します。同時に、さまざまなイベント、会議、ソーシャルメディアでDifyを共有することも歓迎します。
 
+- [Github Discussion](https://github.com/langgenius/dify/discussions). 👉：アプリを共有し、コミュニティとコミュニケーション。
 - [GitHub Issues](https://github.com/langgenius/dify/issues)。最適な使用法：Dify.AIの使用中に遭遇するバグやエラー、[貢献ガイド](CONTRIBUTING.md)を参照。
 - [Email サポート](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify)。最適な使用法：Dify.AIの使用に関する質問。
 - [Discord](https://discord.gg/FngNHpbcY7)。最適な使用法：アプリケーションの共有とコミュニティとの交流。

api/.env.example

@@ -39,7 +39,7 @@ DB_DATABASE=dify
 
 # Storage configuration
 # use for store upload files, private keys...
-# storage type: local, s3
+# storage type: local, s3, azure-blob
 STORAGE_TYPE=local
 STORAGE_LOCAL_PATH=storage
 S3_ENDPOINT=https://your-bucket-name.storage.s3.clooudflare.com
@@ -47,6 +47,11 @@ S3_BUCKET_NAME=your-bucket-name
 S3_ACCESS_KEY=your-access-key
 S3_SECRET_KEY=your-secret-key
 S3_REGION=your-region
+# Azure Blob Storage configuration
+AZURE_BLOB_ACCOUNT_NAME=your-account-name
+AZURE_BLOB_ACCOUNT_KEY=your-account-key
+AZURE_BLOB_CONTAINER_NAME=yout-container-name
+AZURE_BLOB_ACCOUNT_URL=https://<your_account_name>.blob.core.windows.net
 
 # CORS configuration
 WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
@@ -132,3 +137,15 @@ SSRF_PROXY_HTTP_URL=
 SSRF_PROXY_HTTPS_URL=
 
 BATCH_UPLOAD_LIMIT=10
+KEYWORD_DATA_SOURCE_TYPE=database
+
+# CODE EXECUTION CONFIGURATION
+CODE_EXECUTION_ENDPOINT=http://127.0.0.1:8194
+CODE_EXECUTION_API_KEY=dify-sandbox
+CODE_MAX_NUMBER=9223372036854775807
+CODE_MIN_NUMBER=-9223372036854775808
+CODE_MAX_STRING_LENGTH=80000
+TEMPLATE_TRANSFORM_MAX_LENGTH=80000
+CODE_MAX_STRING_ARRAY_LENGTH=30
+CODE_MAX_OBJECT_ARRAY_LENGTH=30
+CODE_MAX_NUMBER_ARRAY_LENGTH=1000

api/.vscode/launch.json

@@ -6,7 +6,7 @@
     "configurations": [
         {
             "name": "Python: Celery",
-            "type": "python",
+            "type": "debugpy",
             "request": "launch",
             "module": "celery",
             "justMyCode": true,
@@ -21,7 +21,7 @@
         },
         {
             "name": "Python: Flask",
-            "type": "python",
+            "type": "debugpy",
             "request": "launch",
             "module": "flask",
             "env": {

api/Dockerfile

@@ -11,7 +11,8 @@ RUN apt-get update \
 
 COPY requirements.txt /requirements.txt
 
-RUN pip install --prefix=/pkg -r requirements.txt
+RUN --mount=type=cache,target=/root/.cache/pip \
+    pip install --prefix=/pkg -r requirements.txt
 
 # production stage
 FROM base AS production

api/README.md

@@ -5,7 +5,7 @@
 1. Start the docker-compose stack
 
    The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using `docker-compose`.
-   
+
    ```bash
    cd ../docker
    docker-compose -f docker-compose.middleware.yaml -p dify up -d
@@ -15,18 +15,18 @@
 3. Generate a `SECRET_KEY` in the `.env` file.
 
    ```bash
-   openssl rand -base64 42
+   sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
    ```
-3.5 If you use annaconda, create a new environment and activate it
+4. If you use Anaconda, create a new environment and activate it
    ```bash
    conda create --name dify python=3.10
    conda activate dify
    ```
-4. Install dependencies
+5. Install dependencies
    ```bash
    pip install -r requirements.txt
    ```
-5. Run migrate
+6. Run migrate
 
    Before the first launch, migrate the database to the latest version.
 
@@ -46,10 +46,12 @@
    ```
    pip install -r requirements.txt --upgrade --force-reinstall
    ```
-   
-6. Start backend:
+
+7. Start backend:
    ```bash
    flask run --host 0.0.0.0 --port=5001 --debug
    ```
-7. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
-8. If you need to debug local async processing, you can run `celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail`, celery can do dataset importing and other async tasks.
+8. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
+9. If you need to debug local async processing, please start the worker service by running 
+`celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail`.
+The started celery app handles the async tasks, e.g. dataset importing and documents indexing.

api/app.py

@@ -26,6 +26,7 @@ from config import CloudEditionConfig, Config
 from extensions import (
     ext_celery,
     ext_code_based_extension,
+    ext_compress,
     ext_database,
     ext_hosting_provider,
     ext_login,
@@ -96,6 +97,7 @@ def create_app(test_config=None) -> Flask:
 def initialize_extensions(app):
     # Since the application instance is now created, pass it to each Flask
     # extension instance to bind it to the Flask application instance (app)
+    ext_compress.init_app(app)
     ext_code_based_extension.init()
     ext_database.init_app(app)
     ext_migrate.init(app, db)

api/commands.py

@@ -15,7 +15,7 @@ from libs.rsa import generate_key_pair
 from models.account import Tenant
 from models.dataset import Dataset, DatasetCollectionBinding, DocumentSegment
 from models.dataset import Document as DatasetDocument
-from models.model import Account, App, AppAnnotationSetting, MessageAnnotation
+from models.model import Account, App, AppAnnotationSetting, AppMode, Conversation, MessageAnnotation
 from models.provider import Provider, ProviderModel
 
 
@@ -109,19 +109,20 @@ def reset_encrypt_key_pair():
         click.echo(click.style('Sorry, only support SELF_HOSTED mode.', fg='red'))
         return
 
-    tenant = db.session.query(Tenant).first()
-    if not tenant:
-        click.echo(click.style('Sorry, no workspace found. Please enter /install to initialize.', fg='red'))
-        return
+    tenants = db.session.query(Tenant).all()
+    for tenant in tenants:
+        if not tenant:
+            click.echo(click.style('Sorry, no workspace found. Please enter /install to initialize.', fg='red'))
+            return
 
-    tenant.encrypt_public_key = generate_key_pair(tenant.id)
+        tenant.encrypt_public_key = generate_key_pair(tenant.id)
 
-    db.session.query(Provider).filter(Provider.provider_type == 'custom').delete()
-    db.session.query(ProviderModel).delete()
-    db.session.commit()
+        db.session.query(Provider).filter(Provider.provider_type == 'custom', Provider.tenant_id == tenant.id).delete()
+        db.session.query(ProviderModel).filter(ProviderModel.tenant_id == tenant.id).delete()
+        db.session.commit()
 
-    click.echo(click.style('Congratulations! '
-                           'the asymmetric key pair of workspace {} has been reset.'.format(tenant.id), fg='green'))
+        click.echo(click.style('Congratulations! '
+                               'the asymmetric key pair of workspace {} has been reset.'.format(tenant.id), fg='green'))
 
 
 @click.command('vdb-migrate', help='migrate vector db.')
@@ -254,7 +255,7 @@ def migrate_knowledge_vector_database():
         for dataset in datasets:
             total_count = total_count + 1
             click.echo(f'Processing the {total_count} dataset {dataset.id}. '
-                       + f'{create_count} created, ${skipped_count} skipped.')
+                       + f'{create_count} created, {skipped_count} skipped.')
             try:
                 click.echo('Create dataset vdb index: {}'.format(dataset.id))
                 if dataset.index_struct_dict:
@@ -370,8 +371,70 @@ def migrate_knowledge_vector_database():
                     fg='green'))
 
 
+@click.command('convert-to-agent-apps', help='Convert Agent Assistant to Agent App.')
+def convert_to_agent_apps():
+    """
+    Convert Agent Assistant to Agent App.
+    """
+    click.echo(click.style('Start convert to agent apps.', fg='green'))
+
+    proceeded_app_ids = []
+
+    while True:
+        # fetch first 1000 apps
+        sql_query = """SELECT a.id AS id FROM apps a
+            INNER JOIN app_model_configs am ON a.app_model_config_id=am.id
+            WHERE a.mode = 'chat' 
+            AND am.agent_mode is not null 
+            AND (
+				am.agent_mode like '%"strategy": "function_call"%' 
+                OR am.agent_mode  like '%"strategy": "react"%'
+			) 
+            AND (
+				am.agent_mode like '{"enabled": true%' 
+                OR am.agent_mode like '{"max_iteration": %'
+			) ORDER BY a.created_at DESC LIMIT 1000
+        """
+
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(sql_query))
+
+            apps = []
+            for i in rs:
+                app_id = str(i.id)
+                if app_id not in proceeded_app_ids:
+                    proceeded_app_ids.append(app_id)
+                    app = db.session.query(App).filter(App.id == app_id).first()
+                    apps.append(app)
+
+            if len(apps) == 0:
+                break
+
+        for app in apps:
+            click.echo('Converting app: {}'.format(app.id))
+
+            try:
+                app.mode = AppMode.AGENT_CHAT.value
+                db.session.commit()
+
+                # update conversation mode to agent
+                db.session.query(Conversation).filter(Conversation.app_id == app.id).update(
+                    {Conversation.mode: AppMode.AGENT_CHAT.value}
+                )
+
+                db.session.commit()
+                click.echo(click.style('Converted app: {}'.format(app.id), fg='green'))
+            except Exception as e:
+                click.echo(
+                    click.style('Convert app error: {} {}'.format(e.__class__.__name__,
+                                                                  str(e)), fg='red'))
+
+    click.echo(click.style('Congratulations! Converted {} agent apps.'.format(len(proceeded_app_ids)), fg='green'))
+
+
 def register_commands(app):
     app.cli.add_command(reset_password)
     app.cli.add_command(reset_email)
     app.cli.add_command(reset_encrypt_key_pair)
     app.cli.add_command(vdb_migrate)
+    app.cli.add_command(convert_to_agent_apps)

api/config.py

@@ -22,11 +22,13 @@ DEFAULTS = {
     'SERVICE_API_URL': 'https://api.dify.ai',
     'APP_WEB_URL': 'https://udify.app',
     'FILES_URL': '',
+    'S3_ADDRESS_STYLE': 'auto',
     'STORAGE_TYPE': 'local',
     'STORAGE_LOCAL_PATH': 'storage',
     'CHECK_UPDATE_URL': 'https://updates.dify.ai',
     'DEPLOY_ENV': 'PRODUCTION',
     'SQLALCHEMY_POOL_SIZE': 30,
+    'SQLALCHEMY_MAX_OVERFLOW': 10,
     'SQLALCHEMY_POOL_RECYCLE': 3600,
     'SQLALCHEMY_ECHO': 'False',
     'SENTRY_TRACES_SAMPLE_RATE': 1.0,
@@ -40,7 +42,7 @@ DEFAULTS = {
     'HOSTED_OPENAI_TRIAL_ENABLED': 'False',
     'HOSTED_OPENAI_TRIAL_MODELS': 'gpt-3.5-turbo,gpt-3.5-turbo-1106,gpt-3.5-turbo-instruct,gpt-3.5-turbo-16k,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-0613,gpt-3.5-turbo-0125,text-davinci-003',
     'HOSTED_OPENAI_PAID_ENABLED': 'False',
-    'HOSTED_OPENAI_PAID_MODELS': 'gpt-4,gpt-4-turbo-preview,gpt-4-1106-preview,gpt-4-0125-preview,gpt-3.5-turbo,gpt-3.5-turbo-16k,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-1106,gpt-3.5-turbo-0613,gpt-3.5-turbo-0125,gpt-3.5-turbo-instruct,text-davinci-003',
+    'HOSTED_OPENAI_PAID_MODELS': 'gpt-4,gpt-4-turbo-preview,gpt-4-turbo-2024-04-09,gpt-4-1106-preview,gpt-4-0125-preview,gpt-3.5-turbo,gpt-3.5-turbo-16k,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-1106,gpt-3.5-turbo-0613,gpt-3.5-turbo-0125,gpt-3.5-turbo-instruct,text-davinci-003',
     'HOSTED_AZURE_OPENAI_ENABLED': 'False',
     'HOSTED_AZURE_OPENAI_QUOTA_LIMIT': 200,
     'HOSTED_ANTHROPIC_QUOTA_LIMIT': 600000,
@@ -48,6 +50,8 @@ DEFAULTS = {
     'HOSTED_ANTHROPIC_PAID_ENABLED': 'False',
     'HOSTED_MODERATION_ENABLED': 'False',
     'HOSTED_MODERATION_PROVIDERS': '',
+    'HOSTED_FETCH_APP_TEMPLATES_MODE': 'remote',
+    'HOSTED_FETCH_APP_TEMPLATES_REMOTE_DOMAIN': 'https://tmpl.dify.ai',
     'CLEAN_DAY_SETTING': 30,
     'UPLOAD_FILE_SIZE_LIMIT': 15,
     'UPLOAD_FILE_BATCH_LIMIT': 5,
@@ -59,7 +63,12 @@ DEFAULTS = {
     'CAN_REPLACE_LOGO': 'False',
     'ETL_TYPE': 'dify',
     'KEYWORD_STORE': 'jieba',
-    'BATCH_UPLOAD_LIMIT': 20
+    'BATCH_UPLOAD_LIMIT': 20,
+    'CODE_EXECUTION_ENDPOINT': '',
+    'CODE_EXECUTION_API_KEY': '',
+    'TOOL_ICON_CACHE_MAX_AGE': 3600,
+    'MILVUS_DATABASE': 'default',
+    'KEYWORD_DATA_SOURCE_TYPE': 'database',
 }
 
 
@@ -90,7 +99,7 @@ class Config:
         # ------------------------
         # General Configurations.
         # ------------------------
-        self.CURRENT_VERSION = "0.5.8"
+        self.CURRENT_VERSION = "0.6.2"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')
@@ -146,6 +155,7 @@ class Config:
         self.SQLALCHEMY_DATABASE_URI = f"postgresql://{db_credentials['DB_USERNAME']}:{db_credentials['DB_PASSWORD']}@{db_credentials['DB_HOST']}:{db_credentials['DB_PORT']}/{db_credentials['DB_DATABASE']}{db_extras}"
         self.SQLALCHEMY_ENGINE_OPTIONS = {
             'pool_size': int(get_env('SQLALCHEMY_POOL_SIZE')),
+            'max_overflow': int(get_env('SQLALCHEMY_MAX_OVERFLOW')),
             'pool_recycle': int(get_env('SQLALCHEMY_POOL_RECYCLE'))
         }
 
@@ -180,6 +190,11 @@ class Config:
         self.S3_ACCESS_KEY = get_env('S3_ACCESS_KEY')
         self.S3_SECRET_KEY = get_env('S3_SECRET_KEY')
         self.S3_REGION = get_env('S3_REGION')
+        self.S3_ADDRESS_STYLE = get_env('S3_ADDRESS_STYLE')
+        self.AZURE_BLOB_ACCOUNT_NAME = get_env('AZURE_BLOB_ACCOUNT_NAME')
+        self.AZURE_BLOB_ACCOUNT_KEY = get_env('AZURE_BLOB_ACCOUNT_KEY')
+        self.AZURE_BLOB_CONTAINER_NAME = get_env('AZURE_BLOB_CONTAINER_NAME')
+        self.AZURE_BLOB_ACCOUNT_URL = get_env('AZURE_BLOB_ACCOUNT_URL')
 
         # ------------------------
         # Vector Store Configurations.
@@ -198,6 +213,7 @@ class Config:
         self.MILVUS_USER = get_env('MILVUS_USER')
         self.MILVUS_PASSWORD = get_env('MILVUS_PASSWORD')
         self.MILVUS_SECURE = get_env('MILVUS_SECURE')
+        self.MILVUS_DATABASE = get_env('MILVUS_DATABASE')
 
         # weaviate settings
         self.WEAVIATE_ENDPOINT = get_env('WEAVIATE_ENDPOINT')
@@ -286,6 +302,10 @@ class Config:
         self.HOSTED_MODERATION_ENABLED = get_bool_env('HOSTED_MODERATION_ENABLED')
         self.HOSTED_MODERATION_PROVIDERS = get_env('HOSTED_MODERATION_PROVIDERS')
 
+        # fetch app templates mode, remote, builtin, db(only for dify SaaS), default: remote
+        self.HOSTED_FETCH_APP_TEMPLATES_MODE = get_env('HOSTED_FETCH_APP_TEMPLATES_MODE')
+        self.HOSTED_FETCH_APP_TEMPLATES_REMOTE_DOMAIN = get_env('HOSTED_FETCH_APP_TEMPLATES_REMOTE_DOMAIN')
+
         self.ETL_TYPE = get_env('ETL_TYPE')
         self.UNSTRUCTURED_API_URL = get_env('UNSTRUCTURED_API_URL')
         self.BILLING_ENABLED = get_bool_env('BILLING_ENABLED')
@@ -293,6 +313,13 @@ class Config:
 
         self.BATCH_UPLOAD_LIMIT = get_env('BATCH_UPLOAD_LIMIT')
 
+        self.CODE_EXECUTION_ENDPOINT = get_env('CODE_EXECUTION_ENDPOINT')
+        self.CODE_EXECUTION_API_KEY = get_env('CODE_EXECUTION_API_KEY')
+
+        self.API_COMPRESSION_ENABLED = get_bool_env('API_COMPRESSION_ENABLED')
+        self.TOOL_ICON_CACHE_MAX_AGE = get_env('TOOL_ICON_CACHE_MAX_AGE')
+
+        self.KEYWORD_DATA_SOURCE_TYPE = get_env('KEYWORD_DATA_SOURCE_TYPE')
 
 class CloudEditionConfig(Config):
 

api/constants/languages.py

@@ -1,8 +1,6 @@
-import json
 
-from models.model import AppModelConfig
 
-languages = ['en-US', 'zh-Hans', 'pt-BR', 'es-ES', 'fr-FR', 'de-DE', 'ja-JP', 'ko-KR', 'ru-RU', 'it-IT', 'uk-UA']
+languages = ['en-US', 'zh-Hans', 'pt-BR', 'es-ES', 'fr-FR', 'de-DE', 'ja-JP', 'ko-KR', 'ru-RU', 'it-IT', 'uk-UA', 'vi-VN']
 
 language_timezone_mapping = {
     'en-US': 'America/New_York',
@@ -16,6 +14,7 @@ language_timezone_mapping = {
     'ru-RU': 'Europe/Moscow',
     'it-IT': 'Europe/Rome',
     'uk-UA': 'Europe/Kyiv',
+    'vi-VN': 'Asia/Ho_Chi_Minh',
 }
 
 
@@ -26,439 +25,3 @@ def supported_language(lang):
     error = ('{lang} is not a valid language.'
              .format(lang=lang))
     raise ValueError(error)
-
-
-user_input_form_template = {
-    "en-US": [
-        {
-            "paragraph": {
-                "label": "Query",
-                "variable": "default_input",
-                "required": False,
-                "default": ""
-            }
-        }
-    ],
-    "zh-Hans": [
-        {
-            "paragraph": {
-                "label": "查询内容",
-                "variable": "default_input",
-                "required": False,
-                "default": ""
-            }
-        }
-    ],
-    "pt-BR": [
-        {
-            "paragraph": {
-                "label": "Consulta",
-                "variable": "default_input",
-                "required": False,
-                "default": ""
-            }
-        }
-    ],
-    "es-ES": [
-        {
-            "paragraph": {
-                "label": "Consulta",
-                "variable": "default_input",
-                "required": False,
-                "default": ""
-            }
-        }
-    ],
-    "ua-UK": [
-        {
-            "paragraph": {
-                "label": "Запит",
-                "variable": "default_input",
-                "required": False,
-                "default": ""
-            }
-        }
-    ],
-}
-
-demo_model_templates = {
-    'en-US': [
-        {
-            'name': 'Translation Assistant',
-            'icon': '',
-            'icon_background': '',
-            'description': 'A multilingual translator that provides translation capabilities in multiple languages, translating user input into the language they need.',
-            'mode': 'completion',
-            'model_config': AppModelConfig(
-                provider='openai',
-                model_id='gpt-3.5-turbo-instruct',
-                configs={
-                    'prompt_template': "Please translate the following text into {{target_language}}:\n",
-                    'prompt_variables': [
-                        {
-                            "key": "target_language",
-                            "name": "Target Language",
-                            "description": "The language you want to translate into.",
-                            "type": "select",
-                            "default": "Chinese",
-                            'options': [
-                                'Chinese',
-                                'English',
-                                'Japanese',
-                                'French',
-                                'Russian',
-                                'German',
-                                'Spanish',
-                                'Korean',
-                                'Italian',
-                            ]
-                        }
-                    ],
-                    'completion_params': {
-                        'max_token': 1000,
-                        'temperature': 0,
-                        'top_p': 0,
-                        'presence_penalty': 0.1,
-                        'frequency_penalty': 0.1,
-                    }
-                },
-                opening_statement='',
-                suggested_questions=None,
-                pre_prompt="Please translate the following text into {{target_language}}:\n{{query}}\ntranslate:",
-                model=json.dumps({
-                    "provider": "openai",
-                    "name": "gpt-3.5-turbo-instruct",
-                    "mode": "completion",
-                    "completion_params": {
-                        "max_tokens": 1000,
-                        "temperature": 0,
-                        "top_p": 0,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1
-                    }
-                }),
-                user_input_form=json.dumps([
-                    {
-                        "select": {
-                            "label": "Target Language",
-                            "variable": "target_language",
-                            "description": "The language you want to translate into.",
-                            "default": "Chinese",
-                            "required": True,
-                            'options': [
-                                'Chinese',
-                                'English',
-                                'Japanese',
-                                'French',
-                                'Russian',
-                                'German',
-                                'Spanish',
-                                'Korean',
-                                'Italian',
-                            ]
-                        }
-                    }, {
-                        "paragraph": {
-                            "label": "Query",
-                            "variable": "query",
-                            "required": True,
-                            "default": ""
-                        }
-                    }
-                ])
-            )
-        },
-        {
-            'name': 'AI Front-end Interviewer',
-            'icon': '',
-            'icon_background': '',
-            'description': 'A simulated front-end interviewer that tests the skill level of front-end development through questioning.',
-            'mode': 'chat',
-            'model_config': AppModelConfig(
-                provider='openai',
-                model_id='gpt-3.5-turbo',
-                configs={
-                    'introduction': 'Hi, welcome to our interview. I am the interviewer for this technology company, and I will test your web front-end development skills. Next, I will ask you some technical questions. Please answer them as thoroughly as possible. ',
-                    'prompt_template': "You will play the role of an interviewer for a technology company, examining the user's web front-end development skills and posing 5-10 sharp technical questions.\n\nPlease note:\n- Only ask one question at a time.\n- After the user answers a question, ask the next question directly, without trying to correct any mistakes made by the candidate.\n- If you think the user has not answered correctly for several consecutive questions, ask fewer questions.\n- After asking the last question, you can ask this question: Why did you leave your last job? After the user answers this question, please express your understanding and support.\n",
-                    'prompt_variables': [],
-                    'completion_params': {
-                        'max_token': 300,
-                        'temperature': 0.8,
-                        'top_p': 0.9,
-                        'presence_penalty': 0.1,
-                        'frequency_penalty': 0.1,
-                    }
-                },
-                opening_statement='Hi, welcome to our interview. I am the interviewer for this technology company, and I will test your web front-end development skills. Next, I will ask you some technical questions. Please answer them as thoroughly as possible. ',
-                suggested_questions=None,
-                pre_prompt="You will play the role of an interviewer for a technology company, examining the user's web front-end development skills and posing 5-10 sharp technical questions.\n\nPlease note:\n- Only ask one question at a time.\n- After the user answers a question, ask the next question directly, without trying to correct any mistakes made by the candidate.\n- If you think the user has not answered correctly for several consecutive questions, ask fewer questions.\n- After asking the last question, you can ask this question: Why did you leave your last job? After the user answers this question, please express your understanding and support.\n",
-                model=json.dumps({
-                    "provider": "openai",
-                    "name": "gpt-3.5-turbo",
-                    "mode": "chat",
-                    "completion_params": {
-                        "max_tokens": 300,
-                        "temperature": 0.8,
-                        "top_p": 0.9,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1
-                    }
-                }),
-                user_input_form=None
-            )
-        }
-    ],
-
-    'zh-Hans': [
-        {
-            'name': '翻译助手',
-            'icon': '',
-            'icon_background': '',
-            'description': '一个多语言翻译器，提供多种语言翻译能力，将用户输入的文本翻译成他们需要的语言。',
-            'mode': 'completion',
-            'model_config': AppModelConfig(
-                provider='openai',
-                model_id='gpt-3.5-turbo-instruct',
-                configs={
-                    'prompt_template': "请将以下文本翻译为{{target_language}}:\n",
-                    'prompt_variables': [
-                        {
-                            "key": "target_language",
-                            "name": "目标语言",
-                            "description": "翻译的目标语言",
-                            "type": "select",
-                            "default": "中文",
-                            "options": [
-                                "中文",
-                                "英文",
-                                "日语",
-                                "法语",
-                                "俄语",
-                                "德语",
-                                "西班牙语",
-                                "韩语",
-                                "意大利语",
-                            ]
-                        }
-                    ],
-                    'completion_params': {
-                        'max_token': 1000,
-                        'temperature': 0,
-                        'top_p': 0,
-                        'presence_penalty': 0.1,
-                        'frequency_penalty': 0.1,
-                    }
-                },
-                opening_statement='',
-                suggested_questions=None,
-                pre_prompt="请将以下文本翻译为{{target_language}}:\n{{query}}\n翻译:",
-                model=json.dumps({
-                    "provider": "openai",
-                    "name": "gpt-3.5-turbo-instruct",
-                    "mode": "completion",
-                    "completion_params": {
-                        "max_tokens": 1000,
-                        "temperature": 0,
-                        "top_p": 0,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1
-                    }
-                }),
-                user_input_form=json.dumps([
-                    {
-                        "select": {
-                            "label": "目标语言",
-                            "variable": "target_language",
-                            "description": "翻译的目标语言",
-                            "default": "中文",
-                            "required": True,
-                            'options': [
-                                "中文",
-                                "英文",
-                                "日语",
-                                "法语",
-                                "俄语",
-                                "德语",
-                                "西班牙语",
-                                "韩语",
-                                "意大利语",
-                            ]
-                        }
-                    }, {
-                        "paragraph": {
-                            "label": "文本内容",
-                            "variable": "query",
-                            "required": True,
-                            "default": ""
-                        }
-                    }
-                ])
-            )
-        },
-        {
-            'name': 'AI 前端面试官',
-            'icon': '',
-            'icon_background': '',
-            'description': '一个模拟的前端面试官，通过提问的方式对前端开发的技能水平进行检验。',
-            'mode': 'chat',
-            'model_config': AppModelConfig(
-                provider='openai',
-                model_id='gpt-3.5-turbo',
-                configs={
-                    'introduction': '你好，欢迎来参加我们的面试，我是这家科技公司的面试官，我将考察你的 Web 前端开发技能。接下来我会向您提出一些技术问题，请您尽可能详尽地回答。',
-                    'prompt_template': "你将扮演一个科技公司的面试官，考察用户作为候选人的 Web 前端开发水平，提出 5-10 个犀利的技术问题。\n\n请注意：\n- 每次只问一个问题\n- 用户回答问题后请直接问下一个问题，而不要试图纠正候选人的错误；\n- 如果你认为用户连续几次回答的都不对，就少问一点；\n- 问完最后一个问题后，你可以问这样一个问题：上一份工作为什么离职？用户回答该问题后，请表示理解与支持。\n",
-                    'prompt_variables': [],
-                    'completion_params': {
-                        'max_token': 300,
-                        'temperature': 0.8,
-                        'top_p': 0.9,
-                        'presence_penalty': 0.1,
-                        'frequency_penalty': 0.1,
-                    }
-                },
-                opening_statement='你好，欢迎来参加我们的面试，我是这家科技公司的面试官，我将考察你的 Web 前端开发技能。接下来我会向您提出一些技术问题，请您尽可能详尽地回答。',
-                suggested_questions=None,
-                pre_prompt="你将扮演一个科技公司的面试官，考察用户作为候选人的 Web 前端开发水平，提出 5-10 个犀利的技术问题。\n\n请注意：\n- 每次只问一个问题\n- 用户回答问题后请直接问下一个问题，而不要试图纠正候选人的错误；\n- 如果你认为用户连续几次回答的都不对，就少问一点；\n- 问完最后一个问题后，你可以问这样一个问题：上一份工作为什么离职？用户回答该问题后，请表示理解与支持。\n",
-                model=json.dumps({
-                    "provider": "openai",
-                    "name": "gpt-3.5-turbo",
-                    "mode": "chat",
-                    "completion_params": {
-                        "max_tokens": 300,
-                        "temperature": 0.8,
-                        "top_p": 0.9,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1
-                    }
-                }),
-                user_input_form=None
-            )
-        }
-    ],
-    'uk-UA': [{
-        "name": "Помічник перекладу",
-        "icon": "",
-        "icon_background": "",
-        "description": "Багатомовний перекладач, який надає можливості перекладу різними мовами, перекладаючи введені користувачем дані на потрібну мову.",
-        "mode": "completion",
-        "model_config": AppModelConfig(
-            provider="openai",
-            model_id="gpt-3.5-turbo-instruct",
-            configs={
-                "prompt_template": "Будь ласка, перекладіть наступний текст на {{target_language}}:\n",
-                "prompt_variables": [
-                    {
-                        "key": "target_language",
-                        "name": "Цільова мова",
-                        "description": "Мова, на яку ви хочете перекласти.",
-                        "type": "select",
-                        "default": "Ukrainian",
-                        "options": [
-                            "Chinese",
-                            "English",
-                            "Japanese",
-                            "French",
-                            "Russian",
-                            "German",
-                            "Spanish",
-                            "Korean",
-                            "Italian",
-                        ],
-                    },
-                ],
-                "completion_params": {
-                    "max_token": 1000,
-                    "temperature": 0,
-                    "top_p": 0,
-                    "presence_penalty": 0.1,
-                    "frequency_penalty": 0.1,
-                },
-            },
-            opening_statement="",
-            suggested_questions=None,
-            pre_prompt="Будь ласка, перекладіть наступний текст на {{target_language}}:\n{{query}}\ntranslate:",
-            model=json.dumps({
-                "provider": "openai",
-                "name": "gpt-3.5-turbo-instruct",
-                "mode": "completion",
-                "completion_params": {
-                    "max_tokens": 1000,
-                    "temperature": 0,
-                    "top_p": 0,
-                    "presence_penalty": 0.1,
-                    "frequency_penalty": 0.1,
-                },
-            }),
-            user_input_form=json.dumps([
-                {
-                    "select": {
-                        "label": "Цільова мова",
-                        "variable": "target_language",
-                        "description": "Мова, на яку ви хочете перекласти.",
-                        "default": "Chinese",
-                        "required": True,
-                        'options': [
-                            'Chinese',
-                            'English',
-                            'Japanese',
-                            'French',
-                            'Russian',
-                            'German',
-                            'Spanish',
-                            'Korean',
-                            'Italian',
-                        ]
-                    }
-                }, {
-                    "paragraph": {
-                        "label": "Запит",
-                        "variable": "query",
-                        "required": True,
-                        "default": ""
-                    }
-                }
-            ])
-        )
-    },
-        {
-            "name": "AI інтерв’юер фронтенду",
-            "icon": "",
-            "icon_background": "",
-            "description": "Симульований інтерв’юер фронтенду, який перевіряє рівень кваліфікації у розробці фронтенду через опитування.",
-            "mode": "chat",
-            "model_config": AppModelConfig(
-                provider="openai",
-                model_id="gpt-3.5-turbo",
-                configs={
-                    "introduction": "Привіт, ласкаво просимо на наше співбесіду. Я інтерв'юер цієї технологічної компанії, і я перевірю ваші навички веб-розробки фронтенду. Далі я поставлю вам декілька технічних запитань. Будь ласка, відповідайте якомога ретельніше. ",
-                    "prompt_template": "Ви будете грати роль інтерв'юера технологічної компанії, перевіряючи навички розробки фронтенду користувача та ставлячи 5-10 чітких технічних питань.\n\nЗверніть увагу:\n- Ставте лише одне запитання за раз.\n- Після того, як користувач відповість на запитання, ставте наступне запитання безпосередньо, не намагаючись виправити будь-які помилки, допущені кандидатом.\n- Якщо ви вважаєте, що користувач не відповів правильно на кілька питань поспіль, задайте менше запитань.\n- Після того, як ви задали останнє запитання, ви можете поставити таке запитання: Чому ви залишили свою попередню роботу? Після того, як користувач відповість на це питання, висловіть своє розуміння та підтримку.\n",
-                    "prompt_variables": [],
-                    "completion_params": {
-                        "max_token": 300,
-                        "temperature": 0.8,
-                        "top_p": 0.9,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1,
-                    },
-                },
-                opening_statement="Привіт, ласкаво просимо на наше співбесіду. Я інтерв'юер цієї технологічної компанії, і я перевірю ваші навички веб-розробки фронтенду. Далі я поставлю вам декілька технічних запитань. Будь ласка, відповідайте якомога ретельніше. ",
-                suggested_questions=None,
-                pre_prompt="Ви будете грати роль інтерв'юера технологічної компанії, перевіряючи навички розробки фронтенду користувача та ставлячи 5-10 чітких технічних питань.\n\nЗверніть увагу:\n- Ставте лише одне запитання за раз.\n- Після того, як користувач відповість на запитання, ставте наступне запитання безпосередньо, не намагаючись виправити будь-які помилки, допущені кандидатом.\n- Якщо ви вважаєте, що користувач не відповів правильно на кілька питань поспіль, задайте менше запитань.\n- Після того, як ви задали останнє запитання, ви можете поставити таке запитання: Чому ви залишили свою попередню роботу? Після того, як користувач відповість на це питання, висловіть своє розуміння та підтримку.\n",
-                model=json.dumps({
-                    "provider": "openai",
-                    "name": "gpt-3.5-turbo",
-                    "mode": "chat",
-                    "completion_params": {
-                        "max_tokens": 300,
-                        "temperature": 0.8,
-                        "top_p": 0.9,
-                        "presence_penalty": 0.1,
-                        "frequency_penalty": 0.1,
-                    },
-                }),
-                user_input_form=None
-            ),
-        }
-    ],
-
-}

api/constants/model_template.py

@@ -1,27 +1,31 @@
 import json
 
-model_templates = {
-    # completion default mode
-    'completion_default': {
+from models.model import AppMode
+
+default_app_templates = {
+    # workflow default mode
+    AppMode.WORKFLOW: {
         'app': {
-            'mode': 'completion',
+            'mode': AppMode.WORKFLOW.value,
             'enable_site': True,
-            'enable_api': True,
-            'is_demo': False,
-            'api_rpm': 0,
-            'api_rph': 0,
-            'status': 'normal'
+            'enable_api': True
+        }
+    },
+
+    # completion default mode
+    AppMode.COMPLETION: {
+        'app': {
+            'mode': AppMode.COMPLETION.value,
+            'enable_site': True,
+            'enable_api': True
         },
         'model_config': {
-            'provider': '',
-            'model_id': '',
-            'configs': {},
-            'model': json.dumps({
+            'model': {
                 "provider": "openai",
-                "name": "gpt-3.5-turbo-instruct",
-                "mode": "completion",
+                "name": "gpt-4",
+                "mode": "chat",
                 "completion_params": {}
-            }),
+            },
             'user_input_form': json.dumps([
                 {
                     "paragraph": {
@@ -33,32 +37,50 @@ model_templates = {
                 }
             ]),
             'pre_prompt': '{{query}}'
-        }
+        },
+
     },
 
     # chat default mode
-    'chat_default': {
+    AppMode.CHAT: {
         'app': {
-            'mode': 'chat',
+            'mode': AppMode.CHAT.value,
             'enable_site': True,
-            'enable_api': True,
-            'is_demo': False,
-            'api_rpm': 0,
-            'api_rph': 0,
-            'status': 'normal'
+            'enable_api': True
         },
         'model_config': {
-            'provider': '',
-            'model_id': '',
-            'configs': {},
-            'model': json.dumps({
+            'model': {
                 "provider": "openai",
-                "name": "gpt-3.5-turbo",
+                "name": "gpt-4",
                 "mode": "chat",
                 "completion_params": {}
-            })
+            }
         }
     },
+
+    # advanced-chat default mode
+    AppMode.ADVANCED_CHAT: {
+        'app': {
+            'mode': AppMode.ADVANCED_CHAT.value,
+            'enable_site': True,
+            'enable_api': True
+        }
+    },
+
+    # agent-chat default mode
+    AppMode.AGENT_CHAT: {
+        'app': {
+            'mode': AppMode.AGENT_CHAT.value,
+            'enable_site': True,
+            'enable_api': True
+        },
+        'model_config': {
+            'model': {
+                "provider": "openai",
+                "name": "gpt-4",
+                "mode": "chat",
+                "completion_params": {}
+            }
+        }
+    }
 }
-
-

api/controllers/console/__init__.py

@@ -5,10 +5,10 @@ bp = Blueprint('console', __name__, url_prefix='/console/api')
 api = ExternalApi(bp)
 
 # Import other controllers
-from . import admin, apikey, extension, feature, setup, version
+from . import admin, apikey, extension, feature, setup, version, ping
 # Import app controllers
 from .app import (advanced_prompt_template, annotation, app, audio, completion, conversation, generator, message,
-                  model_config, site, statistic)
+                  model_config, site, statistic, workflow, workflow_run, workflow_app_log, workflow_statistic, agent)
 # Import auth controllers
 from .auth import activate, data_source_oauth, login, oauth
 # Import billing controllers
@@ -16,6 +16,7 @@ from .billing import billing
 # Import datasets controllers
 from .datasets import data_source, datasets, datasets_document, datasets_segments, file, hit_testing
 # Import explore controllers
-from .explore import audio, completion, conversation, installed_app, message, parameter, recommended_app, saved_message
+from .explore import (audio, completion, conversation, installed_app, message, parameter, recommended_app,
+                      saved_message, workflow)
 # Import workspace controllers
-from .workspace import account, members, model_providers, models, tool_providers, workspace
+from .workspace import account, members, model_providers, models, tool_providers, workspace

api/controllers/console/app/__init__.py

@@ -1,21 +0,0 @@
-from controllers.console.app.error import AppUnavailableError
-from extensions.ext_database import db
-from flask_login import current_user
-from models.model import App
-from werkzeug.exceptions import NotFound
-
-
-def _get_app(app_id, mode=None):
-    app = db.session.query(App).filter(
-        App.id == app_id,
-        App.tenant_id == current_user.current_tenant_id,
-        App.status == 'normal'
-    ).first()
-
-    if not app:
-        raise NotFound("App not found")
-
-    if mode and app.mode != mode:
-        raise NotFound("The {} app not found".format(mode))
-
-    return app

api/controllers/console/app/agent.py

@@ -0,0 +1,32 @@
+from flask_restful import Resource, reqparse
+
+from controllers.console import api
+from controllers.console.app.wraps import get_app_model
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from libs.helper import uuid_value
+from libs.login import login_required
+from models.model import AppMode
+from services.agent_service import AgentService
+
+
+class AgentLogApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.AGENT_CHAT])
+    def get(self, app_model):
+        """Get agent logs"""
+        parser = reqparse.RequestParser()
+        parser.add_argument('message_id', type=uuid_value, required=True, location='args')
+        parser.add_argument('conversation_id', type=uuid_value, required=True, location='args')
+
+        args = parser.parse_args()
+
+        return AgentService.get_agent_logs(
+            app_model,
+            args['conversation_id'],
+            args['message_id']
+        )
+    
+api.add_resource(AgentLogApi, '/apps/<uuid:app_id>/agent/logs')

api/controllers/console/app/app.py

@@ -1,39 +1,28 @@
 import json
-import logging
-from datetime import datetime
 
 from flask_login import current_user
-from flask_restful import Resource, abort, inputs, marshal_with, reqparse
-from werkzeug.exceptions import Forbidden
+from flask_restful import Resource, inputs, marshal_with, reqparse
+from werkzeug.exceptions import Forbidden, BadRequest
 
-from constants.languages import demo_model_templates, languages
-from constants.model_template import model_templates
 from controllers.console import api
-from controllers.console.app.error import AppNotFoundError, ProviderNotInitializeError
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check
-from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
-from core.model_manager import ModelManager
-from core.model_runtime.entities.model_entities import ModelType
-from core.provider_manager import ProviderManager
-from events.app_event import app_was_created, app_was_deleted
+from core.agent.entities import AgentToolEntity
 from extensions.ext_database import db
 from fields.app_fields import (
     app_detail_fields,
     app_detail_fields_with_site,
     app_pagination_fields,
-    template_list_fields,
 )
 from libs.login import login_required
-from models.model import App, AppModelConfig, Site
-from services.app_model_config_service import AppModelConfigService
+from services.app_service import AppService
+from models.model import App, AppModelConfig, AppMode
+from core.tools.utils.configuration import ToolParameterConfigurationManager
+from core.tools.tool_manager import ToolManager
 
 
-def _get_app(app_id, tenant_id):
-    app = db.session.query(App).filter(App.id == app_id, App.tenant_id == tenant_id).first()
-    if not app:
-        raise AppNotFoundError
-    return app
+ALLOW_CREATE_APP_MODES = ['chat', 'agent-chat', 'advanced-chat', 'workflow', 'completion']
 
 
 class AppListApi(Resource):
@@ -47,33 +36,15 @@ class AppListApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument('page', type=inputs.int_range(1, 99999), required=False, default=1, location='args')
         parser.add_argument('limit', type=inputs.int_range(1, 100), required=False, default=20, location='args')
-        parser.add_argument('mode', type=str, choices=['chat', 'completion', 'all'], default='all', location='args', required=False)
+        parser.add_argument('mode', type=str, choices=['chat', 'workflow', 'agent-chat', 'channel', 'all'], default='all', location='args', required=False)
         parser.add_argument('name', type=str, location='args', required=False)
         args = parser.parse_args()
 
-        filters = [
-            App.tenant_id == current_user.current_tenant_id,
-            App.is_universal == False
-        ]
+        # get app list
+        app_service = AppService()
+        app_pagination = app_service.get_paginate_apps(current_user.current_tenant_id, args)
 
-        if args['mode'] == 'completion':
-            filters.append(App.mode == 'completion')
-        elif args['mode'] == 'chat':
-            filters.append(App.mode == 'chat')
-        else:
-            pass
-
-        if 'name' in args and args['name']:
-            filters.append(App.name.ilike(f'%{args["name"]}%'))
-
-        app_models = db.paginate(
-            db.select(App).where(*filters).order_by(App.created_at.desc()),
-            page=args['page'],
-            per_page=args['limit'],
-            error_out=False
-        )
-
-        return app_models
+        return app_pagination
 
     @setup_required
     @login_required
@@ -84,147 +55,49 @@ class AppListApi(Resource):
         """Create app"""
         parser = reqparse.RequestParser()
         parser.add_argument('name', type=str, required=True, location='json')
-        parser.add_argument('mode', type=str, choices=['completion', 'chat', 'assistant'], location='json')
+        parser.add_argument('description', type=str, location='json')
+        parser.add_argument('mode', type=str, choices=ALLOW_CREATE_APP_MODES, location='json')
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
-        parser.add_argument('model_config', type=dict, location='json')
         args = parser.parse_args()
 
         # The role of the current user in the ta table must be admin or owner
         if not current_user.is_admin_or_owner:
             raise Forbidden()
 
-        try:
-            provider_manager = ProviderManager()
-            default_model_entity = provider_manager.get_default_model(
-                tenant_id=current_user.current_tenant_id,
-                model_type=ModelType.LLM
-            )
-        except (ProviderTokenNotInitError, LLMBadRequestError):
-            default_model_entity = None
-        except Exception as e:
-            logging.exception(e)
-            default_model_entity = None
+        if 'mode' not in args or args['mode'] is None:
+            raise BadRequest("mode is required")
 
-        if args['model_config'] is not None:
-            # validate config
-            model_config_dict = args['model_config']
-
-            # Get provider configurations
-            provider_manager = ProviderManager()
-            provider_configurations = provider_manager.get_configurations(current_user.current_tenant_id)
-
-            # get available models from provider_configurations
-            available_models = provider_configurations.get_models(
-                model_type=ModelType.LLM,
-                only_active=True
-            )
-
-            # check if model is available
-            available_models_names = [f'{model.provider.provider}.{model.model}' for model in available_models]
-            provider_model = f"{model_config_dict['model']['provider']}.{model_config_dict['model']['name']}"
-            if provider_model not in available_models_names:
-                if not default_model_entity:
-                    raise ProviderNotInitializeError(
-                        "No Default System Reasoning Model available. Please configure "
-                        "in the Settings -> Model Provider.")
-                else:
-                    model_config_dict["model"]["provider"] = default_model_entity.provider.provider
-                    model_config_dict["model"]["name"] = default_model_entity.model
-
-            model_configuration = AppModelConfigService.validate_configuration(
-                tenant_id=current_user.current_tenant_id,
-                account=current_user,
-                config=model_config_dict,
-                app_mode=args['mode']
-            )
-
-            app = App(
-                enable_site=True,
-                enable_api=True,
-                is_demo=False,
-                api_rpm=0,
-                api_rph=0,
-                status='normal'
-            )
-
-            app_model_config = AppModelConfig()
-            app_model_config = app_model_config.from_model_config_dict(model_configuration)
-        else:
-            if 'mode' not in args or args['mode'] is None:
-                abort(400, message="mode is required")
-
-            model_config_template = model_templates[args['mode'] + '_default']
-
-            app = App(**model_config_template['app'])
-            app_model_config = AppModelConfig(**model_config_template['model_config'])
-
-            # get model provider
-            model_manager = ModelManager()
-
-            try:
-                model_instance = model_manager.get_default_model_instance(
-                    tenant_id=current_user.current_tenant_id,
-                    model_type=ModelType.LLM
-                )
-            except ProviderTokenNotInitError:
-                model_instance = None
-
-            if model_instance:
-                model_dict = app_model_config.model_dict
-                model_dict['provider'] = model_instance.provider
-                model_dict['name'] = model_instance.model
-                app_model_config.model = json.dumps(model_dict)
-
-        app.name = args['name']
-        app.mode = args['mode']
-        app.icon = args['icon']
-        app.icon_background = args['icon_background']
-        app.tenant_id = current_user.current_tenant_id
-
-        db.session.add(app)
-        db.session.flush()
-
-        app_model_config.app_id = app.id
-        db.session.add(app_model_config)
-        db.session.flush()
-
-        app.app_model_config_id = app_model_config.id
-
-        account = current_user
-
-        site = Site(
-            app_id=app.id,
-            title=app.name,
-            default_language=account.interface_language,
-            customize_token_strategy='not_allow',
-            code=Site.generate_code(16)
-        )
-
-        db.session.add(site)
-        db.session.commit()
-
-        app_was_created.send(app)
+        app_service = AppService()
+        app = app_service.create_app(current_user.current_tenant_id, args, current_user)
 
         return app, 201
-    
 
-class AppTemplateApi(Resource):
 
+class AppImportApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @marshal_with(template_list_fields)
-    def get(self):
-        """Get app demo templates"""
-        account = current_user
-        interface_language = account.interface_language
+    @marshal_with(app_detail_fields_with_site)
+    @cloud_edition_billing_resource_check('apps')
+    def post(self):
+        """Import app"""
+        # The role of the current user in the ta table must be admin or owner
+        if not current_user.is_admin_or_owner:
+            raise Forbidden()
 
-        templates = demo_model_templates.get(interface_language)
-        if not templates:
-            templates = demo_model_templates.get(languages[0])
+        parser = reqparse.RequestParser()
+        parser.add_argument('data', type=str, required=True, nullable=False, location='json')
+        parser.add_argument('name', type=str, location='json')
+        parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon', type=str, location='json')
+        parser.add_argument('icon_background', type=str, location='json')
+        args = parser.parse_args()
 
-        return {'data': templates}
+        app_service = AppService()
+        app = app_service.import_app(current_user.current_tenant_id, args['data'], args, current_user)
+
+        return app, 201
 
 
 class AppApi(Resource):
@@ -232,176 +105,198 @@ class AppApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_detail_fields_with_site)
-    def get(self, app_id):
+    def get(self, app_model):
         """Get app detail"""
-        app_id = str(app_id)
-        app = _get_app(app_id, current_user.current_tenant_id)
+        # get original app model config
+        if app_model.mode == AppMode.AGENT_CHAT.value or app_model.is_agent:
+            model_config: AppModelConfig = app_model.app_model_config
+            agent_mode = model_config.agent_mode_dict
+            # decrypt agent tool parameters if it's secret-input
+            for tool in agent_mode.get('tools') or []:
+                if not isinstance(tool, dict) or len(tool.keys()) <= 3:
+                    continue
+                agent_tool_entity = AgentToolEntity(**tool)
+                # get tool
+                try:
+                    tool_runtime = ToolManager.get_agent_tool_runtime(
+                        tenant_id=current_user.current_tenant_id,
+                        agent_tool=agent_tool_entity,
+                    )
+                    manager = ToolParameterConfigurationManager(
+                        tenant_id=current_user.current_tenant_id,
+                        tool_runtime=tool_runtime,
+                        provider_name=agent_tool_entity.provider_id,
+                        provider_type=agent_tool_entity.provider_type,
+                    )
 
-        return app
+                    # get decrypted parameters
+                    if agent_tool_entity.tool_parameters:
+                        parameters = manager.decrypt_tool_parameters(agent_tool_entity.tool_parameters or {})
+                        masked_parameter = manager.mask_tool_parameters(parameters or {})
+                    else:
+                        masked_parameter = {}
+
+                    # override tool parameters
+                    tool['tool_parameters'] = masked_parameter
+                except Exception as e:
+                    pass
+
+            # override agent mode
+            model_config.agent_mode = json.dumps(agent_mode)
+            db.session.commit()
+
+        return app_model
 
     @setup_required
     @login_required
     @account_initialization_required
-    def delete(self, app_id):
-        """Delete app"""
-        app_id = str(app_id)
+    @get_app_model
+    @marshal_with(app_detail_fields_with_site)
+    def put(self, app_model):
+        """Update app"""
+        parser = reqparse.RequestParser()
+        parser.add_argument('name', type=str, required=True, nullable=False, location='json')
+        parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon', type=str, location='json')
+        parser.add_argument('icon_background', type=str, location='json')
+        args = parser.parse_args()
 
+        app_service = AppService()
+        app_model = app_service.update_app(app_model, args)
+
+        return app_model
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def delete(self, app_model):
+        """Delete app"""
         if not current_user.is_admin_or_owner:
             raise Forbidden()
 
-        app = _get_app(app_id, current_user.current_tenant_id)
-
-        db.session.delete(app)
-        db.session.commit()
-
-        # todo delete related data??
-        # model_config, site, api_token, conversation, message, message_feedback, message_annotation
-
-        app_was_deleted.send(app)
+        app_service = AppService()
+        app_service.delete_app(app_model)
 
         return {'result': 'success'}, 204
 
 
+class AppCopyApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    @marshal_with(app_detail_fields_with_site)
+    def post(self, app_model):
+        """Copy app"""
+        # The role of the current user in the ta table must be admin or owner
+        if not current_user.is_admin_or_owner:
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('name', type=str, location='json')
+        parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon', type=str, location='json')
+        parser.add_argument('icon_background', type=str, location='json')
+        args = parser.parse_args()
+
+        app_service = AppService()
+        data = app_service.export_app(app_model)
+        app = app_service.import_app(current_user.current_tenant_id, data, args, current_user)
+
+        return app, 201
+
+
+class AppExportApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def get(self, app_model):
+        """Export app"""
+        app_service = AppService()
+
+        return {
+            "data": app_service.export_app(app_model)
+        }
+
+
 class AppNameApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_detail_fields)
-    def post(self, app_id):
-        app_id = str(app_id)
-        app = _get_app(app_id, current_user.current_tenant_id)
-
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('name', type=str, required=True, location='json')
         args = parser.parse_args()
 
-        app.name = args.get('name')
-        app.updated_at = datetime.utcnow()
-        db.session.commit()
-        return app
+        app_service = AppService()
+        app_model = app_service.update_app_name(app_model, args.get('name'))
+
+        return app_model
 
 
 class AppIconApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_detail_fields)
-    def post(self, app_id):
-        app_id = str(app_id)
-        app = _get_app(app_id, current_user.current_tenant_id)
-
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
         args = parser.parse_args()
 
-        app.icon = args.get('icon')
-        app.icon_background = args.get('icon_background')
-        app.updated_at = datetime.utcnow()
-        db.session.commit()
+        app_service = AppService()
+        app_model = app_service.update_app_icon(app_model, args.get('icon'), args.get('icon_background'))
 
-        return app
+        return app_model
 
 
 class AppSiteStatus(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_detail_fields)
-    def post(self, app_id):
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('enable_site', type=bool, required=True, location='json')
         args = parser.parse_args()
-        app_id = str(app_id)
-        app = db.session.query(App).filter(App.id == app_id, App.tenant_id == current_user.current_tenant_id).first()
-        if not app:
-            raise AppNotFoundError
 
-        if args.get('enable_site') == app.enable_site:
-            return app
+        app_service = AppService()
+        app_model = app_service.update_app_site_status(app_model, args.get('enable_site'))
 
-        app.enable_site = args.get('enable_site')
-        app.updated_at = datetime.utcnow()
-        db.session.commit()
-        return app
+        return app_model
 
 
 class AppApiStatus(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_detail_fields)
-    def post(self, app_id):
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('enable_api', type=bool, required=True, location='json')
         args = parser.parse_args()
 
-        app_id = str(app_id)
-        app = _get_app(app_id, current_user.current_tenant_id)
+        app_service = AppService()
+        app_model = app_service.update_app_api_status(app_model, args.get('enable_api'))
 
-        if args.get('enable_api') == app.enable_api:
-            return app
-
-        app.enable_api = args.get('enable_api')
-        app.updated_at = datetime.utcnow()
-        db.session.commit()
-        return app
-
-
-class AppCopy(Resource):
-    @staticmethod
-    def create_app_copy(app):
-        copy_app = App(
-            name=app.name + ' copy',
-            icon=app.icon,
-            icon_background=app.icon_background,
-            tenant_id=app.tenant_id,
-            mode=app.mode,
-            app_model_config_id=app.app_model_config_id,
-            enable_site=app.enable_site,
-            enable_api=app.enable_api,
-            api_rpm=app.api_rpm,
-            api_rph=app.api_rph
-        )
-        return copy_app
-
-    @staticmethod
-    def create_app_model_config_copy(app_config, copy_app_id):
-        copy_app_model_config = app_config.copy()
-        copy_app_model_config.app_id = copy_app_id
-
-        return copy_app_model_config
-
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @marshal_with(app_detail_fields)
-    def post(self, app_id):
-        app_id = str(app_id)
-        app = _get_app(app_id, current_user.current_tenant_id)
-
-        copy_app = self.create_app_copy(app)
-        db.session.add(copy_app)
-
-        app_config = db.session.query(AppModelConfig). \
-            filter(AppModelConfig.app_id == app_id). \
-            one_or_none()
-
-        if app_config:
-            copy_app_model_config = self.create_app_model_config_copy(app_config, copy_app.id)
-            db.session.add(copy_app_model_config)
-            db.session.commit()
-            copy_app.app_model_config_id = copy_app_model_config.id
-        db.session.commit()
-
-        return copy_app, 201
+        return app_model
 
 
 api.add_resource(AppListApi, '/apps')
-api.add_resource(AppTemplateApi, '/app-templates')
+api.add_resource(AppImportApi, '/apps/import')
 api.add_resource(AppApi, '/apps/<uuid:app_id>')
-api.add_resource(AppCopy, '/apps/<uuid:app_id>/copy')
+api.add_resource(AppCopyApi, '/apps/<uuid:app_id>/copy')
+api.add_resource(AppExportApi, '/apps/<uuid:app_id>/export')
 api.add_resource(AppNameApi, '/apps/<uuid:app_id>/name')
 api.add_resource(AppIconApi, '/apps/<uuid:app_id>/icon')
 api.add_resource(AppSiteStatus, '/apps/<uuid:app_id>/site-enable')

api/controllers/console/app/audio.py

@@ -6,7 +6,6 @@ from werkzeug.exceptions import InternalServerError
 
 import services
 from controllers.console import api
-from controllers.console.app import _get_app
 from controllers.console.app.error import (
     AppUnavailableError,
     AudioTooLargeError,
@@ -18,11 +17,13 @@ from controllers.console.app.error import (
     ProviderQuotaExceededError,
     UnsupportedAudioTypeError,
 )
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from libs.login import login_required
+from models.model import AppMode
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -36,15 +37,13 @@ class ChatMessageAudioApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
-        app_id = str(app_id)
-        app_model = _get_app(app_id, 'chat')
-
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
+    def post(self, app_model):
         file = request.files['file']
 
         try:
             response = AudioService.transcript_asr(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 file=file,
                 end_user=None,
             )
@@ -80,15 +79,13 @@ class ChatMessageTextApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
-        app_id = str(app_id)
-        app_model = _get_app(app_id, None)
-
+    @get_app_model
+    def post(self, app_model):
         try:
             response = AudioService.transcript_tts(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 text=request.form['text'],
-                voice=request.form['voice'] if request.form['voice'] else app_model.app_model_config.text_to_speech_dict.get('voice'),
+                voice=request.form.get('voice'),
                 streaming=False
             )
 
@@ -120,9 +117,11 @@ class ChatMessageTextApi(Resource):
 
 
 class TextModesApi(Resource):
-    def get(self, app_id: str):
-        app_model = _get_app(str(app_id))
-
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def get(self, app_model):
         try:
             parser = reqparse.RequestParser()
             parser.add_argument('language', type=str, required=True, location='args')

api/controllers/console/app/completion.py

@@ -1,16 +1,11 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
 import flask_login
-from flask import Response, stream_with_context
 from flask_restful import Resource, reqparse
 from werkzeug.exceptions import InternalServerError, NotFound
 
 import services
 from controllers.console import api
-from controllers.console.app import _get_app
 from controllers.console.app.error import (
     AppUnavailableError,
     CompletionRequestError,
@@ -19,15 +14,18 @@ from controllers.console.app.error import (
     ProviderNotInitializeError,
     ProviderQuotaExceededError,
 )
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
-from core.application_queue_manager import ApplicationQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
 from libs.helper import uuid_value
 from libs.login import login_required
-from services.completion_service import CompletionService
+from models.model import AppMode
+from services.app_generate_service import AppGenerateService
 
 
 # define completion message api for user
@@ -36,12 +34,8 @@ class CompletionMessageApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
-        app_id = str(app_id)
-
-        # get app info
-        app_model = _get_app(app_id, 'completion')
-
+    @get_app_model(mode=AppMode.COMPLETION)
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('inputs', type=dict, required=True, location='json')
         parser.add_argument('query', type=str, location='json', default='')
@@ -57,16 +51,15 @@ class CompletionMessageApi(Resource):
         account = flask_login.current_user
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=account,
                 args=args,
                 invoke_from=InvokeFrom.DEBUGGER,
-                streaming=streaming,
-                is_model_config_override=True
+                streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -93,15 +86,11 @@ class CompletionMessageStopApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id, task_id):
-        app_id = str(app_id)
-
-        # get app info
-        _get_app(app_id, 'completion')
-
+    @get_app_model(mode=AppMode.COMPLETION)
+    def post(self, app_model, task_id):
         account = flask_login.current_user
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.DEBUGGER, account.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.DEBUGGER, account.id)
 
         return {'result': 'success'}, 200
 
@@ -110,12 +99,8 @@ class ChatMessageApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
-        app_id = str(app_id)
-
-        # get app info
-        app_model = _get_app(app_id, 'chat')
-
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('inputs', type=dict, required=True, location='json')
         parser.add_argument('query', type=str, required=True, location='json')
@@ -132,16 +117,15 @@ class ChatMessageApi(Resource):
         account = flask_login.current_user
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=account,
                 args=args,
                 invoke_from=InvokeFrom.DEBUGGER,
-                streaming=streaming,
-                is_model_config_override=True
+                streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -164,30 +148,15 @@ class ChatMessageApi(Resource):
             raise InternalServerError()
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 class ChatMessageStopApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id, task_id):
-        app_id = str(app_id)
-
-        # get app info
-        _get_app(app_id, 'chat')
-
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
+    def post(self, app_model, task_id):
         account = flask_login.current_user
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.DEBUGGER, account.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.DEBUGGER, account.id)
 
         return {'result': 'success'}, 200
 

api/controllers/console/app/conversation.py

@@ -9,9 +9,10 @@ from sqlalchemy.orm import joinedload
 from werkzeug.exceptions import NotFound
 
 from controllers.console import api
-from controllers.console.app import _get_app
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
+from core.app.entities.app_invoke_entities import InvokeFrom
 from extensions.ext_database import db
 from fields.conversation_fields import (
     conversation_detail_fields,
@@ -21,7 +22,7 @@ from fields.conversation_fields import (
 )
 from libs.helper import datetime_string
 from libs.login import login_required
-from models.model import Conversation, Message, MessageAnnotation
+from models.model import AppMode, Conversation, Message, MessageAnnotation
 
 
 class CompletionConversationApi(Resource):
@@ -29,10 +30,9 @@ class CompletionConversationApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model(mode=AppMode.COMPLETION)
     @marshal_with(conversation_pagination_fields)
-    def get(self, app_id):
-        app_id = str(app_id)
-
+    def get(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('keyword', type=str, location='args')
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -43,10 +43,7 @@ class CompletionConversationApi(Resource):
         parser.add_argument('limit', type=int_range(1, 100), default=20, location='args')
         args = parser.parse_args()
 
-        # get app info
-        app = _get_app(app_id, 'completion')
-
-        query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'completion')
+        query = db.select(Conversation).where(Conversation.app_id == app_model.id, Conversation.mode == 'completion')
 
         if args['keyword']:
             query = query.join(
@@ -106,24 +103,22 @@ class CompletionConversationDetailApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model(mode=AppMode.COMPLETION)
     @marshal_with(conversation_message_detail_fields)
-    def get(self, app_id, conversation_id):
-        app_id = str(app_id)
+    def get(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
 
-        return _get_conversation(app_id, conversation_id, 'completion')
+        return _get_conversation(app_model, conversation_id)
 
     @setup_required
     @login_required
     @account_initialization_required
-    def delete(self, app_id, conversation_id):
-        app_id = str(app_id)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
+    def delete(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
 
-        app = _get_app(app_id, 'chat')
-
         conversation = db.session.query(Conversation) \
-            .filter(Conversation.id == conversation_id, Conversation.app_id == app.id).first()
+            .filter(Conversation.id == conversation_id, Conversation.app_id == app_model.id).first()
 
         if not conversation:
             raise NotFound("Conversation Not Exists.")
@@ -139,10 +134,9 @@ class ChatConversationApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @marshal_with(conversation_with_summary_pagination_fields)
-    def get(self, app_id):
-        app_id = str(app_id)
-
+    def get(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('keyword', type=str, location='args')
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -154,10 +148,7 @@ class ChatConversationApi(Resource):
         parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
         args = parser.parse_args()
 
-        # get app info
-        app = _get_app(app_id, 'chat')
-
-        query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'chat')
+        query = db.select(Conversation).where(Conversation.app_id == app_model.id)
 
         if args['keyword']:
             query = query.join(
@@ -211,6 +202,9 @@ class ChatConversationApi(Resource):
                 .having(func.count(Message.id) >= args['message_count_gte'])
             )
 
+        if app_model.mode == AppMode.ADVANCED_CHAT.value:
+            query = query.where(Conversation.invoke_from != InvokeFrom.DEBUGGER.value)
+
         query = query.order_by(Conversation.created_at.desc())
 
         conversations = db.paginate(
@@ -228,25 +222,22 @@ class ChatConversationDetailApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @marshal_with(conversation_detail_fields)
-    def get(self, app_id, conversation_id):
-        app_id = str(app_id)
+    def get(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
 
-        return _get_conversation(app_id, conversation_id, 'chat')
+        return _get_conversation(app_model, conversation_id)
 
     @setup_required
     @login_required
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @account_initialization_required
-    def delete(self, app_id, conversation_id):
-        app_id = str(app_id)
+    def delete(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
 
-        # get app info
-        app = _get_app(app_id, 'chat')
-
         conversation = db.session.query(Conversation) \
-            .filter(Conversation.id == conversation_id, Conversation.app_id == app.id).first()
+            .filter(Conversation.id == conversation_id, Conversation.app_id == app_model.id).first()
 
         if not conversation:
             raise NotFound("Conversation Not Exists.")
@@ -263,12 +254,9 @@ api.add_resource(ChatConversationApi, '/apps/<uuid:app_id>/chat-conversations')
 api.add_resource(ChatConversationDetailApi, '/apps/<uuid:app_id>/chat-conversations/<uuid:conversation_id>')
 
 
-def _get_conversation(app_id, conversation_id, mode):
-    # get app info
-    app = _get_app(app_id, mode)
-
+def _get_conversation(app_model, conversation_id):
     conversation = db.session.query(Conversation) \
-        .filter(Conversation.id == conversation_id, Conversation.app_id == app.id).first()
+        .filter(Conversation.id == conversation_id, Conversation.app_id == app_model.id).first()
 
     if not conversation:
         raise NotFound("Conversation Not Exists.")

api/controllers/console/app/error.py

@@ -85,3 +85,9 @@ class TooManyFilesError(BaseHTTPException):
     error_code = 'too_many_files'
     description = "Only one file is allowed."
     code = 400
+
+
+class DraftWorkflowNotExist(BaseHTTPException):
+    error_code = 'draft_workflow_not_exist'
+    description = "Draft workflow need to be initialized."
+    code = 400

api/controllers/console/app/generator.py

@@ -11,7 +11,7 @@ from controllers.console.app.error import (
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
-from core.generator.llm_generator import LLMGenerator
+from core.llm_generator.llm_generator import LLMGenerator
 from core.model_runtime.errors.invoke import InvokeError
 from libs.login import login_required
 

api/controllers/console/app/message.py

@@ -1,26 +1,22 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_login import current_user
 from flask_restful import Resource, fields, marshal_with, reqparse
 from flask_restful.inputs import int_range
 from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
 
 from controllers.console import api
-from controllers.console.app import _get_app
 from controllers.console.app.error import (
-    AppMoreLikeThisDisabledError,
     CompletionRequestError,
     ProviderModelCurrentlyNotSupportError,
     ProviderNotInitializeError,
     ProviderQuotaExceededError,
 )
+from controllers.console.app.wraps import get_app_model
+from controllers.console.explore.error import AppSuggestedQuestionsAfterAnswerDisabledError
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check
-from core.entities.application_entities import InvokeFrom
+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 extensions.ext_database import db
@@ -28,12 +24,10 @@ from fields.conversation_fields import annotation_fields, message_detail_fields
 from libs.helper import uuid_value
 from libs.infinite_scroll_pagination import InfiniteScrollPagination
 from libs.login import login_required
-from models.model import Conversation, Message, MessageAnnotation, MessageFeedback
+from models.model import AppMode, Conversation, Message, MessageAnnotation, MessageFeedback
 from services.annotation_service import AppAnnotationService
-from services.completion_service import CompletionService
-from services.errors.app import MoreLikeThisDisabledError
 from services.errors.conversation import ConversationNotExistsError
-from services.errors.message import MessageNotExistsError
+from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
 from services.message_service import MessageService
 
 
@@ -46,14 +40,10 @@ class ChatMessageListApi(Resource):
 
     @setup_required
     @login_required
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @account_initialization_required
     @marshal_with(message_infinite_scroll_pagination_fields)
-    def get(self, app_id):
-        app_id = str(app_id)
-
-        # get app info
-        app = _get_app(app_id, 'chat')
-
+    def get(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('conversation_id', required=True, type=uuid_value, location='args')
         parser.add_argument('first_id', type=uuid_value, location='args')
@@ -62,7 +52,7 @@ class ChatMessageListApi(Resource):
 
         conversation = db.session.query(Conversation).filter(
             Conversation.id == args['conversation_id'],
-            Conversation.app_id == app.id
+            Conversation.app_id == app_model.id
         ).first()
 
         if not conversation:
@@ -110,12 +100,8 @@ class MessageFeedbackApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
-        app_id = str(app_id)
-
-        # get app info
-        app = _get_app(app_id)
-
+    @get_app_model
+    def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('message_id', required=True, type=uuid_value, location='json')
         parser.add_argument('rating', type=str, choices=['like', 'dislike', None], location='json')
@@ -125,7 +111,7 @@ class MessageFeedbackApi(Resource):
 
         message = db.session.query(Message).filter(
             Message.id == message_id,
-            Message.app_id == app.id
+            Message.app_id == app_model.id
         ).first()
 
         if not message:
@@ -141,7 +127,7 @@ class MessageFeedbackApi(Resource):
             raise ValueError('rating cannot be None when feedback not exists')
         else:
             feedback = MessageFeedback(
-                app_id=app.id,
+                app_id=app_model.id,
                 conversation_id=message.conversation_id,
                 message_id=message.id,
                 rating=args['rating'],
@@ -160,21 +146,20 @@ class MessageAnnotationApi(Resource):
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check('annotation')
+    @get_app_model
     @marshal_with(annotation_fields)
-    def post(self, app_id):
+    def post(self, app_model):
         # The role of the current user in the ta table must be admin or owner
         if not current_user.is_admin_or_owner:
             raise Forbidden()
 
-        app_id = str(app_id)
-
         parser = reqparse.RequestParser()
         parser.add_argument('message_id', required=False, type=uuid_value, location='json')
         parser.add_argument('question', required=True, type=str, location='json')
         parser.add_argument('answer', required=True, type=str, location='json')
         parser.add_argument('annotation_reply', required=False, type=dict, location='json')
         args = parser.parse_args()
-        annotation = AppAnnotationService.up_insert_app_annotation_from_message(args, app_id)
+        annotation = AppAnnotationService.up_insert_app_annotation_from_message(args, app_model.id)
 
         return annotation
 
@@ -183,93 +168,29 @@ class MessageAnnotationCountApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
-        app_id = str(app_id)
-
-        # get app info
-        app = _get_app(app_id)
-
+    @get_app_model
+    def get(self, app_model):
         count = db.session.query(MessageAnnotation).filter(
-            MessageAnnotation.app_id == app.id
+            MessageAnnotation.app_id == app_model.id
         ).count()
 
         return {'count': count}
 
 
-class MessageMoreLikeThisApi(Resource):
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, app_id, message_id):
-        app_id = str(app_id)
-        message_id = str(message_id)
-
-        parser = reqparse.RequestParser()
-        parser.add_argument('response_mode', type=str, required=True, choices=['blocking', 'streaming'],
-                            location='args')
-        args = parser.parse_args()
-
-        streaming = args['response_mode'] == 'streaming'
-
-        # get app info
-        app_model = _get_app(app_id, 'completion')
-
-        try:
-            response = CompletionService.generate_more_like_this(
-                app_model=app_model,
-                user=current_user,
-                message_id=message_id,
-                invoke_from=InvokeFrom.DEBUGGER,
-                streaming=streaming
-            )
-            return compact_response(response)
-        except MessageNotExistsError:
-            raise NotFound("Message Not Exists.")
-        except MoreLikeThisDisabledError:
-            raise AppMoreLikeThisDisabledError()
-        except ProviderTokenNotInitError as ex:
-            raise ProviderNotInitializeError(ex.description)
-        except QuotaExceededError:
-            raise ProviderQuotaExceededError()
-        except ModelCurrentlyNotSupportError:
-            raise ProviderModelCurrentlyNotSupportError()
-        except InvokeError as e:
-            raise CompletionRequestError(e.description)
-        except ValueError as e:
-            raise e
-        except Exception as e:
-            logging.exception("internal server error.")
-            raise InternalServerError()
-
-
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 class MessageSuggestedQuestionApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id, message_id):
-        app_id = str(app_id)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
+    def get(self, app_model, message_id):
         message_id = str(message_id)
 
-        # get app info
-        app_model = _get_app(app_id, 'chat')
-
         try:
             questions = MessageService.get_suggested_questions_after_answer(
                 app_model=app_model,
                 message_id=message_id,
                 user=current_user,
-                check_enabled=False
+                invoke_from=InvokeFrom.DEBUGGER
             )
         except MessageNotExistsError:
             raise NotFound("Message not found")
@@ -283,6 +204,8 @@ class MessageSuggestedQuestionApi(Resource):
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
             raise CompletionRequestError(e.description)
+        except SuggestedQuestionsAfterAnswerDisabledError:
+            raise AppSuggestedQuestionsAfterAnswerDisabledError()
         except Exception:
             logging.exception("internal server error.")
             raise InternalServerError()
@@ -294,14 +217,11 @@ class MessageApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(message_detail_fields)
-    def get(self, app_id, message_id):
-        app_id = str(app_id)
+    def get(self, app_model, message_id):
         message_id = str(message_id)
 
-        # get app info
-        app_model = _get_app(app_id)
-
         message = db.session.query(Message).filter(
             Message.id == message_id,
             Message.app_id == app_model.id
@@ -313,7 +233,6 @@ class MessageApi(Resource):
         return message
 
 
-api.add_resource(MessageMoreLikeThisApi, '/apps/<uuid:app_id>/completion-messages/<uuid:message_id>/more-like-this')
 api.add_resource(MessageSuggestedQuestionApi, '/apps/<uuid:app_id>/chat-messages/<uuid:message_id>/suggested-questions')
 api.add_resource(ChatMessageListApi, '/apps/<uuid:app_id>/chat-messages', endpoint='console_chat_messages')
 api.add_resource(MessageFeedbackApi, '/apps/<uuid:app_id>/feedbacks')

api/controllers/console/app/model_config.py

@@ -1,16 +1,20 @@
+import json
 
 from flask import request
 from flask_login import current_user
 from flask_restful import Resource
 
 from controllers.console import api
-from controllers.console.app import _get_app
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
+from core.agent.entities import AgentToolEntity
+from core.tools.tool_manager import ToolManager
+from core.tools.utils.configuration import ToolParameterConfigurationManager
 from events.app_event import app_model_config_was_updated
 from extensions.ext_database import db
 from libs.login import login_required
-from models.model import AppModelConfig
+from models.model import AppMode, AppModelConfig
 from services.app_model_config_service import AppModelConfigService
 
 
@@ -19,33 +23,113 @@ class ModelConfigResource(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id):
+    @get_app_model(mode=[AppMode.AGENT_CHAT, AppMode.CHAT, AppMode.COMPLETION])
+    def post(self, app_model):
         """Modify app model config"""
-        app_id = str(app_id)
-
-        app = _get_app(app_id)
-
         # validate config
         model_configuration = AppModelConfigService.validate_configuration(
             tenant_id=current_user.current_tenant_id,
-            account=current_user,
             config=request.json,
-            app_mode=app.mode
+            app_mode=AppMode.value_of(app_model.mode)
         )
 
         new_app_model_config = AppModelConfig(
-            app_id=app.id,
+            app_id=app_model.id,
         )
         new_app_model_config = new_app_model_config.from_model_config_dict(model_configuration)
 
+        if app_model.mode == AppMode.AGENT_CHAT.value or app_model.is_agent:
+            # get original app model config
+            original_app_model_config: AppModelConfig = db.session.query(AppModelConfig).filter(
+                AppModelConfig.id == app_model.app_model_config_id
+            ).first()
+            agent_mode = original_app_model_config.agent_mode_dict
+            # decrypt agent tool parameters if it's secret-input
+            parameter_map = {}
+            masked_parameter_map = {}
+            tool_map = {}
+            for tool in agent_mode.get('tools') or []:
+                if not isinstance(tool, dict) or len(tool.keys()) <= 3:
+                    continue
+
+                agent_tool_entity = AgentToolEntity(**tool)
+                # get tool
+                try:
+                    tool_runtime = ToolManager.get_agent_tool_runtime(
+                        tenant_id=current_user.current_tenant_id,
+                        agent_tool=agent_tool_entity,
+                    )
+                    manager = ToolParameterConfigurationManager(
+                        tenant_id=current_user.current_tenant_id,
+                        tool_runtime=tool_runtime,
+                        provider_name=agent_tool_entity.provider_id,
+                        provider_type=agent_tool_entity.provider_type,
+                    )
+                except Exception as e:
+                    continue
+
+                # get decrypted parameters
+                if agent_tool_entity.tool_parameters:
+                    parameters = manager.decrypt_tool_parameters(agent_tool_entity.tool_parameters or {})
+                    masked_parameter = manager.mask_tool_parameters(parameters or {})
+                else:
+                    parameters = {}
+                    masked_parameter = {}
+
+                key = f'{agent_tool_entity.provider_id}.{agent_tool_entity.provider_type}.{agent_tool_entity.tool_name}'
+                masked_parameter_map[key] = masked_parameter
+                parameter_map[key] = parameters
+                tool_map[key] = tool_runtime
+
+            # encrypt agent tool parameters if it's secret-input
+            agent_mode = new_app_model_config.agent_mode_dict
+            for tool in agent_mode.get('tools') or []:
+                agent_tool_entity = AgentToolEntity(**tool)
+
+                # get tool
+                key = f'{agent_tool_entity.provider_id}.{agent_tool_entity.provider_type}.{agent_tool_entity.tool_name}'
+                if key in tool_map:
+                    tool_runtime = tool_map[key]
+                else:
+                    try:
+                        tool_runtime = ToolManager.get_agent_tool_runtime(
+                            tenant_id=current_user.current_tenant_id,
+                            agent_tool=agent_tool_entity,
+                        )
+                    except Exception as e:
+                        continue
+
+                manager = ToolParameterConfigurationManager(
+                    tenant_id=current_user.current_tenant_id,
+                    tool_runtime=tool_runtime,
+                    provider_name=agent_tool_entity.provider_id,
+                    provider_type=agent_tool_entity.provider_type,
+                )
+                manager.delete_tool_parameters_cache()
+
+                # override parameters if it equals to masked parameters
+                if agent_tool_entity.tool_parameters:
+                    if key not in masked_parameter_map:
+                        continue
+
+                    if agent_tool_entity.tool_parameters == masked_parameter_map[key]:
+                        agent_tool_entity.tool_parameters = parameter_map[key]
+
+                # encrypt parameters
+                if agent_tool_entity.tool_parameters:
+                    tool['tool_parameters'] = manager.encrypt_tool_parameters(agent_tool_entity.tool_parameters or {})
+
+            # update app model config
+            new_app_model_config.agent_mode = json.dumps(agent_mode)
+
         db.session.add(new_app_model_config)
         db.session.flush()
 
-        app.app_model_config_id = new_app_model_config.id
+        app_model.app_model_config_id = new_app_model_config.id
         db.session.commit()
 
         app_model_config_was_updated.send(
-            app,
+            app_model,
             app_model_config=new_app_model_config
         )
 

api/controllers/console/app/site.py

@@ -4,7 +4,7 @@ from werkzeug.exceptions import Forbidden, NotFound
 
 from constants.languages import supported_language
 from controllers.console import api
-from controllers.console.app import _get_app
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from extensions.ext_database import db
@@ -34,13 +34,11 @@ class AppSite(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_site_fields)
-    def post(self, app_id):
+    def post(self, app_model):
         args = parse_app_site_args()
 
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
-
         # The role of the current user in the ta table must be admin or owner
         if not current_user.is_admin_or_owner:
             raise Forbidden()
@@ -82,11 +80,9 @@ class AppSiteAccessTokenReset(Resource):
     @setup_required
     @login_required
     @account_initialization_required
+    @get_app_model
     @marshal_with(app_site_fields)
-    def post(self, app_id):
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
-
+    def post(self, app_model):
         # The role of the current user in the ta table must be admin or owner
         if not current_user.is_admin_or_owner:
             raise Forbidden()

api/controllers/console/app/statistic.py

@@ -7,12 +7,13 @@ from flask_login import current_user
 from flask_restful import Resource, reqparse
 
 from controllers.console import api
-from controllers.console.app import _get_app
+from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from extensions.ext_database import db
 from libs.helper import datetime_string
 from libs.login import login_required
+from models.model import AppMode
 
 
 class DailyConversationStatistic(Resource):
@@ -20,10 +21,9 @@ class DailyConversationStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -81,10 +81,9 @@ class DailyTerminalsStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -141,10 +140,9 @@ class DailyTokenCostStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -205,10 +203,9 @@ class AverageSessionInteractionStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id, 'chat')
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -271,10 +268,9 @@ class UserSatisfactionRateStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -334,10 +330,9 @@ class AverageResponseTimeStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model(mode=AppMode.COMPLETION)
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id, 'completion')
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
@@ -396,10 +391,9 @@ class TokensPerSecondStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id):
+    @get_app_model
+    def get(self, app_model):
         account = current_user
-        app_id = str(app_id)
-        app_model = _get_app(app_id)
 
         parser = reqparse.RequestParser()
         parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')

api/controllers/console/app/workflow.py

@@ -0,0 +1,324 @@
+import json
+import logging
+
+from flask import abort, request
+from flask_restful import Resource, marshal_with, reqparse
+from werkzeug.exceptions import InternalServerError, NotFound
+
+import services
+from controllers.console import api
+from controllers.console.app.error import ConversationCompletedError, DraftWorkflowNotExist
+from controllers.console.app.wraps import get_app_model
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
+from fields.workflow_fields import workflow_fields
+from fields.workflow_run_fields import workflow_run_node_execution_fields
+from libs import helper
+from libs.helper import TimestampField, uuid_value
+from libs.login import current_user, login_required
+from models.model import App, AppMode
+from services.app_generate_service import AppGenerateService
+from services.workflow_service import WorkflowService
+
+logger = logging.getLogger(__name__)
+
+
+class DraftWorkflowApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_fields)
+    def get(self, app_model: App):
+        """
+        Get draft workflow
+        """
+        # fetch draft workflow by app_model
+        workflow_service = WorkflowService()
+        workflow = workflow_service.get_draft_workflow(app_model=app_model)
+
+        if not workflow:
+            raise DraftWorkflowNotExist()
+
+        # return workflow, if not found, return None (initiate graph by frontend)
+        return workflow
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    def post(self, app_model: App):
+        """
+        Sync draft workflow
+        """
+        content_type = request.headers.get('Content-Type')
+
+        if 'application/json' in content_type:
+            parser = reqparse.RequestParser()
+            parser.add_argument('graph', type=dict, required=True, nullable=False, location='json')
+            parser.add_argument('features', type=dict, required=True, nullable=False, location='json')
+            args = parser.parse_args()
+        elif 'text/plain' in content_type:
+            try:
+                data = json.loads(request.data.decode('utf-8'))
+                if 'graph' not in data or 'features' not in data:
+                    raise ValueError('graph or features not found in data')
+
+                if not isinstance(data.get('graph'), dict) or not isinstance(data.get('features'), dict):
+                    raise ValueError('graph or features is not a dict')
+
+                args = {
+                    'graph': data.get('graph'),
+                    'features': data.get('features')
+                }
+            except json.JSONDecodeError:
+                return {'message': 'Invalid JSON data'}, 400
+        else:
+            abort(415)
+
+        workflow_service = WorkflowService()
+        workflow = workflow_service.sync_draft_workflow(
+            app_model=app_model,
+            graph=args.get('graph'),
+            features=args.get('features'),
+            account=current_user
+        )
+
+        return {
+            "result": "success",
+            "updated_at": TimestampField().format(workflow.updated_at or workflow.created_at)
+        }
+
+
+class AdvancedChatDraftWorkflowRunApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
+    def post(self, app_model: App):
+        """
+        Run draft workflow
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, location='json')
+        parser.add_argument('query', type=str, required=True, location='json', default='')
+        parser.add_argument('files', type=list, location='json')
+        parser.add_argument('conversation_id', type=uuid_value, location='json')
+        args = parser.parse_args()
+
+        try:
+            response = AppGenerateService.generate(
+                app_model=app_model,
+                user=current_user,
+                args=args,
+                invoke_from=InvokeFrom.DEBUGGER,
+                streaming=True
+            )
+
+            return helper.compact_generate_response(response)
+        except services.errors.conversation.ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+        except services.errors.conversation.ConversationCompletedError:
+            raise ConversationCompletedError()
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class DraftWorkflowRunApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.WORKFLOW])
+    def post(self, app_model: App):
+        """
+        Run draft workflow
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, required=True, nullable=False, location='json')
+        parser.add_argument('files', type=list, required=False, location='json')
+        args = parser.parse_args()
+
+        try:
+            response = AppGenerateService.generate(
+                app_model=app_model,
+                user=current_user,
+                args=args,
+                invoke_from=InvokeFrom.DEBUGGER,
+                streaming=True
+            )
+
+            return helper.compact_generate_response(response)
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class WorkflowTaskStopApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    def post(self, app_model: App, task_id: str):
+        """
+        Stop workflow task
+        """
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.DEBUGGER, current_user.id)
+
+        return {
+            "result": "success"
+        }
+
+
+class DraftWorkflowNodeRunApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_run_node_execution_fields)
+    def post(self, app_model: App, node_id: str):
+        """
+        Run draft workflow node
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, required=True, nullable=False, location='json')
+        args = parser.parse_args()
+
+        workflow_service = WorkflowService()
+        workflow_node_execution = workflow_service.run_draft_workflow_node(
+            app_model=app_model,
+            node_id=node_id,
+            user_inputs=args.get('inputs'),
+            account=current_user
+        )
+
+        return workflow_node_execution
+
+
+class PublishedWorkflowApi(Resource):
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_fields)
+    def get(self, app_model: App):
+        """
+        Get published workflow
+        """
+        # fetch published workflow by app_model
+        workflow_service = WorkflowService()
+        workflow = workflow_service.get_published_workflow(app_model=app_model)
+
+        # return workflow, if not found, return None
+        return workflow
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    def post(self, app_model: App):
+        """
+        Publish workflow
+        """
+        workflow_service = WorkflowService()
+        workflow = workflow_service.publish_workflow(app_model=app_model, account=current_user)
+
+        return {
+            "result": "success",
+            "created_at": TimestampField().format(workflow.created_at)
+        }
+
+
+class DefaultBlockConfigsApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    def get(self, app_model: App):
+        """
+        Get default block config
+        """
+        # Get default block configs
+        workflow_service = WorkflowService()
+        return workflow_service.get_default_block_configs()
+
+
+class DefaultBlockConfigApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    def get(self, app_model: App, block_type: str):
+        """
+        Get default block config
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('q', type=str, location='args')
+        args = parser.parse_args()
+
+        filters = None
+        if args.get('q'):
+            try:
+                filters = json.loads(args.get('q'))
+            except json.JSONDecodeError:
+                raise ValueError('Invalid filters')
+
+        # Get default block configs
+        workflow_service = WorkflowService()
+        return workflow_service.get_default_block_config(
+            node_type=block_type,
+            filters=filters
+        )
+
+
+class ConvertToWorkflowApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.CHAT, AppMode.COMPLETION])
+    def post(self, app_model: App):
+        """
+        Convert basic mode of chatbot app to workflow mode
+        Convert expert mode of chatbot app to workflow mode
+        Convert Completion App to Workflow App
+        """
+        if request.data:
+            parser = reqparse.RequestParser()
+            parser.add_argument('name', type=str, required=False, nullable=True, location='json')
+            parser.add_argument('icon', type=str, required=False, nullable=True, location='json')
+            parser.add_argument('icon_background', type=str, required=False, nullable=True, location='json')
+            args = parser.parse_args()
+        else:
+            args = {}
+
+        # convert to workflow mode
+        workflow_service = WorkflowService()
+        new_app_model = workflow_service.convert_to_workflow(
+            app_model=app_model,
+            account=current_user,
+            args=args
+        )
+
+        # return app id
+        return {
+            'new_app_id': new_app_model.id,
+        }
+
+
+api.add_resource(DraftWorkflowApi, '/apps/<uuid:app_id>/workflows/draft')
+api.add_resource(AdvancedChatDraftWorkflowRunApi, '/apps/<uuid:app_id>/advanced-chat/workflows/draft/run')
+api.add_resource(DraftWorkflowRunApi, '/apps/<uuid:app_id>/workflows/draft/run')
+api.add_resource(WorkflowTaskStopApi, '/apps/<uuid:app_id>/workflow-runs/tasks/<string:task_id>/stop')
+api.add_resource(DraftWorkflowNodeRunApi, '/apps/<uuid:app_id>/workflows/draft/nodes/<string:node_id>/run')
+api.add_resource(PublishedWorkflowApi, '/apps/<uuid:app_id>/workflows/publish')
+api.add_resource(DefaultBlockConfigsApi, '/apps/<uuid:app_id>/workflows/default-workflow-block-configs')
+api.add_resource(DefaultBlockConfigApi, '/apps/<uuid:app_id>/workflows/default-workflow-block-configs'
+                                        '/<string:block_type>')
+api.add_resource(ConvertToWorkflowApi, '/apps/<uuid:app_id>/convert-to-workflow')

api/controllers/console/app/workflow_app_log.py

@@ -0,0 +1,41 @@
+from flask_restful import Resource, marshal_with, reqparse
+from flask_restful.inputs import int_range
+
+from controllers.console import api
+from controllers.console.app.wraps import get_app_model
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from fields.workflow_app_log_fields import workflow_app_log_pagination_fields
+from libs.login import login_required
+from models.model import App, AppMode
+from services.workflow_app_service import WorkflowAppService
+
+
+class WorkflowAppLogApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.WORKFLOW])
+    @marshal_with(workflow_app_log_pagination_fields)
+    def get(self, app_model: App):
+        """
+        Get workflow app logs
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('keyword', type=str, location='args')
+        parser.add_argument('status', type=str, choices=['succeeded', 'failed', 'stopped'], location='args')
+        parser.add_argument('page', type=int_range(1, 99999), default=1, location='args')
+        parser.add_argument('limit', type=int_range(1, 100), default=20, location='args')
+        args = parser.parse_args()
+
+        # get paginate workflow app logs
+        workflow_app_service = WorkflowAppService()
+        workflow_app_log_pagination = workflow_app_service.get_paginate_workflow_app_logs(
+            app_model=app_model,
+            args=args
+        )
+
+        return workflow_app_log_pagination
+
+
+api.add_resource(WorkflowAppLogApi, '/apps/<uuid:app_id>/workflow-app-logs')

api/controllers/console/app/workflow_run.py

@@ -0,0 +1,109 @@
+from flask_restful import Resource, marshal_with, reqparse
+from flask_restful.inputs import int_range
+
+from controllers.console import api
+from controllers.console.app.wraps import get_app_model
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from fields.workflow_run_fields import (
+    advanced_chat_workflow_run_pagination_fields,
+    workflow_run_detail_fields,
+    workflow_run_node_execution_list_fields,
+    workflow_run_pagination_fields,
+)
+from libs.helper import uuid_value
+from libs.login import login_required
+from models.model import App, AppMode
+from services.workflow_run_service import WorkflowRunService
+
+
+class AdvancedChatAppWorkflowRunListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
+    @marshal_with(advanced_chat_workflow_run_pagination_fields)
+    def get(self, app_model: App):
+        """
+        Get advanced chat app workflow run list
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('last_id', type=uuid_value, location='args')
+        parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        args = parser.parse_args()
+
+        workflow_run_service = WorkflowRunService()
+        result = workflow_run_service.get_paginate_advanced_chat_workflow_runs(
+            app_model=app_model,
+            args=args
+        )
+
+        return result
+
+
+class WorkflowRunListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_run_pagination_fields)
+    def get(self, app_model: App):
+        """
+        Get workflow run list
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument('last_id', type=uuid_value, location='args')
+        parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        args = parser.parse_args()
+
+        workflow_run_service = WorkflowRunService()
+        result = workflow_run_service.get_paginate_workflow_runs(
+            app_model=app_model,
+            args=args
+        )
+
+        return result
+
+
+class WorkflowRunDetailApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_run_detail_fields)
+    def get(self, app_model: App, run_id):
+        """
+        Get workflow run detail
+        """
+        run_id = str(run_id)
+
+        workflow_run_service = WorkflowRunService()
+        workflow_run = workflow_run_service.get_workflow_run(app_model=app_model, run_id=run_id)
+
+        return workflow_run
+
+
+class WorkflowRunNodeExecutionListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
+    @marshal_with(workflow_run_node_execution_list_fields)
+    def get(self, app_model: App, run_id):
+        """
+        Get workflow run node execution list
+        """
+        run_id = str(run_id)
+
+        workflow_run_service = WorkflowRunService()
+        node_executions = workflow_run_service.get_workflow_run_node_executions(app_model=app_model, run_id=run_id)
+
+        return {
+            'data': node_executions
+        }
+
+
+api.add_resource(AdvancedChatAppWorkflowRunListApi, '/apps/<uuid:app_id>/advanced-chat/workflow-runs')
+api.add_resource(WorkflowRunListApi, '/apps/<uuid:app_id>/workflow-runs')
+api.add_resource(WorkflowRunDetailApi, '/apps/<uuid:app_id>/workflow-runs/<uuid:run_id>')
+api.add_resource(WorkflowRunNodeExecutionListApi, '/apps/<uuid:app_id>/workflow-runs/<uuid:run_id>/node-executions')

api/controllers/console/app/workflow_statistic.py

@@ -0,0 +1,278 @@
+from datetime import datetime
+from decimal import Decimal
+
+import pytz
+from flask import jsonify
+from flask_login import current_user
+from flask_restful import Resource, reqparse
+
+from controllers.console import api
+from controllers.console.app.wraps import get_app_model
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from extensions.ext_database import db
+from libs.helper import datetime_string
+from libs.login import login_required
+from models.model import AppMode
+from models.workflow import WorkflowRunTriggeredFrom
+
+
+class WorkflowDailyRunsStatistic(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def get(self, app_model):
+        account = current_user
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        args = parser.parse_args()
+
+        sql_query = '''
+        SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(id) AS runs
+            FROM workflow_runs 
+            WHERE app_id = :app_id 
+                AND triggered_from = :triggered_from
+        '''
+        arg_dict = {'tz': account.timezone, 'app_id': app_model.id, 'triggered_from': WorkflowRunTriggeredFrom.APP_RUN.value}
+
+        timezone = pytz.timezone(account.timezone)
+        utc_timezone = pytz.utc
+
+        if args['start']:
+            start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
+            start_datetime = start_datetime.replace(second=0)
+
+            start_datetime_timezone = timezone.localize(start_datetime)
+            start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at >= :start'
+            arg_dict['start'] = start_datetime_utc
+
+        if args['end']:
+            end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
+            end_datetime = end_datetime.replace(second=0)
+
+            end_datetime_timezone = timezone.localize(end_datetime)
+            end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at < :end'
+            arg_dict['end'] = end_datetime_utc
+
+        sql_query += ' GROUP BY date order by date'
+
+        response_data = []
+
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(sql_query), arg_dict)
+            for i in rs:
+                response_data.append({
+                    'date': str(i.date),
+                    'runs': i.runs
+                })
+
+        return jsonify({
+            'data': response_data
+        })
+
+class WorkflowDailyTerminalsStatistic(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def get(self, app_model):
+        account = current_user
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        args = parser.parse_args()
+
+        sql_query = '''
+                SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(distinct workflow_runs.created_by) AS terminal_count
+                    FROM workflow_runs 
+                    WHERE app_id = :app_id 
+                        AND triggered_from = :triggered_from
+                '''
+        arg_dict = {'tz': account.timezone, 'app_id': app_model.id, 'triggered_from': WorkflowRunTriggeredFrom.APP_RUN.value}
+
+        timezone = pytz.timezone(account.timezone)
+        utc_timezone = pytz.utc
+
+        if args['start']:
+            start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
+            start_datetime = start_datetime.replace(second=0)
+
+            start_datetime_timezone = timezone.localize(start_datetime)
+            start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at >= :start'
+            arg_dict['start'] = start_datetime_utc
+
+        if args['end']:
+            end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
+            end_datetime = end_datetime.replace(second=0)
+
+            end_datetime_timezone = timezone.localize(end_datetime)
+            end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at < :end'
+            arg_dict['end'] = end_datetime_utc
+
+        sql_query += ' GROUP BY date order by date'
+
+        response_data = []
+
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(sql_query), arg_dict)            
+            for i in rs:
+                response_data.append({
+                    'date': str(i.date),
+                    'terminal_count': i.terminal_count
+                })
+
+        return jsonify({
+            'data': response_data
+        })
+
+class WorkflowDailyTokenCostStatistic(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model
+    def get(self, app_model):
+        account = current_user
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        args = parser.parse_args()
+
+        sql_query = '''
+                SELECT 
+                    date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, 
+                    SUM(workflow_runs.total_tokens) as token_count
+                FROM workflow_runs 
+                WHERE app_id = :app_id 
+                    AND triggered_from = :triggered_from
+                '''
+        arg_dict = {'tz': account.timezone, 'app_id': app_model.id, 'triggered_from': WorkflowRunTriggeredFrom.APP_RUN.value}
+
+        timezone = pytz.timezone(account.timezone)
+        utc_timezone = pytz.utc
+
+        if args['start']:
+            start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
+            start_datetime = start_datetime.replace(second=0)
+
+            start_datetime_timezone = timezone.localize(start_datetime)
+            start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at >= :start'
+            arg_dict['start'] = start_datetime_utc
+
+        if args['end']:
+            end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
+            end_datetime = end_datetime.replace(second=0)
+
+            end_datetime_timezone = timezone.localize(end_datetime)
+            end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query += ' and created_at < :end'
+            arg_dict['end'] = end_datetime_utc
+
+        sql_query += ' GROUP BY date order by date'
+
+        response_data = []
+
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(sql_query), arg_dict)
+            for i in rs:
+                response_data.append({
+                    'date': str(i.date),
+                    'token_count': i.token_count,
+                })
+
+        return jsonify({
+            'data': response_data
+        })
+
+class WorkflowAverageAppInteractionStatistic(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_app_model(mode=[AppMode.WORKFLOW])
+    def get(self, app_model):
+        account = current_user
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
+        args = parser.parse_args()
+
+        sql_query = """
+            SELECT 
+                AVG(sub.interactions) as interactions,
+                sub.date
+            FROM
+                (SELECT 
+                    date(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, 
+                    c.created_by,
+                    COUNT(c.id) AS interactions
+                FROM workflow_runs c
+                WHERE c.app_id = :app_id
+                    AND c.triggered_from = :triggered_from
+                    {{start}}
+                    {{end}}
+                GROUP BY date, c.created_by) sub
+            GROUP BY sub.created_by, sub.date
+            """
+        arg_dict = {'tz': account.timezone, 'app_id': app_model.id, 'triggered_from': WorkflowRunTriggeredFrom.APP_RUN.value}
+
+        timezone = pytz.timezone(account.timezone)
+        utc_timezone = pytz.utc
+
+        if args['start']:
+            start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
+            start_datetime = start_datetime.replace(second=0)
+
+            start_datetime_timezone = timezone.localize(start_datetime)
+            start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query = sql_query.replace('{{start}}', ' AND c.created_at >= :start')
+            arg_dict['start'] = start_datetime_utc
+        else:
+            sql_query = sql_query.replace('{{start}}', '')
+
+        if args['end']:
+            end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
+            end_datetime = end_datetime.replace(second=0)
+
+            end_datetime_timezone = timezone.localize(end_datetime)
+            end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
+
+            sql_query = sql_query.replace('{{end}}', ' and c.created_at < :end')
+            arg_dict['end'] = end_datetime_utc
+        else:
+            sql_query = sql_query.replace('{{end}}', '')
+
+        response_data = []
+        
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(sql_query), arg_dict)
+            for i in rs:
+                response_data.append({
+                    'date': str(i.date),
+                    'interactions': float(i.interactions.quantize(Decimal('0.01')))
+                })
+
+        return jsonify({
+            'data': response_data
+        })
+
+api.add_resource(WorkflowDailyRunsStatistic, '/apps/<uuid:app_id>/workflow/statistics/daily-conversations')
+api.add_resource(WorkflowDailyTerminalsStatistic, '/apps/<uuid:app_id>/workflow/statistics/daily-terminals')
+api.add_resource(WorkflowDailyTokenCostStatistic, '/apps/<uuid:app_id>/workflow/statistics/token-costs')
+api.add_resource(WorkflowAverageAppInteractionStatistic, '/apps/<uuid:app_id>/workflow/statistics/average-app-interactions')

api/controllers/console/app/wraps.py

@@ -0,0 +1,55 @@
+from collections.abc import Callable
+from functools import wraps
+from typing import Optional, Union
+
+from controllers.console.app.error import AppNotFoundError
+from extensions.ext_database import db
+from libs.login import current_user
+from models.model import App, AppMode
+
+
+def get_app_model(view: Optional[Callable] = None, *,
+                  mode: Union[AppMode, list[AppMode]] = None):
+    def decorator(view_func):
+        @wraps(view_func)
+        def decorated_view(*args, **kwargs):
+            if not kwargs.get('app_id'):
+                raise ValueError('missing app_id in path parameters')
+
+            app_id = kwargs.get('app_id')
+            app_id = str(app_id)
+
+            del kwargs['app_id']
+
+            app_model = db.session.query(App).filter(
+                App.id == app_id,
+                App.tenant_id == current_user.current_tenant_id,
+                App.status == 'normal'
+            ).first()
+
+            if not app_model:
+                raise AppNotFoundError()
+
+            app_mode = AppMode.value_of(app_model.mode)
+            if app_mode == AppMode.CHANNEL:
+                raise AppNotFoundError()
+
+            if mode is not None:
+                if isinstance(mode, list):
+                    modes = mode
+                else:
+                    modes = [mode]
+
+                if app_mode not in modes:
+                    mode_values = {m.value for m in modes}
+                    raise AppNotFoundError(f"App mode is not in the supported list: {mode_values}")
+
+            kwargs['app_model'] = app_model
+
+            return view_func(*args, **kwargs)
+        return decorated_view
+
+    if view is None:
+        return decorator
+    else:
+        return decorator(view)

api/controllers/console/datasets/datasets_segments.py

@@ -12,7 +12,11 @@ from controllers.console import api
 from controllers.console.app.error import ProviderNotInitializeError
 from controllers.console.datasets.error import InvalidActionError, NoFileUploadedError, TooManyFilesError
 from controllers.console.setup import setup_required
-from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check
+from controllers.console.wraps import (
+    account_initialization_required,
+    cloud_edition_billing_knowledge_limit_check,
+    cloud_edition_billing_resource_check,
+)
 from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
@@ -207,6 +211,7 @@ class DatasetDocumentSegmentAddApi(Resource):
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check('vector_space')
+    @cloud_edition_billing_knowledge_limit_check('add_segment')
     def post(self, dataset_id, document_id):
         # check dataset
         dataset_id = str(dataset_id)
@@ -357,6 +362,7 @@ class DatasetDocumentSegmentBatchImportApi(Resource):
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check('vector_space')
+    @cloud_edition_billing_knowledge_limit_check('add_segment')
     def post(self, dataset_id, document_id):
         # check dataset
         dataset_id = str(dataset_id)

api/controllers/console/explore/audio.py

@@ -19,7 +19,6 @@ from controllers.console.app.error import (
 from controllers.console.explore.wraps import InstalledAppResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import AppModelConfig
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -32,16 +31,12 @@ from services.errors.audio import (
 class ChatAudioApi(InstalledAppResource):
     def post(self, installed_app):
         app_model = installed_app.app
-        app_model_config: AppModelConfig = app_model.app_model_config
-
-        if not app_model_config.speech_to_text_dict['enabled']:
-            raise AppUnavailableError()
 
         file = request.files['file']
 
         try:
             response = AudioService.transcript_asr(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 file=file,
                 end_user=None
             )
@@ -76,16 +71,12 @@ class ChatAudioApi(InstalledAppResource):
 class ChatTextApi(InstalledAppResource):
     def post(self, installed_app):
         app_model = installed_app.app
-        app_model_config: AppModelConfig = app_model.app_model_config
-
-        if not app_model_config.text_to_speech_dict['enabled']:
-            raise AppUnavailableError()
 
         try:
             response = AudioService.transcript_tts(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 text=request.form['text'],
-                voice=request.form['voice'] if request.form['voice'] else app_model.app_model_config.text_to_speech_dict.get('voice'),
+                voice=request.form.get('voice'),
                 streaming=False
             )
             return {'data': response.data.decode('latin1')}

api/controllers/console/explore/completion.py

@@ -1,10 +1,6 @@
-import json
 import logging
-from collections.abc import Generator
 from datetime import datetime
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_login import current_user
 from flask_restful import reqparse
 from werkzeug.exceptions import InternalServerError, NotFound
@@ -21,13 +17,15 @@ from controllers.console.app.error import (
 )
 from controllers.console.explore.error import NotChatAppError, NotCompletionAppError
 from controllers.console.explore.wraps import InstalledAppResource
-from core.application_queue_manager import ApplicationQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from extensions.ext_database import db
+from libs import helper
 from libs.helper import uuid_value
-from services.completion_service import CompletionService
+from models.model import AppMode
+from services.app_generate_service import AppGenerateService
 
 
 # define completion api for user
@@ -53,7 +51,7 @@ class CompletionApi(InstalledAppResource):
         db.session.commit()
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=current_user,
                 args=args,
@@ -61,7 +59,7 @@ class CompletionApi(InstalledAppResource):
                 streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -90,7 +88,7 @@ class CompletionStopApi(InstalledAppResource):
         if app_model.mode != 'completion':
             raise NotCompletionAppError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.EXPLORE, current_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.EXPLORE, current_user.id)
 
         return {'result': 'success'}, 200
 
@@ -98,34 +96,33 @@ class CompletionStopApi(InstalledAppResource):
 class ChatApi(InstalledAppResource):
     def post(self, installed_app):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
         parser.add_argument('inputs', type=dict, required=True, location='json')
         parser.add_argument('query', type=str, required=True, location='json')
         parser.add_argument('files', type=list, required=False, location='json')
-        parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
         parser.add_argument('conversation_id', type=uuid_value, location='json')
         parser.add_argument('retriever_from', type=str, required=False, default='explore_app', location='json')
         args = parser.parse_args()
 
-        streaming = args['response_mode'] == 'streaming'
         args['auto_generate_name'] = False
 
         installed_app.last_used_at = datetime.utcnow()
         db.session.commit()
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=current_user,
                 args=args,
                 invoke_from=InvokeFrom.EXPLORE,
-                streaming=streaming
+                streaming=True
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -151,25 +148,15 @@ class ChatApi(InstalledAppResource):
 class ChatStopApi(InstalledAppResource):
     def post(self, installed_app, task_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.EXPLORE, current_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.EXPLORE, current_user.id)
 
         return {'result': 'success'}, 200
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 api.add_resource(CompletionApi, '/installed-apps/<uuid:installed_app_id>/completion-messages', endpoint='installed_app_completion')
 api.add_resource(CompletionStopApi, '/installed-apps/<uuid:installed_app_id>/completion-messages/<string:task_id>/stop', endpoint='installed_app_stop_completion')
 api.add_resource(ChatApi, '/installed-apps/<uuid:installed_app_id>/chat-messages', endpoint='installed_app_chat_completion')

api/controllers/console/explore/conversation.py

@@ -6,8 +6,10 @@ from werkzeug.exceptions import NotFound
 from controllers.console import api
 from controllers.console.explore.error import NotChatAppError
 from controllers.console.explore.wraps import InstalledAppResource
+from core.app.entities.app_invoke_entities import InvokeFrom
 from fields.conversation_fields import conversation_infinite_scroll_pagination_fields, simple_conversation_fields
 from libs.helper import uuid_value
+from models.model import AppMode
 from services.conversation_service import ConversationService
 from services.errors.conversation import ConversationNotExistsError, LastConversationNotExistsError
 from services.web_conversation_service import WebConversationService
@@ -18,7 +20,8 @@ class ConversationListApi(InstalledAppResource):
     @marshal_with(conversation_infinite_scroll_pagination_fields)
     def get(self, installed_app):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -37,8 +40,8 @@ class ConversationListApi(InstalledAppResource):
                 user=current_user,
                 last_id=args['last_id'],
                 limit=args['limit'],
+                invoke_from=InvokeFrom.EXPLORE,
                 pinned=pinned,
-                exclude_debug_conversation=True
             )
         except LastConversationNotExistsError:
             raise NotFound("Last Conversation Not Exists.")
@@ -47,7 +50,8 @@ class ConversationListApi(InstalledAppResource):
 class ConversationApi(InstalledAppResource):
     def delete(self, installed_app, c_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -65,7 +69,8 @@ class ConversationRenameApi(InstalledAppResource):
     @marshal_with(simple_conversation_fields)
     def post(self, installed_app, c_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -91,7 +96,8 @@ class ConversationPinApi(InstalledAppResource):
 
     def patch(self, installed_app, c_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -107,7 +113,8 @@ class ConversationPinApi(InstalledAppResource):
 class ConversationUnPinApi(InstalledAppResource):
     def patch(self, installed_app, c_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)

api/controllers/console/explore/error.py

@@ -9,7 +9,13 @@ class NotCompletionAppError(BaseHTTPException):
 
 class NotChatAppError(BaseHTTPException):
     error_code = 'not_chat_app'
-    description = "Not Chat App"
+    description = "App mode is invalid."
+    code = 400
+
+
+class NotWorkflowAppError(BaseHTTPException):
+    error_code = 'not_workflow_app'
+    description = "Only support workflow app."
     code = 400
 
 

api/controllers/console/explore/installed_app.py

@@ -34,8 +34,7 @@ class InstalledAppsListApi(Resource):
                 'is_pinned': installed_app.is_pinned,
                 'last_used_at': installed_app.last_used_at,
                 'editable': current_user.role in ["owner", "admin"],
-                'uninstallable': current_tenant_id == installed_app.app_owner_tenant_id,
-                'is_agent': installed_app.is_agent
+                'uninstallable': current_tenant_id == installed_app.app_owner_tenant_id
             }
             for installed_app in installed_apps
         ]

api/controllers/console/explore/message.py

@@ -1,9 +1,5 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_login import current_user
 from flask_restful import marshal_with, reqparse
 from flask_restful.inputs import int_range
@@ -24,12 +20,14 @@ from controllers.console.explore.error import (
     NotCompletionAppError,
 )
 from controllers.console.explore.wraps import InstalledAppResource
-from core.entities.application_entities import InvokeFrom
+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.message_fields import message_infinite_scroll_pagination_fields
+from libs import helper
 from libs.helper import uuid_value
-from services.completion_service import CompletionService
+from models.model import AppMode
+from services.app_generate_service import AppGenerateService
 from services.errors.app import MoreLikeThisDisabledError
 from services.errors.conversation import ConversationNotExistsError
 from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
@@ -41,7 +39,8 @@ class MessageListApi(InstalledAppResource):
     def get(self, installed_app):
         app_model = installed_app.app
 
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -91,14 +90,14 @@ class MessageMoreLikeThisApi(InstalledAppResource):
         streaming = args['response_mode'] == 'streaming'
 
         try:
-            response = CompletionService.generate_more_like_this(
+            response = AppGenerateService.generate_more_like_this(
                 app_model=app_model,
                 user=current_user,
                 message_id=message_id,
                 invoke_from=InvokeFrom.EXPLORE,
                 streaming=streaming
             )
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except MessageNotExistsError:
             raise NotFound("Message Not Exists.")
         except MoreLikeThisDisabledError:
@@ -118,22 +117,12 @@ class MessageMoreLikeThisApi(InstalledAppResource):
             raise InternalServerError()
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 class MessageSuggestedQuestionApi(InstalledAppResource):
     def get(self, installed_app, message_id):
         app_model = installed_app.app
-        if app_model.mode != 'chat':
-            raise NotCompletionAppError()
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
+            raise NotChatAppError()
 
         message_id = str(message_id)
 
@@ -141,7 +130,8 @@ class MessageSuggestedQuestionApi(InstalledAppResource):
             questions = MessageService.get_suggested_questions_after_answer(
                 app_model=app_model,
                 user=current_user,
-                message_id=message_id
+                message_id=message_id,
+                invoke_from=InvokeFrom.EXPLORE
             )
         except MessageNotExistsError:
             raise NotFound("Message not found")

api/controllers/console/explore/parameter.py

@@ -1,13 +1,12 @@
-import json
 
 from flask import current_app
 from flask_restful import fields, marshal_with
 
 from controllers.console import api
+from controllers.console.app.error import AppUnavailableError
 from controllers.console.explore.wraps import InstalledAppResource
-from extensions.ext_database import db
-from models.model import AppModelConfig, InstalledApp
-from models.tools import ApiToolProvider
+from models.model import AppMode, InstalledApp
+from services.app_service import AppService
 
 
 class AppParameterApi(InstalledAppResource):
@@ -45,61 +44,52 @@ class AppParameterApi(InstalledAppResource):
     def get(self, installed_app: InstalledApp):
         """Retrieve app parameters."""
         app_model = installed_app.app
-        app_model_config = app_model.app_model_config
+
+        if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
+            workflow = app_model.workflow
+            if workflow is None:
+                raise AppUnavailableError()
+
+            features_dict = workflow.features_dict
+            user_input_form = workflow.user_input_form(to_old_structure=True)
+        else:
+            app_model_config = app_model.app_model_config
+            features_dict = app_model_config.to_dict()
+
+            user_input_form = features_dict.get('user_input_form', [])
 
         return {
-            'opening_statement': app_model_config.opening_statement,
-            'suggested_questions': app_model_config.suggested_questions_list,
-            'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
-            'text_to_speech': app_model_config.text_to_speech_dict,
-            'retriever_resource': app_model_config.retriever_resource_dict,
-            'annotation_reply': app_model_config.annotation_reply_dict,
-            'more_like_this': app_model_config.more_like_this_dict,
-            'user_input_form': app_model_config.user_input_form_list,
-            'sensitive_word_avoidance': app_model_config.sensitive_word_avoidance_dict,
-            'file_upload': app_model_config.file_upload_dict,
+            'opening_statement': features_dict.get('opening_statement'),
+            'suggested_questions': features_dict.get('suggested_questions', []),
+            'suggested_questions_after_answer': features_dict.get('suggested_questions_after_answer',
+                                                                  {"enabled": False}),
+            'speech_to_text': features_dict.get('speech_to_text', {"enabled": False}),
+            'text_to_speech': features_dict.get('text_to_speech', {"enabled": False}),
+            'retriever_resource': features_dict.get('retriever_resource', {"enabled": False}),
+            'annotation_reply': features_dict.get('annotation_reply', {"enabled": False}),
+            'more_like_this': features_dict.get('more_like_this', {"enabled": False}),
+            'user_input_form': user_input_form,
+            'sensitive_word_avoidance': features_dict.get('sensitive_word_avoidance',
+                                                          {"enabled": False, "type": "", "configs": []}),
+            'file_upload': features_dict.get('file_upload', {"image": {
+                                                     "enabled": False,
+                                                     "number_limits": 3,
+                                                     "detail": "high",
+                                                     "transfer_methods": ["remote_url", "local_file"]
+                                                 }}),
             'system_parameters': {
                 'image_file_size_limit': current_app.config.get('UPLOAD_IMAGE_FILE_SIZE_LIMIT')
             }
         }
 
+
 class ExploreAppMetaApi(InstalledAppResource):
     def get(self, installed_app: InstalledApp):
         """Get app meta"""
-        app_model_config: AppModelConfig = installed_app.app.app_model_config
+        app_model = installed_app.app
+        return AppService().get_app_meta(app_model)
 
-        agent_config = app_model_config.agent_mode_dict or {}
-        meta = {
-            'tool_icons': {}
-        }
 
-        # get all tools
-        tools = agent_config.get('tools', [])
-        url_prefix = (current_app.config.get("CONSOLE_API_URL")
-                  + "/console/api/workspaces/current/tool-provider/builtin/")
-        for tool in tools:
-            keys = list(tool.keys())
-            if len(keys) >= 4:
-                # current tool standard
-                provider_type = tool.get('provider_type')
-                provider_id = tool.get('provider_id')
-                tool_name = tool.get('tool_name')
-                if provider_type == 'builtin':
-                    meta['tool_icons'][tool_name] = url_prefix + provider_id + '/icon'
-                elif provider_type == 'api':
-                    try:
-                        provider: ApiToolProvider = db.session.query(ApiToolProvider).filter(
-                            ApiToolProvider.id == provider_id
-                        )
-                        meta['tool_icons'][tool_name] = json.loads(provider.icon)
-                    except:
-                        meta['tool_icons'][tool_name] =  {
-                            "background": "#252525",
-                            "content": "\ud83d\ude01"
-                        }
-
-        return meta
-
-api.add_resource(AppParameterApi, '/installed-apps/<uuid:installed_app_id>/parameters', endpoint='installed_app_parameters')
+api.add_resource(AppParameterApi, '/installed-apps/<uuid:installed_app_id>/parameters',
+                 endpoint='installed_app_parameters')
 api.add_resource(ExploreAppMetaApi, '/installed-apps/<uuid:installed_app_id>/meta', endpoint='installed_app_meta')

api/controllers/console/explore/recommended_app.py

@@ -1,15 +1,11 @@
 from flask_login import current_user
-from flask_restful import Resource, fields, marshal_with
-from sqlalchemy import and_
+from flask_restful import Resource, fields, marshal_with, reqparse
 
 from constants.languages import languages
 from controllers.console import api
-from controllers.console.app.error import AppNotFoundError
 from controllers.console.wraps import account_initialization_required
-from extensions.ext_database import db
 from libs.login import login_required
-from models.model import App, InstalledApp, RecommendedApp
-from services.account_service import TenantService
+from services.recommended_app_service import RecommendedAppService
 
 app_fields = {
     'id': fields.String,
@@ -27,11 +23,7 @@ recommended_app_fields = {
     'privacy_policy': fields.String,
     'category': fields.String,
     'position': fields.Integer,
-    'is_listed': fields.Boolean,
-    'install_count': fields.Integer,
-    'installed': fields.Boolean,
-    'editable': fields.Boolean,
-    'is_agent': fields.Boolean
+    'is_listed': fields.Boolean
 }
 
 recommended_app_list_fields = {
@@ -45,96 +37,27 @@ class RecommendedAppListApi(Resource):
     @account_initialization_required
     @marshal_with(recommended_app_list_fields)
     def get(self):
-        language_prefix = current_user.interface_language if current_user.interface_language else languages[0]
+        # language args
+        parser = reqparse.RequestParser()
+        parser.add_argument('language', type=str, location='args')
+        args = parser.parse_args()
 
-        recommended_apps = db.session.query(RecommendedApp).filter(
-            RecommendedApp.is_listed == True,
-            RecommendedApp.language == language_prefix
-        ).all()
+        if args.get('language') and args.get('language') in languages:
+            language_prefix = args.get('language')
+        elif current_user and current_user.interface_language:
+            language_prefix = current_user.interface_language
+        else:
+            language_prefix = languages[0]
 
-        categories = set()
-        current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
-        recommended_apps_result = []
-        for recommended_app in recommended_apps:
-            installed = db.session.query(InstalledApp).filter(
-                and_(
-                    InstalledApp.app_id == recommended_app.app_id,
-                    InstalledApp.tenant_id == current_user.current_tenant_id
-                )
-            ).first() is not None
-
-            app = recommended_app.app
-            if not app or not app.is_public:
-                continue
-
-            site = app.site
-            if not site:
-                continue
-
-            recommended_app_result = {
-                'id': recommended_app.id,
-                'app': app,
-                'app_id': recommended_app.app_id,
-                'description': site.description,
-                'copyright': site.copyright,
-                'privacy_policy': site.privacy_policy,
-                'category': recommended_app.category,
-                'position': recommended_app.position,
-                'is_listed': recommended_app.is_listed,
-                'install_count': recommended_app.install_count,
-                'installed': installed,
-                'editable': current_user.role in ['owner', 'admin'],
-                "is_agent": app.is_agent
-            }
-            recommended_apps_result.append(recommended_app_result)
-
-            categories.add(recommended_app.category)  # add category to categories
-
-        return {'recommended_apps': recommended_apps_result, 'categories': list(categories)}
+        return RecommendedAppService.get_recommended_apps_and_categories(language_prefix)
 
 
 class RecommendedAppApi(Resource):
-    model_config_fields = {
-        'opening_statement': fields.String,
-        'suggested_questions': fields.Raw(attribute='suggested_questions_list'),
-        'suggested_questions_after_answer': fields.Raw(attribute='suggested_questions_after_answer_dict'),
-        'more_like_this': fields.Raw(attribute='more_like_this_dict'),
-        'model': fields.Raw(attribute='model_dict'),
-        'user_input_form': fields.Raw(attribute='user_input_form_list'),
-        'pre_prompt': fields.String,
-        'agent_mode': fields.Raw(attribute='agent_mode_dict'),
-    }
-
-    app_simple_detail_fields = {
-        'id': fields.String,
-        'name': fields.String,
-        'icon': fields.String,
-        'icon_background': fields.String,
-        'mode': fields.String,
-        'app_model_config': fields.Nested(model_config_fields),
-    }
-
     @login_required
     @account_initialization_required
-    @marshal_with(app_simple_detail_fields)
     def get(self, app_id):
         app_id = str(app_id)
-
-        # is in public recommended list
-        recommended_app = db.session.query(RecommendedApp).filter(
-            RecommendedApp.is_listed == True,
-            RecommendedApp.app_id == app_id
-        ).first()
-
-        if not recommended_app:
-            raise AppNotFoundError
-
-        # get app detail
-        app = db.session.query(App).filter(App.id == app_id).first()
-        if not app or not app.is_public:
-            raise AppNotFoundError
-
-        return app
+        return RecommendedAppService.get_recommend_app_detail(app_id)
 
 
 api.add_resource(RecommendedAppListApi, '/explore/apps')

api/controllers/console/explore/workflow.py

@@ -0,0 +1,85 @@
+import logging
+
+from flask_restful import reqparse
+from werkzeug.exceptions import InternalServerError
+
+from controllers.console import api
+from controllers.console.app.error import (
+    CompletionRequestError,
+    ProviderModelCurrentlyNotSupportError,
+    ProviderNotInitializeError,
+    ProviderQuotaExceededError,
+)
+from controllers.console.explore.error import NotWorkflowAppError
+from controllers.console.explore.wraps import InstalledAppResource
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
+from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
+from libs.login import current_user
+from models.model import AppMode, InstalledApp
+from services.app_generate_service import AppGenerateService
+
+logger = logging.getLogger(__name__)
+
+
+class InstalledAppWorkflowRunApi(InstalledAppResource):
+    def post(self, installed_app: InstalledApp):
+        """
+        Run workflow
+        """
+        app_model = installed_app.app
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, required=True, nullable=False, location='json')
+        parser.add_argument('files', type=list, required=False, location='json')
+        args = parser.parse_args()
+
+        try:
+            response = AppGenerateService.generate(
+                app_model=app_model,
+                user=current_user,
+                args=args,
+                invoke_from=InvokeFrom.EXPLORE,
+                streaming=True
+            )
+
+            return helper.compact_generate_response(response)
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class InstalledAppWorkflowTaskStopApi(InstalledAppResource):
+    def post(self, installed_app: InstalledApp, task_id: str):
+        """
+        Stop workflow task
+        """
+        app_model = installed_app.app
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.EXPLORE, current_user.id)
+
+        return {
+            "result": "success"
+        }
+
+
+api.add_resource(InstalledAppWorkflowRunApi, '/installed-apps/<uuid:installed_app_id>/workflows/run')
+api.add_resource(InstalledAppWorkflowTaskStopApi, '/installed-apps/<uuid:installed_app_id>/workflows/tasks/<string:task_id>/stop')

api/controllers/console/ping.py

@@ -0,0 +1,17 @@
+from flask_restful import Resource
+
+from controllers.console import api
+
+
+class PingApi(Resource):
+
+    def get(self):
+        """
+        For connection health check
+        """
+        return {
+            "result": "pong"
+        }
+
+
+api.add_resource(PingApi, '/ping')

api/controllers/console/workspace/account.py

@@ -16,26 +16,13 @@ from controllers.console.workspace.error import (
 )
 from controllers.console.wraps import account_initialization_required
 from extensions.ext_database import db
+from fields.member_fields import account_fields
 from libs.helper import TimestampField, timezone
 from libs.login import login_required
 from models.account import AccountIntegrate, InvitationCode
 from services.account_service import AccountService
 from services.errors.account import CurrentPasswordIncorrectError as ServiceCurrentPasswordIncorrectError
 
-account_fields = {
-    'id': fields.String,
-    'name': fields.String,
-    'avatar': fields.String,
-    'email': fields.String,
-    'is_password_set': fields.Boolean,
-    'interface_language': fields.String,
-    'interface_theme': fields.String,
-    'timezone': fields.String,
-    'last_login_at': TimestampField,
-    'last_login_ip': fields.String,
-    'created_at': TimestampField
-}
-
 
 class AccountInitApi(Resource):
 

api/controllers/console/workspace/members.py

@@ -1,33 +1,18 @@
 from flask import current_app
 from flask_login import current_user
-from flask_restful import Resource, abort, fields, marshal_with, reqparse
+from flask_restful import Resource, abort, marshal_with, reqparse
 
 import services
 from controllers.console import api
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check
 from extensions.ext_database import db
-from libs.helper import TimestampField
+from fields.member_fields import account_with_role_list_fields
 from libs.login import login_required
 from models.account import Account
 from services.account_service import RegisterService, TenantService
 from services.errors.account import AccountAlreadyInTenantError
 
-account_fields = {
-    'id': fields.String,
-    'name': fields.String,
-    'avatar': fields.String,
-    'email': fields.String,
-    'last_login_at': TimestampField,
-    'created_at': TimestampField,
-    'role': fields.String,
-    'status': fields.String,
-}
-
-account_list_fields = {
-    'accounts': fields.List(fields.Nested(account_fields))
-}
-
 
 class MemberListApi(Resource):
     """List all members of current tenant."""
@@ -35,7 +20,7 @@ class MemberListApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @marshal_with(account_list_fields)
+    @marshal_with(account_with_role_list_fields)
     def get(self):
         members = TenantService.get_tenant_members(current_user.current_tenant)
         return {'result': 'success', 'accounts': members}, 200

api/controllers/console/workspace/tool_providers.py

@@ -1,6 +1,6 @@
 import io
 
-from flask import send_file
+from flask import current_app, send_file
 from flask_login import current_user
 from flask_restful import Resource, reqparse
 from werkzeug.exceptions import Forbidden
@@ -8,6 +8,7 @@ from werkzeug.exceptions import Forbidden
 from controllers.console import api
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
+from core.model_runtime.utils.encoders import jsonable_encoder
 from libs.login import login_required
 from services.tools_manage_service import ToolManageService
 
@@ -30,11 +31,11 @@ class ToolBuiltinProviderListToolsApi(Resource):
         user_id = current_user.id
         tenant_id = current_user.current_tenant_id
 
-        return ToolManageService.list_builtin_tool_provider_tools(
+        return jsonable_encoder(ToolManageService.list_builtin_tool_provider_tools(
             user_id,
             tenant_id,
             provider,
-        )
+        ))
 
 class ToolBuiltinProviderDeleteApi(Resource):
     @setup_required
@@ -75,13 +76,52 @@ class ToolBuiltinProviderUpdateApi(Resource):
             provider,
             args['credentials'],
         )
+    
+class ToolBuiltinProviderGetCredentialsApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, provider):
+        user_id = current_user.id
+        tenant_id = current_user.current_tenant_id
+
+        return ToolManageService.get_builtin_tool_provider_credentials(
+            user_id,
+            tenant_id,
+            provider,
+        )
 
 class ToolBuiltinProviderIconApi(Resource):
     @setup_required
     def get(self, provider):
-        icon_bytes, minetype = ToolManageService.get_builtin_tool_provider_icon(provider)
-        return send_file(io.BytesIO(icon_bytes), mimetype=minetype)
+        icon_bytes, mimetype = ToolManageService.get_builtin_tool_provider_icon(provider)
+        icon_cache_max_age = int(current_app.config.get('TOOL_ICON_CACHE_MAX_AGE'))
+        return send_file(io.BytesIO(icon_bytes), mimetype=mimetype, max_age=icon_cache_max_age)
 
+class ToolModelProviderIconApi(Resource):
+    @setup_required
+    def get(self, provider):
+        icon_bytes, mimetype = ToolManageService.get_model_tool_provider_icon(provider)
+        return send_file(io.BytesIO(icon_bytes), mimetype=mimetype)
+    
+class ToolModelProviderListToolsApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        user_id = current_user.id
+        tenant_id = current_user.current_tenant_id
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('provider', type=str, required=True, nullable=False, location='args')
+
+        args = parser.parse_args()
+
+        return jsonable_encoder(ToolManageService.list_model_tool_provider_tools(
+            user_id,
+            tenant_id,
+            args['provider'],
+        ))
 
 class ToolApiProviderAddApi(Resource):
     @setup_required
@@ -146,11 +186,11 @@ class ToolApiProviderListToolsApi(Resource):
 
         args = parser.parse_args()
 
-        return ToolManageService.list_api_tool_provider_tools(
+        return jsonable_encoder(ToolManageService.list_api_tool_provider_tools(
             user_id,
             tenant_id,
             args['provider'],
-        )
+        ))
 
 class ToolApiProviderUpdateApi(Resource):
     @setup_required
@@ -277,17 +317,49 @@ class ToolApiProviderPreviousTestApi(Resource):
             args['schema'],
         )
 
+class ToolBuiltinListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        user_id = current_user.id
+        tenant_id = current_user.current_tenant_id
+
+        return jsonable_encoder([provider.to_dict() for provider in ToolManageService.list_builtin_tools(
+            user_id,
+            tenant_id,
+        )])
+    
+class ToolApiListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        user_id = current_user.id
+        tenant_id = current_user.current_tenant_id
+
+        return jsonable_encoder([provider.to_dict() for provider in ToolManageService.list_api_tools(
+            user_id,
+            tenant_id,
+        )])
+
 api.add_resource(ToolProviderListApi, '/workspaces/current/tool-providers')
 api.add_resource(ToolBuiltinProviderListToolsApi, '/workspaces/current/tool-provider/builtin/<provider>/tools')
 api.add_resource(ToolBuiltinProviderDeleteApi, '/workspaces/current/tool-provider/builtin/<provider>/delete')
 api.add_resource(ToolBuiltinProviderUpdateApi, '/workspaces/current/tool-provider/builtin/<provider>/update')
+api.add_resource(ToolBuiltinProviderGetCredentialsApi, '/workspaces/current/tool-provider/builtin/<provider>/credentials')
 api.add_resource(ToolBuiltinProviderCredentialsSchemaApi, '/workspaces/current/tool-provider/builtin/<provider>/credentials_schema')
 api.add_resource(ToolBuiltinProviderIconApi, '/workspaces/current/tool-provider/builtin/<provider>/icon')
+api.add_resource(ToolModelProviderIconApi, '/workspaces/current/tool-provider/model/<provider>/icon')
+api.add_resource(ToolModelProviderListToolsApi, '/workspaces/current/tool-provider/model/tools')
 api.add_resource(ToolApiProviderAddApi, '/workspaces/current/tool-provider/api/add')
 api.add_resource(ToolApiProviderGetRemoteSchemaApi, '/workspaces/current/tool-provider/api/remote')
 api.add_resource(ToolApiProviderListToolsApi, '/workspaces/current/tool-provider/api/tools')
-api.add_resource(ToolApiProviderUpdateApi, '/workspaces/current/tool-provider/api/update') 
+api.add_resource(ToolApiProviderUpdateApi, '/workspaces/current/tool-provider/api/update')
 api.add_resource(ToolApiProviderDeleteApi, '/workspaces/current/tool-provider/api/delete')
 api.add_resource(ToolApiProviderGetApi, '/workspaces/current/tool-provider/api/get')
 api.add_resource(ToolApiProviderSchemaApi, '/workspaces/current/tool-provider/api/schema')
 api.add_resource(ToolApiProviderPreviousTestApi, '/workspaces/current/tool-provider/api/test/pre')
+
+api.add_resource(ToolBuiltinListApi, '/workspaces/current/tools/builtin')
+api.add_resource(ToolApiListApi, '/workspaces/current/tools/api')

api/controllers/console/wraps.py

@@ -51,14 +51,12 @@ def cloud_edition_billing_resource_check(resource: str,
         @wraps(view)
         def decorated(*args, **kwargs):
             features = FeatureService.get_features(current_user.current_tenant_id)
-
             if features.billing.enabled:
                 members = features.members
                 apps = features.apps
                 vector_space = features.vector_space
                 documents_upload_quota = features.documents_upload_quota
                 annotation_quota_limit = features.annotation_quota_limit
-
                 if resource == 'members' and 0 < members.limit <= members.size:
                     abort(403, error_msg)
                 elif resource == 'apps' and 0 < apps.limit <= apps.size:
@@ -80,7 +78,29 @@ def cloud_edition_billing_resource_check(resource: str,
                     return view(*args, **kwargs)
 
             return view(*args, **kwargs)
+
         return decorated
+
+    return interceptor
+
+
+def cloud_edition_billing_knowledge_limit_check(resource: str,
+                                                error_msg: str = "To unlock this feature and elevate your Dify experience, please upgrade to a paid plan."):
+    def interceptor(view):
+        @wraps(view)
+        def decorated(*args, **kwargs):
+            features = FeatureService.get_features(current_user.current_tenant_id)
+            if features.billing.enabled:
+                if resource == 'add_segment':
+                    if features.billing.subscription.plan == 'sandbox':
+                        abort(403, error_msg)
+                else:
+                    return view(*args, **kwargs)
+
+            return view(*args, **kwargs)
+
+        return decorated
+
     return interceptor
 
 
@@ -99,4 +119,5 @@ def cloud_utm_record(view):
         except Exception as e:
             pass
         return view(*args, **kwargs)
+
     return decorated

api/controllers/files/tool_files.py

@@ -27,7 +27,7 @@ class ToolFilePreviewApi(Resource):
             raise Forbidden('Invalid request.')
         
         try:
-            result = ToolFileManager.get_file_generator_by_message_file_id(
+            result = ToolFileManager.get_file_generator_by_tool_file_id(
                 file_id,
             )
 

api/controllers/service_api/__init__.py

@@ -7,5 +7,5 @@ api = ExternalApi(bp)
 
 
 from . import index
-from .app import app, audio, completion, conversation, file, message
+from .app import app, audio, completion, conversation, file, message, workflow
 from .dataset import dataset, document, segment

api/controllers/service_api/app/app.py

@@ -1,13 +1,12 @@
-import json
 
 from flask import current_app
-from flask_restful import fields, marshal_with, Resource
+from flask_restful import Resource, fields, marshal_with
 
 from controllers.service_api import api
+from controllers.service_api.app.error import AppUnavailableError
 from controllers.service_api.wraps import validate_app_token
-from extensions.ext_database import db
-from models.model import App, AppModelConfig
-from models.tools import ApiToolProvider
+from models.model import App, AppMode
+from services.app_service import AppService
 
 
 class AppParameterApi(Resource):
@@ -46,62 +45,60 @@ class AppParameterApi(Resource):
     @marshal_with(parameters_fields)
     def get(self, app_model: App):
         """Retrieve app parameters."""
-        app_model_config = app_model.app_model_config
+        if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
+            workflow = app_model.workflow
+            if workflow is None:
+                raise AppUnavailableError()
+
+            features_dict = workflow.features_dict
+            user_input_form = workflow.user_input_form(to_old_structure=True)
+        else:
+            app_model_config = app_model.app_model_config
+            features_dict = app_model_config.to_dict()
+
+            user_input_form = features_dict.get('user_input_form', [])
 
         return {
-            'opening_statement': app_model_config.opening_statement,
-            'suggested_questions': app_model_config.suggested_questions_list,
-            'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
-            'text_to_speech': app_model_config.text_to_speech_dict,
-            'retriever_resource': app_model_config.retriever_resource_dict,
-            'annotation_reply': app_model_config.annotation_reply_dict,
-            'more_like_this': app_model_config.more_like_this_dict,
-            'user_input_form': app_model_config.user_input_form_list,
-            'sensitive_word_avoidance': app_model_config.sensitive_word_avoidance_dict,
-            'file_upload': app_model_config.file_upload_dict,
+            'opening_statement': features_dict.get('opening_statement'),
+            'suggested_questions': features_dict.get('suggested_questions', []),
+            'suggested_questions_after_answer': features_dict.get('suggested_questions_after_answer',
+                                                                  {"enabled": False}),
+            'speech_to_text': features_dict.get('speech_to_text', {"enabled": False}),
+            'text_to_speech': features_dict.get('text_to_speech', {"enabled": False}),
+            'retriever_resource': features_dict.get('retriever_resource', {"enabled": False}),
+            'annotation_reply': features_dict.get('annotation_reply', {"enabled": False}),
+            'more_like_this': features_dict.get('more_like_this', {"enabled": False}),
+            'user_input_form': user_input_form,
+            'sensitive_word_avoidance': features_dict.get('sensitive_word_avoidance',
+                                                          {"enabled": False, "type": "", "configs": []}),
+            'file_upload': features_dict.get('file_upload', {"image": {
+                                                     "enabled": False,
+                                                     "number_limits": 3,
+                                                     "detail": "high",
+                                                     "transfer_methods": ["remote_url", "local_file"]
+                                                 }}),
             'system_parameters': {
                 'image_file_size_limit': current_app.config.get('UPLOAD_IMAGE_FILE_SIZE_LIMIT')
             }
         }
 
+
 class AppMetaApi(Resource):
     @validate_app_token
     def get(self, app_model: App):
         """Get app meta"""
-        app_model_config: AppModelConfig = app_model.app_model_config
+        return AppService().get_app_meta(app_model)
 
-        agent_config = app_model_config.agent_mode_dict or {}
-        meta = {
-            'tool_icons': {}
-        }
+class AppInfoApi(Resource):
+    @validate_app_token
+    def get(self, app_model: App):
+        """Get app infomation"""
+        return {
+            'name':app_model.name,
+            'description':app_model.description
+        } 
 
-        # get all tools
-        tools = agent_config.get('tools', [])
-        url_prefix = (current_app.config.get("CONSOLE_API_URL")
-                  + "/console/api/workspaces/current/tool-provider/builtin/")
-        for tool in tools:
-            keys = list(tool.keys())
-            if len(keys) >= 4:
-                # current tool standard
-                provider_type = tool.get('provider_type')
-                provider_id = tool.get('provider_id')
-                tool_name = tool.get('tool_name')
-                if provider_type == 'builtin':
-                    meta['tool_icons'][tool_name] = url_prefix + provider_id + '/icon'
-                elif provider_type == 'api':
-                    try:
-                        provider: ApiToolProvider = db.session.query(ApiToolProvider).filter(
-                            ApiToolProvider.id == provider_id
-                        )
-                        meta['tool_icons'][tool_name] = json.loads(provider.icon)
-                    except:
-                        meta['tool_icons'][tool_name] =  {
-                            "background": "#252525",
-                            "content": "\ud83d\ude01"
-                        }
-
-        return meta
 
 api.add_resource(AppParameterApi, '/parameters')
 api.add_resource(AppMetaApi, '/meta')
+api.add_resource(AppInfoApi, '/info')

api/controllers/service_api/app/audio.py

@@ -20,7 +20,7 @@ from controllers.service_api.app.error import (
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppModelConfig, EndUser
+from models.model import App, EndUser
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -33,16 +33,11 @@ from services.errors.audio import (
 class AudioApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.FORM))
     def post(self, app_model: App, end_user: EndUser):
-        app_model_config: AppModelConfig = app_model.app_model_config
-
-        if not app_model_config.speech_to_text_dict['enabled']:
-            raise AppUnavailableError()
-
         file = request.files['file']
 
         try:
             response = AudioService.transcript_asr(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 file=file,
                 end_user=end_user
             )
@@ -75,19 +70,20 @@ class AudioApi(Resource):
 
 
 class TextApi(Resource):
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON, required=True))
+    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
     def post(self, app_model: App, end_user: EndUser):
         parser = reqparse.RequestParser()
         parser.add_argument('text', type=str, required=True, nullable=False, location='json')
+        parser.add_argument('voice', type=str, location='json')
         parser.add_argument('streaming', type=bool, required=False, nullable=False, location='json')
         args = parser.parse_args()
 
         try:
             response = AudioService.transcript_tts(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 text=args['text'],
                 end_user=end_user,
-                voice=args['voice'] if args['voice'] else app_model.app_model_config.text_to_speech_dict.get('voice'),
+                voice=args.get('voice'),
                 streaming=args['streaming']
             )
 

api/controllers/service_api/app/completion.py

@@ -1,9 +1,5 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_restful import Resource, reqparse
 from werkzeug.exceptions import InternalServerError, NotFound
 
@@ -19,13 +15,14 @@ from controllers.service_api.app.error import (
     ProviderQuotaExceededError,
 )
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
-from core.application_queue_manager import ApplicationQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
 from libs.helper import uuid_value
-from models.model import App, EndUser
-from services.completion_service import CompletionService
+from models.model import App, AppMode, EndUser
+from services.app_generate_service import AppGenerateService
 
 
 class CompletionApi(Resource):
@@ -48,7 +45,7 @@ class CompletionApi(Resource):
         args['auto_generate_name'] = False
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=end_user,
                 args=args,
@@ -56,7 +53,7 @@ class CompletionApi(Resource):
                 streaming=streaming,
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -85,7 +82,7 @@ class CompletionStopApi(Resource):
         if app_model.mode != 'completion':
             raise AppUnavailableError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
 
         return {'result': 'success'}, 200
 
@@ -93,7 +90,8 @@ class CompletionStopApi(Resource):
 class ChatApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON, required=True))
     def post(self, app_model: App, end_user: EndUser):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -110,7 +108,7 @@ class ChatApi(Resource):
         streaming = args['response_mode'] == 'streaming'
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=end_user,
                 args=args,
@@ -118,7 +116,7 @@ class ChatApi(Resource):
                 streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -144,25 +142,15 @@ class ChatApi(Resource):
 class ChatStopApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON, required=True))
     def post(self, app_model: App, end_user: EndUser, task_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
 
         return {'result': 'success'}, 200
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 api.add_resource(CompletionApi, '/completion-messages')
 api.add_resource(CompletionStopApi, '/completion-messages/<string:task_id>/stop')
 api.add_resource(ChatApi, '/chat-messages')

api/controllers/service_api/app/conversation.py

@@ -6,9 +6,10 @@ import services
 from controllers.service_api import api
 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 conversation_infinite_scroll_pagination_fields, simple_conversation_fields
 from libs.helper import uuid_value
-from models.model import App, EndUser
+from models.model import App, AppMode, EndUser
 from services.conversation_service import ConversationService
 
 
@@ -17,7 +18,8 @@ class ConversationApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
     @marshal_with(conversation_infinite_scroll_pagination_fields)
     def get(self, app_model: App, end_user: EndUser):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -26,15 +28,23 @@ class ConversationApi(Resource):
         args = parser.parse_args()
 
         try:
-            return ConversationService.pagination_by_last_id(app_model, end_user, args['last_id'], args['limit'])
+            return ConversationService.pagination_by_last_id(
+                app_model=app_model,
+                user=end_user,
+                last_id=args['last_id'],
+                limit=args['limit'],
+                invoke_from=InvokeFrom.SERVICE_API
+            )
         except services.errors.conversation.LastConversationNotExistsError:
             raise NotFound("Last Conversation Not Exists.")
 
+
 class ConversationDetailApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
     @marshal_with(simple_conversation_fields)
     def delete(self, app_model: App, end_user: EndUser, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -51,7 +61,8 @@ class ConversationRenameApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
     @marshal_with(simple_conversation_fields)
     def post(self, app_model: App, end_user: EndUser, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)

api/controllers/service_api/app/error.py

@@ -15,7 +15,13 @@ class NotCompletionAppError(BaseHTTPException):
 
 class NotChatAppError(BaseHTTPException):
     error_code = 'not_chat_app'
-    description = "Please check if your Chat app mode matches the right API route."
+    description = "Please check if your app mode matches the right API route."
+    code = 400
+
+
+class NotWorkflowAppError(BaseHTTPException):
+    error_code = 'not_workflow_app'
+    description = "Please check if your app mode matches the right API route."
     code = 400
 
 

api/controllers/service_api/app/message.py

@@ -1,14 +1,18 @@
+import logging
+
 from flask_restful import Resource, fields, marshal_with, reqparse
 from flask_restful.inputs import int_range
-from werkzeug.exceptions import NotFound
+from werkzeug.exceptions import BadRequest, InternalServerError, NotFound
 
 import services
 from controllers.service_api import api
 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 libs.helper import TimestampField, uuid_value
-from models.model import App, EndUser
+from models.model import App, AppMode, EndUser
+from services.errors.message import SuggestedQuestionsAfterAnswerDisabledError
 from services.message_service import MessageService
 
 
@@ -54,12 +58,14 @@ class MessageListApi(Resource):
         'conversation_id': fields.String,
         'inputs': fields.Raw,
         'query': fields.String,
-        'answer': fields.String,
+        'answer': fields.String(attribute='re_sign_file_url_answer'),
         'message_files': fields.List(fields.Nested(message_file_fields), attribute='files'),
         'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
         'retriever_resources': fields.List(fields.Nested(retriever_resource_fields)),
         'created_at': TimestampField,
-        'agent_thoughts': fields.List(fields.Nested(agent_thought_fields))
+        'agent_thoughts': fields.List(fields.Nested(agent_thought_fields)),
+        'status': fields.String,
+        'error': fields.String,
     }
 
     message_infinite_scroll_pagination_fields = {
@@ -71,7 +77,8 @@ class MessageListApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
     @marshal_with(message_infinite_scroll_pagination_fields)
     def get(self, app_model: App, end_user: EndUser):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -110,7 +117,8 @@ class MessageSuggestedApi(Resource):
     @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
     def get(self, app_model: App, end_user: EndUser, message_id):
         message_id = str(message_id)
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         try:
@@ -118,10 +126,15 @@ class MessageSuggestedApi(Resource):
                 app_model=app_model,
                 user=end_user,
                 message_id=message_id,
-                check_enabled=False
+                invoke_from=InvokeFrom.SERVICE_API
             )
         except services.errors.message.MessageNotExistsError:
             raise NotFound("Message Not Exists.")
+        except SuggestedQuestionsAfterAnswerDisabledError:
+            raise BadRequest("Message Not Exists.")
+        except Exception:
+            logging.exception("internal server error.")
+            raise InternalServerError()
 
         return {'result': 'success', 'data': questions}
 

api/controllers/service_api/app/workflow.py

@@ -0,0 +1,87 @@
+import logging
+
+from flask_restful import Resource, reqparse
+from werkzeug.exceptions import InternalServerError
+
+from controllers.service_api import api
+from controllers.service_api.app.error import (
+    CompletionRequestError,
+    NotWorkflowAppError,
+    ProviderModelCurrentlyNotSupportError,
+    ProviderNotInitializeError,
+    ProviderQuotaExceededError,
+)
+from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
+from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
+from models.model import App, AppMode, EndUser
+from services.app_generate_service import AppGenerateService
+
+logger = logging.getLogger(__name__)
+
+
+class WorkflowRunApi(Resource):
+    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON, required=True))
+    def post(self, app_model: App, end_user: EndUser):
+        """
+        Run workflow
+        """
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, required=True, nullable=False, location='json')
+        parser.add_argument('files', type=list, required=False, location='json')
+        parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
+        args = parser.parse_args()
+
+        streaming = args.get('response_mode') == 'streaming'
+
+        try:
+            response = AppGenerateService.generate(
+                app_model=app_model,
+                user=end_user,
+                args=args,
+                invoke_from=InvokeFrom.SERVICE_API,
+                streaming=streaming
+            )
+
+            return helper.compact_generate_response(response)
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class WorkflowTaskStopApi(Resource):
+    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON, required=True))
+    def post(self, app_model: App, end_user: EndUser, task_id: str):
+        """
+        Stop workflow task
+        """
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
+
+        return {
+            "result": "success"
+        }
+
+
+api.add_resource(WorkflowRunApi, '/workflows/run')
+api.add_resource(WorkflowTaskStopApi, '/workflows/tasks/<string:task_id>/stop')

api/controllers/service_api/dataset/segment.py

@@ -4,7 +4,11 @@ from werkzeug.exceptions import NotFound
 
 from controllers.service_api import api
 from controllers.service_api.app.error import ProviderNotInitializeError
-from controllers.service_api.wraps import DatasetApiResource, cloud_edition_billing_resource_check
+from controllers.service_api.wraps import (
+    DatasetApiResource,
+    cloud_edition_billing_knowledge_limit_check,
+    cloud_edition_billing_resource_check,
+)
 from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
@@ -18,6 +22,7 @@ class SegmentApi(DatasetApiResource):
     """Resource for segments."""
 
     @cloud_edition_billing_resource_check('vector_space', 'dataset')
+    @cloud_edition_billing_knowledge_limit_check('add_segment', 'dataset')
     def post(self, tenant_id, dataset_id, document_id):
         """Create single segment."""
         # check dataset
@@ -197,11 +202,11 @@ class DatasetSegmentApi(DatasetApiResource):
 
         # validate args
         parser = reqparse.RequestParser()
-        parser.add_argument('segments', type=dict, required=False, nullable=True, location='json')
+        parser.add_argument('segment', type=dict, required=False, nullable=True, location='json')
         args = parser.parse_args()
 
-        SegmentService.segment_create_args_validate(args['segments'], document)
-        segment = SegmentService.update_segment(args['segments'], segment, document, dataset)
+        SegmentService.segment_create_args_validate(args['segment'], document)
+        segment = SegmentService.update_segment(args['segment'], segment, document, dataset)
         return {
             'data': marshal(segment, segment_fields),
             'doc_form': document.doc_form

api/controllers/service_api/wraps.py

@@ -8,7 +8,7 @@ from flask import current_app, request
 from flask_login import user_logged_in
 from flask_restful import Resource
 from pydantic import BaseModel
-from werkzeug.exceptions import NotFound, Unauthorized
+from werkzeug.exceptions import Forbidden, NotFound, Unauthorized
 
 from extensions.ext_database import db
 from libs.login import _get_user
@@ -92,13 +92,13 @@ def cloud_edition_billing_resource_check(resource: str,
                 documents_upload_quota = features.documents_upload_quota
 
                 if resource == 'members' and 0 < members.limit <= members.size:
-                    raise Unauthorized(error_msg)
+                    raise Forbidden(error_msg)
                 elif resource == 'apps' and 0 < apps.limit <= apps.size:
-                    raise Unauthorized(error_msg)
+                    raise Forbidden(error_msg)
                 elif resource == 'vector_space' and 0 < vector_space.limit <= vector_space.size:
-                    raise Unauthorized(error_msg)
+                    raise Forbidden(error_msg)
                 elif resource == 'documents' and 0 < documents_upload_quota.limit <= documents_upload_quota.size:
-                    raise Unauthorized(error_msg)
+                    raise Forbidden(error_msg)
                 else:
                     return view(*args, **kwargs)
 
@@ -107,6 +107,27 @@ def cloud_edition_billing_resource_check(resource: str,
     return interceptor
 
 
+def cloud_edition_billing_knowledge_limit_check(resource: str,
+                                                api_token_type: str,
+                                                error_msg: str = "To unlock this feature and elevate your Dify experience, please upgrade to a paid plan."):
+    def interceptor(view):
+        @wraps(view)
+        def decorated(*args, **kwargs):
+            api_token = validate_and_get_api_token(api_token_type)
+            features = FeatureService.get_features(api_token.tenant_id)
+            if features.billing.enabled:
+                if resource == 'add_segment':
+                    if features.billing.subscription.plan == 'sandbox':
+                        raise Forbidden(error_msg)
+                else:
+                    return view(*args, **kwargs)
+
+            return view(*args, **kwargs)
+
+        return decorated
+
+    return interceptor
+
 def validate_dataset_token(view=None):
     def decorator(view):
         @wraps(view)

api/controllers/web/__init__.py

@@ -6,4 +6,4 @@ bp = Blueprint('web', __name__, url_prefix='/api')
 api = ExternalApi(bp)
 
 
-from . import app, audio, completion, conversation, file, message, passport, saved_message, site
+from . import app, audio, completion, conversation, file, message, passport, saved_message, site, workflow

api/controllers/web/app.py

@@ -4,10 +4,12 @@ from flask import current_app
 from flask_restful import fields, marshal_with
 
 from controllers.web import api
+from controllers.web.error import AppUnavailableError
 from controllers.web.wraps import WebApiResource
 from extensions.ext_database import db
-from models.model import App, AppModelConfig
+from models.model import App, AppModelConfig, AppMode
 from models.tools import ApiToolProvider
+from services.app_service import AppService
 
 
 class AppParameterApi(WebApiResource):
@@ -44,61 +46,49 @@ class AppParameterApi(WebApiResource):
     @marshal_with(parameters_fields)
     def get(self, app_model: App, end_user):
         """Retrieve app parameters."""
-        app_model_config = app_model.app_model_config
+        if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
+            workflow = app_model.workflow
+            if workflow is None:
+                raise AppUnavailableError()
+
+            features_dict = workflow.features_dict
+            user_input_form = workflow.user_input_form(to_old_structure=True)
+        else:
+            app_model_config = app_model.app_model_config
+            features_dict = app_model_config.to_dict()
+
+            user_input_form = features_dict.get('user_input_form', [])
 
         return {
-            'opening_statement': app_model_config.opening_statement,
-            'suggested_questions': app_model_config.suggested_questions_list,
-            'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
-            'text_to_speech': app_model_config.text_to_speech_dict,
-            'retriever_resource': app_model_config.retriever_resource_dict,
-            'annotation_reply': app_model_config.annotation_reply_dict,
-            'more_like_this': app_model_config.more_like_this_dict,
-            'user_input_form': app_model_config.user_input_form_list,
-            'sensitive_word_avoidance': app_model_config.sensitive_word_avoidance_dict,
-            'file_upload': app_model_config.file_upload_dict,
+            'opening_statement': features_dict.get('opening_statement'),
+            'suggested_questions': features_dict.get('suggested_questions', []),
+            'suggested_questions_after_answer': features_dict.get('suggested_questions_after_answer',
+                                                                  {"enabled": False}),
+            'speech_to_text': features_dict.get('speech_to_text', {"enabled": False}),
+            'text_to_speech': features_dict.get('text_to_speech', {"enabled": False}),
+            'retriever_resource': features_dict.get('retriever_resource', {"enabled": False}),
+            'annotation_reply': features_dict.get('annotation_reply', {"enabled": False}),
+            'more_like_this': features_dict.get('more_like_this', {"enabled": False}),
+            'user_input_form': user_input_form,
+            'sensitive_word_avoidance': features_dict.get('sensitive_word_avoidance',
+                                                          {"enabled": False, "type": "", "configs": []}),
+            'file_upload': features_dict.get('file_upload', {"image": {
+                "enabled": False,
+                "number_limits": 3,
+                "detail": "high",
+                "transfer_methods": ["remote_url", "local_file"]
+            }}),
             'system_parameters': {
                 'image_file_size_limit': current_app.config.get('UPLOAD_IMAGE_FILE_SIZE_LIMIT')
             }
         }
 
+
 class AppMeta(WebApiResource):
     def get(self, app_model: App, end_user):
         """Get app meta"""
-        app_model_config: AppModelConfig = app_model.app_model_config
+        return AppService().get_app_meta(app_model)
 
-        agent_config = app_model_config.agent_mode_dict or {}
-        meta = {
-            'tool_icons': {}
-        }
-
-        # get all tools
-        tools = agent_config.get('tools', [])
-        url_prefix = (current_app.config.get("CONSOLE_API_URL")
-                  + "/console/api/workspaces/current/tool-provider/builtin/")
-        for tool in tools:
-            keys = list(tool.keys())
-            if len(keys) >= 4:
-                # current tool standard
-                provider_type = tool.get('provider_type')
-                provider_id = tool.get('provider_id')
-                tool_name = tool.get('tool_name')
-                if provider_type == 'builtin':
-                    meta['tool_icons'][tool_name] = url_prefix + provider_id + '/icon'
-                elif provider_type == 'api':
-                    try:
-                        provider: ApiToolProvider = db.session.query(ApiToolProvider).filter(
-                            ApiToolProvider.id == provider_id
-                        )
-                        meta['tool_icons'][tool_name] = json.loads(provider.icon)
-                    except:
-                        meta['tool_icons'][tool_name] =  {
-                            "background": "#252525",
-                            "content": "\ud83d\ude01"
-                        }
-
-        return meta
 
 api.add_resource(AppParameterApi, '/parameters')
 api.add_resource(AppMeta, '/meta')

api/controllers/web/audio.py

@@ -19,7 +19,7 @@ from controllers.web.error import (
 from controllers.web.wraps import WebApiResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppModelConfig
+from models.model import App
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -31,16 +31,11 @@ from services.errors.audio import (
 
 class AudioApi(WebApiResource):
     def post(self, app_model: App, end_user):
-        app_model_config: AppModelConfig = app_model.app_model_config
-
-        if not app_model_config.speech_to_text_dict['enabled']:
-            raise AppUnavailableError()
-
         file = request.files['file']
 
         try:
             response = AudioService.transcript_asr(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 file=file,
                 end_user=end_user
             )
@@ -74,17 +69,12 @@ class AudioApi(WebApiResource):
 
 class TextApi(WebApiResource):
     def post(self, app_model: App, end_user):
-        app_model_config: AppModelConfig = app_model.app_model_config
-
-        if not app_model_config.text_to_speech_dict['enabled']:
-            raise AppUnavailableError()
-
         try:
             response = AudioService.transcript_tts(
-                tenant_id=app_model.tenant_id,
+                app_model=app_model,
                 text=request.form['text'],
                 end_user=end_user.external_user_id,
-                voice=request.form['voice'] if request.form['voice'] else app_model.app_model_config.text_to_speech_dict.get('voice'),
+                voice=request.form.get('voice'),
                 streaming=False
             )
 

api/controllers/web/completion.py

@@ -1,9 +1,5 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_restful import reqparse
 from werkzeug.exceptions import InternalServerError, NotFound
 
@@ -20,12 +16,14 @@ from controllers.web.error import (
     ProviderQuotaExceededError,
 )
 from controllers.web.wraps import WebApiResource
-from core.application_queue_manager import ApplicationQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
 from libs.helper import uuid_value
-from services.completion_service import CompletionService
+from models.model import AppMode
+from services.app_generate_service import AppGenerateService
 
 
 # define completion api for user
@@ -48,7 +46,7 @@ class CompletionApi(WebApiResource):
         args['auto_generate_name'] = False
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=end_user,
                 args=args,
@@ -56,7 +54,7 @@ class CompletionApi(WebApiResource):
                 streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -84,14 +82,15 @@ class CompletionStopApi(WebApiResource):
         if app_model.mode != 'completion':
             raise NotCompletionAppError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.WEB_APP, end_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.WEB_APP, end_user.id)
 
         return {'result': 'success'}, 200
 
 
 class ChatApi(WebApiResource):
     def post(self, app_model, end_user):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -108,7 +107,7 @@ class ChatApi(WebApiResource):
         args['auto_generate_name'] = False
 
         try:
-            response = CompletionService.completion(
+            response = AppGenerateService.generate(
                 app_model=app_model,
                 user=end_user,
                 args=args,
@@ -116,7 +115,7 @@ class ChatApi(WebApiResource):
                 streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")
         except services.errors.conversation.ConversationCompletedError:
@@ -141,25 +140,15 @@ class ChatApi(WebApiResource):
 
 class ChatStopApi(WebApiResource):
     def post(self, app_model, end_user, task_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.WEB_APP, end_user.id)
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.WEB_APP, end_user.id)
 
         return {'result': 'success'}, 200
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 api.add_resource(CompletionApi, '/completion-messages')
 api.add_resource(CompletionStopApi, '/completion-messages/<string:task_id>/stop')
 api.add_resource(ChatApi, '/chat-messages')

api/controllers/web/conversation.py

@@ -5,8 +5,10 @@ from werkzeug.exceptions import NotFound
 from controllers.web import api
 from controllers.web.error import NotChatAppError
 from controllers.web.wraps import WebApiResource
+from core.app.entities.app_invoke_entities import InvokeFrom
 from fields.conversation_fields import conversation_infinite_scroll_pagination_fields, simple_conversation_fields
 from libs.helper import uuid_value
+from models.model import AppMode
 from services.conversation_service import ConversationService
 from services.errors.conversation import ConversationNotExistsError, LastConversationNotExistsError
 from services.web_conversation_service import WebConversationService
@@ -16,7 +18,8 @@ class ConversationListApi(WebApiResource):
 
     @marshal_with(conversation_infinite_scroll_pagination_fields)
     def get(self, app_model, end_user):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -35,7 +38,8 @@ class ConversationListApi(WebApiResource):
                 user=end_user,
                 last_id=args['last_id'],
                 limit=args['limit'],
-                pinned=pinned
+                invoke_from=InvokeFrom.WEB_APP,
+                pinned=pinned,
             )
         except LastConversationNotExistsError:
             raise NotFound("Last Conversation Not Exists.")
@@ -43,7 +47,8 @@ class ConversationListApi(WebApiResource):
 
 class ConversationApi(WebApiResource):
     def delete(self, app_model, end_user, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -60,7 +65,8 @@ class ConversationRenameApi(WebApiResource):
 
     @marshal_with(simple_conversation_fields)
     def post(self, app_model, end_user, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -85,7 +91,8 @@ class ConversationRenameApi(WebApiResource):
 class ConversationPinApi(WebApiResource):
 
     def patch(self, app_model, end_user, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -100,7 +107,8 @@ class ConversationPinApi(WebApiResource):
 
 class ConversationUnPinApi(WebApiResource):
     def patch(self, app_model, end_user, c_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         conversation_id = str(c_id)

api/controllers/web/error.py

@@ -15,7 +15,13 @@ class NotCompletionAppError(BaseHTTPException):
 
 class NotChatAppError(BaseHTTPException):
     error_code = 'not_chat_app'
-    description = "Please check if your Chat app mode matches the right API route."
+    description = "Please check if your app mode matches the right API route."
+    code = 400
+
+
+class NotWorkflowAppError(BaseHTTPException):
+    error_code = 'not_workflow_app'
+    description = "Please check if your Workflow app mode matches the right API route."
     code = 400
 
 

api/controllers/web/message.py

@@ -1,9 +1,5 @@
-import json
 import logging
-from collections.abc import Generator
-from typing import Union
 
-from flask import Response, stream_with_context
 from flask_restful import fields, marshal_with, reqparse
 from flask_restful.inputs import int_range
 from werkzeug.exceptions import InternalServerError, NotFound
@@ -21,13 +17,15 @@ from controllers.web.error import (
     ProviderQuotaExceededError,
 )
 from controllers.web.wraps import WebApiResource
-from core.entities.application_entities import InvokeFrom
+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
+from libs import helper
 from libs.helper import TimestampField, uuid_value
-from services.completion_service import CompletionService
+from models.model import AppMode
+from services.app_generate_service import AppGenerateService
 from services.errors.app import MoreLikeThisDisabledError
 from services.errors.conversation import ConversationNotExistsError
 from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
@@ -63,12 +61,14 @@ class MessageListApi(WebApiResource):
         'conversation_id': fields.String,
         'inputs': fields.Raw,
         'query': fields.String,
-        'answer': fields.String,
+        'answer': fields.String(attribute='re_sign_file_url_answer'),
         'message_files': fields.List(fields.Nested(message_file_fields), attribute='files'),
         'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
         'retriever_resources': fields.List(fields.Nested(retriever_resource_fields)),
         'created_at': TimestampField,
-        'agent_thoughts': fields.List(fields.Nested(agent_thought_fields))
+        'agent_thoughts': fields.List(fields.Nested(agent_thought_fields)),
+        'status': fields.String,
+        'error': fields.String,
     }
 
     message_infinite_scroll_pagination_fields = {
@@ -79,7 +79,8 @@ class MessageListApi(WebApiResource):
 
     @marshal_with(message_infinite_scroll_pagination_fields)
     def get(self, app_model, end_user):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotChatAppError()
 
         parser = reqparse.RequestParser()
@@ -127,7 +128,7 @@ class MessageMoreLikeThisApi(WebApiResource):
         streaming = args['response_mode'] == 'streaming'
 
         try:
-            response = CompletionService.generate_more_like_this(
+            response = AppGenerateService.generate_more_like_this(
                 app_model=app_model,
                 user=end_user,
                 message_id=message_id,
@@ -135,7 +136,7 @@ class MessageMoreLikeThisApi(WebApiResource):
                 streaming=streaming
             )
 
-            return compact_response(response)
+            return helper.compact_generate_response(response)
         except MessageNotExistsError:
             raise NotFound("Message Not Exists.")
         except MoreLikeThisDisabledError:
@@ -155,20 +156,10 @@ class MessageMoreLikeThisApi(WebApiResource):
             raise InternalServerError()
 
 
-def compact_response(response: Union[dict, Generator]) -> Response:
-    if isinstance(response, dict):
-        return Response(response=json.dumps(response), status=200, mimetype='application/json')
-    else:
-        def generate() -> Generator:
-            yield from response
-
-        return Response(stream_with_context(generate()), status=200,
-                        mimetype='text/event-stream')
-
-
 class MessageSuggestedQuestionApi(WebApiResource):
     def get(self, app_model, end_user, message_id):
-        if app_model.mode != 'chat':
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode not in [AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT]:
             raise NotCompletionAppError()
 
         message_id = str(message_id)
@@ -177,7 +168,8 @@ class MessageSuggestedQuestionApi(WebApiResource):
             questions = MessageService.get_suggested_questions_after_answer(
                 app_model=app_model,
                 user=end_user,
-                message_id=message_id
+                message_id=message_id,
+                invoke_from=InvokeFrom.WEB_APP
             )
         except MessageNotExistsError:
             raise NotFound("Message not found")

api/controllers/web/site.py

@@ -83,7 +83,3 @@ class AppSiteInfo:
                 'remove_webapp_brand': remove_webapp_brand,
                 'replace_webapp_logo': replace_webapp_logo,
             }
-
-        if app.enable_site and site.prompt_public:
-            app_model_config = app.app_model_config
-            self.model_config = app_model_config

api/controllers/web/workflow.py

@@ -0,0 +1,82 @@
+import logging
+
+from flask_restful import reqparse
+from werkzeug.exceptions import InternalServerError
+
+from controllers.web import api
+from controllers.web.error import (
+    CompletionRequestError,
+    NotWorkflowAppError,
+    ProviderModelCurrentlyNotSupportError,
+    ProviderNotInitializeError,
+    ProviderQuotaExceededError,
+)
+from controllers.web.wraps import WebApiResource
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.entities.app_invoke_entities import InvokeFrom
+from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.model_runtime.errors.invoke import InvokeError
+from libs import helper
+from models.model import App, AppMode, EndUser
+from services.app_generate_service import AppGenerateService
+
+logger = logging.getLogger(__name__)
+
+
+class WorkflowRunApi(WebApiResource):
+    def post(self, app_model: App, end_user: EndUser):
+        """
+        Run workflow
+        """
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('inputs', type=dict, required=True, nullable=False, location='json')
+        parser.add_argument('files', type=list, required=False, location='json')
+        args = parser.parse_args()
+
+        try:
+            response = AppGenerateService.generate(
+                app_model=app_model,
+                user=end_user,
+                args=args,
+                invoke_from=InvokeFrom.WEB_APP,
+                streaming=True
+            )
+
+            return helper.compact_generate_response(response)
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class WorkflowTaskStopApi(WebApiResource):
+    def post(self, app_model: App, end_user: EndUser, task_id: str):
+        """
+        Stop workflow task
+        """
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode != AppMode.WORKFLOW:
+            raise NotWorkflowAppError()
+
+        AppQueueManager.set_stop_flag(task_id, InvokeFrom.WEB_APP, end_user.id)
+
+        return {
+            "result": "success"
+        }
+
+
+api.add_resource(WorkflowRunApi, '/workflows/run')
+api.add_resource(WorkflowTaskStopApi, '/workflows/tasks/<string:task_id>/stop')

api/core/agent/base_agent_runner.py

@@ -2,22 +2,20 @@ import json
 import logging
 import uuid
 from datetime import datetime
-from mimetypes import guess_extension
 from typing import Optional, Union, cast
 
-from core.app_runner.app_runner import AppRunner
-from core.application_queue_manager import ApplicationQueueManager
+from core.agent.entities import AgentEntity, AgentToolEntity
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
+from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.apps.base_app_runner import AppRunner
+from core.app.entities.app_invoke_entities import (
+    AgentChatAppGenerateEntity,
+    ModelConfigWithCredentialsEntity,
+)
 from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import (
-    AgentEntity,
-    AgentToolEntity,
-    ApplicationGenerateEntity,
-    AppOrchestrationConfigEntity,
-    InvokeFrom,
-    ModelConfigEntity,
-)
-from core.file.message_file_parser import FileTransferMethod
+from core.file.message_file_parser import MessageFileParser
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMUsage
@@ -26,6 +24,7 @@ from core.model_runtime.entities.message_entities import (
     PromptMessage,
     PromptMessageTool,
     SystemPromptMessage,
+    TextPromptMessageContent,
     ToolPromptMessage,
     UserPromptMessage,
 )
@@ -34,27 +33,26 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.tools.entities.tool_entities import (
     ToolInvokeMessage,
-    ToolInvokeMessageBinary,
     ToolParameter,
     ToolRuntimeVariablePool,
 )
 from core.tools.tool.dataset_retriever_tool import DatasetRetrieverTool
 from core.tools.tool.tool import Tool
-from core.tools.tool_file_manager import ToolFileManager
 from core.tools.tool_manager import ToolManager
 from extensions.ext_database import db
-from models.model import Message, MessageAgentThought, MessageFile
+from models.model import Conversation, Message, MessageAgentThought
 from models.tools import ToolConversationVariables
 
 logger = logging.getLogger(__name__)
 
-class BaseAssistantApplicationRunner(AppRunner):
+class BaseAgentRunner(AppRunner):
     def __init__(self, tenant_id: str,
-                 application_generate_entity: ApplicationGenerateEntity,
-                 app_orchestration_config: AppOrchestrationConfigEntity,
-                 model_config: ModelConfigEntity,
+                 application_generate_entity: AgentChatAppGenerateEntity,
+                 conversation: Conversation,
+                 app_config: AgentChatAppConfig,
+                 model_config: ModelConfigWithCredentialsEntity,
                  config: AgentEntity,
-                 queue_manager: ApplicationQueueManager,
+                 queue_manager: AppQueueManager,
                  message: Message,
                  user_id: str,
                  memory: Optional[TokenBufferMemory] = None,
@@ -66,7 +64,7 @@ class BaseAssistantApplicationRunner(AppRunner):
         """
         Agent runner
         :param tenant_id: tenant id
-        :param app_orchestration_config: app orchestration config
+        :param app_config: app generate entity
         :param model_config: model config
         :param config: dataset config
         :param queue_manager: queue manager
@@ -78,7 +76,8 @@ class BaseAssistantApplicationRunner(AppRunner):
         """
         self.tenant_id = tenant_id
         self.application_generate_entity = application_generate_entity
-        self.app_orchestration_config = app_orchestration_config
+        self.conversation = conversation
+        self.app_config = app_config
         self.model_config = model_config
         self.config = config
         self.queue_manager = queue_manager
@@ -97,16 +96,16 @@ class BaseAssistantApplicationRunner(AppRunner):
         # init dataset tools
         hit_callback = DatasetIndexToolCallbackHandler(
             queue_manager=queue_manager,
-            app_id=self.application_generate_entity.app_id,
+            app_id=self.app_config.app_id,
             message_id=message.id,
             user_id=user_id,
             invoke_from=self.application_generate_entity.invoke_from,
         )
         self.dataset_tools = DatasetRetrieverTool.get_dataset_tools(
             tenant_id=tenant_id,
-            dataset_ids=app_orchestration_config.dataset.dataset_ids if app_orchestration_config.dataset else [],
-            retrieve_config=app_orchestration_config.dataset.retrieve_config if app_orchestration_config.dataset else None,
-            return_resource=app_orchestration_config.show_retrieve_source,
+            dataset_ids=app_config.dataset.dataset_ids if app_config.dataset else [],
+            retrieve_config=app_config.dataset.retrieve_config if app_config.dataset else None,
+            return_resource=app_config.additional_features.show_retrieve_source,
             invoke_from=application_generate_entity.invoke_from,
             hit_callback=hit_callback
         )
@@ -114,6 +113,7 @@ class BaseAssistantApplicationRunner(AppRunner):
         self.agent_thought_count = db.session.query(MessageAgentThought).filter(
             MessageAgentThought.message_id == self.message.id,
         ).count()
+        db.session.close()
 
         # check if model supports stream tool call
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
@@ -123,14 +123,21 @@ class BaseAssistantApplicationRunner(AppRunner):
         else:
             self.stream_tool_call = False
 
-    def _repack_app_orchestration_config(self, app_orchestration_config: AppOrchestrationConfigEntity) -> AppOrchestrationConfigEntity:
-        """
-        Repack app orchestration config
-        """
-        if app_orchestration_config.prompt_template.simple_prompt_template is None:
-            app_orchestration_config.prompt_template.simple_prompt_template = ''
+        # check if model supports vision
+        if model_schema and ModelFeature.VISION in (model_schema.features or []):
+            self.files = application_generate_entity.files
+        else:
+            self.files = []
 
-        return app_orchestration_config
+    def _repack_app_generate_entity(self, app_generate_entity: AgentChatAppGenerateEntity) \
+            -> AgentChatAppGenerateEntity:
+        """
+        Repack app generate entity
+        """
+        if app_generate_entity.app_config.prompt_template.simple_prompt_template is None:
+            app_generate_entity.app_config.prompt_template.simple_prompt_template = ''
+
+        return app_generate_entity
 
     def _convert_tool_response_to_str(self, tool_response: list[ToolInvokeMessage]) -> str:
         """
@@ -144,7 +151,7 @@ class BaseAssistantApplicationRunner(AppRunner):
                 result += f"result link: {response.message}. please tell user to check it."
             elif response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \
                  response.type == ToolInvokeMessage.MessageType.IMAGE:
-                result += "image has been created and sent to user already, you should tell user to check it now."
+                result += "image has been created and sent to user already, you do not need to create it, just tell the user to check it now."
             else:
                 result += f"tool response: {response.message}."
 
@@ -154,10 +161,9 @@ class BaseAssistantApplicationRunner(AppRunner):
         """
             convert tool to prompt message tool
         """
-        tool_entity = ToolManager.get_tool_runtime(
-            provider_type=tool.provider_type, provider_name=tool.provider_id, tool_name=tool.tool_name, 
-            tenant_id=self.application_generate_entity.tenant_id,
-            agent_callback=self.agent_callback
+        tool_entity = ToolManager.get_agent_tool_runtime(
+            tenant_id=self.tenant_id,
+            agent_tool=tool,
         )
         tool_entity.load_variables(self.variables_pool)
 
@@ -171,33 +177,11 @@ class BaseAssistantApplicationRunner(AppRunner):
             }
         )
 
-        runtime_parameters = {}
-
-        parameters = tool_entity.parameters or []
-        user_parameters = tool_entity.get_runtime_parameters() or []
-
-        # override parameters
-        for parameter in user_parameters:
-            # check if parameter in tool parameters
-            found = False
-            for tool_parameter in parameters:
-                if tool_parameter.name == parameter.name:
-                    found = True
-                    break
-
-            if found:
-                # override parameter
-                tool_parameter.type = parameter.type
-                tool_parameter.form = parameter.form
-                tool_parameter.required = parameter.required
-                tool_parameter.default = parameter.default
-                tool_parameter.options = parameter.options
-                tool_parameter.llm_description = parameter.llm_description
-            else:
-                # add new parameter
-                parameters.append(parameter)
-
+        parameters = tool_entity.get_all_runtime_parameters()
         for parameter in parameters:
+            if parameter.form != ToolParameter.ToolParameterForm.LLM:
+                continue
+
             parameter_type = 'string'
             enum = []
             if parameter.type == ToolParameter.ToolParameterType.STRING:
@@ -213,59 +197,16 @@ class BaseAssistantApplicationRunner(AppRunner):
             else:
                 raise ValueError(f"parameter type {parameter.type} is not supported")
             
-            if parameter.form == ToolParameter.ToolParameterForm.FORM:
-                # get tool parameter from form
-                tool_parameter_config = tool.tool_parameters.get(parameter.name)
-                if not tool_parameter_config:
-                    # get default value
-                    tool_parameter_config = parameter.default
-                    if not tool_parameter_config and parameter.required:
-                        raise ValueError(f"tool parameter {parameter.name} not found in tool config")
-                    
-                if parameter.type == ToolParameter.ToolParameterType.SELECT:
-                    # check if tool_parameter_config in options
-                    options = list(map(lambda x: x.value, parameter.options))
-                    if tool_parameter_config not in options:
-                        raise ValueError(f"tool parameter {parameter.name} value {tool_parameter_config} not in options {options}")
-                    
-                # convert tool parameter config to correct type
-                try:
-                    if parameter.type == ToolParameter.ToolParameterType.NUMBER:
-                        # check if tool parameter is integer
-                        if isinstance(tool_parameter_config, int):
-                            tool_parameter_config = tool_parameter_config
-                        elif isinstance(tool_parameter_config, float):
-                            tool_parameter_config = tool_parameter_config
-                        elif isinstance(tool_parameter_config, str):
-                            if '.' in tool_parameter_config:
-                                tool_parameter_config = float(tool_parameter_config)
-                            else:
-                                tool_parameter_config = int(tool_parameter_config)
-                    elif parameter.type == ToolParameter.ToolParameterType.BOOLEAN:
-                        tool_parameter_config = bool(tool_parameter_config)
-                    elif parameter.type not in [ToolParameter.ToolParameterType.SELECT, ToolParameter.ToolParameterType.STRING]:
-                        tool_parameter_config = str(tool_parameter_config)
-                    elif parameter.type == ToolParameter.ToolParameterType:
-                        tool_parameter_config = str(tool_parameter_config)
-                except Exception as e:
-                    raise ValueError(f"tool parameter {parameter.name} value {tool_parameter_config} is not correct type")
-                
-                # save tool parameter to tool entity memory
-                runtime_parameters[parameter.name] = tool_parameter_config
-            
-            elif parameter.form == ToolParameter.ToolParameterForm.LLM:
-                message_tool.parameters['properties'][parameter.name] = {
-                    "type": parameter_type,
-                    "description": parameter.llm_description or '',
-                }
+            message_tool.parameters['properties'][parameter.name] = {
+                "type": parameter_type,
+                "description": parameter.llm_description or '',
+            }
 
-                if len(enum) > 0:
-                    message_tool.parameters['properties'][parameter.name]['enum'] = enum
+            if len(enum) > 0:
+                message_tool.parameters['properties'][parameter.name]['enum'] = enum
 
-                if parameter.required:
-                    message_tool.parameters['required'].append(parameter.name)
-
-        tool_entity.runtime.runtime_parameters.update(runtime_parameters)
+            if parameter.required:
+                message_tool.parameters['required'].append(parameter.name)
 
         return message_tool, tool_entity
     
@@ -297,6 +238,34 @@ class BaseAssistantApplicationRunner(AppRunner):
 
         return prompt_tool
     
+    def _init_prompt_tools(self) -> tuple[dict[str, Tool], list[PromptMessageTool]]:
+        """
+        Init tools
+        """
+        tool_instances = {}
+        prompt_messages_tools = []
+
+        for tool in self.app_config.agent.tools if self.app_config.agent else []:
+            try:
+                prompt_tool, tool_entity = self._convert_tool_to_prompt_message_tool(tool)
+            except Exception:
+                # api tool may be deleted
+                continue
+            # save tool entity
+            tool_instances[tool.tool_name] = tool_entity
+            # save prompt tool
+            prompt_messages_tools.append(prompt_tool)
+
+        # convert dataset tools into ModelRuntime Tool format
+        for dataset_tool in self.dataset_tools:
+            prompt_tool = self._convert_dataset_retriever_tool_to_prompt_message_tool(dataset_tool)
+            # save prompt tool
+            prompt_messages_tools.append(prompt_tool)
+            # save tool entity
+            tool_instances[dataset_tool.identity.name] = dataset_tool
+
+        return tool_instances, prompt_messages_tools
+
     def update_prompt_message_tool(self, tool: Tool, prompt_tool: PromptMessageTool) -> PromptMessageTool:
         """
         update prompt message tool
@@ -305,6 +274,9 @@ class BaseAssistantApplicationRunner(AppRunner):
         tool_runtime_parameters = tool.get_runtime_parameters() or []
 
         for parameter in tool_runtime_parameters:
+            if parameter.form != ToolParameter.ToolParameterForm.LLM:
+                continue
+
             parameter_type = 'string'
             enum = []
             if parameter.type == ToolParameter.ToolParameterType.STRING:
@@ -320,98 +292,19 @@ class BaseAssistantApplicationRunner(AppRunner):
             else:
                 raise ValueError(f"parameter type {parameter.type} is not supported")
         
-            if parameter.form == ToolParameter.ToolParameterForm.LLM:
-                prompt_tool.parameters['properties'][parameter.name] = {
-                    "type": parameter_type,
-                    "description": parameter.llm_description or '',
-                }
+            prompt_tool.parameters['properties'][parameter.name] = {
+                "type": parameter_type,
+                "description": parameter.llm_description or '',
+            }
 
-                if len(enum) > 0:
-                    prompt_tool.parameters['properties'][parameter.name]['enum'] = enum
+            if len(enum) > 0:
+                prompt_tool.parameters['properties'][parameter.name]['enum'] = enum
 
-                if parameter.required:
-                    if parameter.name not in prompt_tool.parameters['required']:
-                        prompt_tool.parameters['required'].append(parameter.name)
+            if parameter.required:
+                if parameter.name not in prompt_tool.parameters['required']:
+                    prompt_tool.parameters['required'].append(parameter.name)
 
         return prompt_tool
-    
-    def extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) -> list[ToolInvokeMessageBinary]:
-        """
-        Extract tool response binary
-        """
-        result = []
-
-        for response in tool_response:
-            if response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \
-                response.type == ToolInvokeMessage.MessageType.IMAGE:
-                result.append(ToolInvokeMessageBinary(
-                    mimetype=response.meta.get('mime_type', 'octet/stream'),
-                    url=response.message,
-                    save_as=response.save_as,
-                ))
-            elif response.type == ToolInvokeMessage.MessageType.BLOB:
-                result.append(ToolInvokeMessageBinary(
-                    mimetype=response.meta.get('mime_type', 'octet/stream'),
-                    url=response.message,
-                    save_as=response.save_as,
-                ))
-            elif response.type == ToolInvokeMessage.MessageType.LINK:
-                # check if there is a mime type in meta
-                if response.meta and 'mime_type' in response.meta:
-                    result.append(ToolInvokeMessageBinary(
-                        mimetype=response.meta.get('mime_type', 'octet/stream') if response.meta else 'octet/stream',
-                        url=response.message,
-                        save_as=response.save_as,
-                    ))
-
-        return result
-    
-    def create_message_files(self, messages: list[ToolInvokeMessageBinary]) -> list[tuple[MessageFile, bool]]:
-        """
-        Create message file
-
-        :param messages: messages
-        :return: message files, should save as variable
-        """
-        result = []
-
-        for message in messages:
-            file_type = 'bin'
-            if 'image' in message.mimetype:
-                file_type = 'image'
-            elif 'video' in message.mimetype:
-                file_type = 'video'
-            elif 'audio' in message.mimetype:
-                file_type = 'audio'
-            elif 'text' in message.mimetype:
-                file_type = 'text'
-            elif 'pdf' in message.mimetype:
-                file_type = 'pdf'
-            elif 'zip' in message.mimetype:
-                file_type = 'archive'
-            # ...
-
-            invoke_from = self.application_generate_entity.invoke_from
-
-            message_file = MessageFile(
-                message_id=self.message.id,
-                type=file_type,
-                transfer_method=FileTransferMethod.TOOL_FILE.value,
-                belongs_to='assistant',
-                url=message.url,
-                upload_file_id=None,
-                created_by_role=('account'if invoke_from in [InvokeFrom.EXPLORE, InvokeFrom.DEBUGGER] else 'end_user'),
-                created_by=self.user_id,
-            )
-            db.session.add(message_file)
-            result.append((
-                message_file,
-                message.save_as
-            ))
-            
-        db.session.commit()
-
-        return result
         
     def create_agent_thought(self, message_id: str, message: str, 
                              tool_name: str, tool_input: str, messages_ids: list[str]
@@ -425,6 +318,7 @@ class BaseAssistantApplicationRunner(AppRunner):
             thought='',
             tool=tool_name,
             tool_labels_str='{}',
+            tool_meta_str='{}',
             tool_input=tool_input,
             message=message,
             message_token=0,
@@ -447,6 +341,8 @@ class BaseAssistantApplicationRunner(AppRunner):
 
         db.session.add(thought)
         db.session.commit()
+        db.session.refresh(thought)
+        db.session.close()
 
         self.agent_thought_count += 1
 
@@ -457,13 +353,18 @@ class BaseAssistantApplicationRunner(AppRunner):
                            tool_name: str,
                            tool_input: Union[str, dict],
                            thought: str, 
-                           observation: str, 
+                           observation: Union[str, dict], 
+                           tool_invoke_meta: Union[str, dict],
                            answer: str,
                            messages_ids: list[str],
                            llm_usage: LLMUsage = None) -> MessageAgentThought:
         """
         Save agent thought
         """
+        agent_thought = db.session.query(MessageAgentThought).filter(
+            MessageAgentThought.id == agent_thought.id
+        ).first()
+
         if thought is not None:
             agent_thought.thought = thought
 
@@ -480,6 +381,12 @@ class BaseAssistantApplicationRunner(AppRunner):
             agent_thought.tool_input = tool_input
 
         if observation is not None:
+            if isinstance(observation, dict):
+                try:
+                    observation = json.dumps(observation, ensure_ascii=False)
+                except Exception as e:
+                    observation = json.dumps(observation)
+                    
             agent_thought.observation = observation
 
         if answer is not None:
@@ -513,82 +420,30 @@ class BaseAssistantApplicationRunner(AppRunner):
 
         agent_thought.tool_labels_str = json.dumps(labels)
 
-        db.session.commit()
-    
-    def transform_tool_invoke_messages(self, messages: list[ToolInvokeMessage]) -> list[ToolInvokeMessage]:
-        """
-        Transform tool message into agent thought
-        """
-        result = []
-
-        for message in messages:
-            if message.type == ToolInvokeMessage.MessageType.TEXT:
-                result.append(message)
-            elif message.type == ToolInvokeMessage.MessageType.LINK:
-                result.append(message)
-            elif message.type == ToolInvokeMessage.MessageType.IMAGE:
-                # try to download image
+        if tool_invoke_meta is not None:
+            if isinstance(tool_invoke_meta, dict):
                 try:
-                    file = ToolFileManager.create_file_by_url(user_id=self.user_id, tenant_id=self.tenant_id,
-                                                               conversation_id=self.message.conversation_id,
-                                                               file_url=message.message)
-                    
-                    url = f'/files/tools/{file.id}{guess_extension(file.mimetype) or ".png"}'
-
-                    result.append(ToolInvokeMessage(
-                        type=ToolInvokeMessage.MessageType.IMAGE_LINK,
-                        message=url,
-                        save_as=message.save_as,
-                        meta=message.meta.copy() if message.meta is not None else {},
-                    ))
+                    tool_invoke_meta = json.dumps(tool_invoke_meta, ensure_ascii=False)
                 except Exception as e:
-                    logger.exception(e)
-                    result.append(ToolInvokeMessage(
-                        type=ToolInvokeMessage.MessageType.TEXT,
-                        message=f"Failed to download image: {message.message}, you can try to download it yourself.",
-                        meta=message.meta.copy() if message.meta is not None else {},
-                        save_as=message.save_as,
-                    ))
-            elif message.type == ToolInvokeMessage.MessageType.BLOB:
-                # get mime type and save blob to storage
-                mimetype = message.meta.get('mime_type', 'octet/stream')
-                # if message is str, encode it to bytes
-                if isinstance(message.message, str):
-                    message.message = message.message.encode('utf-8')
-                file = ToolFileManager.create_file_by_raw(user_id=self.user_id, tenant_id=self.tenant_id,
-                                                            conversation_id=self.message.conversation_id,
-                                                            file_binary=message.message,
-                                                            mimetype=mimetype)
-                                                            
-                url = f'/files/tools/{file.id}{guess_extension(file.mimetype) or ".bin"}'
+                    tool_invoke_meta = json.dumps(tool_invoke_meta)
 
-                # check if file is image
-                if 'image' in mimetype:
-                    result.append(ToolInvokeMessage(
-                        type=ToolInvokeMessage.MessageType.IMAGE_LINK,
-                        message=url,
-                        save_as=message.save_as,
-                        meta=message.meta.copy() if message.meta is not None else {},
-                    ))
-                else:
-                    result.append(ToolInvokeMessage(
-                        type=ToolInvokeMessage.MessageType.LINK,
-                        message=url,
-                        save_as=message.save_as,
-                        meta=message.meta.copy() if message.meta is not None else {},
-                    ))
-            else:
-                result.append(message)
+            agent_thought.tool_meta_str = tool_invoke_meta
 
-        return result
+        db.session.commit()
+        db.session.close()
     
     def update_db_variables(self, tool_variables: ToolRuntimeVariablePool, db_variables: ToolConversationVariables):
         """
         convert tool variables to db variables
         """
+        db_variables = db.session.query(ToolConversationVariables).filter(
+            ToolConversationVariables.conversation_id == self.message.conversation_id,
+        ).first()
+
         db_variables.updated_at = datetime.utcnow()
         db_variables.variables_str = json.dumps(jsonable_encoder(tool_variables.pool))
         db.session.commit()
+        db.session.close()
 
     def organize_agent_history(self, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
         """
@@ -596,15 +451,19 @@ class BaseAssistantApplicationRunner(AppRunner):
         """
         result = []
         # check if there is a system message in the beginning of the conversation
-        if prompt_messages and isinstance(prompt_messages[0], SystemPromptMessage):
-            result.append(prompt_messages[0])
+        for prompt_message in prompt_messages:
+            if isinstance(prompt_message, SystemPromptMessage):
+                result.append(prompt_message)
 
         messages: list[Message] = db.session.query(Message).filter(
             Message.conversation_id == self.message.conversation_id,
         ).order_by(Message.created_at.asc()).all()
 
         for message in messages:
-            result.append(UserPromptMessage(content=message.query))
+            if message.id == self.message.id:
+                continue
+            
+            result.append(self.organize_agent_user_prompt(message))
             agent_thoughts: list[MessageAgentThought] = message.agent_thoughts
             if agent_thoughts:
                 for agent_thought in agent_thoughts:
@@ -613,7 +472,15 @@ class BaseAssistantApplicationRunner(AppRunner):
                         tools = tools.split(';')
                         tool_calls: list[AssistantPromptMessage.ToolCall] = []
                         tool_call_response: list[ToolPromptMessage] = []
-                        tool_inputs = json.loads(agent_thought.tool_input)
+                        try:
+                            tool_inputs = json.loads(agent_thought.tool_input)
+                        except Exception as e:
+                            tool_inputs = { tool: {} for tool in tools }
+                        try:
+                            tool_responses = json.loads(agent_thought.observation)
+                        except Exception as e:
+                            tool_responses = { tool: agent_thought.observation for tool in tools }
+
                         for tool in tools:
                             # generate a uuid for tool call
                             tool_call_id = str(uuid.uuid4())
@@ -626,7 +493,7 @@ class BaseAssistantApplicationRunner(AppRunner):
                                 )
                             ))
                             tool_call_response.append(ToolPromptMessage(
-                                content=agent_thought.observation,
+                                content=tool_responses.get(tool, agent_thought.observation),
                                 name=tool,
                                 tool_call_id=tool_call_id,
                             ))
@@ -644,4 +511,35 @@ class BaseAssistantApplicationRunner(AppRunner):
                 if message.answer:
                     result.append(AssistantPromptMessage(content=message.answer))
 
-        return result
+        db.session.close()
+
+        return result
+
+    def organize_agent_user_prompt(self, message: Message) -> UserPromptMessage:
+        message_file_parser = MessageFileParser(
+            tenant_id=self.tenant_id,
+            app_id=self.app_config.app_id,
+        )
+
+        files = message.message_files
+        if files:
+            file_extra_config = FileUploadConfigManager.convert(message.app_model_config.to_dict())
+
+            if file_extra_config:
+                file_objs = message_file_parser.transform_message_files(
+                    files,
+                    file_extra_config
+                )
+            else:
+                file_objs = []
+
+            if not file_objs:
+                return UserPromptMessage(content=message.query)
+            else:
+                prompt_message_contents = [TextPromptMessageContent(data=message.query)]
+                for file_obj in file_objs:
+                    prompt_message_contents.append(file_obj.prompt_message_content)
+
+                return UserPromptMessage(content=prompt_message_contents)
+        else:
+            return UserPromptMessage(content=message.query)

api/core/agent/cot_agent_runner.py

@@ -0,0 +1,424 @@
+import json
+from abc import ABC, abstractmethod
+from collections.abc import Generator
+from typing import Union
+
+from core.agent.base_agent_runner import BaseAgentRunner
+from core.agent.entities import AgentScratchpadUnit
+from core.agent.output_parser.cot_output_parser import CotAgentOutputParser
+from core.app.apps.base_app_queue_manager import PublishFrom
+from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.tools.entities.tool_entities import ToolInvokeMeta
+from core.tools.tool.tool import Tool
+from core.tools.tool_engine import ToolEngine
+from models.model import Message
+
+
+class CotAgentRunner(BaseAgentRunner, ABC):
+    _is_first_iteration = True
+    _ignore_observation_providers = ['wenxin']
+    _historic_prompt_messages: list[PromptMessage] = None
+    _agent_scratchpad: list[AgentScratchpadUnit] = None
+    _instruction: str = None
+    _query: str = None
+    _prompt_messages_tools: list[PromptMessage] = None
+
+    def run(self, message: Message,
+        query: str,
+        inputs: dict[str, str],
+    ) -> Union[Generator, LLMResult]:
+        """
+        Run Cot agent application
+        """
+        app_generate_entity = self.application_generate_entity
+        self._repack_app_generate_entity(app_generate_entity)
+        self._init_react_state(query)
+
+        # check model mode
+        if 'Observation' not in app_generate_entity.model_config.stop:
+            if app_generate_entity.model_config.provider not in self._ignore_observation_providers:
+                app_generate_entity.model_config.stop.append('Observation')
+
+        app_config = self.app_config
+
+        # init instruction
+        inputs = inputs or {}
+        instruction = app_config.prompt_template.simple_prompt_template
+        self._instruction = self._fill_in_inputs_from_external_data_tools(instruction, inputs)
+
+        iteration_step = 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1
+
+        # convert tools into ModelRuntime Tool format
+        tool_instances, self._prompt_messages_tools = self._init_prompt_tools()
+
+        prompt_messages = self._organize_prompt_messages()
+        
+        function_call_state = True
+        llm_usage = {
+            'usage': None
+        }
+        final_answer = ''
+
+        def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage):
+            if not final_llm_usage_dict['usage']:
+                final_llm_usage_dict['usage'] = usage
+            else:
+                llm_usage = final_llm_usage_dict['usage']
+                llm_usage.prompt_tokens += usage.prompt_tokens
+                llm_usage.completion_tokens += usage.completion_tokens
+                llm_usage.prompt_price += usage.prompt_price
+                llm_usage.completion_price += usage.completion_price
+
+        model_instance = self.model_instance
+
+        while function_call_state and iteration_step <= max_iteration_steps:
+            # continue to run until there is not any tool call
+            function_call_state = False
+
+            if iteration_step == max_iteration_steps:
+                # the last iteration, remove all tools
+                self._prompt_messages_tools = []
+
+            message_file_ids = []
+
+            agent_thought = self.create_agent_thought(
+                message_id=message.id,
+                message='',
+                tool_name='',
+                tool_input='',
+                messages_ids=message_file_ids
+            )
+
+            if iteration_step > 1:
+                self.queue_manager.publish(QueueAgentThoughtEvent(
+                    agent_thought_id=agent_thought.id
+                ), PublishFrom.APPLICATION_MANAGER)
+
+            # recalc llm max tokens
+            prompt_messages = self._organize_prompt_messages()
+            self.recalc_llm_max_tokens(self.model_config, prompt_messages)
+            # invoke model
+            chunks: Generator[LLMResultChunk, None, None] = model_instance.invoke_llm(
+                prompt_messages=prompt_messages,
+                model_parameters=app_generate_entity.model_config.parameters,
+                tools=[],
+                stop=app_generate_entity.model_config.stop,
+                stream=True,
+                user=self.user_id,
+                callbacks=[],
+            )
+
+            # check llm result
+            if not chunks:
+                raise ValueError("failed to invoke llm")
+            
+            usage_dict = {}
+            react_chunks = CotAgentOutputParser.handle_react_stream_output(chunks)
+            scratchpad = AgentScratchpadUnit(
+                agent_response='',
+                thought='',
+                action_str='',
+                observation='',
+                action=None,
+            )
+
+            # publish agent thought if it's first iteration
+            if iteration_step == 1:
+                self.queue_manager.publish(QueueAgentThoughtEvent(
+                    agent_thought_id=agent_thought.id
+                ), PublishFrom.APPLICATION_MANAGER)
+
+            for chunk in react_chunks:
+                if isinstance(chunk, AgentScratchpadUnit.Action):
+                    action = chunk
+                    # detect action
+                    scratchpad.agent_response += json.dumps(chunk.dict())
+                    scratchpad.action_str = json.dumps(chunk.dict())
+                    scratchpad.action = action
+                else:
+                    scratchpad.agent_response += chunk
+                    scratchpad.thought += chunk
+                    yield LLMResultChunk(
+                        model=self.model_config.model,
+                        prompt_messages=prompt_messages,
+                        system_fingerprint='',
+                        delta=LLMResultChunkDelta(
+                            index=0,
+                            message=AssistantPromptMessage(
+                                content=chunk
+                            ),
+                            usage=None
+                        )
+                    )
+
+            scratchpad.thought = scratchpad.thought.strip() or 'I am thinking about how to help you'
+            self._agent_scratchpad.append(scratchpad)
+            
+            # get llm usage
+            if 'usage' in usage_dict:
+                increase_usage(llm_usage, usage_dict['usage'])
+            else:
+                usage_dict['usage'] = LLMUsage.empty_usage()
+            
+            self.save_agent_thought(
+                agent_thought=agent_thought,
+                tool_name=scratchpad.action.action_name if scratchpad.action else '',
+                tool_input={
+                    scratchpad.action.action_name: scratchpad.action.action_input
+                } if scratchpad.action else {},
+                tool_invoke_meta={},
+                thought=scratchpad.thought,
+                observation='',
+                answer=scratchpad.agent_response,
+                messages_ids=[],
+                llm_usage=usage_dict['usage']
+            )
+            
+            if not scratchpad.is_final():
+                self.queue_manager.publish(QueueAgentThoughtEvent(
+                    agent_thought_id=agent_thought.id
+                ), PublishFrom.APPLICATION_MANAGER)
+
+            if not scratchpad.action:
+                # failed to extract action, return final answer directly
+                final_answer = scratchpad.agent_response or ''
+            else:
+                if scratchpad.action.action_name.lower() == "final answer":
+                    # action is final answer, return final answer directly
+                    try:
+                        if isinstance(scratchpad.action.action_input, dict):
+                            final_answer = json.dumps(scratchpad.action.action_input)
+                        elif isinstance(scratchpad.action.action_input, str):
+                            final_answer = scratchpad.action.action_input
+                        else:
+                            final_answer = f'{scratchpad.action.action_input}'
+                    except json.JSONDecodeError:
+                        final_answer = f'{scratchpad.action.action_input}'
+                else:
+                    function_call_state = True
+                    # action is tool call, invoke tool
+                    tool_invoke_response, tool_invoke_meta = self._handle_invoke_action(
+                        action=scratchpad.action, 
+                        tool_instances=tool_instances,
+                        message_file_ids=message_file_ids
+                    )
+                    scratchpad.observation = tool_invoke_response
+                    scratchpad.agent_response = tool_invoke_response
+
+                    self.save_agent_thought(
+                        agent_thought=agent_thought,
+                        tool_name=scratchpad.action.action_name,
+                        tool_input={scratchpad.action.action_name: scratchpad.action.action_input},
+                        thought=scratchpad.thought,
+                        observation={scratchpad.action.action_name: tool_invoke_response},
+                        tool_invoke_meta=tool_invoke_meta.to_dict(),
+                        answer=scratchpad.agent_response,
+                        messages_ids=message_file_ids,
+                        llm_usage=usage_dict['usage']
+                    )
+
+                    self.queue_manager.publish(QueueAgentThoughtEvent(
+                        agent_thought_id=agent_thought.id
+                    ), PublishFrom.APPLICATION_MANAGER)
+
+                # update prompt tool message
+                for prompt_tool in self._prompt_messages_tools:
+                    self.update_prompt_message_tool(tool_instances[prompt_tool.name], prompt_tool)
+
+            iteration_step += 1
+
+        yield LLMResultChunk(
+            model=model_instance.model,
+            prompt_messages=prompt_messages,
+            delta=LLMResultChunkDelta(
+                index=0,
+                message=AssistantPromptMessage(
+                    content=final_answer
+                ),
+                usage=llm_usage['usage']
+            ),
+            system_fingerprint=''
+        )
+
+        # save agent thought
+        self.save_agent_thought(
+            agent_thought=agent_thought, 
+            tool_name='',
+            tool_input={},
+            tool_invoke_meta={},
+            thought=final_answer,
+            observation={}, 
+            answer=final_answer,
+            messages_ids=[]
+        )
+
+        self.update_db_variables(self.variables_pool, self.db_variables_pool)
+        # publish end event
+        self.queue_manager.publish(QueueMessageEndEvent(llm_result=LLMResult(
+            model=model_instance.model,
+            prompt_messages=prompt_messages,
+            message=AssistantPromptMessage(
+                content=final_answer
+            ),
+            usage=llm_usage['usage'] if llm_usage['usage'] else LLMUsage.empty_usage(),
+            system_fingerprint=''
+        )), PublishFrom.APPLICATION_MANAGER)
+
+    def _handle_invoke_action(self, action: AgentScratchpadUnit.Action, 
+                              tool_instances: dict[str, Tool],
+                              message_file_ids: list[str]) -> tuple[str, ToolInvokeMeta]:
+        """
+        handle invoke action
+        :param action: action
+        :param tool_instances: tool instances
+        :return: observation, meta
+        """
+        # action is tool call, invoke tool
+        tool_call_name = action.action_name
+        tool_call_args = action.action_input
+        tool_instance = tool_instances.get(tool_call_name)
+
+        if not tool_instance:
+            answer = f"there is not a tool named {tool_call_name}"
+            return answer, ToolInvokeMeta.error_instance(answer)
+        
+        if isinstance(tool_call_args, str):
+            try:
+                tool_call_args = json.loads(tool_call_args)
+            except json.JSONDecodeError:
+                pass
+
+        # invoke tool
+        tool_invoke_response, message_files, tool_invoke_meta = ToolEngine.agent_invoke(
+            tool=tool_instance,
+            tool_parameters=tool_call_args,
+            user_id=self.user_id,
+            tenant_id=self.tenant_id,
+            message=self.message,
+            invoke_from=self.application_generate_entity.invoke_from,
+            agent_tool_callback=self.agent_callback
+        )
+
+        # publish files
+        for message_file, save_as in message_files:
+            if save_as:
+                self.variables_pool.set_file(tool_name=tool_call_name, value=message_file.id, name=save_as)
+
+            # publish message file
+            self.queue_manager.publish(QueueMessageFileEvent(
+                message_file_id=message_file.id
+            ), PublishFrom.APPLICATION_MANAGER)
+            # add message file ids
+            message_file_ids.append(message_file.id)
+
+        return tool_invoke_response, tool_invoke_meta
+
+    def _convert_dict_to_action(self, action: dict) -> AgentScratchpadUnit.Action:
+        """
+        convert dict to action
+        """
+        return AgentScratchpadUnit.Action(
+            action_name=action['action'],
+            action_input=action['action_input']
+        )
+
+    def _fill_in_inputs_from_external_data_tools(self, instruction: str, inputs: dict) -> str:
+        """
+        fill in inputs from external data tools
+        """
+        for key, value in inputs.items():
+            try:
+                instruction = instruction.replace(f'{{{{{key}}}}}', str(value))
+            except Exception as e:
+                continue
+
+        return instruction
+    
+    def _init_react_state(self, query) -> None:
+        """
+        init agent scratchpad
+        """
+        self._query = query
+        self._agent_scratchpad = []
+        self._historic_prompt_messages = self._organize_historic_prompt_messages()
+    
+    @abstractmethod
+    def _organize_prompt_messages(self) -> list[PromptMessage]:
+        """
+            organize prompt messages
+        """
+
+    def _format_assistant_message(self, agent_scratchpad: list[AgentScratchpadUnit]) -> str:
+        """
+            format assistant message
+        """
+        message = ''
+        for scratchpad in agent_scratchpad:
+            if scratchpad.is_final():
+                message += f"Final Answer: {scratchpad.agent_response}"
+            else:
+                message += f"Thought: {scratchpad.thought}\n\n"
+                if scratchpad.action_str:
+                    message += f"Action: {scratchpad.action_str}\n\n"
+                if scratchpad.observation:
+                    message += f"Observation: {scratchpad.observation}\n\n"
+
+        return message
+
+    def _organize_historic_prompt_messages(self) -> list[PromptMessage]:
+        """
+            organize historic prompt messages
+        """
+        result: list[PromptMessage] = []
+        scratchpad: list[AgentScratchpadUnit] = []
+        current_scratchpad: AgentScratchpadUnit = None
+
+        for message in self.history_prompt_messages:
+            if isinstance(message, AssistantPromptMessage):
+                current_scratchpad = AgentScratchpadUnit(
+                    agent_response=message.content,
+                    thought=message.content or 'I am thinking about how to help you',
+                    action_str='',
+                    action=None,
+                    observation=None,
+                )
+                if message.tool_calls:
+                    try:
+                        current_scratchpad.action = AgentScratchpadUnit.Action(
+                            action_name=message.tool_calls[0].function.name,
+                            action_input=json.loads(message.tool_calls[0].function.arguments)
+                        )
+                        current_scratchpad.action_str = json.dumps(
+                            current_scratchpad.action.to_dict()
+                        )
+                    except:
+                        pass
+                
+                scratchpad.append(current_scratchpad)
+            elif isinstance(message, ToolPromptMessage):
+                if current_scratchpad:
+                    current_scratchpad.observation = message.content
+            elif isinstance(message, UserPromptMessage):
+                result.append(message)
+
+                if scratchpad:
+                    result.append(AssistantPromptMessage(
+                        content=self._format_assistant_message(scratchpad)
+                    ))
+
+                scratchpad = []
+
+        if scratchpad:
+            result.append(AssistantPromptMessage(
+                content=self._format_assistant_message(scratchpad)
+            ))
+        
+        return result

api/core/agent/cot_chat_agent_runner.py

@@ -0,0 +1,71 @@
+import json
+
+from core.agent.cot_agent_runner import CotAgentRunner
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.utils.encoders import jsonable_encoder
+
+
+class CotChatAgentRunner(CotAgentRunner):
+    def _organize_system_prompt(self) -> SystemPromptMessage:
+        """
+        Organize system prompt
+        """
+        prompt_entity = self.app_config.agent.prompt
+        first_prompt = prompt_entity.first_prompt
+
+        system_prompt = first_prompt \
+            .replace("{{instruction}}", self._instruction) \
+            .replace("{{tools}}", json.dumps(jsonable_encoder(self._prompt_messages_tools))) \
+            .replace("{{tool_names}}", ', '.join([tool.name for tool in self._prompt_messages_tools]))
+
+        return SystemPromptMessage(content=system_prompt)
+
+    def _organize_prompt_messages(self) -> list[PromptMessage]:
+        """
+        Organize 
+        """
+        # organize system prompt
+        system_message = self._organize_system_prompt()
+
+        # organize historic prompt messages
+        historic_messages = self._historic_prompt_messages
+
+        # organize current assistant messages
+        agent_scratchpad = self._agent_scratchpad
+        if not agent_scratchpad:
+            assistant_messages = []
+        else:
+            assistant_message = AssistantPromptMessage(content='')
+            for unit in agent_scratchpad:
+                if unit.is_final():
+                    assistant_message.content += f"Final Answer: {unit.agent_response}"
+                else:
+                    assistant_message.content += f"Thought: {unit.thought}\n\n"
+                    if unit.action_str:
+                        assistant_message.content += f"Action: {unit.action_str}\n\n"
+                    if unit.observation:
+                        assistant_message.content += f"Observation: {unit.observation}\n\n"
+
+            assistant_messages = [assistant_message]
+
+        # query messages
+        query_messages = UserPromptMessage(content=self._query)
+
+        if assistant_messages:
+            messages = [
+                system_message,
+                *historic_messages,
+                query_messages,
+                *assistant_messages,
+                UserPromptMessage(content='continue')
+            ]
+        else:
+            messages = [system_message, *historic_messages, query_messages]
+
+        # join all messages
+        return messages

api/core/agent/cot_completion_agent_runner.py

@@ -0,0 +1,69 @@
+import json
+
+from core.agent.cot_agent_runner import CotAgentRunner
+from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
+from core.model_runtime.utils.encoders import jsonable_encoder
+
+
+class CotCompletionAgentRunner(CotAgentRunner):
+    def _organize_instruction_prompt(self) -> str:
+        """
+        Organize instruction prompt
+        """
+        prompt_entity = self.app_config.agent.prompt
+        first_prompt = prompt_entity.first_prompt
+
+        system_prompt = first_prompt.replace("{{instruction}}", self._instruction) \
+            .replace("{{tools}}", json.dumps(jsonable_encoder(self._prompt_messages_tools))) \
+            .replace("{{tool_names}}", ', '.join([tool.name for tool in self._prompt_messages_tools]))
+        
+        return system_prompt
+
+    def _organize_historic_prompt(self) -> str:
+        """
+        Organize historic prompt
+        """
+        historic_prompt_messages = self._historic_prompt_messages
+        historic_prompt = ""
+
+        for message in historic_prompt_messages:
+            if isinstance(message, UserPromptMessage):
+                historic_prompt += f"Question: {message.content}\n\n"
+            elif isinstance(message, AssistantPromptMessage):
+                historic_prompt += message.content + "\n\n"
+
+        return historic_prompt
+
+    def _organize_prompt_messages(self) -> list[PromptMessage]:
+        """
+        Organize prompt messages
+        """
+        # organize system prompt
+        system_prompt = self._organize_instruction_prompt()
+
+        # organize historic prompt messages
+        historic_prompt = self._organize_historic_prompt()
+
+        # organize current assistant messages
+        agent_scratchpad = self._agent_scratchpad
+        assistant_prompt = ''
+        for unit in agent_scratchpad:
+            if unit.is_final():
+                assistant_prompt += f"Final Answer: {unit.agent_response}"
+            else:
+                assistant_prompt += f"Thought: {unit.thought}\n\n"
+                if unit.action_str:
+                    assistant_prompt += f"Action: {unit.action_str}\n\n"
+                if unit.observation:
+                    assistant_prompt += f"Observation: {unit.observation}\n\n"
+
+        # query messages
+        query_prompt = f"Question: {self._query}"
+
+        # join all messages
+        prompt = system_prompt \
+            .replace("{{historic_messages}}", historic_prompt) \
+            .replace("{{agent_scratchpad}}", assistant_prompt) \
+            .replace("{{query}}", query_prompt)
+
+        return [UserPromptMessage(content=prompt)]

api/core/agent/entities.py

@@ -0,0 +1,78 @@
+from enum import Enum
+from typing import Any, Literal, Optional, Union
+
+from pydantic import BaseModel
+
+
+class AgentToolEntity(BaseModel):
+    """
+    Agent Tool Entity.
+    """
+    provider_type: Literal["builtin", "api"]
+    provider_id: str
+    tool_name: str
+    tool_parameters: dict[str, Any] = {}
+
+
+class AgentPromptEntity(BaseModel):
+    """
+    Agent Prompt Entity.
+    """
+    first_prompt: str
+    next_iteration: str
+
+
+class AgentScratchpadUnit(BaseModel):
+    """
+    Agent First Prompt Entity.
+    """
+
+    class Action(BaseModel):
+        """
+        Action Entity.
+        """
+        action_name: str
+        action_input: Union[dict, str]
+
+        def to_dict(self) -> dict:
+            """
+            Convert to dictionary.
+            """
+            return {
+                'action': self.action_name,
+                'action_input': self.action_input,
+            }
+
+    agent_response: Optional[str] = None
+    thought: Optional[str] = None
+    action_str: Optional[str] = None
+    observation: Optional[str] = None
+    action: Optional[Action] = None
+
+    def is_final(self) -> bool:
+        """
+        Check if the scratchpad unit is final.
+        """
+        return self.action is None or (
+            'final' in self.action.action_name.lower() and 
+            'answer' in self.action.action_name.lower()
+        )
+
+class AgentEntity(BaseModel):
+    """
+    Agent Entity.
+    """
+
+    class Strategy(Enum):
+        """
+        Agent Strategy.
+        """
+        CHAIN_OF_THOUGHT = 'chain-of-thought'
+        FUNCTION_CALLING = 'function-calling'
+
+    provider: str
+    model: str
+    strategy: Strategy
+    prompt: Optional[AgentPromptEntity] = None
+    tools: list[AgentToolEntity] = None
+    max_iteration: int = 5

api/core/agent/fc_agent_runner.py

@@ -1,77 +1,52 @@
 import json
 import logging
 from collections.abc import Generator
+from copy import deepcopy
 from typing import Any, Union
 
-from core.application_queue_manager import PublishFrom
-from core.features.assistant_base_runner import BaseAssistantApplicationRunner
+from core.agent.base_agent_runner import BaseAgentRunner
+from core.app.apps.base_app_queue_manager import PublishFrom
+from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
     PromptMessage,
-    PromptMessageTool,
+    PromptMessageContentType,
     SystemPromptMessage,
+    TextPromptMessageContent,
     ToolPromptMessage,
     UserPromptMessage,
 )
-from core.tools.errors import (
-    ToolInvokeError,
-    ToolNotFoundError,
-    ToolNotSupportedError,
-    ToolParameterValidationError,
-    ToolProviderCredentialValidationError,
-    ToolProviderNotFoundError,
-)
-from models.model import Conversation, Message, MessageAgentThought
+from core.tools.entities.tool_entities import ToolInvokeMeta
+from core.tools.tool_engine import ToolEngine
+from models.model import Message
 
 logger = logging.getLogger(__name__)
 
-class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
-    def run(self, conversation: Conversation,
-                message: Message,
-                query: str,
+class FunctionCallAgentRunner(BaseAgentRunner):
+    def run(self, 
+            message: Message, query: str, **kwargs: Any
     ) -> Generator[LLMResultChunk, None, None]:
         """
         Run FunctionCall agent application
         """
-        app_orchestration_config = self.app_orchestration_config
+        app_generate_entity = self.application_generate_entity
 
-        prompt_template = self.app_orchestration_config.prompt_template.simple_prompt_template or ''
+        app_config = self.app_config
+
+        prompt_template = app_config.prompt_template.simple_prompt_template or ''
         prompt_messages = self.history_prompt_messages
-        prompt_messages = self.organize_prompt_messages(
-            prompt_template=prompt_template,
-            query=query,
-            prompt_messages=prompt_messages
-        )
+        prompt_messages = self._init_system_message(prompt_template, prompt_messages)
+        prompt_messages = self._organize_user_query(query, prompt_messages)
 
         # convert tools into ModelRuntime Tool format
-        prompt_messages_tools: list[PromptMessageTool] = []
-        tool_instances = {}
-        for tool in self.app_orchestration_config.agent.tools if self.app_orchestration_config.agent else []:
-            try:
-                prompt_tool, tool_entity = self._convert_tool_to_prompt_message_tool(tool)
-            except Exception:
-                # api tool may be deleted
-                continue
-            # save tool entity
-            tool_instances[tool.tool_name] = tool_entity
-            # save prompt tool
-            prompt_messages_tools.append(prompt_tool)
-
-        # convert dataset tools into ModelRuntime Tool format
-        for dataset_tool in self.dataset_tools:
-            prompt_tool = self._convert_dataset_retriever_tool_to_prompt_message_tool(dataset_tool)
-            # save prompt tool
-            prompt_messages_tools.append(prompt_tool)
-            # save tool entity
-            tool_instances[dataset_tool.identity.name] = dataset_tool
+        tool_instances, prompt_messages_tools = self._init_prompt_tools()
 
         iteration_step = 1
-        max_iteration_steps = min(app_orchestration_config.agent.max_iteration, 5) + 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1
 
         # continue to run until there is not any tool call
         function_call_state = True
-        agent_thoughts: list[MessageAgentThought] = []
         llm_usage = {
             'usage': None
         }
@@ -110,9 +85,9 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
             # invoke model
             chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = model_instance.invoke_llm(
                 prompt_messages=prompt_messages,
-                model_parameters=app_orchestration_config.model_config.parameters,
+                model_parameters=app_generate_entity.model_config.parameters,
                 tools=prompt_messages_tools,
-                stop=app_orchestration_config.model_config.stop,
+                stop=app_generate_entity.model_config.stop,
                 stream=self.stream_tool_call,
                 user=self.user_id,
                 callbacks=[],
@@ -133,7 +108,9 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                 is_first_chunk = True
                 for chunk in chunks:
                     if is_first_chunk:
-                        self.queue_manager.publish_agent_thought(agent_thought, PublishFrom.APPLICATION_MANAGER)
+                        self.queue_manager.publish(QueueAgentThoughtEvent(
+                            agent_thought_id=agent_thought.id
+                        ), PublishFrom.APPLICATION_MANAGER)
                         is_first_chunk = False
                     # check if there is any tool call
                     if self.check_tool_calls(chunk):
@@ -193,7 +170,9 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                 if not result.message.content:
                     result.message.content = ''
 
-                self.queue_manager.publish_agent_thought(agent_thought, PublishFrom.APPLICATION_MANAGER)
+                self.queue_manager.publish(QueueAgentThoughtEvent(
+                    agent_thought_id=agent_thought.id
+                ), PublishFrom.APPLICATION_MANAGER)
                 
                 yield LLMResultChunk(
                     model=model_instance.model,
@@ -206,19 +185,25 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                     )
                 )
 
+            assistant_message = AssistantPromptMessage(
+                content='',
+                tool_calls=[]
+            )
             if tool_calls:
-                prompt_messages.append(AssistantPromptMessage(
-                    content='',
-                    name='',
-                    tool_calls=[AssistantPromptMessage.ToolCall(
+                assistant_message.tool_calls=[
+                    AssistantPromptMessage.ToolCall(
                         id=tool_call[0],
                         type='function',
                         function=AssistantPromptMessage.ToolCall.ToolCallFunction(
                             name=tool_call[1],
                             arguments=json.dumps(tool_call[2], ensure_ascii=False)
                         )
-                    ) for tool_call in tool_calls]
-                ))
+                    ) for tool_call in tool_calls
+                ]
+            else:
+                assistant_message.content = response
+            
+            prompt_messages.append(assistant_message)
 
             # save thought
             self.save_agent_thought(
@@ -226,22 +211,18 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                 tool_name=tool_call_names,
                 tool_input=tool_call_inputs,
                 thought=response,
+                tool_invoke_meta=None,
                 observation=None,
                 answer=response,
                 messages_ids=[],
                 llm_usage=current_llm_usage
             )
-
-            self.queue_manager.publish_agent_thought(agent_thought, PublishFrom.APPLICATION_MANAGER)
+            self.queue_manager.publish(QueueAgentThoughtEvent(
+                agent_thought_id=agent_thought.id
+            ), PublishFrom.APPLICATION_MANAGER)
             
             final_answer += response + '\n'
 
-            # update prompt messages
-            if response.strip():
-                prompt_messages.append(AssistantPromptMessage(
-                    content=response,
-                ))
-            
             # call tools
             tool_responses = []
             for tool_call_id, tool_call_name, tool_call_args in tool_calls:
@@ -250,68 +231,41 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                     tool_response = {
                         "tool_call_id": tool_call_id,
                         "tool_call_name": tool_call_name,
-                        "tool_response": f"there is not a tool named {tool_call_name}"
+                        "tool_response": f"there is not a tool named {tool_call_name}",
+                        "meta": ToolInvokeMeta.error_instance(f"there is not a tool named {tool_call_name}").to_dict()
                     }
-                    tool_responses.append(tool_response)
                 else:
                     # invoke tool
-                    error_response = None
-                    try:
-                        tool_invoke_message = tool_instance.invoke(
-                            user_id=self.user_id, 
-                            tool_parameters=tool_call_args, 
-                        )
-                        # transform tool invoke message to get LLM friendly message
-                        tool_invoke_message = self.transform_tool_invoke_messages(tool_invoke_message)
-                        # extract binary data from tool invoke message
-                        binary_files = self.extract_tool_response_binary(tool_invoke_message)
-                        # create message file
-                        message_files = self.create_message_files(binary_files)
-                        # publish files
-                        for message_file, save_as in message_files:
-                            if save_as:
-                                self.variables_pool.set_file(tool_name=tool_call_name, value=message_file.id, name=save_as)
+                    tool_invoke_response, message_files, tool_invoke_meta = ToolEngine.agent_invoke(
+                        tool=tool_instance,
+                        tool_parameters=tool_call_args,
+                        user_id=self.user_id,
+                        tenant_id=self.tenant_id,
+                        message=self.message,
+                        invoke_from=self.application_generate_entity.invoke_from,
+                        agent_tool_callback=self.agent_callback,
+                    )
+                    # publish files
+                    for message_file, save_as in message_files:
+                        if save_as:
+                            self.variables_pool.set_file(tool_name=tool_call_name, value=message_file.id, name=save_as)
 
-                            # publish message file
-                            self.queue_manager.publish_message_file(message_file, PublishFrom.APPLICATION_MANAGER)
-                            # add message file ids
-                            message_file_ids.append(message_file.id)
-                            
-                    except ToolProviderCredentialValidationError as e:
-                        error_response = "Please check your tool provider credentials"
-                    except (
-                        ToolNotFoundError, ToolNotSupportedError, ToolProviderNotFoundError
-                    ) as e:
-                        error_response = f"there is not a tool named {tool_call_name}"
-                    except (
-                        ToolParameterValidationError
-                    ) as e:
-                        error_response = f"tool parameters validation error: {e}, please check your tool parameters"
-                    except ToolInvokeError as e:
-                        error_response = f"tool invoke error: {e}"
-                    except Exception as e:
-                        error_response = f"unknown error: {e}"
-
-                    if error_response:
-                        observation = error_response
-                        tool_response = {
-                            "tool_call_id": tool_call_id,
-                            "tool_call_name": tool_call_name,
-                            "tool_response": error_response
-                        }
-                        tool_responses.append(tool_response)
-                    else:
-                        observation = self._convert_tool_response_to_str(tool_invoke_message)
-                        tool_response = {
-                            "tool_call_id": tool_call_id,
-                            "tool_call_name": tool_call_name,
-                            "tool_response": observation
-                        }
-                        tool_responses.append(tool_response)
-
-                prompt_messages = self.organize_prompt_messages(
-                    prompt_template=prompt_template,
-                    query=None,
+                        # publish message file
+                        self.queue_manager.publish(QueueMessageFileEvent(
+                            message_file_id=message_file.id
+                        ), PublishFrom.APPLICATION_MANAGER)
+                        # add message file ids
+                        message_file_ids.append(message_file.id)
+                    
+                    tool_response = {
+                        "tool_call_id": tool_call_id,
+                        "tool_call_name": tool_call_name,
+                        "tool_response": tool_invoke_response,
+                        "meta": tool_invoke_meta.to_dict()
+                    }
+                
+                tool_responses.append(tool_response)
+                prompt_messages = self._organize_assistant_message(
                     tool_call_id=tool_call_id,
                     tool_call_name=tool_call_name,
                     tool_response=tool_response['tool_response'],
@@ -325,11 +279,20 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
                     tool_name=None,
                     tool_input=None,
                     thought=None, 
-                    observation=tool_response['tool_response'], 
+                    tool_invoke_meta={
+                        tool_response['tool_call_name']: tool_response['meta'] 
+                        for tool_response in tool_responses
+                    },
+                    observation={
+                        tool_response['tool_call_name']: tool_response['tool_response'] 
+                        for tool_response in tool_responses
+                    },
                     answer=None,
                     messages_ids=message_file_ids
                 )
-                self.queue_manager.publish_agent_thought(agent_thought, PublishFrom.APPLICATION_MANAGER)
+                self.queue_manager.publish(QueueAgentThoughtEvent(
+                    agent_thought_id=agent_thought.id
+                ), PublishFrom.APPLICATION_MANAGER)
 
             # update prompt tool
             for prompt_tool in prompt_messages_tools:
@@ -337,17 +300,19 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
 
             iteration_step += 1
 
+            prompt_messages = self._clear_user_prompt_image_messages(prompt_messages)
+
         self.update_db_variables(self.variables_pool, self.db_variables_pool)
         # publish end event
-        self.queue_manager.publish_message_end(LLMResult(
+        self.queue_manager.publish(QueueMessageEndEvent(llm_result=LLMResult(
             model=model_instance.model,
             prompt_messages=prompt_messages,
             message=AssistantPromptMessage(
-                content=final_answer,
+                content=final_answer
             ),
             usage=llm_usage['usage'] if llm_usage['usage'] else LLMUsage.empty_usage(),
             system_fingerprint=''
-        ), PublishFrom.APPLICATION_MANAGER)
+        )), PublishFrom.APPLICATION_MANAGER)
 
     def check_tool_calls(self, llm_result_chunk: LLMResultChunk) -> bool:
         """
@@ -399,29 +364,68 @@ class AssistantFunctionCallApplicationRunner(BaseAssistantApplicationRunner):
 
         return tool_calls
 
-    def organize_prompt_messages(self, prompt_template: str,
-                                 query: str = None, 
-                                 tool_call_id: str = None, tool_call_name: str = None, tool_response: str = None,
-                                 prompt_messages: list[PromptMessage] = None
-                                 ) -> list[PromptMessage]:
+    def _init_system_message(self, prompt_template: str, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
         """
-        Organize prompt messages
+        Initialize system message
         """
-        
-        if not prompt_messages:
-            prompt_messages = [
+        if not prompt_messages and prompt_template:
+            return [
                 SystemPromptMessage(content=prompt_template),
-                UserPromptMessage(content=query),
             ]
+        
+        if prompt_messages and not isinstance(prompt_messages[0], SystemPromptMessage) and prompt_template:
+            prompt_messages.insert(0, SystemPromptMessage(content=prompt_template))
+
+        return prompt_messages
+
+    def _organize_user_query(self, query,  prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+        """
+        Organize user query
+        """
+        if self.files:
+            prompt_message_contents = [TextPromptMessageContent(data=query)]
+            for file_obj in self.files:
+                prompt_message_contents.append(file_obj.prompt_message_content)
+
+            prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
         else:
-            if tool_response:
-                prompt_messages = prompt_messages.copy()
-                prompt_messages.append(
-                    ToolPromptMessage(
-                        content=tool_response,
-                        tool_call_id=tool_call_id,
-                        name=tool_call_name,
-                    )
+            prompt_messages.append(UserPromptMessage(content=query))
+
+        return prompt_messages
+    
+    def _organize_assistant_message(self, tool_call_id: str = None, tool_call_name: str = None, tool_response: str = None, 
+                                    prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+        """
+        Organize assistant message
+        """
+        prompt_messages = deepcopy(prompt_messages)
+
+        if tool_response is not None:
+            prompt_messages.append(
+                ToolPromptMessage(
+                    content=tool_response,
+                    tool_call_id=tool_call_id,
+                    name=tool_call_name,
                 )
+            )
+
+        return prompt_messages
+    
+    def _clear_user_prompt_image_messages(self, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
+        """
+        As for now, gpt supports both fc and vision at the first iteration.
+        We need to remove the image messages from the prompt messages at the first iteration.
+        """
+        prompt_messages = deepcopy(prompt_messages)
+
+        for prompt_message in prompt_messages:
+            if isinstance(prompt_message, UserPromptMessage):
+                if isinstance(prompt_message.content, list):
+                    prompt_message.content = '\n'.join([
+                        content.data if content.type == PromptMessageContentType.TEXT else 
+                        '[image]' if content.type == PromptMessageContentType.IMAGE else
+                        '[file]' 
+                        for content in prompt_message.content 
+                    ])
 
         return prompt_messages

api/core/agent/output_parser/cot_output_parser.py

@@ -0,0 +1,183 @@
+import json
+import re
+from collections.abc import Generator
+from typing import Union
+
+from core.agent.entities import AgentScratchpadUnit
+from core.model_runtime.entities.llm_entities import LLMResultChunk
+
+
+class CotAgentOutputParser:
+    @classmethod
+    def handle_react_stream_output(cls, llm_response: Generator[LLMResultChunk, None, None]) -> \
+        Generator[Union[str, AgentScratchpadUnit.Action], None, None]:
+        def parse_action(json_str):
+            try:
+                action = json.loads(json_str)
+                action_name = None
+                action_input = None
+
+                for key, value in action.items():
+                    if 'input' in key.lower():
+                        action_input = value
+                    else:
+                        action_name = value
+
+                if action_name is not None and action_input is not None:
+                    return AgentScratchpadUnit.Action(
+                        action_name=action_name,
+                        action_input=action_input,
+                    )
+                else:
+                    return json_str or ''
+            except:
+                return json_str or ''
+            
+        def extra_json_from_code_block(code_block) -> Generator[Union[dict, str], None, None]:
+            code_blocks = re.findall(r'```(.*?)```', code_block, re.DOTALL)
+            if not code_blocks:
+                return
+            for block in code_blocks:
+                json_text = re.sub(r'^[a-zA-Z]+\n', '', block.strip(), flags=re.MULTILINE)
+                yield parse_action(json_text)
+            
+        code_block_cache = ''
+        code_block_delimiter_count = 0
+        in_code_block = False
+        json_cache = ''
+        json_quote_count = 0
+        in_json = False
+        got_json = False
+
+        action_cache = ''
+        action_str = 'action:'
+        action_idx = 0
+
+        thought_cache = ''
+        thought_str = 'thought:'
+        thought_idx = 0
+
+        for response in llm_response:
+            response = response.delta.message.content
+            if not isinstance(response, str):
+                continue
+
+            # stream
+            index = 0
+            while index < len(response):
+                steps = 1
+                delta = response[index:index+steps]
+                last_character = response[index-1] if index > 0 else ''
+
+                if delta == '`':
+                    code_block_cache += delta
+                    code_block_delimiter_count += 1
+                else:
+                    if not in_code_block:
+                        if code_block_delimiter_count > 0:
+                            yield code_block_cache
+                        code_block_cache = ''
+                    else:
+                        code_block_cache += delta
+                    code_block_delimiter_count = 0
+
+                if not in_code_block and not in_json:
+                    if delta.lower() == action_str[action_idx] and action_idx == 0:
+                        if last_character not in ['\n', ' ', '']:
+                            index += steps
+                            yield delta
+                            continue
+
+                        action_cache += delta
+                        action_idx += 1
+                        if action_idx == len(action_str):
+                            action_cache = ''
+                            action_idx = 0
+                        index += steps
+                        continue
+                    elif delta.lower() == action_str[action_idx] and action_idx > 0:
+                        action_cache += delta
+                        action_idx += 1
+                        if action_idx == len(action_str):
+                            action_cache = ''
+                            action_idx = 0
+                        index += steps
+                        continue
+                    else:
+                        if action_cache:
+                            yield action_cache
+                            action_cache = ''
+                            action_idx = 0
+                    
+                    if delta.lower() == thought_str[thought_idx] and thought_idx == 0:
+                        if last_character not in ['\n', ' ', '']:
+                            index += steps
+                            yield delta
+                            continue
+
+                        thought_cache += delta
+                        thought_idx += 1
+                        if thought_idx == len(thought_str):
+                            thought_cache = ''
+                            thought_idx = 0
+                        index += steps
+                        continue
+                    elif delta.lower() == thought_str[thought_idx] and thought_idx > 0:
+                        thought_cache += delta
+                        thought_idx += 1
+                        if thought_idx == len(thought_str):
+                            thought_cache = ''
+                            thought_idx = 0
+                        index += steps
+                        continue
+                    else:
+                        if thought_cache:
+                            yield thought_cache
+                            thought_cache = ''
+                            thought_idx = 0
+
+                if code_block_delimiter_count == 3:
+                    if in_code_block:
+                        yield from extra_json_from_code_block(code_block_cache)
+                        code_block_cache = ''
+                        
+                    in_code_block = not in_code_block
+                    code_block_delimiter_count = 0
+
+                if not in_code_block:
+                    # handle single json
+                    if delta == '{':
+                        json_quote_count += 1
+                        in_json = True
+                        json_cache += delta
+                    elif delta == '}':
+                        json_cache += delta
+                        if json_quote_count > 0:
+                            json_quote_count -= 1
+                            if json_quote_count == 0:
+                                in_json = False
+                                got_json = True
+                                index += steps
+                                continue
+                    else:
+                        if in_json:
+                            json_cache += delta
+
+                    if got_json:
+                        got_json = False
+                        yield parse_action(json_cache)
+                        json_cache = ''
+                        json_quote_count = 0
+                        in_json = False
+                    
+                if not in_code_block and not in_json:
+                    yield delta.replace('`', '')
+
+                index += steps
+
+        if code_block_cache:
+            yield code_block_cache
+
+        if json_cache:
+            yield parse_action(json_cache)
+

api/core/app/app_config/base_app_config_manager.py

@@ -0,0 +1,76 @@
+from typing import Optional, Union
+
+from core.app.app_config.entities import AppAdditionalFeatures, EasyUIBasedAppModelConfigFrom
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.more_like_this.manager import MoreLikeThisConfigManager
+from core.app.app_config.features.opening_statement.manager import OpeningStatementConfigManager
+from core.app.app_config.features.retrieval_resource.manager import RetrievalResourceConfigManager
+from core.app.app_config.features.speech_to_text.manager import SpeechToTextConfigManager
+from core.app.app_config.features.suggested_questions_after_answer.manager import (
+    SuggestedQuestionsAfterAnswerConfigManager,
+)
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from models.model import AppMode, AppModelConfig
+
+
+class BaseAppConfigManager:
+
+    @classmethod
+    def convert_to_config_dict(cls, config_from: EasyUIBasedAppModelConfigFrom,
+                               app_model_config: Union[AppModelConfig, dict],
+                               config_dict: Optional[dict] = None) -> dict:
+        """
+        Convert app model config to config dict
+        :param config_from: app model config from
+        :param app_model_config: app model config
+        :param config_dict: app model config dict
+        :return:
+        """
+        if config_from != EasyUIBasedAppModelConfigFrom.ARGS:
+            app_model_config_dict = app_model_config.to_dict()
+            config_dict = app_model_config_dict.copy()
+
+        return config_dict
+
+    @classmethod
+    def convert_features(cls, config_dict: dict, app_mode: AppMode) -> AppAdditionalFeatures:
+        """
+        Convert app config to app model config
+
+        :param config_dict: app config
+        :param app_mode: app mode
+        """
+        config_dict = config_dict.copy()
+
+        additional_features = AppAdditionalFeatures()
+        additional_features.show_retrieve_source = RetrievalResourceConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.file_upload = FileUploadConfigManager.convert(
+            config=config_dict,
+            is_vision=app_mode in [AppMode.CHAT, AppMode.COMPLETION, AppMode.AGENT_CHAT]
+        )
+
+        additional_features.opening_statement, additional_features.suggested_questions = \
+            OpeningStatementConfigManager.convert(
+                config=config_dict
+            )
+
+        additional_features.suggested_questions_after_answer = SuggestedQuestionsAfterAnswerConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.more_like_this = MoreLikeThisConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.speech_to_text = SpeechToTextConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.text_to_speech = TextToSpeechConfigManager.convert(
+            config=config_dict
+        )
+
+        return additional_features

api/core/app/app_config/common/sensitive_word_avoidance/manager.py

@@ -0,0 +1,50 @@
+from typing import Optional
+
+from core.app.app_config.entities import SensitiveWordAvoidanceEntity
+from core.moderation.factory import ModerationFactory
+
+
+class SensitiveWordAvoidanceConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[SensitiveWordAvoidanceEntity]:
+        sensitive_word_avoidance_dict = config.get('sensitive_word_avoidance')
+        if not sensitive_word_avoidance_dict:
+            return None
+
+        if 'enabled' in sensitive_word_avoidance_dict and sensitive_word_avoidance_dict['enabled']:
+            return SensitiveWordAvoidanceEntity(
+                type=sensitive_word_avoidance_dict.get('type'),
+                config=sensitive_word_avoidance_dict.get('config'),
+            )
+        else:
+            return None
+
+    @classmethod
+    def validate_and_set_defaults(cls, tenant_id, config: dict, only_structure_validate: bool = False) \
+            -> tuple[dict, list[str]]:
+        if not config.get("sensitive_word_avoidance"):
+            config["sensitive_word_avoidance"] = {
+                "enabled": False
+            }
+
+        if not isinstance(config["sensitive_word_avoidance"], dict):
+            raise ValueError("sensitive_word_avoidance must be of dict type")
+
+        if "enabled" not in config["sensitive_word_avoidance"] or not config["sensitive_word_avoidance"]["enabled"]:
+            config["sensitive_word_avoidance"]["enabled"] = False
+
+        if config["sensitive_word_avoidance"]["enabled"]:
+            if not config["sensitive_word_avoidance"].get("type"):
+                raise ValueError("sensitive_word_avoidance.type is required")
+
+            if not only_structure_validate:
+                typ = config["sensitive_word_avoidance"]["type"]
+                sensitive_word_avoidance_config = config["sensitive_word_avoidance"]["config"]
+
+                ModerationFactory.validate_config(
+                    name=typ,
+                    tenant_id=tenant_id,
+                    config=sensitive_word_avoidance_config
+                )
+
+        return config, ["sensitive_word_avoidance"]

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

@@ -0,0 +1,78 @@
+from typing import Optional
+
+from core.agent.entities import AgentEntity, AgentPromptEntity, AgentToolEntity
+from core.tools.prompt.template import REACT_PROMPT_TEMPLATES
+
+
+class AgentConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[AgentEntity]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        if 'agent_mode' in config and config['agent_mode'] \
+                and 'enabled' in config['agent_mode']:
+
+            agent_dict = config.get('agent_mode', {})
+            agent_strategy = agent_dict.get('strategy', 'cot')
+
+            if agent_strategy == 'function_call':
+                strategy = AgentEntity.Strategy.FUNCTION_CALLING
+            elif agent_strategy == 'cot' or agent_strategy == 'react':
+                strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
+            else:
+                # old configs, try to detect default strategy
+                if config['model']['provider'] == 'openai':
+                    strategy = AgentEntity.Strategy.FUNCTION_CALLING
+                else:
+                    strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
+
+            agent_tools = []
+            for tool in agent_dict.get('tools', []):
+                keys = tool.keys()
+                if len(keys) >= 4:
+                    if "enabled" not in tool or not tool["enabled"]:
+                        continue
+
+                    agent_tool_properties = {
+                        'provider_type': tool['provider_type'],
+                        'provider_id': tool['provider_id'],
+                        'tool_name': tool['tool_name'],
+                        'tool_parameters': tool['tool_parameters'] if 'tool_parameters' in tool else {}
+                    }
+
+                    agent_tools.append(AgentToolEntity(**agent_tool_properties))
+
+            if 'strategy' in config['agent_mode'] and \
+                    config['agent_mode']['strategy'] not in ['react_router', 'router']:
+                agent_prompt = agent_dict.get('prompt', None) or {}
+                # check model mode
+                model_mode = config.get('model', {}).get('mode', 'completion')
+                if model_mode == 'completion':
+                    agent_prompt_entity = AgentPromptEntity(
+                        first_prompt=agent_prompt.get('first_prompt',
+                                                      REACT_PROMPT_TEMPLATES['english']['completion']['prompt']),
+                        next_iteration=agent_prompt.get('next_iteration',
+                                                        REACT_PROMPT_TEMPLATES['english']['completion'][
+                                                            'agent_scratchpad']),
+                    )
+                else:
+                    agent_prompt_entity = AgentPromptEntity(
+                        first_prompt=agent_prompt.get('first_prompt',
+                                                      REACT_PROMPT_TEMPLATES['english']['chat']['prompt']),
+                        next_iteration=agent_prompt.get('next_iteration',
+                                                        REACT_PROMPT_TEMPLATES['english']['chat']['agent_scratchpad']),
+                    )
+
+                return AgentEntity(
+                    provider=config['model']['provider'],
+                    model=config['model']['name'],
+                    strategy=strategy,
+                    prompt=agent_prompt_entity,
+                    tools=agent_tools,
+                    max_iteration=agent_dict.get('max_iteration', 5)
+                )
+
+        return None

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

@@ -0,0 +1,224 @@
+from typing import Optional
+
+from core.app.app_config.entities import DatasetEntity, DatasetRetrieveConfigEntity
+from core.entities.agent_entities import PlanningStrategy
+from models.model import AppMode
+from services.dataset_service import DatasetService
+
+
+class DatasetConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[DatasetEntity]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        dataset_ids = []
+        if 'datasets' in config.get('dataset_configs', {}):
+            datasets = config.get('dataset_configs', {}).get('datasets', {
+                'strategy': 'router',
+                'datasets': []
+            })
+
+            for dataset in datasets.get('datasets', []):
+                keys = list(dataset.keys())
+                if len(keys) == 0 or keys[0] != 'dataset':
+                    continue
+
+                dataset = dataset['dataset']
+
+                if 'enabled' not in dataset or not dataset['enabled']:
+                    continue
+
+                dataset_id = dataset.get('id', None)
+                if dataset_id:
+                    dataset_ids.append(dataset_id)
+
+        if 'agent_mode' in config and config['agent_mode'] \
+                and 'enabled' in config['agent_mode'] \
+                and config['agent_mode']['enabled']:
+
+            agent_dict = config.get('agent_mode', {})
+
+            for tool in agent_dict.get('tools', []):
+                keys = tool.keys()
+                if len(keys) == 1:
+                    # old standard
+                    key = list(tool.keys())[0]
+
+                    if key != 'dataset':
+                        continue
+
+                    tool_item = tool[key]
+
+                    if "enabled" not in tool_item or not tool_item["enabled"]:
+                        continue
+
+                    dataset_id = tool_item['id']
+                    dataset_ids.append(dataset_id)
+
+        if len(dataset_ids) == 0:
+            return None
+
+        # dataset configs
+        dataset_configs = config.get('dataset_configs', {'retrieval_model': 'single'})
+        query_variable = config.get('dataset_query_variable')
+
+        if dataset_configs['retrieval_model'] == 'single':
+            return DatasetEntity(
+                dataset_ids=dataset_ids,
+                retrieve_config=DatasetRetrieveConfigEntity(
+                    query_variable=query_variable,
+                    retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
+                        dataset_configs['retrieval_model']
+                    )
+                )
+            )
+        else:
+            return DatasetEntity(
+                dataset_ids=dataset_ids,
+                retrieve_config=DatasetRetrieveConfigEntity(
+                    query_variable=query_variable,
+                    retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
+                        dataset_configs['retrieval_model']
+                    ),
+                    top_k=dataset_configs.get('top_k'),
+                    score_threshold=dataset_configs.get('score_threshold'),
+                    reranking_model=dataset_configs.get('reranking_model')
+                )
+            )
+
+    @classmethod
+    def validate_and_set_defaults(cls, tenant_id: str, app_mode: AppMode, config: dict) -> tuple[dict, list[str]]:
+        """
+        Validate and set defaults for dataset feature
+
+        :param tenant_id: tenant ID
+        :param app_mode: app mode
+        :param config: app model config args
+        """
+        # Extract dataset config for legacy compatibility
+        config = cls.extract_dataset_config_for_legacy_compatibility(tenant_id, app_mode, config)
+
+        # dataset_configs
+        if not config.get("dataset_configs"):
+            config["dataset_configs"] = {'retrieval_model': 'single'}
+
+        if not config["dataset_configs"].get("datasets"):
+            config["dataset_configs"]["datasets"] = {
+                "strategy": "router",
+                "datasets": []
+            }
+
+        if not isinstance(config["dataset_configs"], dict):
+            raise ValueError("dataset_configs must be of object type")
+
+        if config["dataset_configs"]['retrieval_model'] == 'multiple':
+            if not config["dataset_configs"]['reranking_model']:
+                raise ValueError("reranking_model has not been set")
+            if not isinstance(config["dataset_configs"]['reranking_model'], dict):
+                raise ValueError("reranking_model must be of object type")
+
+        if not isinstance(config["dataset_configs"], dict):
+            raise ValueError("dataset_configs must be of object type")
+
+        need_manual_query_datasets = (config.get("dataset_configs")
+                                      and config["dataset_configs"].get("datasets", {}).get("datasets"))
+
+        if need_manual_query_datasets and app_mode == AppMode.COMPLETION:
+            # Only check when mode is completion
+            dataset_query_variable = config.get("dataset_query_variable")
+
+            if not dataset_query_variable:
+                raise ValueError("Dataset query variable is required when dataset is exist")
+
+        return config, ["agent_mode", "dataset_configs", "dataset_query_variable"]
+
+    @classmethod
+    def extract_dataset_config_for_legacy_compatibility(cls, tenant_id: str, app_mode: AppMode, config: dict) -> dict:
+        """
+        Extract dataset config for legacy compatibility
+
+        :param tenant_id: tenant ID
+        :param app_mode: app mode
+        :param config: app model config args
+        """
+        # Extract dataset config for legacy compatibility
+        if not config.get("agent_mode"):
+            config["agent_mode"] = {
+                "enabled": False,
+                "tools": []
+            }
+
+        if not isinstance(config["agent_mode"], dict):
+            raise ValueError("agent_mode must be of object type")
+
+        # enabled
+        if "enabled" not in config["agent_mode"] or not config["agent_mode"]["enabled"]:
+            config["agent_mode"]["enabled"] = False
+
+        if not isinstance(config["agent_mode"]["enabled"], bool):
+            raise ValueError("enabled in agent_mode must be of boolean type")
+
+        # tools
+        if not config["agent_mode"].get("tools"):
+            config["agent_mode"]["tools"] = []
+
+        if not isinstance(config["agent_mode"]["tools"], list):
+            raise ValueError("tools in agent_mode must be a list of objects")
+
+        # strategy
+        if not config["agent_mode"].get("strategy"):
+            config["agent_mode"]["strategy"] = PlanningStrategy.ROUTER.value
+
+        has_datasets = False
+        if config["agent_mode"]["strategy"] in [PlanningStrategy.ROUTER.value, PlanningStrategy.REACT_ROUTER.value]:
+            for tool in config["agent_mode"]["tools"]:
+                key = list(tool.keys())[0]
+                if key == "dataset":
+                    # old style, use tool name as key
+                    tool_item = tool[key]
+
+                    if "enabled" not in tool_item or not tool_item["enabled"]:
+                        tool_item["enabled"] = False
+
+                    if not isinstance(tool_item["enabled"], bool):
+                        raise ValueError("enabled in agent_mode.tools must be of boolean type")
+
+                    if 'id' not in tool_item:
+                        raise ValueError("id is required in dataset")
+
+                    try:
+                        uuid.UUID(tool_item["id"])
+                    except ValueError:
+                        raise ValueError("id in dataset must be of UUID type")
+
+                    if not cls.is_dataset_exists(tenant_id, tool_item["id"]):
+                        raise ValueError("Dataset ID does not exist, please check your permission.")
+
+                    has_datasets = True
+
+        need_manual_query_datasets = has_datasets and config["agent_mode"]["enabled"]
+
+        if need_manual_query_datasets and app_mode == AppMode.COMPLETION:
+            # Only check when mode is completion
+            dataset_query_variable = config.get("dataset_query_variable")
+
+            if not dataset_query_variable:
+                raise ValueError("Dataset query variable is required when dataset is exist")
+
+        return config
+
+    @classmethod
+    def is_dataset_exists(cls, tenant_id: str, dataset_id: str) -> bool:
+        # verify if the dataset ID exists
+        dataset = DatasetService.get_dataset(dataset_id)
+
+        if not dataset:
+            return False
+
+        if dataset.tenant_id != tenant_id:
+            return False
+
+        return True

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

@@ -0,0 +1,103 @@
+from typing import cast
+
+from core.app.app_config.entities import EasyUIBasedAppConfig
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
+from core.entities.model_entities import ModelStatus
+from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.provider_manager import ProviderManager
+
+
+class ModelConfigConverter:
+    @classmethod
+    def convert(cls, app_config: EasyUIBasedAppConfig,
+                skip_check: bool = False) \
+            -> ModelConfigWithCredentialsEntity:
+        """
+        Convert app model config dict to entity.
+        :param app_config: app config
+        :param skip_check: skip check
+        :raises ProviderTokenNotInitError: provider token not init error
+        :return: app orchestration config entity
+        """
+        model_config = app_config.model
+
+        provider_manager = ProviderManager()
+        provider_model_bundle = provider_manager.get_provider_model_bundle(
+            tenant_id=app_config.tenant_id,
+            provider=model_config.provider,
+            model_type=ModelType.LLM
+        )
+
+        provider_name = provider_model_bundle.configuration.provider.provider
+        model_name = model_config.model
+
+        model_type_instance = provider_model_bundle.model_type_instance
+        model_type_instance = cast(LargeLanguageModel, model_type_instance)
+
+        # check model credentials
+        model_credentials = provider_model_bundle.configuration.get_current_credentials(
+            model_type=ModelType.LLM,
+            model=model_config.model
+        )
+
+        if model_credentials is None:
+            if not skip_check:
+                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
+            else:
+                model_credentials = {}
+
+        if not skip_check:
+            # check model
+            provider_model = provider_model_bundle.configuration.get_provider_model(
+                model=model_config.model,
+                model_type=ModelType.LLM
+            )
+
+            if provider_model is None:
+                model_name = model_config.model
+                raise ValueError(f"Model {model_name} not exist.")
+
+            if provider_model.status == ModelStatus.NO_CONFIGURE:
+                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
+            elif provider_model.status == ModelStatus.NO_PERMISSION:
+                raise ModelCurrentlyNotSupportError(f"Dify Hosted OpenAI {model_name} currently not support.")
+            elif provider_model.status == ModelStatus.QUOTA_EXCEEDED:
+                raise QuotaExceededError(f"Model provider {provider_name} quota exceeded.")
+
+        # model config
+        completion_params = model_config.parameters
+        stop = []
+        if 'stop' in completion_params:
+            stop = completion_params['stop']
+            del completion_params['stop']
+
+        # get model mode
+        model_mode = model_config.mode
+        if not model_mode:
+            mode_enum = model_type_instance.get_model_mode(
+                model=model_config.model,
+                credentials=model_credentials
+            )
+
+            model_mode = mode_enum.value
+
+        model_schema = model_type_instance.get_model_schema(
+            model_config.model,
+            model_credentials
+        )
+
+        if not skip_check and not model_schema:
+            raise ValueError(f"Model {model_name} not exist.")
+
+        return ModelConfigWithCredentialsEntity(
+            provider=model_config.provider,
+            model=model_config.model,
+            model_schema=model_schema,
+            mode=model_mode,
+            provider_model_bundle=provider_model_bundle,
+            credentials=model_credentials,
+            parameters=completion_params,
+            stop=stop,
+        )