fix

1. Fix provider type select showing blank when editing: await
   loadRequesters() before loadProvider() to ensure options are
   populated before setting the selected value.

2. Split 'Add Model' into two separate entries: a '+ Add Model'
   button for manual add and a Radar icon button for scan. Each
   opens its own popover with only one layer of tabs (model type
   for manual, no tabs for scan since types are auto-detected).

3. Fix popover position: side='bottom' instead of 'left'.

4. Fix popover scroll: model type tabs stay fixed at top, content
   area scrolls independently when it overflows.

5. Scan mode now fetches all model types at once (no modelType
   filter), and routes each scanned model to the correct API
   based on its own type field.

.dockerignore

@@ -0,0 +1,8 @@
+.github
+.venv
+.vscode
+.data
+.temp
+web/.next
+web/node_modules
+web/.env

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,5 +1,5 @@
 name: 漏洞反馈
-description: 【供中文用户】报错或漏洞请使用这个模板创建，不使用此模板创建的异常、漏洞相关issue将被直接关闭。由于自己操作不当/不甚了解所用技术栈引起的网络连接问题恕无法解决，请勿提 issue。容器间网络连接问题，参考文档 https://docs.langbot.app/zh/workshop/network-details.html  
+description: 【供中文用户】报错或漏洞请使用这个模板创建，不使用此模板创建的异常、漏洞相关issue将被直接关闭。由于自己操作不当/不甚了解所用技术栈引起的网络连接问题恕无法解决，请勿提 issue。容器间网络连接问题，参考文档 https://link.langbot.app/zh/docs/network  
 title: "[Bug]: "
 labels: ["bug?"]
 body:
@@ -19,7 +19,7 @@ body:
   - type: textarea
     attributes:
       label: 复现步骤
-      description: 如何重现这个问题，越详细越好；提供越多信息，我们会越快解决问题。
+      description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果涉及 Dify、n8n、Langflow 等外部平台，请提供应用的导出文件（如 Dify 应用的 DSL），我们将更快回复您。**
     validations:
       required: false
   - type: textarea

.github/ISSUE_TEMPLATE/bug-report_en.yml

@@ -1,5 +1,5 @@
 name: Bug report
-description: Report bugs or vulnerabilities using this template. For container network connection issues, refer to the documentation https://docs.langbot.app/en/workshop/network-details.html
+description: Report bugs or vulnerabilities using this template. For container network connection issues, refer to the documentation https://link.langbot.app/en/docs/network
 title: "[Bug]: "
 labels: ["bug?"]
 body:

.github/pull_request_template.md

@@ -2,6 +2,17 @@
 
 > 请在此部分填写你实现/解决/优化的内容:  
 > Summary of what you implemented/solved/optimized:
+> 
+
+### 更改前后对比截图 / Screenshots
+
+> 请在此部分粘贴更改前后对比截图（可以是界面截图、控制台输出、对话截图等）:  
+> Please paste the screenshots of changes before and after here (can be interface screenshots, console output, conversation screenshots, etc.):
+> 
+> 修改前 / Before:
+> 
+> 修改后 / After:
+> 
 
 ## 检查清单 / Checklist
 
@@ -9,7 +20,7 @@
 
 *请在方括号间写`x`以打勾 / Please tick the box with `x`*
 
-- [ ] 阅读仓库[贡献指引](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)?
+- [ ] 阅读仓库[贡献指引](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)?
 - [ ] 与项目所有者沟通过了吗？ / Have you communicated with the project maintainer?
 - [ ] 我确定已自行测试所作的更改，确保功能符合预期。 / I have tested the changes and ensured they work as expected.
 

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

@@ -1,7 +1,5 @@
 name: Build Docker Image
 on:
-  #防止fork乱用action设置只能手动触发构建
-  workflow_dispatch:
   ## 发布release的时候会自动构建
   release:
     types: [published]
@@ -41,5 +39,9 @@ jobs:
         run: docker login --username=${{ secrets.DOCKER_USERNAME }} --password ${{ secrets.DOCKER_PASSWORD }}
       - name: Create Buildx
         run: docker buildx create --name mybuilder --use
-      - name: Build  # image name: rockchin/langbot:<VERSION>
+      - name: Build for Release # only relase, exlude pre-release
+        if: ${{ github.event.release.prerelease == false }}
         run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Pre-release # no update for latest tag
+        if: ${{ github.event.release.prerelease == true }}
+        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.github/workflows/build-release-artifacts.yaml

@@ -43,10 +43,10 @@ jobs:
         run: |
           cd /tmp/langbot_build_web/web
           npm install
-          npm run build
+          npx vite build
       - name: Package Output
         run: |
-          cp -r /tmp/langbot_build_web/web/out ./web
+          cp -r /tmp/langbot_build_web/web/dist ./web
       - name: Upload Artifact
         uses: actions/upload-artifact@v4
         with:

.github/workflows/check-i18n.yml

@@ -0,0 +1,25 @@
+name: Check i18n Keys
+
+on:
+  push:
+    branches:
+      - main
+      - master
+
+jobs:
+  check-i18n:
+    name: Check i18n Key Consistency
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '20'
+
+      - name: Check i18n keys against en-US reference
+        run: node web/scripts/check-i18n.mjs

.github/workflows/lint.yml

@@ -0,0 +1,60 @@
+name: Lint
+
+on:
+  push:
+    branches:
+      - main
+      - master
+      - dev
+  pull_request:
+    types: [opened, synchronize, reopened, ready_for_review]
+
+jobs:
+  ruff:
+    name: Ruff Lint & Format
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run ruff check
+        run: uv run ruff check src
+
+      - name: Run ruff format
+        run: uv run ruff format src --check
+
+  frontend:
+    name: Frontend Lint
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '25'
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Install dependencies
+        working-directory: web
+        run: pnpm install
+
+      - name: Run lint
+        working-directory: web
+        run: pnpm lint

.github/workflows/publish-to-pypi.yml

@@ -0,0 +1,46 @@
+name: Build and Publish to PyPI
+
+on:
+  workflow_dispatch:
+  release:
+    types: [published]
+
+jobs:
+  build-and-publish:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      id-token: write  # Required for trusted publishing to PyPI
+    
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          persist-credentials: false
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '22'
+
+      - name: Build frontend
+        run: |
+          cd web
+          npm install -g pnpm
+          pnpm install
+          pnpm build
+          mkdir -p ../src/langbot/web/dist
+          cp -r dist ../src/langbot/web/
+
+      - name: Install the latest version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "latest"
+
+      - name: Build package
+        run: |
+          uv build
+
+      - name: Publish to PyPI
+        run: |
+          uv publish --token ${{ secrets.PYPI_TOKEN }}

.github/workflows/run-tests.yml

@@ -0,0 +1,136 @@
+name: Unit Tests
+
+on:
+  pull_request:
+    types: [opened, ready_for_review, synchronize]
+    paths:
+      - 'src/langbot/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'uv.lock'
+      - 'run_tests.sh'
+      - 'scripts/test-*.sh'
+  push:
+    branches:
+      - master
+      - develop
+    paths:
+      - 'src/langbot/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'uv.lock'
+      - 'run_tests.sh'
+      - 'scripts/test-*.sh'
+
+jobs:
+  test:
+    name: Unit Tests
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.11', '3.12', '3.13']
+      fail-fast: false
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run unit + smoke tests
+        run: uv run pytest tests/unit_tests/ tests/smoke/ -q --tb=short
+
+      - name: Test Summary
+        if: always()
+        run: |
+          echo "## Unit Tests Results" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "Python Version: ${{ matrix.python-version }}" >> $GITHUB_STEP_SUMMARY
+          echo "Test Status: ${{ job.status }}" >> $GITHUB_STEP_SUMMARY
+
+  integration:
+    name: Fast Integration Tests
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run fast integration tests
+        run: uv run pytest tests/integration/ -m "not slow" -q --tb=short
+
+      - name: Integration Test Summary
+        if: always()
+        run: |
+          echo "## Integration Tests Results" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "Test Status: ${{ job.status }}" >> $GITHUB_STEP_SUMMARY
+
+  coverage:
+    name: Coverage Gate
+    runs-on: ubuntu-latest
+    needs: [test, integration]
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run coverage (unit + smoke)
+        run: |
+          uv run pytest tests/unit_tests/ tests/smoke/ \
+            --cov=langbot \
+            --cov-report=xml \
+            --cov-report=term-missing \
+            --cov-fail-under=18 \
+            -q --tb=short
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          files: ./coverage.xml
+          flags: unit-tests
+          name: coverage-report
+          fail_ci_if_error: false
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Coverage Summary
+        if: always()
+        run: |
+          echo "## Coverage Results" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "Threshold: 18%" >> $GITHUB_STEP_SUMMARY
+          echo "Status: ${{ job.status }}" >> $GITHUB_STEP_SUMMARY

.github/workflows/test-dev-image.yaml

@@ -0,0 +1,108 @@
+name: Test Dev Image
+
+on:
+  workflow_run:
+    workflows: ["Build Dev Image"]
+    types:
+      - completed
+    branches:
+      - master
+
+jobs:
+  test-dev-image:
+    runs-on: ubuntu-latest
+    # Only run if the build workflow succeeded
+    if: ${{ github.event.workflow_run.conclusion == 'success' }}
+    
+    permissions:
+      contents: read
+    
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Update Docker Compose to use master tag
+        working-directory: ./docker
+        run: |
+          # Replace 'latest' with 'master' tag for testing the dev image
+          sed -i 's/rockchin\/langbot:latest/rockchin\/langbot:master/g' docker-compose.yaml
+          echo "Updated docker-compose.yaml to use master tag:"
+          cat docker-compose.yaml
+
+      - name: Start Docker Compose
+        working-directory: ./docker
+        run: docker compose up -d
+
+      - name: Wait and Test API
+        run: |
+          # Function to test API endpoint
+          test_api() {
+            echo "Testing API endpoint..."
+            response=$(curl -s --connect-timeout 10 --max-time 30 -w "\n%{http_code}" http://localhost:5300/api/v1/system/info 2>&1)
+            curl_exit_code=$?
+            
+            if [ $curl_exit_code -ne 0 ]; then
+              echo "Curl failed with exit code: $curl_exit_code"
+              echo "Error: $response"
+              return 1
+            fi
+            
+            http_code=$(echo "$response" | tail -n 1)
+            response_body=$(echo "$response" | head -n -1)
+            
+            if [ "$http_code" = "200" ]; then
+              echo "API is healthy! Response code: $http_code"
+              echo "Response: $response_body"
+              return 0
+            else
+              echo "API returned non-200 response: $http_code"
+              echo "Response body: $response_body"
+              return 1
+            fi
+          }
+
+          # Wait 30 seconds before first attempt
+          echo "Waiting 30 seconds for services to start..."
+          sleep 30
+
+          # Try up to 3 times with 30-second intervals
+          max_attempts=3
+          attempt=1
+
+          while [ $attempt -le $max_attempts ]; do
+            echo "Attempt $attempt of $max_attempts"
+            
+            if test_api; then
+              echo "Success! API is responding correctly."
+              exit 0
+            fi
+            
+            if [ $attempt -lt $max_attempts ]; then
+              echo "Retrying in 30 seconds..."
+              sleep 30
+            fi
+            
+            attempt=$((attempt + 1))
+          done
+
+          # All attempts failed
+          echo "Failed to get healthy response after $max_attempts attempts"
+          exit 1
+
+      - name: Show Container Logs on Failure
+        if: failure()
+        working-directory: ./docker
+        run: |
+          echo "=== Docker Compose Status ==="
+          docker compose ps
+          echo ""
+          echo "=== LangBot Logs ==="
+          docker compose logs langbot
+          echo ""
+          echo "=== Plugin Runtime Logs ==="
+          docker compose logs langbot_plugin_runtime
+
+      - name: Cleanup
+        if: always()
+        working-directory: ./docker
+        run: docker compose down

.github/workflows/test-migrations.yml

@@ -0,0 +1,78 @@
+name: Test Migrations
+
+on:
+  push:
+    branches:
+      - main
+      - master
+      - dev
+    paths:
+      - 'src/langbot/pkg/persistence/**'
+      - 'src/langbot/pkg/entity/persistence/**'
+      - 'tests/integration/persistence/**'
+  pull_request:
+    types: [opened, synchronize, reopened, ready_for_review]
+    paths:
+      - 'src/langbot/pkg/persistence/**'
+      - 'src/langbot/pkg/entity/persistence/**'
+      - 'tests/integration/persistence/**'
+
+jobs:
+  test-migrations-sqlite:
+    name: Migrations (SQLite)
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run SQLite migration tests
+        run: uv run pytest tests/integration/persistence/test_migrations.py -q --tb=short
+
+  test-migrations-postgres:
+    name: Migrations (PostgreSQL)
+    runs-on: ubuntu-latest
+    services:
+      postgres:
+        image: postgres:16
+        env:
+          POSTGRES_USER: langbot
+          POSTGRES_PASSWORD: langbot
+          POSTGRES_DB: langbot_test
+        ports:
+          - 5432:5432
+        options: >-
+          --health-cmd="pg_isready -U langbot"
+          --health-interval=5s
+          --health-timeout=5s
+          --health-retries=5
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run PostgreSQL migration tests
+        env:
+          TEST_POSTGRES_URL: postgresql+asyncpg://langbot:langbot@localhost:5432/langbot_test
+        run: uv run pytest tests/integration/persistence/test_migrations_postgres.py -q --tb=short

.gitignore

@@ -22,7 +22,7 @@ tips.py
 venv*
 bin/
 .vscode
-test_*
+/test_*
 venv/
 hugchat.json
 qcapi
@@ -42,4 +42,17 @@ botpy.log*
 test.py
 /web_ui
 .venv/
-uv.lock
+/test
+plugins.bak
+coverage.xml
+.coverage
+src/langbot/web/
+testsdk/
+
+# Build artifacts
+/dist
+/build
+*.egg-info
+
+# Next.js build cache (legacy)
+web/.next/

.mcp.json

@@ -0,0 +1,37 @@
+{
+  "mcpServers": {
+    "shadcn": {
+      "command": "npx",
+      "args": [
+        "shadcn@latest",
+        "mcp"
+      ]
+    },
+    "sequential-thinking": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-sequential-thinking"],
+      "env": {}
+    },
+    "github": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-github"],
+      "env": {
+        "GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_PERSONAL_ACCESS_TOKEN}"
+      }
+    },
+    "fetch": {
+      "type": "stdio",
+      "command": "uvx",
+      "args": ["mcp-server-fetch"],
+      "env": {}
+    },
+    "playwright": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@playwright/mcp@latest"],
+      "env": {}
+    }
+  }
+}

.pre-commit-config.yaml

@@ -9,16 +9,14 @@ repos:
       # Run the formatter of backend.
       - id: ruff-format
 
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v3.1.0
-    hooks:
-      - id: prettier
-        types_or: [javascript, jsx, ts, tsx, css, scss]
-        additional_dependencies:
-          - prettier@3.1.0
-
   - repo: local
     hooks:
+      - id: prettier
+        name: prettier
+        entry: npx --prefix web prettier --write --ignore-unknown
+        language: system
+        types_or: [javascript, jsx, ts, tsx, css, scss]
+
       - id: lint-staged
         name: lint-staged
         entry: cd web && pnpm lint-staged

.python-version

@@ -1 +0,0 @@
-3.12

AGENTS.md

@@ -0,0 +1,88 @@
+# AGENTS.md
+
+This file is for guiding code agents (like Claude Code, GitHub Copilot, OpenAI Codex, etc.) to work in LangBot project.
+
+## Project Overview
+
+LangBot is a open-source LLM native instant messaging bot development platform, aiming to provide an out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, supporting global instant messaging platforms, and providing rich API interfaces, supporting custom development.
+
+LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
+
+- `./src/langbot`: The main python package of the project, below are the main modules in this package:
+    - `./pkg`: The core python package of the project backend.
+        - `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
+        - `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
+        - `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
+        - `./pkg/api`: The api module of the project, containing the http api controllers and services.
+        - `./pkg/plugin`: LangBot bridge for connecting with plugin system.
+    - `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
+    - `./templates`: Templates of config files, components, etc.
+    - `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
+    - `./docker`: docker-compose deployment files.
+
+## Backend Development
+
+We use `uv` to manage dependencies.
+
+```bash
+pip install uv
+uv sync --dev
+```
+
+Start the backend and run the project in development mode.
+
+```bash
+uv run main.py
+```
+
+Then you can access the project at `http://127.0.0.1:5300`.
+
+## Frontend Development
+
+We use `pnpm` to manage dependencies.
+
+```bash
+cd web
+cp .env.example .env
+pnpm install
+pnpm dev
+```
+
+Then you can access the project at `http://127.0.0.1:3000`.
+
+## Plugin System Architecture
+
+LangBot is composed of various internal components such as Large Language Model tools, commands, messaging platform adapters, LLM requesters, and more. To meet extensibility and flexibility requirements, we have implemented a production-grade plugin system.
+
+Each plugin runs in an independent process, managed uniformly by the Plugin Runtime. It has two operating modes: `stdio` and `websocket`. When LangBot is started directly by users (not running in a container), it uses `stdio` mode, which is common for personal users or lightweight environments. When LangBot runs in a container, it uses `websocket` mode, designed specifically for production environments.
+
+Plugin Runtime automatically starts each installed plugin and interacts through stdio. In plugin development scenarios, developers can use the lbp command-line tool to start plugins and connect to the running Runtime via WebSocket for debugging.
+
+> Plugin SDK, CLI, Runtime, and entities definitions shared between LangBot and plugins are contained in the [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk) repository.
+
+## Some Development Tips and Standards
+
+- LangBot is a global project, any comments in code should be in English, and user experience should be considered in all aspects.
+- Thus you should consider the i18n support in all aspects.
+- LangBot is widely adopted in both toC and toB scenarios, so you should consider the compatibility and security in all aspects.
+- If you were asked to make a commit, please follow the commit message format: 
+    - format: <type>(<scope>): <subject>
+    - type: must be a specific type, such as feat (new feature), fix (bug fix), docs (documentation), style (code style), refactor (refactoring), perf (performance optimization), etc.
+    - scope: the scope of the commit, such as the package name, the file name, the function name, the class name, the module name, etc.
+    - subject: the subject of the commit, such as the description of the commit, the reason for the commit, the impact of the commit, etc.
+- LangBot uses [Alembic](https://alembic.sqlalchemy.org/) to manage database migrations, supporting both SQLite and PostgreSQL. Migration files are located in `src/langbot/pkg/persistence/alembic/versions/`. If you changed the definition of database entities (ORM models), generate a new migration script by running `uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description of your change"` in the project root (requires `data/config.yaml` to exist). Review and edit the generated script before committing. Migrations are executed automatically on LangBot startup. For data migrations (e.g. modifying JSON field content), you need to manually add the migration code in the generated script.
+
+## Some Principles
+
+- Keep it simple, stupid.
+- Entities should not be multiplied unnecessarily
+- 八荣八耻
+
+    以瞎猜接口为耻，以认真查询为荣。
+    以模糊执行为耻，以寻求确认为荣。
+    以臆想业务为耻，以人类确认为荣。
+    以创造接口为耻，以复用现有为荣。
+    以跳过验证为耻，以主动测试为荣。
+    以破坏架构为耻，以遵循规范为荣。
+    以假装理解为耻，以诚实无知为荣。
+    以盲目修改为耻，以谨慎重构为荣。

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

Dockerfile

@@ -4,7 +4,7 @@ WORKDIR /app
 
 COPY web ./web
 
-RUN cd web && npm install && npm run build
+RUN cd web && npm install && npx vite build
 
 FROM python:3.12.7-slim
 
@@ -12,7 +12,7 @@ WORKDIR /app
 
 COPY . .
 
-COPY --from=node /app/web/out ./web/out
+COPY --from=node /app/web/dist ./web/dist
 
 RUN apt update \
     && apt install gcc -y \
@@ -20,4 +20,4 @@ RUN apt update \
     && uv sync \
     && touch /.dockerenv
 
-CMD [ "uv", "run", "main.py" ]
+CMD [ "uv", "run", "--no-sync", "main.py" ]

LICENSE

@@ -1,661 +1,201 @@
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Makefile

@@ -0,0 +1,36 @@
+# LangBot Makefile
+# Quick developer commands
+
+.PHONY: test test-quick test-integration-fast test-coverage test-all-local lint
+
+# Run all tests (full suite with coverage)
+test:
+	bash run_tests.sh
+
+# Quick self-test for developers (lint + unit + smoke, no real credentials needed)
+test-quick:
+	bash scripts/test-quick.sh
+
+# Fast integration tests (SQLite/API/Pipeline, no external services)
+test-integration-fast:
+	bash scripts/test-integration-fast.sh
+
+# Coverage gate (all tests, enforces minimum threshold)
+test-coverage:
+	bash scripts/test-coverage.sh
+
+# Full local quality gate (quick + integration + coverage)
+test-all-local:
+	bash scripts/test-quick.sh
+	bash scripts/test-integration-fast.sh
+	bash scripts/test-coverage.sh
+
+# Run linting only
+lint:
+	ruff check src/langbot/ tests/
+	ruff format --check src/langbot/ tests/
+
+# Fix linting issues
+lint-fix:
+	ruff check --fix src/langbot/ tests/
+	ruff format src/langbot/ tests/

README.md

@@ -1,156 +1,178 @@
-
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
-<a href="https://langbot.app">项目主页</a> ｜
-<a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a> ｜
-<a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">插件介绍</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
+<h3>Production-grade platform for building agentic IM bots.</h3>
+<h4>Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.</h4>
 
-<div align="center">
-😎高稳定、🧩支持扩展、🦄多模态 - 大模型原生即时通信机器人平台🤖  
-</div>
-
-<br/>
+English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
-[简体中文](README.md) / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
+<a href="https://langbot.app">Website</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Features</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Docs</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app/cloud">Cloud</a> ｜
+<a href="https://space.langbot.app">Plugin Market</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
 
 </div>
 
 </p>
 
-> 近期 GeWeChat 项目归档，我们已经适配 WeChatPad 协议端，个微恢复正常使用，详情请查看文档。
+---
 
-## ✨ 特性
+## What is LangBot?
 
-- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态能力，并深度适配 [Dify](https://dify.ai)。目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
-- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。
-- 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
-- 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
+LangBot is an **open-source, production-grade platform** for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.
 
-## 📦 开始使用
+### Key Capabilities
 
-#### Docker Compose 部署
+- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
+- **Universal IM Platform Support** — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
+- **Production-Ready** — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
+- **Plugin Ecosystem** — Hundreds of plugins, event-driven architecture, component extensions, and [MCP protocol](https://modelcontextprotocol.io/) support.
+- **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
+- **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
+
+[→ Learn more about all features](https://link.langbot.app/en/docs/features)
+
+📍 Practical guides: [deploy a multi-platform AI bot in 5 minutes](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connect DeepSeek to WeChat, Discord, and Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [run a Dify Agent in Discord, Telegram, and Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/), and [build an n8n-powered chatbot](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## Quick Start
+
+### ☁️ LangBot Cloud (Recommended)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — Zero deployment, ready to use.
+
+### One-Line Launch
 
 ```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
+uvx langbot
+```
+
+> Requires [uv](https://docs.astral.sh/uv/getting-started/installation/). Visit http://localhost:5300 — done.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
-访问 http://localhost:5300 即可开始使用。
-
-详细文档[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
-
-#### 宝塔面板部署
-
-已上架宝塔面板，若您已安装宝塔面板，可以根据[文档](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
-
-#### Zeabur 云部署
-
-社区贡献的 Zeabur 模板。
-
-[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
-
-#### Railway 云部署
+### One-Click Cloud Deploy
 
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-#### 手动部署
+**More options:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
 
-直接使用发行版运行，查看文档[手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
+---
 
-## 📸 效果展示
+## Supported Platforms
 
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="450px"/>
+| Platform | Status | Notes |
+|----------|--------|-------|
+| Discord | ✅ | Official |
+| Telegram | ✅ | Official |
+| Slack | ✅ | Official |
+| LINE | ✅ | Official |
+| QQ | ✅ | Personal & Official API (Channel, DM, Group) |
+| WeCom | ✅ | Enterprise WeChat, External CS, AI Bot |
+| WeChat | ✅ | Personal & Official Account |
+| Lark | ✅ | Official |
+| DingTalk | ✅ | Official |
+| KOOK | ✅ | Official |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Supports multiple bridged platforms such as Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, and more |
 
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="450px"/>
+---
 
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="450px"/>
+## Supported LLMs & Integrations
 
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="450px"/>
+| Provider                                                                                                          | Type         | Status |
+| ----------------------------------------------------------------------------------------------------------------- | ------------ | ------ |
+| [OpenAI](https://platform.openai.com/)                                                                            | LLM          | ✅     |
+| [Anthropic](https://www.anthropic.com/)                                                                           | LLM          | ✅     |
+| [DeepSeek](https://www.deepseek.com/)                                                                             | LLM          | ✅     |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat)                                                     | LLM          | ✅     |
+| [xAI](https://x.ai/)                                                                                              | LLM          | ✅     |
+| [Moonshot](https://www.moonshot.cn/)                                                                              | LLM          | ✅     |
+| [Zhipu AI](https://open.bigmodel.cn/)                                                                             | LLM          | ✅     |
+| [Ollama](https://ollama.com/)                                                                                     | Local LLM    | ✅     |
+| [LM Studio](https://lmstudio.ai/)                                                                                 | Local LLM    | ✅     |
+| [Dify](https://dify.ai)                                                                                           | LLMOps       | ✅     |
+| [MCP](https://modelcontextprotocol.io/)                                                                           | Protocol     | ✅     |
+| [SiliconFlow](https://siliconflow.cn/)                                                                            | Gateway      | ✅     |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/)                                                             | Gateway      | ✅     |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Gateway      | ✅     |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro)                                        | Gateway      | ✅     |
+| [GiteeAI](https://ai.gitee.com/)                                                                                  | Gateway      | ✅     |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot)                                                     | GPU Platform | ✅     |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot)                             | GPU Platform | ✅     |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758)                                                    | GPU Platform | ✅     |
+| [接口 AI](https://jiekou.ai/)                                                                                     | Gateway      | ✅     |
+| [302.AI](https://share.302.ai/SuTG99)                                                                             | Gateway      | ✅     |
+| [Qiniu](https://www.qiniu.com/ai/agent)                                                                           | Gateway      | ✅     |
 
-<img alt="回复效果（带有联网插件）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+[→ View all integrations](https://link.langbot.app/en/docs/features)
 
-- WebUI Demo: https://demo.langbot.dev/
-    - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
-    - 注意：仅展示webui效果，公开环境，请不要在其中填入您的任何敏感信息。
+---
 
-## 🔌 组件兼容性
+## Why LangBot?
 
-### 消息平台
+| Use Case                    | How LangBot Helps                                                                          |
+| --------------------------- | ------------------------------------------------------------------------------------------ |
+| **Customer Support**        | Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base |
+| **Internal Tools**          | Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes              |
+| **Community Management**    | Moderate QQ/Discord groups with AI-powered content filtering and interaction               |
+| **Multi-Platform Presence** | One bot, all platforms. Manage from a single dashboard                                     |
 
-| 平台 | 状态 | 备注 |
-| --- | --- | --- |
-| QQ 个人号 | ✅ | QQ 个人号私聊、群聊 |
-| QQ 官方机器人 | ✅ | QQ 官方机器人，支持频道、私聊、群聊 |
-| 企业微信 | ✅ |  |
-| 企微对外客服 | ✅ |  |
-| 个人微信 | ✅ |  |
-| 微信公众号 | ✅ |  |
-| 飞书 | ✅ |  |
-| 钉钉 | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
+---
 
-🚧: 正在开发中
+## Live Demo
 
-### 大模型能力
+**Try it now:** https://demo.langbot.dev/
 
-| 模型 | 状态 | 备注 |
-| --- | --- | --- |
-| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 接口格式模型 |
-| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
-| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
-| [Anthropic](https://www.anthropic.com/) | ✅ |  |
-| [xAI](https://x.ai/) | ✅ |  |
-| [智谱AI](https://open.bigmodel.cn/) | ✅ |  |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
-| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
-| [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 |
-| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型运行平台 |
-| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型接口聚合平台 |
-| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
-| [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
-| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
-| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
+- Email: `demo@langbot.app`
+- Password: `langbot123456`
 
-### TTS
+_Note: Public demo environment. Do not enter sensitive information._
 
-| 平台/模型 | 备注 |
-| --- | --- |
-| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
-| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
-| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
+---
 
-### 文生图
+## Community
 
-| 平台/模型 | 备注 |
-| --- | --- |
-| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
 
-## 😘 社区贡献
+- [Discord Community](https://discord.gg/wdNEHETs87)
 
-感谢以下[代码贡献者](https://github.com/RockChinQ/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
+---
 
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## Contributors
+
+Thanks to all [contributors](https://github.com/langbot-app/LangBot/graphs/contributors) who have helped make LangBot better:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>

README_CN.md

@@ -0,0 +1,201 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>生产级 AI 即时通信机器人开发平台。</h3>
+<h4>快速构建、调试和部署 AI 机器人到微信、QQ、飞书、Slack、Discord、Telegram 等平台。</h4>
+
+[English](README.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
+
+<a href="https://langbot.app">官网</a> ｜
+<a href="https://link.langbot.app/zh/docs/features">特性</a> ｜
+<a href="https://link.langbot.app/zh/docs/guide">文档</a> ｜
+<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
+<a href="https://space.langbot.app/cloud">Cloud</a> ｜
+<a href="https://space.langbot.app">插件市场</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">路线图</a>
+
+</div>
+
+</p>
+
+---
+
+LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
+
+### 核心能力
+
+- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
+- **全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
+- **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
+- **插件生态** — 数百个插件，跨进程的事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
+- **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
+- **多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
+
+[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
+
+📍 实践指南：[5 分钟部署多平台 AI 机器人](https://blog.langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[将 DeepSeek 接入微信、企业微信与 Discord](https://blog.langbot.app/zh/blog/connect-deepseek-to-wechat/)、[让 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://blog.langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 构建多平台 AI 聊天机器人](https://blog.langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
+
+---
+
+## 快速开始
+
+### ☁️ LangBot Cloud（推荐）
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，开箱即用。
+
+### 一键启动
+
+```bash
+uvx langbot
+```
+
+> 需要安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)。访问 http://localhost:5300 即可使用。
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### 一键云部署
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**更多方式：** [Docker](https://link.langbot.app/zh/docs/docker) · [手动部署](https://link.langbot.app/zh/docs/manual-deploy) · [宝塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## 支持的平台
+
+| 平台 | 状态 | 备注 |
+|------|------|------|
+| QQ | ✅ | 个人号、官方机器人（频道、私聊、群聊） |
+| 微信 | ✅ | 个人微信、微信公众号 |
+| 企业微信 | ✅ | 应用消息、对外客服、智能机器人 |
+| 飞书 | ✅ | 官方 |
+| 钉钉 | ✅ | 官方 |
+| Satori | ✅ |  |
+| Discord | ✅ | 官方 |
+| Telegram | ✅ | 官方 |
+| Slack | ✅ | 官方 |
+| LINE | ✅ | 官方 |
+| KOOK | ✅ | 官方 |
+| Email | ✅ | 只 Matrix、Satori |
+| Matrix | ✅ | 支持多种桥接平台，如 Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip 等 |
+
+---
+
+## 支持的大模型与集成
+
+| 提供商 | 类型 | 状态 |
+|--------|------|------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [智谱AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
+| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | 协议 | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
+| [阿里云百炼](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
+| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
+| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
+| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
+| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
+| [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
+| [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
+| [七牛云Qiniu](https://www.qiniu.com/ai/agent) | 聚合平台 | ✅ |
+
+[→ 查看完整集成列表](https://link.langbot.app/zh/docs/features)
+
+### TTS（语音合成）
+
+| 平台/模型 | 备注 |
+|-----------|------|
+| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
+| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
+| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
+
+### 文生图
+
+| 平台/模型 | 备注 |
+|-----------|------|
+| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
+
+---
+
+## 为什么选择 LangBot？
+
+| 使用场景 | LangBot 如何帮助 |
+|----------|------------------|
+| **客户服务** | 将 AI Agent 部署到微信/企微/钉钉/飞书，基于知识库自动回答用户问题 |
+| **内部工具** | 将 n8n/Dify 工作流接入企微/钉钉，实现业务流程自动化 |
+| **社群运营** | 在 QQ/Discord 群中使用 AI 驱动的内容审核与智能互动 |
+| **多平台触达** | 一个机器人，覆盖所有平台。通过统一面板集中管理 |
+
+---
+
+## 在线演示
+
+**立即体验：** https://demo.langbot.dev/
+- 邮箱：`demo@langbot.app`
+- 密码：`langbot123456`
+
+*注意：公开演示环境，请不要在其中填入任何敏感信息。*
+
+---
+
+## 社区
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
+
+- [Discord 社区](https://discord.gg/wdNEHETs87)
+- [QQ 社区群](https://qm.qq.com/q/DxZZcNxM1W)
+
+---
+
+## Star 趋势
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## 贡献者
+
+感谢所有[贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)对 LangBot 的帮助：
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>
+
+<!--
+## For Code Agents
+
+If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
+-->

README_EN.md

@@ -1,137 +0,0 @@
-<p align="center">
-<a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
-</a>
-
-<div align="center">
-
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-
-<a href="https://langbot.app">Home</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a> ｜
-<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
-
-<div align="center">
-😎High Stability, 🧩Extension Supported, 🦄Multi-modal - LLM Native Instant Messaging Bot Platform🤖  
-</div>
-
-<br/>
-
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-
-[简体中文](README.md) / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
-
-</div>
-
-</p>
-
-## ✨ Features
-
-- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, and multi-modal capabilities. Deeply integrates with [Dify](https://dify.ai). Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
-- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
-- 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
-- 😻 [New] Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
-
-## 📦 Getting Started
-
-#### Docker Compose Deployment
-
-```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
-docker compose up -d
-```
-
-Visit http://localhost:5300 to start using it.
-
-Detailed documentation [Docker Deployment](https://docs.langbot.app/en/deploy/langbot/docker.html).
-
-#### One-click Deployment on BTPanel
-
-LangBot has been listed on the BTPanel, if you have installed the BTPanel, you can use the [document](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) to use it.
-
-#### Zeabur Cloud Deployment
-
-Community contributed Zeabur template.
-
-[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
-
-#### Railway Cloud Deployment
-
-[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
-
-#### Other Deployment Methods
-
-Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
-
-## 📸 Demo
-
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
-
-<img alt="Reply Effect (with Internet Plugin)" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
-
-- WebUI Demo: https://demo.langbot.dev/
-    - Login information: Email: `demo@langbot.app` Password: `langbot123456`
-    - Note: Only the WebUI effect is shown, please do not fill in any sensitive information in the public environment.
-
-## 🔌 Component Compatibility
-
-### Message Platform
-
-| Platform | Status | Remarks |
-| --- | --- | --- |
-| Personal QQ | ✅ |  |
-| QQ Official API | ✅ |  |
-| WeCom | ✅ |  |
-| WeComCS | ✅ |  |
-| Personal WeChat | ✅ |  |
-| Lark | ✅ |  |
-| DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
-
-🚧: In development
-
-### LLMs
-
-| LLM | Status | Remarks |
-| --- | --- | --- |
-| [OpenAI](https://platform.openai.com/) | ✅ | Available for any OpenAI interface format model |
-| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
-| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
-| [Anthropic](https://www.anthropic.com/) | ✅ |  |
-| [xAI](https://x.ai/) | ✅ |  |
-| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
-| [Dify](https://dify.ai) | ✅ | LLMOps platform |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
-| [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |
-| [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform |
-| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM interface gateway(MaaS) |
-| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM gateway(MaaS) |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM gateway(MaaS), LLMOps platform |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM gateway(MaaS), LLMOps platform |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM gateway(MaaS) |
-| [MCP](https://modelcontextprotocol.io/) | ✅ | Support tool access through MCP protocol |
-
-## 🤝 Community Contribution
-
-Thank you for the following [code contributors](https://github.com/RockChinQ/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
-
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
-</a>

README_ES.md

@@ -0,0 +1,176 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Plataforma de grado de producción para construir bots de mensajería instantánea con agentes de IA.</h3>
+<h4>Construya, depure y despliegue bots de IA rápidamente en Slack, Discord, Telegram, WeChat y más.</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / Español / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+
+<a href="https://langbot.app">Inicio</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Características</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Documentación</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app">Mercado de Plugins</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
+
+</div>
+
+</p>
+
+---
+
+## ¿Qué es LangBot?
+
+LangBot es una **plataforma de código abierto y grado de producción** para construir bots de mensajería instantánea impulsados por IA. Conecta modelos de lenguaje de gran escala (LLMs) con cualquier plataforma de chat, permitiéndole crear agentes inteligentes que pueden conversar, ejecutar tareas e integrarse con sus flujos de trabajo existentes.
+
+### Capacidades Clave
+
+- **Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
+- **Soporte Universal de Plataformas de MI** — Un solo código base para Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
+- **Listo para Producción** — Control de acceso, limitación de velocidad, filtrado de palabras sensibles, monitoreo completo y manejo de excepciones. De confianza para empresas.
+- **Ecosistema de Plugins** — Cientos de plugins, arquitectura basada en eventos, extensiones de componentes y soporte del [protocolo MCP](https://modelcontextprotocol.io/).
+- **Panel de Gestión Web** — Configure, gestione y monitoree sus bots a través de una interfaz de navegador intuitiva. Sin necesidad de editar YAML.
+- **Arquitectura Multi-Pipeline** — Diferentes bots para diferentes escenarios, con monitoreo completo y manejo de excepciones.
+
+[→ Conocer más sobre todas las funcionalidades](https://link.langbot.app/en/docs/features)
+
+📍 Guías prácticas: [desplegar un bot de IA multiplataforma en 5 minutos](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [conectar DeepSeek a WeChat, Discord y Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [ejecutar un Dify Agent en Discord, Telegram y Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) y [crear un chatbot con n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## Inicio Rápido
+
+### ☁️ LangBot Cloud (Recomendado)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — Sin despliegue, listo para usar.
+
+### Lanzamiento en una línea
+
+```bash
+uvx langbot
+```
+
+> Requiere [uv](https://docs.astral.sh/uv/getting-started/installation/). Visite http://localhost:5300 — listo.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### Despliegue en la Nube con un Clic
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**Más opciones:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## Plataformas Soportadas
+
+| Plataforma | Estado | Notas |
+|----------|--------|-------|
+| Discord | ✅ | Oficial |
+| Telegram | ✅ | Oficial |
+| Slack | ✅ | Oficial |
+| LINE | ✅ | Oficial |
+| QQ | ✅ | Personal y API Oficial (Canal, DM, Grupo) |
+| WeCom | ✅ | WeChat Empresarial, CS Externo, AI Bot |
+| WeChat | ✅ | Personal y Cuenta Oficial |
+| Lark | ✅ | Oficial |
+| DingTalk | ✅ | Oficial |
+| KOOK | ✅ | Oficial |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Admite varias plataformas puenteadas como Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip y más |
+
+---
+
+## LLMs e Integraciones Soportadas
+
+| Proveedor | Tipo | Estado |
+|----------|------|--------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | LLM Local | ✅ |
+| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | Protocolo | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | Pasarela | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Pasarela | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Pasarela | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Pasarela | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | Pasarela | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plataforma GPU | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plataforma GPU | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plataforma GPU | ✅ |
+| [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | Pasarela | ✅ |
+
+[→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)
+
+---
+
+## ¿Por qué LangBot?
+
+| Caso de Uso | Cómo Ayuda LangBot |
+|----------|-------------------|
+| **Atención al cliente** | Despliegue agentes de IA en Slack/Discord/Telegram que respondan preguntas usando su base de conocimientos |
+| **Herramientas internas** | Conecte flujos de trabajo de n8n/Dify a WeCom/DingTalk para procesos empresariales automatizados |
+| **Gestión de comunidades** | Modere grupos de QQ/Discord con filtrado de contenido e interacción impulsados por IA |
+| **Presencia multiplataforma** | Un solo bot, todas las plataformas. Gestione desde un único panel de control |
+
+---
+
+## Demo en Vivo
+
+**Pruébelo ahora:** https://demo.langbot.dev/
+- Correo electrónico: `demo@langbot.app`
+- Contraseña: `langbot123456`
+
+*Nota: Entorno de demostración público. No ingrese información confidencial.*
+
+---
+
+## Comunidad
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Comunidad de Discord](https://discord.gg/wdNEHETs87)
+
+---
+
+## Historial de Stars
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## Colaboradores
+
+Gracias a todos los [colaboradores](https://github.com/langbot-app/LangBot/graphs/contributors) que han ayudado a mejorar LangBot:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_FR.md

@@ -0,0 +1,176 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Plateforme de niveau production pour construire des bots de messagerie instantanée avec agents IA.</h3>
+<h4>Créez, déboguez et déployez rapidement des bots IA sur Slack, Discord, Telegram, WeChat et plus.</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / Français / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+
+<a href="https://langbot.app">Accueil</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Fonctionnalités</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Documentation</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app">Marché des Plugins</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
+
+</div>
+
+</p>
+
+---
+
+## Qu'est-ce que LangBot ?
+
+LangBot est une **plateforme open-source de niveau production** pour créer des bots de messagerie instantanée alimentés par l'IA. Elle connecte les grands modèles de langage (LLMs) à n'importe quelle plateforme de chat, vous permettant de créer des agents intelligents capables de converser, d'exécuter des tâches et de s'intégrer à vos workflows existants.
+
+### Capacités Clés
+
+- **Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
+- **Support Universel des Plateformes de MI** — Un seul code pour Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
+- **Prêt pour la Production** — Contrôle d'accès, limitation de débit, filtrage de mots sensibles, surveillance complète et gestion des exceptions. Approuvé par les entreprises.
+- **Écosystème de Plugins** — Des centaines de plugins, architecture événementielle, extensions de composants, et support du [protocole MCP](https://modelcontextprotocol.io/).
+- **Panneau de Gestion Web** — Configurez, gérez et surveillez vos bots via une interface navigateur intuitive. Aucune édition de YAML requise.
+- **Architecture Multi-Pipeline** — Différents bots pour différents scénarios, avec surveillance complète et gestion des exceptions.
+
+[→ En savoir plus sur toutes les fonctionnalités](https://link.langbot.app/en/docs/features)
+
+📍 Guides pratiques : [déployer un bot IA multiplateforme en 5 minutes](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connecter DeepSeek à WeChat, Discord et Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [exécuter un Dify Agent dans Discord, Telegram et Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) et [créer un chatbot avec n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## Démarrage Rapide
+
+### ☁️ LangBot Cloud (Recommandé)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — Sans déploiement, prêt à utiliser.
+
+### Lancement en une ligne
+
+```bash
+uvx langbot
+```
+
+> Nécessite [uv](https://docs.astral.sh/uv/getting-started/installation/). Visitez http://localhost:5300 — c'est prêt.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### Déploiement Cloud en un Clic
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**Plus d'options :** [Docker](https://link.langbot.app/en/docs/docker) · [Manuel](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## Plateformes Supportées
+
+| Plateforme | Statut | Notes |
+|----------|--------|-------|
+| Discord | ✅ | Officiel |
+| Telegram | ✅ | Officiel |
+| Slack | ✅ | Officiel |
+| LINE | ✅ | Officiel |
+| QQ | ✅ | Personnel & API Officielle (Canal, DM, Groupe) |
+| WeCom | ✅ | WeChat Entreprise, CS Externe, AI Bot |
+| WeChat | ✅ | Personnel & Compte Officiel |
+| Lark | ✅ | Officiel |
+| DingTalk | ✅ | Officiel |
+| KOOK | ✅ | Officiel |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Prend en charge plusieurs plateformes via ponts, comme Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, etc. |
+
+---
+
+## LLMs et Intégrations Supportés
+
+| Fournisseur | Type | Statut |
+|----------|------|--------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | LLM Local | ✅ |
+| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | Protocole | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | Passerelle | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Passerelle | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Passerelle | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Passerelle | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | Passerelle | ✅ |
+| [接口 AI](https://jiekou.ai/) | Passerelle | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | Passerelle | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plateforme GPU | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | Passerelle | ✅ |
+
+[→ Voir toutes les intégrations](https://link.langbot.app/en/docs/features)
+
+---
+
+## Pourquoi LangBot ?
+
+| Cas d'Usage | Comment LangBot Aide |
+|----------|-------------------|
+| **Support Client** | Déployez des agents IA sur Slack/Discord/Telegram qui répondent aux questions en utilisant votre base de connaissances |
+| **Outils Internes** | Connectez les workflows n8n/Dify à WeCom/DingTalk pour automatiser vos processus métier |
+| **Gestion de Communauté** | Modérez les groupes QQ/Discord avec un filtrage de contenu et des interactions alimentés par l'IA |
+| **Présence Multi-plateforme** | Un seul bot, toutes les plateformes. Gérez tout depuis un tableau de bord unique |
+
+---
+
+## Démo en Ligne
+
+**Essayez maintenant :** https://demo.langbot.dev/
+- Email : `demo@langbot.app`
+- Mot de passe : `langbot123456`
+
+*Note : Environnement de démonstration public. Ne saisissez pas d'informations sensibles.*
+
+---
+
+## Communauté
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Communauté Discord](https://discord.gg/wdNEHETs87)
+
+---
+
+## Historique des Stars
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## Contributeurs
+
+Merci à tous les [contributeurs](https://github.com/langbot-app/LangBot/graphs/contributors) qui ont aidé à améliorer LangBot :
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_JP.md

@@ -1,136 +1,176 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
-<a href="https://langbot.app">ホーム</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">デプロイ</a> ｜
-<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">プラグイン</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
+<h3>AIエージェント搭載IMボットを構築するための本番グレードプラットフォーム。</h3>
+<h4>Slack、Discord、Telegram、WeChat などに AI ボットを素早く構築、デバッグ、デプロイ。</h4>
 
-<div align="center">
-😎高い安定性、🧩拡張サポート、🦄マルチモーダル - LLMネイティブインスタントメッセージングボットプラットフォーム🤖  
-</div>
-
-<br/>
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / 日本語 / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
-[简体中文](README.md) / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
+<a href="https://langbot.app">ホーム</a> ｜
+<a href="https://link.langbot.app/ja/docs/features">機能</a> ｜
+<a href="https://link.langbot.app/ja/docs/guide">ドキュメント</a> ｜
+<a href="https://link.langbot.app/ja/docs/api">API</a> ｜
+<a href="https://space.langbot.app">プラグインマーケット</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
 
 </div>
 
 </p>
 
-## ✨ 機能
+---
 
-- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル機能をサポート。 [Dify](https://dify.ai) と深く統合。現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
-- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
-- 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
-- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
+## LangBot とは？
 
-## 📦 始め方
+LangBot は、AI搭載のインスタントメッセージングボットを構築するための**オープンソースの本番グレードプラットフォーム**です。大規模言語モデル（LLM）をあらゆるチャットプラットフォームに接続し、会話、タスク実行、既存のワークフローとの統合が可能なインテリジェントエージェントを作成できます。
 
-#### Docker Compose デプロイ
+### 主な機能
+
+- **AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAG（ナレッジベース）を内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) と深く統合。
+- **ユニバーサルIMプラットフォーム対応** — 単一のコードベースで Discord、Telegram、Slack、LINE、QQ、WeChat、WeCom、Lark、DingTalk、KOOK に対応。
+- **本番環境対応** — アクセス制御、レート制限、センシティブワードフィルタリング、包括的な監視、例外処理を搭載。エンタープライズの信頼に応える品質。
+- **プラグインエコシステム** — 数百のプラグイン、イベント駆動アーキテクチャ、コンポーネント拡張、[MCPプロトコル](https://modelcontextprotocol.io/)対応。
+- **Web管理パネル** — 直感的なブラウザインターフェースからボットの設定、管理、監視が可能。YAML編集は不要。
+- **マルチパイプラインアーキテクチャ** — 異なるシナリオに異なるボットを配置し、包括的な監視と例外処理を実現。
+
+[→ すべての機能について詳しく見る](https://link.langbot.app/ja/docs/features)
+
+📍 実践ガイド: [5分でマルチプラットフォームAIボットをデプロイ](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/)、[DeepSeekをWeChat・Discord・Telegramに接続](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/)、[Dify AgentをDiscord・Telegram・Slackで動かす](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/)、[n8n連携チャットボットを構築](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/)。
+
+---
+
+## クイックスタート
+
+### ☁️ LangBot Cloud（推奨）
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — デプロイ不要、すぐに使えます。
+
+### ワンライン起動
 
 ```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
+uvx langbot
+```
+
+> [uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です。http://localhost:5300 にアクセスして完了。
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
-http://localhost:5300 にアクセスして使用を開始します。
-
-詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
-
-#### BTPanelでのワンクリックデプロイ
-
-LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
-
-#### Zeaburクラウドデプロイ
-
-コミュニティが提供するZeaburテンプレート。
+### ワンクリッククラウドデプロイ
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
-
-#### Railwayクラウドデプロイ
-
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-#### その他のデプロイ方法
+**その他:** [Docker](https://link.langbot.app/en/docs/docker) · [手動デプロイ](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
 
-リリースバージョンを直接使用して実行します。[手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html)のドキュメントを参照してください。
+---
 
-## 📸 デモ
-
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
-
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
-
-<img alt="返信効果（インターネットプラグイン付き）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
-
-- WebUIデモ: https://demo.langbot.dev/
-    - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
-    - 注意: WebUIの効果のみを示しています。公開環境では、機密情報を入力しないでください。
-
-## 🔌 コンポーネントの互換性
-
-### メッセージプラットフォーム
+## 対応プラットフォーム
 
 | プラットフォーム | ステータス | 備考 |
-| --- | --- | --- |
-| 個人QQ | ✅ |  |
-| QQ公式API | ✅ |  |
-| WeCom | ✅ |  |
-| WeComCS | ✅ |  |
-| 個人WeChat | ✅ | |
-| Lark | ✅ |  |
-| DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
+|----------|--------|-------|
+| Discord | ✅ | 公式 |
+| Telegram | ✅ | 公式 |
+| Slack | ✅ | 公式 |
+| LINE | ✅ | 公式 |
+| QQ | ✅ | 個人・公式API（チャンネル・DM・グループ） |
+| WeCom | ✅ | 企業WeChat、外部CS、AIボット |
+| WeChat | ✅ | 個人・公式アカウント |
+| Lark | ✅ | 公式 |
+| DingTalk | ✅ | 公式 |
+| KOOK | ✅ | 公式 |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix、Satori |
+| Matrix | ✅ | Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip など複数のブリッジ先プラットフォームに対応 |
 
-🚧: 開発中
+---
 
-### LLMs
+## 対応LLMと統合
 
-| LLM | ステータス | 備考 |
-| --- | --- | --- |
-| [OpenAI](https://platform.openai.com/) | ✅ | 任意のOpenAIインターフェース形式モデルに対応 |
-| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
-| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
-| [Anthropic](https://www.anthropic.com/) | ✅ |  |
-| [xAI](https://x.ai/) | ✅ |  |
-| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
-| [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |
-| [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム |
-| [LMStudio](https://lmstudio.ai/) | ✅ | ローカルLLM実行プラットフォーム |
-| [GiteeAI](https://ai.gitee.com/) | ✅ | LLMインターフェースゲートウェイ(MaaS) |
-| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLMゲートウェイ(MaaS) |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLMゲートウェイ(MaaS) |
-| [MCP](https://modelcontextprotocol.io/) | ✅ | MCPプロトコルをサポート |
+| プロバイダー | タイプ | ステータス |
+|----------|------|--------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | ローカルLLM | ✅ |
+| [LM Studio](https://lmstudio.ai/) | ローカルLLM | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | プロトコル | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | ゲートウェイ | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ゲートウェイ | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ゲートウェイ | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ゲートウェイ | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | ゲートウェイ | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPUプラットフォーム | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPUプラットフォーム | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPUプラットフォーム | ✅ |
+| [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | ゲートウェイ | ✅ |
 
-## 🤝 コミュニティ貢献
+[→ すべての統合を表示](https://link.langbot.app/en/docs/features)
 
-LangBot への貢献に対して、以下の [コード貢献者](https://github.com/RockChinQ/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
+---
 
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+## なぜ LangBot？
+
+| ユースケース | LangBot の活用方法 |
+|----------|-------------------|
+| **カスタマーサポート** | ナレッジベースを活用して質問に回答するAIエージェントをSlack/Discord/Telegramにデプロイ |
+| **社内ツール** | n8n/Difyのワークフローを WeCom/DingTalk に接続し、業務プロセスを自動化 |
+| **コミュニティ管理** | AI搭載のコンテンツフィルタリングとインタラクションでQQ/Discordグループをモデレーション |
+| **マルチプラットフォーム展開** | 1つのボットで全プラットフォームに対応。単一のダッシュボードから管理 |
+
+---
+
+## ライブデモ
+
+**今すぐ試す:** https://demo.langbot.dev/
+- メール: `demo@langbot.app`
+- パスワード: `langbot123456`
+
+*注意: 公開デモ環境です。機密情報を入力しないでください。*
+
+---
+
+## コミュニティ
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Discord コミュニティ](https://discord.gg/wdNEHETs87)
+
+---
+
+## Star 推移
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## コントリビューター
+
+LangBot をより良くするために貢献してくださったすべての[コントリビューター](https://github.com/langbot-app/LangBot/graphs/contributors)に感謝します:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>

README_KO.md

@@ -0,0 +1,176 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>AI 에이전트 IM 봇 구축을 위한 프로덕션 등급 플랫폼.</h3>
+<h4>Slack, Discord, Telegram, WeChat 등에 AI 봇을 빠르게 구축, 디버그 및 배포.</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / 한국어 / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+
+<a href="https://langbot.app">홈</a> ｜
+<a href="https://link.langbot.app/en/docs/features">기능</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">문서</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app">플러그인 마켓</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
+
+</div>
+
+</p>
+
+---
+
+## LangBot이란?
+
+LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈소스 프로덕션 등급 플랫폼**입니다. 대규모 언어 모델(LLM)을 모든 채팅 플랫폼에 연결하여 대화, 작업 실행, 기존 워크플로우와의 통합이 가능한 지능형 에이전트를 만들 수 있습니다.
+
+### 핵심 기능
+
+- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) 심층 통합.
+- **유니버설 IM 플랫폼 지원** — 단일 코드베이스로 Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK 지원.
+- **프로덕션 레디** — 접근 제어, 속도 제한, 민감어 필터링, 종합 모니터링 및 예외 처리. 기업 환경에서 검증됨.
+- **플러그인 생태계** — 수백 개의 플러그인, 이벤트 기반 아키텍처, 컴포넌트 확장, [MCP 프로토콜](https://modelcontextprotocol.io/) 지원.
+- **웹 관리 패널** — 직관적인 브라우저 인터페이스로 봇을 구성, 관리 및 모니터링. YAML 편집 불필요.
+- **멀티 파이프라인 아키텍처** — 다양한 시나리오에 맞는 다양한 봇 구성, 종합 모니터링 및 예외 처리.
+
+[→ 모든 기능 자세히 보기](https://link.langbot.app/en/docs/features)
+
+📍 실전 가이드: [5분 만에 멀티 플랫폼 AI 봇 배포하기](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [DeepSeek를 WeChat, Discord, Telegram에 연결하기](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [Dify Agent를 Discord, Telegram, Slack에서 실행하기](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/), [n8n 기반 챗봇 만들기](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## 빠른 시작
+
+### ☁️ LangBot Cloud (추천)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — 배포 없이 바로 사용.
+
+### 원라인 실행
+
+```bash
+uvx langbot
+```
+
+> [uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요. http://localhost:5300 방문 — 완료.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### 원클릭 클라우드 배포
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**더 많은 옵션:** [Docker](https://link.langbot.app/en/docs/docker) · [수동 배포](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## 지원 플랫폼
+
+| 플랫폼 | 상태 | 비고 |
+|--------|------|------|
+| Discord | ✅ | 공식 |
+| Telegram | ✅ | 공식 |
+| Slack | ✅ | 공식 |
+| LINE | ✅ | 공식 |
+| QQ | ✅ | 개인 및 공식 API (채널, DM, 그룹) |
+| WeCom | ✅ | 기업 WeChat, 외부 CS, AI Bot |
+| WeChat | ✅ | 개인 및 공식 계정 |
+| Lark | ✅ | 공식 |
+| DingTalk | ✅ | 공식 |
+| KOOK | ✅ | 공식 |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip 등 여러 브리지 플랫폼 지원 |
+
+---
+
+## 지원 LLM 및 통합
+
+| 제공자 | 유형 | 상태 |
+|--------|------|------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | 로컬 LLM | ✅ |
+| [LM Studio](https://lmstudio.ai/) | 로컬 LLM | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | 프로토콜 | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | 게이트웨이 | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | 게이트웨이 | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 게이트웨이 | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 게이트웨이 | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | 게이트웨이 | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 플랫폼 | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 플랫폼 | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 플랫폼 | ✅ |
+| [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | 게이트웨이 | ✅ |
+
+[→ 모든 통합 보기](https://link.langbot.app/en/docs/features)
+
+---
+
+## 왜 LangBot인가?
+
+| 사용 사례 | LangBot 활용 방법 |
+|-----------|-------------------|
+| **고객 지원** | 지식 베이스를 활용하여 질문에 답변하는 AI 에이전트를 Slack/Discord/Telegram에 배포 |
+| **내부 도구** | n8n/Dify 워크플로우를 WeCom/DingTalk에 연결하여 비즈니스 프로세스 자동화 |
+| **커뮤니티 관리** | AI 기반 콘텐츠 필터링 및 상호작용으로 QQ/Discord 그룹 관리 |
+| **멀티 플랫폼** | 하나의 봇으로 모든 플랫폼 지원. 단일 대시보드에서 관리 |
+
+---
+
+## 라이브 데모
+
+**지금 체험:** https://demo.langbot.dev/
+- 이메일: `demo@langbot.app`
+- 비밀번호: `langbot123456`
+
+*참고: 공개 데모 환경입니다. 민감한 정보를 입력하지 마세요.*
+
+---
+
+## 커뮤니티
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Discord 커뮤니티](https://discord.gg/wdNEHETs87)
+
+---
+
+## Star 추이
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## 기여자
+
+LangBot을 더 나은 프로젝트로 만들어 주신 모든 [기여자](https://github.com/langbot-app/LangBot/graphs/contributors)분들께 감사드립니다:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_RU.md

@@ -0,0 +1,176 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Платформа производственного уровня для создания агентных IM-ботов.</h3>
+<h4>Быстро создавайте, отлаживайте и развертывайте ИИ-ботов в Slack, Discord, Telegram, WeChat и других платформах.</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / Русский / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+
+<a href="https://langbot.app">Главная</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Возможности</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Документация</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app">Магазин плагинов</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
+
+</div>
+
+</p>
+
+---
+
+## Что такое LangBot?
+
+LangBot — это **платформа с открытым исходным кодом производственного уровня** для создания ИИ-ботов в мессенджерах. Она связывает большие языковые модели (LLM) с любой чат-платформой, позволяя создавать интеллектуальных агентов, которые могут вести диалоги, выполнять задачи и интегрироваться с вашими существующими рабочими процессами.
+
+### Ключевые возможности
+
+- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
+- **Универсальная поддержка IM-платформ** — Единая кодовая база для Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
+- **Готовность к продакшену** — Контроль доступа, ограничение скорости, фильтрация чувствительных слов, комплексный мониторинг и обработка исключений. Проверено в корпоративной среде.
+- **Экосистема плагинов** — Сотни плагинов, событийно-ориентированная архитектура, расширения компонентов и поддержка [протокола MCP](https://modelcontextprotocol.io/).
+- **Веб-панель управления** — Настраивайте, управляйте и мониторьте ваших ботов через интуитивный браузерный интерфейс. Ручное редактирование YAML не требуется.
+- **Мультиконвейерная архитектура** — Разные боты для разных сценариев с комплексным мониторингом и обработкой исключений.
+
+[→ Подробнее обо всех возможностях](https://link.langbot.app/en/docs/features)
+
+📍 Практические руководства: [развернуть мультиплатформенного ИИ-бота за 5 минут](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [подключить DeepSeek к WeChat, Discord и Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [запустить Dify Agent в Discord, Telegram и Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) и [создать чат-бота на n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## Быстрый старт
+
+### ☁️ LangBot Cloud (Рекомендуется)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — Без развёртывания, готово к использованию.
+
+### Запуск одной командой
+
+```bash
+uvx langbot
+```
+
+> Требуется [uv](https://docs.astral.sh/uv/getting-started/installation/). Откройте http://localhost:5300 — готово.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### Облачное развертывание одним кликом
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**Другие варианты:** [Docker](https://link.langbot.app/en/docs/docker) · [Ручная установка](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## Поддерживаемые платформы
+
+| Платформа | Статус | Примечания |
+|-----------|--------|------------|
+| Discord | ✅ | Официальный |
+| Telegram | ✅ | Официальный |
+| Slack | ✅ | Официальный |
+| LINE | ✅ | Официальный |
+| QQ | ✅ | Личный и официальный API (Канал, ЛС, Группа) |
+| WeCom | ✅ | Корпоративный WeChat, внешний CS, AI-бот |
+| WeChat | ✅ | Личный и официальный аккаунт |
+| Lark | ✅ | Официальный |
+| DingTalk | ✅ | Официальный |
+| KOOK | ✅ | Официальный |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Поддерживает несколько платформ через мосты, включая Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip и другие |
+
+---
+
+## Поддерживаемые LLM и интеграции
+
+| Провайдер | Тип | Статус |
+|-----------|-----|--------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | Локальный LLM | ✅ |
+| [LM Studio](https://lmstudio.ai/) | Локальный LLM | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | Протокол | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | Шлюз | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Шлюз | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Шлюз | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Шлюз | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | Шлюз | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | Шлюз | ✅ |
+| [接口 AI](https://jiekou.ai/) | Шлюз | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Платформа GPU | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | Шлюз | ✅ |
+
+[→ Смотреть все интеграции](https://link.langbot.app/en/docs/features)
+
+---
+
+## Почему LangBot?
+
+| Сценарий использования | Как помогает LangBot |
+|------------------------|----------------------|
+| **Поддержка клиентов** | Разверните ИИ-агентов в Slack/Discord/Telegram, которые отвечают на вопросы, используя вашу базу знаний |
+| **Внутренние инструменты** | Подключите рабочие процессы n8n/Dify к WeCom/DingTalk для автоматизации бизнес-процессов |
+| **Управление сообществом** | Модерируйте группы QQ/Discord с помощью ИИ-фильтрации контента и взаимодействия |
+| **Мультиплатформенное присутствие** | Один бот — все платформы. Управляйте из единой панели |
+
+---
+
+## Демо
+
+**Попробуйте прямо сейчас:** https://demo.langbot.dev/
+- Email: `demo@langbot.app`
+- Пароль: `langbot123456`
+
+*Примечание: Публичная демо-среда. Не вводите конфиденциальную информацию.*
+
+---
+
+## Сообщество
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Сообщество Discord](https://discord.gg/wdNEHETs87)
+
+---
+
+## История Stars
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## Участники
+
+Спасибо всем [участникам](https://github.com/langbot-app/LangBot/graphs/contributors), которые помогли сделать LangBot лучше:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_TW.md

@@ -0,0 +1,194 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>生產級 AI 即時通訊機器人開發平台。</h3>
+<h4>快速建構、除錯和部署 AI 機器人到微信、QQ、飛書、Slack、Discord、Telegram 等平台。</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / 繁體中文 / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
+
+<a href="https://langbot.app">官網</a> ｜
+<a href="https://link.langbot.app/zh/docs/features">特性</a> ｜
+<a href="https://link.langbot.app/zh/docs/guide">文件</a> ｜
+<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
+<a href="https://space.langbot.app">外掛市場</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">路線圖</a>
+
+</div>
+
+</p>
+
+---
+
+## 什麼是 LangBot？
+
+LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時通訊機器人。它將大語言模型（LLM）連接到各種聊天平台，幫助你創建能夠對話、執行任務、並整合到現有工作流程中的智能 Agent。
+
+### 核心能力
+
+- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG（知識庫），深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
+- **全平台支援** — 一套程式碼，覆蓋 QQ、微信、企業微信、飛書、釘釘、Discord、Telegram、Slack、LINE、KOOK 等平台。
+- **生產就緒** — 存取控制、限速、敏感詞過濾、全面監控與異常處理，已被多家企業採用。
+- **外掛生態** — 數百個外掛，事件驅動架構，組件擴展，適配 [MCP 協議](https://modelcontextprotocol.io/)。
+- **Web 管理面板** — 透過瀏覽器直觀地配置、管理和監控機器人，無需手動編輯設定檔。
+- **多流水線架構** — 不同機器人用於不同場景，具備全面的監控和異常處理能力。
+
+[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
+
+📍 實踐指南：[5 分鐘部署多平台 AI 機器人](https://blog.langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[將 DeepSeek 接入微信、企業微信與 Discord](https://blog.langbot.app/zh/blog/connect-deepseek-to-wechat/)、[讓 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://blog.langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 建構多平台 AI 聊天機器人](https://blog.langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
+
+---
+
+## 快速開始
+
+### ☁️ LangBot Cloud（推薦）
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，開箱即用。
+
+### 一鍵啟動
+
+```bash
+uvx langbot
+```
+
+> 需要安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/)。訪問 http://localhost:5300 即可使用。
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### 一鍵雲端部署
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**更多方式：** [Docker](https://link.langbot.app/zh/docs/docker) · [手動部署](https://link.langbot.app/zh/docs/manual-deploy) · [寶塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## 支援的平台
+
+| 平台 | 狀態 | 備註 |
+|------|------|------|
+| Discord | ✅ | 官方 |
+| Telegram | ✅ | 官方 |
+| Slack | ✅ | 官方 |
+| LINE | ✅ | 官方 |
+| QQ | ✅ | 個人號、官方機器人（頻道、私聊、群聊） |
+| 企業微信 | ✅ | 應用訊息、對外客服、智能機器人 |
+| 微信 | ✅ | 個人微信、微信公眾號 |
+| 飛書 | ✅ | 官方 |
+| 釘釘 | ✅ | 官方 |
+| KOOK | ✅ | 官方 |
+| Satori | ✅ |  |
+| Email | ✅ | 只 Matrix、Satori |
+| Matrix | ✅ | 支援多種橋接平台，如 Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip 等 |
+
+---
+
+## 支援的大模型與整合
+
+| 提供商 | 類型 | 狀態 |
+|--------|------|------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [智譜AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
+| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | 協議 | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
+| [阿里雲百煉](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
+| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
+| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
+| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
+| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | 聚合平台 | ✅ |
+
+### TTS（語音合成）
+
+| 平台/模型 | 備註 |
+|-----------|------|
+| [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
+| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
+| [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) |
+
+### 文生圖
+
+| 平台/模型 | 備註 |
+|-----------|------|
+| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
+
+[→ 查看完整整合列表](https://link.langbot.app/zh/docs/features)
+
+---
+
+## 為什麼選擇 LangBot？
+
+| 使用場景 | LangBot 如何幫助 |
+|----------|------------------|
+| **客戶服務** | 將 AI Agent 部署到微信/企微/釘釘/飛書，基於知識庫自動回答使用者問題 |
+| **內部工具** | 將 n8n/Dify 工作流接入企微/釘釘，實現業務流程自動化 |
+| **社群運營** | 在 QQ/Discord 群中使用 AI 驅動的內容審核與智能互動 |
+| **多平台觸達** | 一個機器人，覆蓋所有平台。透過統一面板集中管理 |
+
+---
+
+## 線上演示
+
+**立即體驗：** https://demo.langbot.dev/
+- 信箱：`demo@langbot.app`
+- 密碼：`langbot123456`
+
+*注意：公開演示環境，請不要在其中填入任何敏感資訊。*
+
+---
+
+## 社群
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
+
+- [Discord 社群](https://discord.gg/wdNEHETs87)
+- [QQ 社群群](https://qm.qq.com/q/JLi38whHum)
+
+---
+
+## Star 趨勢
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## 貢獻者
+
+感謝所有[貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)對 LangBot 的幫助：
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_VI.md

@@ -0,0 +1,176 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Nền tảng cấp sản xuất để xây dựng bot IM với AI agent.</h3>
+<h4>Xây dựng, gỡ lỗi và triển khai bot AI nhanh chóng trên Slack, Discord, Telegram, WeChat và nhiều nền tảng khác.</h4>
+
+[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / Tiếng Việt
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+
+<a href="https://langbot.app">Trang chủ</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Tính năng</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Tài liệu</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://space.langbot.app">Chợ Plugin</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
+
+</div>
+
+</p>
+
+---
+
+## LangBot là gì?
+
+LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để xây dựng bot nhắn tin tức thời được hỗ trợ bởi AI. Nó kết nối các Mô hình Ngôn ngữ Lớn (LLM) với bất kỳ nền tảng chat nào, cho phép bạn tạo các agent thông minh có thể trò chuyện, thực hiện tác vụ và tích hợp với quy trình làm việc hiện có của bạn.
+
+### Khả năng chính
+
+- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
+- **Hỗ trợ đa nền tảng IM** — Một mã nguồn cho Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
+- **Sẵn sàng cho sản xuất** — Kiểm soát truy cập, giới hạn tốc độ, lọc từ nhạy cảm, giám sát toàn diện và xử lý ngoại lệ. Được doanh nghiệp tin dùng.
+- **Hệ sinh thái Plugin** — Hàng trăm plugin, kiến trúc hướng sự kiện, mở rộng thành phần, và hỗ trợ [giao thức MCP](https://modelcontextprotocol.io/).
+- **Bảng quản lý Web** — Cấu hình, quản lý và giám sát bot thông qua giao diện trình duyệt trực quan. Không cần chỉnh sửa YAML.
+- **Kiến trúc đa Pipeline** — Các bot khác nhau cho các kịch bản khác nhau, với giám sát toàn diện và xử lý ngoại lệ.
+
+[→ Tìm hiểu thêm về tất cả tính năng](https://link.langbot.app/en/docs/features)
+
+📍 Hướng dẫn thực hành: [triển khai bot AI đa nền tảng trong 5 phút](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [kết nối DeepSeek với WeChat, Discord và Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [chạy Dify Agent trên Discord, Telegram và Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) và [xây dựng chatbot với n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+
+---
+
+## Bắt đầu nhanh
+
+### ☁️ LangBot Cloud (Khuyên dùng)
+
+**[LangBot Cloud](https://space.langbot.app/cloud)** — Không cần triển khai, sẵn sàng sử dụng.
+
+### Khởi chạy một dòng
+
+```bash
+uvx langbot
+```
+
+> Yêu cầu [uv](https://docs.astral.sh/uv/getting-started/installation/). Truy cập http://localhost:5300 — xong.
+
+### Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+### Triển khai đám mây một cú nhấp
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+**Thêm tùy chọn:** [Docker](https://link.langbot.app/en/docs/docker) · [Thủ công](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+
+---
+
+## Nền tảng được hỗ trợ
+
+| Nền tảng | Trạng thái | Ghi chú |
+|----------|--------|-------|
+| Discord | ✅ | Chính thức |
+| Telegram | ✅ | Chính thức |
+| Slack | ✅ | Chính thức |
+| LINE | ✅ | Chính thức |
+| QQ | ✅ | Cá nhân & API chính thức (Kênh, DM, Nhóm) |
+| WeCom | ✅ | WeChat doanh nghiệp, CS bên ngoài, AI Bot |
+| WeChat | ✅ | Cá nhân & Tài khoản công khai |
+| Lark | ✅ | Chính thức |
+| DingTalk | ✅ | Chính thức |
+| KOOK | ✅ | Chính thức |
+| Satori | ✅ |  |
+| Email | ✅ | Matrix, Satori |
+| Matrix | ✅ | Hỗ trợ nhiều nền tảng qua bridge như Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip và hơn thế nữa |
+
+---
+
+## LLM và tích hợp được hỗ trợ
+
+| Nhà cung cấp | Loại | Trạng thái |
+|----------|------|--------|
+| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
+| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
+| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
+| [xAI](https://x.ai/) | LLM | ✅ |
+| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
+| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
+| [Ollama](https://ollama.com/) | LLM cục bộ | ✅ |
+| [LM Studio](https://lmstudio.ai/) | LLM cục bộ | ✅ |
+| [Dify](https://dify.ai) | LLMOps | ✅ |
+| [MCP](https://modelcontextprotocol.io/) | Giao thức | ✅ |
+| [SiliconFlow](https://siliconflow.cn/) | Cổng | ✅ |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Cổng | ✅ |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Cổng | ✅ |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Cổng | ✅ |
+| [GiteeAI](https://ai.gitee.com/) | Cổng | ✅ |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Nền tảng GPU | ✅ |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Nền tảng GPU | ✅ |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Nền tảng GPU | ✅ |
+| [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
+| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
+| [Qiniu](https://www.qiniu.com/ai/agent) | Cổng | ✅ |
+
+[→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)
+
+---
+
+## Tại sao chọn LangBot?
+
+| Trường hợp sử dụng | LangBot giúp như thế nào |
+|----------|-------------------|
+| **Hỗ trợ khách hàng** | Triển khai agent AI trên Slack/Discord/Telegram để trả lời câu hỏi bằng cơ sở kiến thức của bạn |
+| **Công cụ nội bộ** | Kết nối quy trình n8n/Dify với WeCom/DingTalk để tự động hóa quy trình kinh doanh |
+| **Quản lý cộng đồng** | Quản lý nhóm QQ/Discord với tính năng lọc nội dung và tương tác được hỗ trợ bởi AI |
+| **Đa nền tảng** | Một bot, tất cả nền tảng. Quản lý từ một bảng điều khiển duy nhất |
+
+---
+
+## Demo trực tuyến
+
+**Thử ngay:** https://demo.langbot.dev/
+- Email: `demo@langbot.app`
+- Mật khẩu: `langbot123456`
+
+*Lưu ý: Môi trường demo công khai. Không nhập thông tin nhạy cảm.*
+
+---
+
+## Cộng đồng
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
+
+- [Cộng đồng Discord](https://discord.gg/wdNEHETs87)
+
+---
+
+## Lịch sử Star
+
+[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
+
+---
+
+## Người đóng góp
+
+Cảm ơn tất cả [người đóng góp](https://github.com/langbot-app/LangBot/graphs/contributors) đã giúp LangBot trở nên tốt hơn:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

codecov.yml

@@ -0,0 +1,4 @@
+coverage:
+  status:
+    project: off
+    patch: off

compare_nodes.py

@@ -0,0 +1,163 @@
+#!/usr/bin/env python3
+"""Compare YAML node definitions with frontend node-configs."""
+
+import yaml
+import os
+import re
+import json
+
+# 1. Parse YAML files
+yaml_dir = 'src/langbot/templates/metadata/nodes'
+yaml_nodes = {}
+
+for filename in sorted(os.listdir(yaml_dir)):
+    if filename.endswith('.yaml'):
+        filepath = os.path.join(yaml_dir, filename)
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+            node_name = data.get('name', filename.replace('.yaml', ''))
+            yaml_nodes[node_name] = {
+                'category': data.get('category', ''),
+                'inputs': [i['name'] for i in data.get('inputs', [])],
+                'outputs': [o['name'] for o in data.get('outputs', [])],
+                'config': [c['name'] for c in data.get('config', [])]
+            }
+
+# 2. Parse frontend node-configs TypeScript files
+node_configs_dir = 'web/src/app/home/workflows/components/workflow-editor/node-configs'
+
+frontend_nodes = {}
+
+def parse_ts_file(filepath):
+    """Parse a TypeScript file to extract node configurations."""
+    with open(filepath, 'r') as f:
+        content = f.read()
+    
+    # Find all node type definitions
+    # Pattern: nodeType: 'xxx'
+    node_type_pattern = r"nodeType:\s*'([^']+)'"
+    node_types = re.findall(node_type_pattern, content)
+    
+    # For each node type, extract inputs, outputs, and config
+    for node_type in node_types:
+        # Find the config object for this node type
+        # Look for the section between this nodeType and the next one or end of object
+        pattern = rf"nodeType:\s*'({re.escape(node_type)})'.*?(?=nodeType:|export\s+(const|function)|$)"
+        match = re.search(pattern, content, re.DOTALL)
+        
+        if match:
+            section = match.group(0)
+            
+            # Extract inputs
+            inputs = re.findall(r"createInput\('([^']+)'", section)
+            
+            # Extract outputs  
+            outputs = re.findall(r"createOutput\('([^']+)'", section)
+            
+            # Extract config names
+            config_names = re.findall(r"name:\s*'([^']+)'", section)
+            # Remove duplicates while preserving order
+            seen = set()
+            unique_config = []
+            for c in config_names:
+                if c not in seen:
+                    seen.add(c)
+                    unique_config.append(c)
+            
+            frontend_nodes[node_type] = {
+                'inputs': inputs,
+                'outputs': outputs,
+                'config': unique_config
+            }
+
+# Parse all config files
+for filename in os.listdir(node_configs_dir):
+    if filename.endswith('.ts') and filename != 'types.ts' and filename != 'index.ts':
+        filepath = os.path.join(node_configs_dir, filename)
+        parse_ts_file(filepath)
+
+# 3. Compare and report differences
+print("=" * 80)
+print("WORKFLOW NODE COMPARISON REPORT: YAML vs Frontend")
+print("=" * 80)
+
+all_node_types = sorted(set(list(yaml_nodes.keys()) + list(frontend_nodes.keys())))
+
+discrepancies = []
+
+for node_type in all_node_types:
+    yaml_def = yaml_nodes.get(node_type)
+    frontend_def = frontend_nodes.get(node_type)
+    
+    node_discrepancies = []
+    
+    if not yaml_def:
+        print(f"\n⚠️  {node_type}: ONLY in frontend (not in YAML)")
+        continue
+    if not frontend_def:
+        print(f"\n⚠️  {node_type}: ONLY in YAML (not in frontend)")
+        continue
+    
+    # Compare inputs
+    yaml_inputs = set(yaml_def['inputs'])
+    frontend_inputs = set(frontend_def['inputs'])
+    if yaml_inputs != frontend_inputs:
+        only_yaml = yaml_inputs - frontend_inputs
+        only_frontend = frontend_inputs - yaml_inputs
+        node_discrepancies.append({
+            'type': 'inputs',
+            'only_yaml': list(only_yaml),
+            'only_frontend': list(only_frontend)
+        })
+    
+    # Compare outputs
+    yaml_outputs = set(yaml_def['outputs'])
+    frontend_outputs = set(frontend_def['outputs'])
+    if yaml_outputs != frontend_outputs:
+        only_yaml = yaml_outputs - frontend_outputs
+        only_frontend = frontend_outputs - yaml_outputs
+        node_discrepancies.append({
+            'type': 'outputs',
+            'only_yaml': list(only_yaml),
+            'only_frontend': list(only_frontend)
+        })
+    
+    # Compare config
+    yaml_config = set(yaml_def['config'])
+    frontend_config = set(frontend_def['config'])
+    if yaml_config != frontend_config:
+        only_yaml = yaml_config - frontend_config
+        only_frontend = frontend_config - yaml_config
+        node_discrepancies.append({
+            'type': 'config',
+            'only_yaml': list(only_yaml),
+            'only_frontend': list(only_frontend)
+        })
+    
+    if node_discrepancies:
+        print(f"\n❌ {node_type} ({yaml_def['category']}): HAS DISCREPANCIES")
+        for d in node_discrepancies:
+            print(f"   {d['type']}:")
+            if d['only_yaml']:
+                print(f"     Only in YAML: {d['only_yaml']}")
+            if d['only_frontend']:
+                print(f"     Only in Frontend: {d['only_frontend']}")
+        discrepancies.append((node_type, node_discrepancies))
+    else:
+        print(f"\n✅ {node_type} ({yaml_def['category']}): OK")
+
+print(f"\n{'=' * 80}")
+print(f"SUMMARY: {len(discrepancies)} nodes with discrepancies out of {len(all_node_types)} total")
+print(f"{'=' * 80}")
+
+# Output as JSON for further processing
+output = {
+    'yaml_nodes': {k: v for k, v in yaml_nodes.items()},
+    'frontend_nodes': {k: v for k, v in frontend_nodes.items()},
+    'discrepancies': {k: v for k, v in discrepancies}
+}
+
+with open('node_comparison.json', 'w') as f:
+    json.dump(output, f, indent=2)
+
+print(f"\nDetailed comparison saved to node_comparison.json")

docker-compose.yaml

@@ -1,16 +0,0 @@
-version: "3"
-
-services:
-  langbot:
-    image: rockchin/langbot:latest
-    container_name: langbot
-    volumes:
-      - ./data:/app/data
-      - ./plugins:/app/plugins
-    restart: on-failure
-    environment:
-      - TZ=Asia/Shanghai
-    ports:
-      - 5300:5300  # 供 WebUI 使用
-      - 2280-2290:2280-2290  # 供消息平台适配器方向连接
-    # 根据具体环境配置网络

docker/README_K8S.md

@@ -0,0 +1,629 @@
+# LangBot Kubernetes 部署指南 / Kubernetes Deployment Guide
+
+[简体中文](#简体中文) | [English](#english)
+
+---
+
+## 简体中文
+
+### 概述
+
+本指南提供了在 Kubernetes 集群中部署 LangBot 的完整步骤。Kubernetes 部署配置基于 `docker-compose.yaml`，适用于生产环境的容器化部署。
+
+### 前置要求
+
+- Kubernetes 集群（版本 1.19+）
+- `kubectl` 命令行工具已配置并可访问集群
+- 集群中有可用的存储类（StorageClass）用于持久化存储（可选但推荐）
+- 至少 2 vCPU 和 4GB RAM 的可用资源
+
+### 架构说明
+
+Kubernetes 部署包含以下组件：
+
+1. **langbot**: 主应用服务
+   - 提供 Web UI（端口 5300）
+   - 处理平台 webhook（端口 2280-2290）
+   - 数据持久化卷
+   
+2. **langbot-plugin-runtime**: 插件运行时服务
+   - WebSocket 通信（端口 5400）
+   - 插件数据持久化卷
+
+3. **持久化存储**:
+   - `langbot-data`: LangBot 主数据
+   - `langbot-plugins`: 插件文件
+   - `langbot-plugin-runtime-data`: 插件运行时数据
+
+### 快速开始
+
+#### 1. 下载部署文件
+
+```bash
+# 克隆仓库
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# 或直接下载 kubernetes.yaml
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. 部署到 Kubernetes
+
+```bash
+# 应用所有配置
+kubectl apply -f kubernetes.yaml
+
+# 检查部署状态
+kubectl get all -n langbot
+
+# 查看 Pod 日志
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. 访问 LangBot
+
+默认情况下，LangBot 服务使用 ClusterIP 类型，只能在集群内部访问。您可以选择以下方式之一来访问：
+
+**选项 A: 端口转发（推荐用于测试）**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+然后访问 http://localhost:5300
+
+**选项 B: NodePort（适用于开发环境）**
+
+编辑 `kubernetes.yaml`，取消注释 NodePort Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取节点 IP
+kubectl get nodes -o wide
+# 访问 http://<NODE_IP>:30300
+```
+
+**选项 C: LoadBalancer（适用于云环境）**
+
+编辑 `kubernetes.yaml`，取消注释 LoadBalancer Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取外部 IP
+kubectl get svc -n langbot langbot-loadbalancer
+# 访问 http://<EXTERNAL_IP>
+```
+
+**选项 D: Ingress（推荐用于生产环境）**
+
+确保集群中已安装 Ingress Controller（如 nginx-ingress），然后：
+
+1. 编辑 `kubernetes.yaml` 中的 Ingress 配置
+2. 修改域名为您的实际域名
+3. 应用配置：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 访问 http://langbot.yourdomain.com
+```
+
+### 配置说明
+
+#### 环境变量
+
+在 `ConfigMap` 中配置环境变量：
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # 修改为您的时区
+```
+
+#### 存储配置
+
+默认使用动态存储分配。如果您有特定的 StorageClass，请在 PVC 中指定：
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### 资源限制
+
+根据您的需求调整资源限制：
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### 常用操作
+
+#### 查看日志
+
+```bash
+# 查看 LangBot 主服务日志
+kubectl logs -n langbot -l app=langbot -f
+
+# 查看插件运行时日志
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### 重启服务
+
+```bash
+# 重启 LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# 重启插件运行时
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### 更新镜像
+
+```bash
+# 更新到最新版本
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# 检查更新状态
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### 扩容（不推荐）
+
+注意：由于 LangBot 使用 ReadWriteOnce 的持久化存储，不支持多副本扩容。如需高可用，请考虑使用 ReadWriteMany 存储或其他架构方案。
+
+#### 备份数据
+
+```bash
+# 备份 PVC 数据
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### 卸载
+
+```bash
+# 删除所有资源（保留 PVC）
+kubectl delete deployment,service,configmap -n langbot --all
+
+# 删除 PVC（会删除数据）
+kubectl delete pvc -n langbot --all
+
+# 删除命名空间
+kubectl delete namespace langbot
+```
+
+### 故障排查
+
+#### Pod 无法启动
+
+```bash
+# 查看 Pod 状态
+kubectl get pods -n langbot
+
+# 查看详细信息
+kubectl describe pod -n langbot <pod-name>
+
+# 查看事件
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### 存储问题
+
+```bash
+# 检查 PVC 状态
+kubectl get pvc -n langbot
+
+# 检查 PV
+kubectl get pv
+```
+
+#### 网络访问问题
+
+```bash
+# 检查 Service
+kubectl get svc -n langbot
+
+# 检查端口转发
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### 生产环境建议
+
+1. **使用特定版本标签**：避免使用 `latest` 标签，使用具体版本号如 `rockchin/langbot:v1.0.0`
+2. **配置资源限制**：根据实际负载调整 CPU 和内存限制
+3. **使用 Ingress + TLS**：配置 HTTPS 访问和证书管理
+4. **配置监控和告警**：集成 Prometheus、Grafana 等监控工具
+5. **定期备份**：配置自动备份策略保护数据
+6. **使用专用 StorageClass**：为生产环境配置高性能存储
+7. **配置亲和性规则**：确保 Pod 调度到合适的节点
+
+### 高级配置
+
+#### 使用 Secrets 管理敏感信息
+
+如果需要配置 API 密钥等敏感信息：
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+然后在 Deployment 中引用：
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### 配置水平自动扩缩容（HPA）
+
+注意：需要确保使用 ReadWriteMany 存储类型
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### 参考资源
+
+- [LangBot 官方文档](https://docs.langbot.app)
+- [Docker 部署文档](https://link.langbot.app/zh/docs/docker)
+- [Kubernetes 官方文档](https://kubernetes.io/docs/)
+
+---
+
+## English
+
+### Overview
+
+This guide provides complete steps for deploying LangBot in a Kubernetes cluster. The Kubernetes deployment configuration is based on `docker-compose.yaml` and is suitable for production containerized deployments.
+
+### Prerequisites
+
+- Kubernetes cluster (version 1.19+)
+- `kubectl` command-line tool configured with cluster access
+- Available StorageClass in the cluster for persistent storage (optional but recommended)
+- At least 2 vCPU and 4GB RAM of available resources
+
+### Architecture
+
+The Kubernetes deployment includes the following components:
+
+1. **langbot**: Main application service
+   - Provides Web UI (port 5300)
+   - Handles platform webhooks (ports 2280-2290)
+   - Data persistence volume
+   
+2. **langbot-plugin-runtime**: Plugin runtime service
+   - WebSocket communication (port 5400)
+   - Plugin data persistence volume
+
+3. **Persistent Storage**:
+   - `langbot-data`: LangBot main data
+   - `langbot-plugins`: Plugin files
+   - `langbot-plugin-runtime-data`: Plugin runtime data
+
+### Quick Start
+
+#### 1. Download Deployment Files
+
+```bash
+# Clone repository
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# Or download kubernetes.yaml directly
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. Deploy to Kubernetes
+
+```bash
+# Apply all configurations
+kubectl apply -f kubernetes.yaml
+
+# Check deployment status
+kubectl get all -n langbot
+
+# View Pod logs
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. Access LangBot
+
+By default, LangBot service uses ClusterIP type, accessible only within the cluster. Choose one of the following methods to access:
+
+**Option A: Port Forwarding (Recommended for testing)**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+Then visit http://localhost:5300
+
+**Option B: NodePort (Suitable for development)**
+
+Edit `kubernetes.yaml`, uncomment the NodePort Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get node IP
+kubectl get nodes -o wide
+# Visit http://<NODE_IP>:30300
+```
+
+**Option C: LoadBalancer (Suitable for cloud environments)**
+
+Edit `kubernetes.yaml`, uncomment the LoadBalancer Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get external IP
+kubectl get svc -n langbot langbot-loadbalancer
+# Visit http://<EXTERNAL_IP>
+```
+
+**Option D: Ingress (Recommended for production)**
+
+Ensure an Ingress Controller (e.g., nginx-ingress) is installed in the cluster, then:
+
+1. Edit the Ingress configuration in `kubernetes.yaml`
+2. Change the domain to your actual domain
+3. Apply configuration:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Visit http://langbot.yourdomain.com
+```
+
+### Configuration
+
+#### Environment Variables
+
+Configure environment variables in ConfigMap:
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # Change to your timezone
+```
+
+#### Storage Configuration
+
+Uses dynamic storage provisioning by default. If you have a specific StorageClass, specify it in PVC:
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### Resource Limits
+
+Adjust resource limits based on your needs:
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### Common Operations
+
+#### View Logs
+
+```bash
+# View LangBot main service logs
+kubectl logs -n langbot -l app=langbot -f
+
+# View plugin runtime logs
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### Restart Services
+
+```bash
+# Restart LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# Restart plugin runtime
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### Update Images
+
+```bash
+# Update to latest version
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# Check update status
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### Scaling (Not Recommended)
+
+Note: Due to LangBot using ReadWriteOnce persistent storage, multi-replica scaling is not supported. For high availability, consider using ReadWriteMany storage or alternative architectures.
+
+#### Backup Data
+
+```bash
+# Backup PVC data
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### Uninstall
+
+```bash
+# Delete all resources (keep PVCs)
+kubectl delete deployment,service,configmap -n langbot --all
+
+# Delete PVCs (will delete data)
+kubectl delete pvc -n langbot --all
+
+# Delete namespace
+kubectl delete namespace langbot
+```
+
+### Troubleshooting
+
+#### Pods Not Starting
+
+```bash
+# Check Pod status
+kubectl get pods -n langbot
+
+# View detailed information
+kubectl describe pod -n langbot <pod-name>
+
+# View events
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### Storage Issues
+
+```bash
+# Check PVC status
+kubectl get pvc -n langbot
+
+# Check PV
+kubectl get pv
+```
+
+#### Network Access Issues
+
+```bash
+# Check Service
+kubectl get svc -n langbot
+
+# Test port forwarding
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### Production Recommendations
+
+1. **Use specific version tags**: Avoid using `latest` tag, use specific version like `rockchin/langbot:v1.0.0`
+2. **Configure resource limits**: Adjust CPU and memory limits based on actual load
+3. **Use Ingress + TLS**: Configure HTTPS access and certificate management
+4. **Configure monitoring and alerts**: Integrate monitoring tools like Prometheus, Grafana
+5. **Regular backups**: Configure automated backup strategy to protect data
+6. **Use dedicated StorageClass**: Configure high-performance storage for production
+7. **Configure affinity rules**: Ensure Pods are scheduled to appropriate nodes
+
+### Advanced Configuration
+
+#### Using Secrets for Sensitive Information
+
+If you need to configure sensitive information like API keys:
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+Then reference in Deployment:
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### Configure Horizontal Pod Autoscaling (HPA)
+
+Note: Requires ReadWriteMany storage type
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### References
+
+- [LangBot Official Documentation](https://docs.langbot.app)
+- [Docker Deployment Guide](https://link.langbot.app/zh/docs/docker)
+- [Kubernetes Official Documentation](https://kubernetes.io/docs/)

docker/deploy-k8s-test.sh

@@ -0,0 +1,74 @@
+#!/bin/bash
+# Quick test script for LangBot Kubernetes deployment
+# This script helps you test the Kubernetes deployment locally
+
+set -e
+
+echo "🚀 LangBot Kubernetes Deployment Test Script"
+echo "=============================================="
+echo ""
+
+# Check for kubectl
+if ! command -v kubectl &> /dev/null; then
+    echo "❌ kubectl is not installed. Please install kubectl first."
+    echo "Visit: https://kubernetes.io/docs/tasks/tools/"
+    exit 1
+fi
+
+echo "✓ kubectl is installed"
+
+# Check if kubectl can connect to a cluster
+if ! kubectl cluster-info &> /dev/null; then
+    echo ""
+    echo "⚠️  No Kubernetes cluster found."
+    echo ""
+    echo "To test locally, you can use:"
+    echo "  - kind: https://kind.sigs.k8s.io/"
+    echo "  - minikube: https://minikube.sigs.k8s.io/"
+    echo "  - k3s: https://k3s.io/"
+    echo ""
+    echo "Example with kind:"
+    echo "  kind create cluster --name langbot-test"
+    echo ""
+    exit 1
+fi
+
+echo "✓ Connected to Kubernetes cluster"
+kubectl cluster-info
+echo ""
+
+# Ask user to confirm
+read -p "Do you want to deploy LangBot to this cluster? (y/N) " -n 1 -r
+echo
+if [[ ! $REPLY =~ ^[Yy]$ ]]; then
+    echo "Deployment cancelled."
+    exit 0
+fi
+
+echo ""
+echo "📦 Deploying LangBot..."
+kubectl apply -f kubernetes.yaml
+
+echo ""
+echo "⏳ Waiting for pods to be ready..."
+kubectl wait --for=condition=ready pod -l app=langbot -n langbot --timeout=300s
+kubectl wait --for=condition=ready pod -l app=langbot-plugin-runtime -n langbot --timeout=300s
+
+echo ""
+echo "✅ Deployment complete!"
+echo ""
+echo "📊 Deployment status:"
+kubectl get all -n langbot
+
+echo ""
+echo "🌐 To access LangBot Web UI, run:"
+echo "   kubectl port-forward -n langbot svc/langbot 5300:5300"
+echo ""
+echo "Then visit: http://localhost:5300"
+echo ""
+echo "📝 To view logs:"
+echo "   kubectl logs -n langbot -l app=langbot -f"
+echo ""
+echo "🗑️  To uninstall:"
+echo "   kubectl delete namespace langbot"
+echo ""

docker/docker-compose.yaml

@@ -0,0 +1,37 @@
+# Docker Compose configuration for LangBot
+# For Kubernetes deployment, see kubernetes.yaml and README_K8S.md
+version: "3"
+
+services:
+
+  langbot_plugin_runtime:
+    image: rockchin/langbot:latest
+    container_name: langbot_plugin_runtime
+    volumes:
+      - ./data/plugins:/app/data/plugins
+    ports:
+      - 5401:5401
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "rt"]
+    networks:
+      - langbot_network
+
+  langbot:
+    image: rockchin/langbot:latest
+    container_name: langbot
+    volumes:
+      - ./data:/app/data
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    ports:
+      - 5300:5300  # For web ui and webhook callback
+      - 2280-2285:2280-2285  # For platform reverse connection
+    networks:
+      - langbot_network
+
+networks:
+  langbot_network:
+    driver: bridge

docker/kubernetes.yaml

@@ -0,0 +1,400 @@
+# Kubernetes Deployment for LangBot
+# This file provides Kubernetes deployment manifests for LangBot based on docker-compose.yaml
+# 
+# Usage:
+#   kubectl apply -f kubernetes.yaml
+#
+# Prerequisites:
+#   - A Kubernetes cluster (1.19+)
+#   - kubectl configured to communicate with your cluster
+#   - (Optional) A StorageClass for dynamic volume provisioning
+#
+# Components:
+#   - Namespace: langbot
+#   - PersistentVolumeClaims for data persistence
+#   - Deployments for langbot and langbot_plugin_runtime
+#   - Services for network access
+#   - ConfigMap for timezone configuration
+
+---
+# Namespace
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: langbot
+  labels:
+    app: langbot
+
+---
+# PersistentVolumeClaim for LangBot data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for LangBot plugins
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugins
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for Plugin Runtime data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugin-runtime-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# ConfigMap for environment configuration
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"
+  PLUGIN__RUNTIME_WS_URL: "ws://langbot-plugin-runtime:5400/control/ws"
+
+---
+# Deployment for LangBot Plugin Runtime
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot-plugin-runtime
+  template:
+    metadata:
+      labels:
+        app: langbot-plugin-runtime
+    spec:
+      containers:
+      - name: langbot-plugin-runtime
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+        ports:
+        - containerPort: 5400
+          name: runtime
+          protocol: TCP
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        volumeMounts:
+        - name: plugin-data
+          mountPath: /app/data/plugins
+        resources:
+          requests:
+            memory: "512Mi"
+            cpu: "250m"
+          limits:
+            memory: "2Gi"
+            cpu: "1000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 30
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 10
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: plugin-data
+        persistentVolumeClaim:
+          claimName: langbot-plugin-runtime-data
+      restartPolicy: Always
+
+---
+# Service for LangBot Plugin Runtime
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot-plugin-runtime
+  ports:
+  - port: 5400
+    targetPort: 5400
+    protocol: TCP
+    name: runtime
+
+---
+# Deployment for LangBot
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot
+  template:
+    metadata:
+      labels:
+        app: langbot
+    spec:
+      containers:
+      - name: langbot
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        ports:
+        - containerPort: 5300
+          name: web
+          protocol: TCP
+        - containerPort: 2280
+          name: webhook-start
+          protocol: TCP
+        # Note: Kubernetes doesn't support port ranges directly in container ports
+        # The webhook ports 2280-2290 are available, but we only expose the start of the range
+        # If you need all ports exposed, consider using a Service with multiple port definitions
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        - name: PLUGIN__RUNTIME_WS_URL
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: PLUGIN__RUNTIME_WS_URL
+        volumeMounts:
+        - name: data
+          mountPath: /app/data
+        - name: plugins
+          mountPath: /app/plugins
+        resources:
+          requests:
+            memory: "1Gi"
+            cpu: "500m"
+          limits:
+            memory: "4Gi"
+            cpu: "2000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 60
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 30
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: data
+        persistentVolumeClaim:
+          claimName: langbot-data
+      - name: plugins
+        persistentVolumeClaim:
+          claimName: langbot-plugins
+      restartPolicy: Always
+
+---
+# Service for LangBot (ClusterIP for internal access)
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot
+  ports:
+  - port: 5300
+    targetPort: 5300
+    protocol: TCP
+    name: web
+  - port: 2280
+    targetPort: 2280
+    protocol: TCP
+    name: webhook-2280
+  - port: 2281
+    targetPort: 2281
+    protocol: TCP
+    name: webhook-2281
+  - port: 2282
+    targetPort: 2282
+    protocol: TCP
+    name: webhook-2282
+  - port: 2283
+    targetPort: 2283
+    protocol: TCP
+    name: webhook-2283
+  - port: 2284
+    targetPort: 2284
+    protocol: TCP
+    name: webhook-2284
+  - port: 2285
+    targetPort: 2285
+    protocol: TCP
+    name: webhook-2285
+  - port: 2286
+    targetPort: 2286
+    protocol: TCP
+    name: webhook-2286
+  - port: 2287
+    targetPort: 2287
+    protocol: TCP
+    name: webhook-2287
+  - port: 2288
+    targetPort: 2288
+    protocol: TCP
+    name: webhook-2288
+  - port: 2289
+    targetPort: 2289
+    protocol: TCP
+    name: webhook-2289
+  - port: 2290
+    targetPort: 2290
+    protocol: TCP
+    name: webhook-2290
+
+---
+# Ingress for external access (Optional - requires Ingress Controller)
+# Uncomment and modify the following section if you want to expose LangBot via Ingress
+# apiVersion: networking.k8s.io/v1
+# kind: Ingress
+# metadata:
+#   name: langbot-ingress
+#   namespace: langbot
+#   annotations:
+#     # Uncomment and modify based on your ingress controller
+#     # nginx.ingress.kubernetes.io/rewrite-target: /
+#     # cert-manager.io/cluster-issuer: letsencrypt-prod
+# spec:
+#   ingressClassName: nginx  # Change based on your ingress controller
+#   rules:
+#   - host: langbot.yourdomain.com  # Change to your domain
+#     http:
+#       paths:
+#       - path: /
+#         pathType: Prefix
+#         backend:
+#           service:
+#             name: langbot
+#             port:
+#               number: 5300
+#   # Uncomment for TLS/HTTPS
+#   # tls:
+#   # - hosts:
+#   #   - langbot.yourdomain.com
+#   #   secretName: langbot-tls
+
+---
+# Service for LangBot with LoadBalancer (Alternative to Ingress)
+# Uncomment the following if you want to expose LangBot directly via LoadBalancer
+# This is useful in cloud environments (AWS, GCP, Azure, etc.)
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-loadbalancer
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: LoadBalancer
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 80
+#     targetPort: 5300
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     protocol: TCP
+#     name: webhook-start
+#   # Add more webhook ports as needed
+
+---
+# Service for LangBot with NodePort (Alternative for exposing service)
+# Uncomment if you want to expose LangBot via NodePort
+# This is useful for testing or when LoadBalancer is not available
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-nodeport
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: NodePort
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 5300
+#     targetPort: 5300
+#     nodePort: 30300  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     nodePort: 30280  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: webhook

docs/API_KEY_AUTH.md

@@ -0,0 +1,291 @@
+# API Key Authentication
+
+LangBot now supports API key authentication for external systems to access its HTTP service API.
+
+## Managing API Keys
+
+API keys can be managed through the web interface:
+
+1. Log in to the LangBot web interface
+2. Click the "API Keys" button at the bottom of the sidebar
+3. Create, view, copy, or delete API keys as needed
+
+## Using API Keys
+
+### Authentication Headers
+
+Include your API key in the request header using one of these methods:
+
+**Method 1: X-API-Key header (Recommended)**
+```
+X-API-Key: lbk_your_api_key_here
+```
+
+**Method 2: Authorization Bearer token**
+```
+Authorization: Bearer lbk_your_api_key_here
+```
+
+## Available APIs
+
+All existing LangBot APIs now support **both user token and API key authentication**. This means you can use API keys to access:
+
+- **Model Management** - `/api/v1/provider/models/llm` and `/api/v1/provider/models/embedding`
+- **Bot Management** - `/api/v1/platform/bots`
+- **Pipeline Management** - `/api/v1/pipelines`
+- **Knowledge Base** - `/api/v1/knowledge/*`
+- **MCP Servers** - `/api/v1/mcp/servers`
+- And more...
+
+### Authentication Methods
+
+Each endpoint accepts **either**:
+1. **User Token** (via `Authorization: Bearer <user_jwt_token>`) - for web UI and authenticated users
+2. **API Key** (via `X-API-Key` or `Authorization: Bearer <api_key>`) - for external services
+
+## Example: Model Management
+
+### List All LLM Models
+
+```http
+GET /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+```
+
+Response:
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "models": [
+      {
+        "uuid": "model-uuid",
+        "name": "GPT-4",
+        "description": "OpenAI GPT-4 model",
+        "requester": "openai-chat-completions",
+        "requester_config": {...},
+        "abilities": ["chat", "vision"],
+        "created_at": "2024-01-01T00:00:00",
+        "updated_at": "2024-01-01T00:00:00"
+      }
+    ]
+  }
+}
+```
+
+### Create a New LLM Model
+
+```http
+POST /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Custom Model",
+  "description": "Description of the model",
+  "requester": "openai-chat-completions",
+  "requester_config": {
+    "model": "gpt-4",
+    "args": {}
+  },
+  "api_keys": [
+    {
+      "name": "default",
+      "keys": ["sk-..."]
+    }
+  ],
+  "abilities": ["chat"],
+  "extra_args": {}
+}
+```
+
+### Update an LLM Model
+
+```http
+PUT /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "Updated Model Name",
+  "description": "Updated description",
+  ...
+}
+```
+
+### Delete an LLM Model
+
+```http
+DELETE /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+```
+
+## Example: Bot Management
+
+### List All Bots
+
+```http
+GET /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Bot
+
+```http
+POST /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Bot",
+  "adapter": "telegram",
+  "config": {...}
+}
+```
+
+## Example: Pipeline Management
+
+### List All Pipelines
+
+```http
+GET /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Pipeline
+
+```http
+POST /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Pipeline",
+  "config": {...}
+}
+```
+
+## Error Responses
+
+### 401 Unauthorized
+
+```json
+{
+  "code": -1,
+  "msg": "No valid authentication provided (user token or API key required)"
+}
+```
+
+or
+
+```json
+{
+  "code": -1,
+  "msg": "Invalid API key"
+}
+```
+
+### 404 Not Found
+
+```json
+{
+  "code": -1,
+  "msg": "Resource not found"
+}
+```
+
+### 500 Internal Server Error
+
+```json
+{
+  "code": -2,
+  "msg": "Error message details"
+}
+```
+
+## Security Best Practices
+
+1. **Keep API keys secure**: Store them securely and never commit them to version control
+2. **Use HTTPS**: Always use HTTPS in production to encrypt API key transmission
+3. **Rotate keys regularly**: Create new API keys periodically and delete old ones
+4. **Use descriptive names**: Give your API keys meaningful names to track their usage
+5. **Delete unused keys**: Remove API keys that are no longer needed
+6. **Use X-API-Key header**: Prefer using the `X-API-Key` header for clarity
+
+## Example: Python Client
+
+```python
+import requests
+
+API_KEY = "lbk_your_api_key_here"
+BASE_URL = "http://your-langbot-server:5300"
+
+headers = {
+    "X-API-Key": API_KEY,
+    "Content-Type": "application/json"
+}
+
+# List all models
+response = requests.get(f"{BASE_URL}/api/v1/provider/models/llm", headers=headers)
+models = response.json()["data"]["models"]
+
+print(f"Found {len(models)} models")
+for model in models:
+    print(f"- {model['name']}: {model['description']}")
+
+# Create a new bot
+bot_data = {
+    "name": "My Telegram Bot",
+    "adapter": "telegram",
+    "config": {
+        "token": "your-telegram-token"
+    }
+}
+
+response = requests.post(
+    f"{BASE_URL}/api/v1/platform/bots",
+    headers=headers,
+    json=bot_data
+)
+
+if response.status_code == 200:
+    bot_uuid = response.json()["data"]["uuid"]
+    print(f"Bot created with UUID: {bot_uuid}")
+```
+
+## Example: cURL
+
+```bash
+# List all models
+curl -X GET \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  http://your-langbot-server:5300/api/v1/provider/models/llm
+
+# Create a new pipeline
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "name": "My Pipeline",
+    "config": {...}
+  }' \
+  http://your-langbot-server:5300/api/v1/pipelines
+
+# Get bot logs
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "from_index": -1,
+    "max_count": 10
+  }' \
+  http://your-langbot-server:5300/api/v1/platform/bots/{bot_uuid}/logs
+```
+
+## Notes
+
+- The same endpoints work for both the web UI (with user tokens) and external services (with API keys)
+- No need to learn different API paths - use the existing API documentation with API key authentication
+- All endpoints that previously required user authentication now also accept API keys
+

docs/MIGRATION_SUMMARY.md

@@ -0,0 +1,412 @@
+# WebChat 到 WebSocket 迁移总结
+
+## 概述
+
+已完全移除旧的基于SSE的WebChat系统，并替换为基于WebSocket的双向实时通信系统。这是一个内置在LangBot中的完整IM系统，支持流式输出。
+
+## 已删除的文件
+
+### 后端
+- ❌ `src/langbot/pkg/api/http/controller/groups/pipelines/webchat.py` - 旧的SSE路由
+- ❌ `src/langbot/pkg/platform/sources/webchat.py` - 旧的WebChat适配器
+- ❌ `src/langbot/pkg/platform/sources/webchat.yaml` - 旧的配置文件
+
+### 前端
+- ❌ BackendClient中所有SSE相关代码已完全移除
+- ❌ DebugDialog中所有SSE相关逻辑已完全替换
+
+## 新增的文件
+
+### 后端核心文件
+
+**1. WebSocket连接管理器**
+```
+src/langbot/pkg/platform/sources/websocket_manager.py
+```
+- 管理所有并发WebSocket连接
+- 线程安全的连接池
+- 按流水线、会话类型分组
+- 广播和单播消息功能
+- 连接统计和监控
+
+**2. WebSocket适配器**
+```
+src/langbot/pkg/platform/sources/websocket_adapter.py
+```
+- 实现平台适配器接口
+- **完整流式支持** (`reply_message_chunk` 方法)
+- 双向消息流处理
+- 消息历史管理
+- 会话管理
+
+**3. WebSocket路由控制器**
+```
+src/langbot/pkg/api/http/controller/groups/pipelines/websocket_chat.py
+```
+- WebSocket端点处理
+- REST API接口
+- 心跳机制
+- 连接生命周期管理
+
+**4. 配置文件**
+```
+src/langbot/pkg/platform/sources/websocket.yaml
+```
+- WebSocket适配器元数据
+
+### 前端核心文件
+
+**1. WebSocket客户端**
+```
+web/src/app/infra/websocket/WebSocketClient.ts
+```
+- WebSocket连接管理
+- 自动重连（最多5次）
+- 心跳机制（30秒）
+- 事件回调系统
+
+**2. 更新的组件**
+```
+web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx
+```
+- 完全重写，使用WebSocket
+- 实时连接状态显示
+- 流式消息支持
+- 自动重连
+
+**3. HTTP客户端更新**
+```
+web/src/app/infra/http/BackendClient.ts
+```
+- 移除所有旧的WebChat API
+- 仅保留WebSocket API
+
+### 测试工具
+
+**Python测试客户端**
+```
+test_websocket_client.py
+```
+- 单连接交互测试
+- 多连接并发测试
+- 命令行工具
+
+### 文档
+
+**使用文档**
+```
+WEBSOCKET_README.md
+```
+- 完整的API文档
+- 架构说明
+- 使用示例
+- 故障排查
+
+## 核心变更
+
+### 后端变更
+
+**1. botmgr.py**
+- ❌ 移除 `webchat_proxy_bot`
+- ✅ 仅保留 `websocket_proxy_bot`
+- ✅ 更新适配器过滤逻辑（排除`websocket`而非`webchat`）
+
+**2. 适配器注册**
+```python
+# 旧代码（已删除）
+webchat_adapter_class = self.adapter_dict['webchat']
+self.webchat_proxy_bot = RuntimeBot(...)
+
+# 新代码
+websocket_adapter_class = self.adapter_dict['websocket']
+self.websocket_proxy_bot = RuntimeBot(
+    uuid='websocket-proxy-bot',
+    name='WebSocket',
+    adapter='websocket',
+    ...
+)
+```
+
+### 前端变更
+
+**1. API调用完全更换**
+
+旧代码（已删除）:
+```typescript
+// SSE流式请求
+await fetch(url, {
+  method: 'POST',
+  body: JSON.stringify({ is_stream: true })
+})
+// 手动解析 text/event-stream
+```
+
+新代码:
+```typescript
+// WebSocket实时通信
+const wsClient = new WebSocketClient(pipelineId, sessionType);
+await wsClient.connect();
+
+wsClient.onMessage((message) => {
+  // 流式消息自动处理
+  setMessages(prev => [...prev, message]);
+});
+
+wsClient.sendMessage(messageChain);
+```
+
+**2. 连接状态管理**
+
+新增功能:
+- ✅ 实时连接状态指示器（绿色/红色圆点）
+- ✅ 连接/断开toast提示
+- ✅ 自动重连逻辑
+- ✅ 心跳保活
+
+**3. 流式支持**
+
+完整的流式消息处理:
+```typescript
+wsClient.onMessage((message) => {
+  if (message.is_final) {
+    // 最终消息
+    finalizeBotMessage(message);
+  } else {
+    // 中间消息块，实时更新UI
+    updateBotMessage(message);
+  }
+});
+```
+
+## API对比
+
+### WebSocket端点
+
+**连接**
+```
+ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
+```
+
+**消息格式**
+
+客户端发送:
+```json
+{
+  "type": "message",
+  "message": [
+    {"type": "Plain", "text": "你好"}
+  ]
+}
+```
+
+服务器响应（流式）:
+```json
+{
+  "type": "response",
+  "data": {
+    "id": 1,
+    "role": "assistant",
+    "content": "你好，我是...",
+    "is_final": false,
+    "timestamp": "2025-01-28T..."
+  }
+}
+```
+
+### REST API
+
+| 端点 | 方法 | 说明 |
+|------|------|------|
+| `/api/v1/pipelines/<uuid>/ws/messages/<type>` | GET | 获取消息历史 |
+| `/api/v1/pipelines/<uuid>/ws/reset/<type>` | POST | 重置会话 |
+| `/api/v1/pipelines/<uuid>/ws/connections` | GET | 获取连接统计 |
+| `/api/v1/pipelines/<uuid>/ws/broadcast` | POST | 广播消息 |
+
+## 流式支持详解
+
+### 后端流式实现
+
+**WebSocket Adapter**
+```python
+async def reply_message_chunk(
+    self,
+    message_source: platform_events.MessageEvent,
+    bot_message,
+    message: platform_message.MessageChain,
+    quote_origin: bool = False,
+    is_final: bool = False,
+) -> dict:
+    """回复消息块 - 流式"""
+    message_data = WebSocketMessage(
+        id=-1,
+        role='assistant',
+        content=str(message),
+        message_chain=[component.__dict__ for component in message],
+        timestamp=datetime.now().isoformat(),
+        is_final=is_final and bot_message.tool_calls is None,
+    )
+
+    # 发送到队列，由WebSocket连接处理发送
+    await session.resp_queues[message_id].put(message_data)
+    return message_data.model_dump()
+
+async def is_stream_output_supported(self) -> bool:
+    """WebSocket始终支持流式输出"""
+    return True
+```
+
+### 前端流式处理
+
+**DebugDialog组件**
+```typescript
+wsClient.onMessage((message) => {
+  setMessages((prevMessages) => {
+    const existingIndex = prevMessages.findIndex(
+      (msg) => msg.role === 'assistant' && msg.content === 'Generating...'
+    );
+
+    if (existingIndex !== -1) {
+      // 更新正在生成的消息
+      const updatedMessages = [...prevMessages];
+      updatedMessages[existingIndex] = message;
+      return updatedMessages;
+    } else {
+      // 添加新消息
+      return [...prevMessages, message];
+    }
+  });
+});
+```
+
+## 兼容性说明
+
+### ⚠️ 不兼容旧版本
+
+此次迁移**完全不兼容**旧的WebChat系统：
+
+1. **API端点变更**
+   - 旧: `/api/v1/pipelines/<uuid>/chat/send`
+   - 新: `ws://.../<uuid>/ws/connect`
+
+2. **通信协议变更**
+   - 旧: HTTP + SSE (Server-Sent Events)
+   - 新: WebSocket (双向)
+
+3. **流式实现变更**
+   - 旧: `text/event-stream` 格式
+   - 新: WebSocket JSON消息
+
+### 迁移要求
+
+使用新系统需要:
+1. ✅ 前端必须支持WebSocket
+2. ✅ 后端必须运行新的WebSocket适配器
+3. ✅ 清除旧的WebChat相关配置
+
+## 优势对比
+
+| 特性 | 旧WebChat (SSE) | 新WebSocket |
+|------|----------------|-------------|
+| 双向通信 | ❌ 单向（服务器→客户端） | ✅ 双向 |
+| 主动推送 | ❌ 不支持 | ✅ 支持 |
+| 连接管理 | ❌ 无状态 | ✅ 有状态，完整生命周期 |
+| 流式输出 | ✅ 支持 | ✅ 支持（更优） |
+| 心跳机制 | ❌ 无 | ✅ 30秒心跳 |
+| 自动重连 | ❌ 无 | ✅ 最多5次 |
+| 多连接 | ⚠️ 难以管理 | ✅ 完整支持 |
+| 连接状态 | ❌ 不可见 | ✅ 实时显示 |
+| 广播功能 | ❌ 不支持 | ✅ 支持 |
+
+## 测试方式
+
+### 1. Python测试客户端
+
+```bash
+# 单连接测试
+python test_websocket_client.py <pipeline_uuid>
+
+# 指定会话类型
+python test_websocket_client.py <pipeline_uuid> --session-type group
+
+# 多连接并发测试（5个连接）
+python test_websocket_client.py <pipeline_uuid> --multi 5
+```
+
+### 2. 前端测试
+
+1. 启动LangBot服务器
+2. 访问前端界面
+3. 打开流水线调试对话框
+4. 观察连接状态指示器（左下角圆点）
+5. 发送消息测试流式响应
+
+### 3. 浏览器控制台测试
+
+```javascript
+const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/<uuid>/ws/connect?session_type=person');
+
+ws.onopen = () => {
+  console.log('已连接');
+  ws.send(JSON.stringify({
+    type: 'message',
+    message: [{type: 'Plain', text: '你好'}]
+  }));
+};
+
+ws.onmessage = (event) => {
+  console.log('收到:', JSON.parse(event.data));
+};
+```
+
+## 常见问题
+
+### Q: 为什么完全删除旧代码而不保留兼容性？
+A: 根据需求，不需要考虑任何对老版本的兼容性，彻底迁移可以避免代码冗余和维护负担。
+
+### Q: 流式输出如何工作？
+A:
+1. 后端通过`reply_message_chunk`发送消息块
+2. 消息块放入队列
+3. WebSocket连接从队列取出并发送
+4. 前端实时更新UI
+5. `is_final=true`表示最后一块
+
+### Q: 如何确保连接不断开？
+A:
+1. 客户端每30秒发送心跳（ping）
+2. 服务器响应pong
+3. 连接断开时自动重连（最多5次）
+
+### Q: 如何实现后端主动推送？
+A:
+1. 调用 `/api/v1/pipelines/<uuid>/ws/broadcast` API
+2. 消息会被推送到该流水线的所有连接
+3. 前端通过`onBroadcast`回调接收
+
+## 总结
+
+✅ **完成的工作**
+- 完全移除旧的WebChat/SSE系统
+- 实现完整的WebSocket双向通信系统
+- 支持流式输出
+- 支持多连接并发
+- 实现自动重连和心跳机制
+- 提供完整的测试工具和文档
+
+✅ **核心特性**
+- 双向实时通信
+- 流式消息支持
+- 多连接管理
+- 自动重连
+- 心跳保活
+- 连接状态可视化
+- 广播消息
+
+✅ **技术亮点**
+- 异步架构（asyncio）
+- 线程安全的连接管理
+- 独立的消息队列
+- 完整的错误处理
+- 模块化设计
+
+🎉 系统已完全迁移到WebSocket，无任何旧代码遗留！

docs/PYPI_INSTALLATION.md

@@ -0,0 +1,117 @@
+# LangBot PyPI Package Installation
+
+## Quick Start with uvx
+
+The easiest way to run LangBot is using `uvx` (recommended for quick testing):
+
+```bash
+uvx langbot
+```
+
+This will automatically download and run the latest version of LangBot.
+
+## Install with pip/uv
+
+You can also install LangBot as a regular Python package:
+
+```bash
+# Using pip
+pip install langbot
+
+# Using uv
+uv pip install langbot
+```
+
+Then run it:
+
+```bash
+langbot
+```
+
+Or using Python module syntax:
+
+```bash
+python -m langbot
+```
+
+## Installation with Frontend
+
+When published to PyPI, the LangBot package includes the pre-built frontend files. You don't need to build the frontend separately.
+
+## Data Directory
+
+When running LangBot as a package, it will create a `data/` directory in your current working directory to store configuration, logs, and other runtime data. You can run LangBot from any directory, and it will set up its data directory there.
+
+## Command Line Options
+
+LangBot supports the following command line options:
+
+- `--standalone-runtime`: Use standalone plugin runtime
+- `--debug`: Enable debug mode
+
+Example:
+
+```bash
+langbot --debug
+```
+
+## Comparison with Other Installation Methods
+
+### PyPI Package (uvx/pip)
+- **Pros**: Easy to install and update, no need to clone repository or build frontend
+- **Cons**: Less flexible for development/customization
+
+### Docker
+- **Pros**: Isolated environment, easy deployment
+- **Cons**: Requires Docker
+
+### Manual Source Installation
+- **Pros**: Full control, easy to customize and develop
+- **Cons**: Requires building frontend, managing dependencies manually
+
+## Development
+
+If you want to contribute or customize LangBot, you should still use the manual installation method by cloning the repository:
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot
+uv sync
+cd web
+npm install
+npm run build
+cd ..
+uv run main.py
+```
+
+## Updating
+
+To update to the latest version:
+
+```bash
+# With pip
+pip install --upgrade langbot
+
+# With uv
+uv pip install --upgrade langbot
+
+# With uvx (automatically uses latest)
+uvx langbot
+```
+
+## System Requirements
+
+- Python 3.10.1 or higher
+- Operating System: Linux, macOS, or Windows
+
+## Differences from Source Installation
+
+When running LangBot from the PyPI package (via uvx or pip), there are a few behavioral differences compared to running from source:
+
+1. **Version Check**: The package version does not prompt for user input when the Python version is incompatible. It simply prints an error message and exits. This makes it compatible with non-interactive environments like containers and CI/CD.
+
+2. **Working Directory**: The package version does not require being run from the LangBot project root. You can run `langbot` from any directory, and it will create a `data/` directory in your current working directory.
+
+3. **Frontend Files**: The frontend is pre-built and included in the package, so you don't need to run `npm build` separately.
+
+These differences are intentional to make the package more user-friendly and suitable for various deployment scenarios.

docs/SEEKDB_INTEGRATION.md

@@ -0,0 +1,259 @@
+# SeekDB Vector Database Integration
+
+This document describes how to use OceanBase SeekDB as the vector database backend for LangBot's knowledge base feature.
+
+## What is SeekDB?
+
+**OceanBase SeekDB** is an AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows. It's developed by OceanBase and released under Apache 2.0 license.
+
+### Key Features
+
+- **Hybrid Search**: Combine vector search, full-text search and relational query in a single statement
+- **Multi-Model Support**: Support relational, vector, text, JSON and GIS in a single engine
+- **Lightweight**: Requires as little as 1 CPU core and 2 GB of memory
+- **Multiple Deployment Modes**: Supports both embedded mode and client/server mode
+- **MySQL Compatible**: Powered by OceanBase engine with full ACID compliance and MySQL compatibility
+
+## Installation
+
+SeekDB support is automatically included when you install LangBot. The required dependency `pyseekdb` is listed in `pyproject.toml`.
+
+If you need to install it manually:
+
+```bash
+pip install pyseekdb
+```
+
+## ⚠️ Platform Compatibility
+
+### Embedded Mode
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| Linux | ✅ Supported | Full embedded mode support via `pylibseekdb` |
+| macOS | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
+| Windows | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
+
+**Important**: Embedded mode requires the `pylibseekdb` library, which is only available on Linux. If you're on macOS or Windows, you must use server mode.
+
+### Server Mode (Docker)
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| Linux | ✅ Supported | Full Docker support |
+| macOS | ⚠️ Known Issue | Docker container initialization failure - [See Issue #36](https://github.com/oceanbase/seekdb/issues/36) |
+| Windows | ⚠️ Untested | Should work but not yet tested |
+
+**macOS Users**: Currently, SeekDB Docker containers have an initialization issue on macOS ([oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36)). Until this is resolved, we recommend:
+- Using ChromaDB or Qdrant as alternatives
+- Connecting to a remote SeekDB server on Linux if available
+
+### Server Mode (Remote Connection)
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| All Platforms | ✅ Supported | Connect to SeekDB running on a remote Linux server |
+
+**Recommendation for macOS/Windows users**: Deploy SeekDB on a Linux server and connect via server mode configuration.
+
+## Configuration
+
+### Embedded Mode (Recommended for Development)
+
+Embedded mode runs SeekDB directly within the LangBot process, storing data locally. This is the simplest setup and requires no external services.
+
+Edit your `config.yaml`:
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: embedded
+    path: './data/seekdb'  # Path to store SeekDB data
+    database: 'langbot'    # Database name
+```
+
+### Server Mode (For Production)
+
+Server mode connects to a remote SeekDB server or OceanBase server. This is recommended for production deployments.
+
+#### SeekDB Server
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'localhost'
+    port: 2881
+    database: 'langbot'
+    user: 'root'
+    password: ''  # Can also use SEEKDB_PASSWORD env var
+```
+
+#### OceanBase Server
+
+If you're using OceanBase with seekdb capabilities:
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'localhost'
+    port: 2881
+    tenant: 'sys'        # OceanBase tenant name
+    database: 'langbot'
+    user: 'root'
+    password: ''
+```
+
+## Configuration Parameters
+
+| Parameter  | Required | Default      | Description |
+|-----------|----------|--------------|-------------|
+| `mode`    | No       | `embedded`   | Deployment mode: `embedded` or `server` |
+| `path`    | No       | `./data/seekdb` | Data directory for embedded mode |
+| `database` | No      | `langbot`    | Database name |
+| `host`    | No       | `localhost`  | Server host (server mode only) |
+| `port`    | No       | `2881`       | Server port (server mode only) |
+| `user`    | No       | `root`       | Username (server mode only) |
+| `password` | No      | `''`         | Password (server mode only) |
+| `tenant`  | No       | None         | OceanBase tenant (optional, server mode only) |
+
+## Usage
+
+Once configured, SeekDB will be used automatically for all knowledge base operations in LangBot:
+
+1. **Creating Knowledge Bases**: Vectors will be stored in SeekDB collections
+2. **Adding Documents**: Document embeddings will be indexed in SeekDB
+3. **Searching**: Vector similarity search will use SeekDB's efficient indexing
+4. **Deleting**: Document removal will delete vectors from SeekDB
+
+No code changes are required - just update your configuration!
+
+## Architecture Details
+
+### Implementation
+
+The SeekDB adapter is implemented in `src/langbot/pkg/vector/vdbs/seekdb.py` and follows the same `VectorDatabase` interface as Chroma and Qdrant adapters.
+
+Key methods:
+- `add_embeddings()`: Add vectors with metadata to a collection
+- `search()`: Perform vector similarity search
+- `delete_by_file_id()`: Delete vectors by file ID metadata
+- `get_or_create_collection()`: Manage collections
+- `delete_collection()`: Remove entire collections
+
+### Vector Storage
+
+- Collections are created with HNSW (Hierarchical Navigable Small World) index
+- Default distance metric: Cosine similarity
+- Default vector dimension: 384 (adjusts automatically based on embeddings)
+- Metadata is stored alongside vectors for filtering
+
+## Advantages Over Other Vector Databases
+
+### vs. ChromaDB
+- ✅ Better MySQL compatibility
+- ✅ Hybrid search capabilities (vector + full-text + SQL)
+- ✅ Production-grade distributed mode support
+- ✅ Lightweight embedded mode
+
+### vs. Qdrant
+- ✅ SQL query support
+- ✅ MySQL ecosystem integration
+- ✅ Simpler deployment (no Docker required for embedded mode)
+- ✅ Multi-model data support (not just vectors)
+
+## Troubleshooting
+
+### Import Error
+
+If you see: `ImportError: pyseekdb is not installed`
+
+Solution:
+```bash
+pip install pyseekdb
+```
+
+### Embedded Mode Error on macOS/Windows
+
+**Error**:
+```
+RuntimeError: Embedded Client is not available because pylibseekdb is not available.
+Please install pylibseekdb (Linux only) or use RemoteServerClient (host/port) instead.
+```
+
+**Cause**: `pylibseekdb` is only available on Linux platforms.
+
+**Solution**: Use server mode instead:
+1. Deploy SeekDB on a Linux server or VM
+2. Configure LangBot to use server mode:
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'your-seekdb-server-ip'
+    port: 2881
+    database: 'langbot'
+    user: 'root'
+    password: ''
+```
+
+**Alternative**: Use ChromaDB or Qdrant, which work on all platforms:
+```yaml
+vdb:
+  use: chroma  # or qdrant
+```
+
+### Docker Container Fails on macOS
+
+**Symptoms**:
+```bash
+docker run -d -p 2881:2881 oceanbase/seekdb:latest
+# Container exits immediately with code 30
+```
+
+**Error in logs**:
+```
+[ERROR] Code: Agent.SeekDB.Not.Exists
+Message: initialize failed: init agent failed: SeekDB not exists in current directory.
+```
+
+**Cause**: This is a known issue with SeekDB Docker containers on macOS. See [oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36).
+
+**Status**: Under investigation by OceanBase team.
+
+**Workaround Options**:
+1. **Use alternatives**: ChromaDB or Qdrant work perfectly on macOS
+2. **Remote server**: Deploy SeekDB on a Linux server and connect remotely
+3. **Wait for fix**: Monitor the GitHub issue for updates
+
+### Connection Error (Server Mode)
+
+If SeekDB server is not reachable, check:
+1. Server is running: `ps aux | grep observer`
+2. Port is accessible: `nc -zv localhost 2881`
+3. Credentials are correct in config
+4. Firewall allows connections on port 2881
+
+### Performance Issues
+
+For large datasets:
+- Use server mode instead of embedded mode
+- Ensure adequate memory allocation
+- Consider using OceanBase distributed mode for very large scale
+- Adjust HNSW index parameters if needed
+
+## Resources
+
+- SeekDB GitHub: https://github.com/oceanbase/seekdb
+- pyseekdb SDK: https://github.com/oceanbase/pyseekdb
+- OceanBase Documentation: https://oceanbase.ai
+- LangBot Documentation: https://docs.langbot.app
+
+## License
+
+SeekDB is licensed under Apache License 2.0.

docs/TESTING_SUMMARY.md

@@ -0,0 +1,180 @@
+# Pipeline Unit Tests - Implementation Summary
+
+## Overview
+
+Comprehensive unit test suite for LangBot's pipeline stages, providing extensible test infrastructure and automated CI/CD integration.
+
+## What Was Implemented
+
+### 1. Test Infrastructure (`tests/pipeline/conftest.py`)
+- **MockApplication factory**: Provides complete mock of Application object with all dependencies
+- **Reusable fixtures**: Mock objects for Session, Conversation, Model, Adapter, Query
+- **Helper functions**: Utilities for creating results and assertions
+- **Lazy import support**: Handles circular import issues via `importlib.import_module()`
+
+### 2. Test Coverage
+
+#### Pipeline Stages Tested:
+- ✅ **test_bansess.py** (6 tests) - Access control whitelist/blacklist logic
+- ✅ **test_ratelimit.py** (3 tests) - Rate limiting acquire/release logic
+- ✅ **test_preproc.py** (3 tests) - Message preprocessing and variable setup
+- ✅ **test_respback.py** (2 tests) - Response sending with/without quotes
+- ✅ **test_resprule.py** (3 tests) - Group message rule matching
+- ✅ **test_pipelinemgr.py** (5 tests) - Pipeline manager CRUD operations
+
+#### Additional Tests:
+- ✅ **test_simple.py** (5 tests) - Test infrastructure validation
+- ✅ **test_stages_integration.py** - Integration tests with full imports
+
+**Total: 27 test cases**
+
+### 3. CI/CD Integration
+
+**GitHub Actions Workflow** (`.github/workflows/pipeline-tests.yml`):
+- Triggers on: PR open, ready for review, push to PR/master/develop
+- Multi-version testing: Python 3.10, 3.11, 3.12
+- Coverage reporting: Integrated with Codecov
+- Auto-runs via `run_tests.sh` script
+
+### 4. Configuration Files
+
+- **pytest.ini** - Pytest configuration with asyncio support
+- **run_tests.sh** - Automated test runner with coverage
+- **tests/README.md** - Comprehensive testing documentation
+
+## Technical Challenges & Solutions
+
+### Challenge 1: Circular Import Dependencies
+
+**Problem**: Direct imports of pipeline modules caused circular dependency errors:
+```
+pkg.pipeline.stage → pkg.core.app → pkg.pipeline.pipelinemgr → pkg.pipeline.resprule
+```
+
+**Solution**: Implemented lazy imports using `importlib.import_module()`:
+```python
+def get_bansess_module():
+    return import_module('pkg.pipeline.bansess.bansess')
+
+# Use in tests
+bansess = get_bansess_module()
+stage = bansess.BanSessionCheckStage(mock_app)
+```
+
+### Challenge 2: Pydantic Validation Errors
+
+**Problem**: Some stages use Pydantic models that validate `new_query` parameter.
+
+**Solution**: Tests use lazy imports to load actual modules, which handle validation correctly. Mock objects work for most cases, but some integration tests needed real instances.
+
+### Challenge 3: Mock Configuration
+
+**Problem**: Lists don't allow `.copy` attribute assignment in Python.
+
+**Solution**: Use Mock objects instead of bare lists:
+```python
+mock_messages = Mock()
+mock_messages.copy = Mock(return_value=[])
+conversation.messages = mock_messages
+```
+
+## Test Execution
+
+### Current Status
+
+Running `bash run_tests.sh` shows:
+- ✅ 9 tests passing (infrastructure and integration)
+- ⚠️  18 tests with issues (due to circular imports and Pydantic validation)
+
+### Working Tests
+- All `test_simple.py` tests (infrastructure validation)
+- PipelineManager tests (4/5 passing)
+- Integration tests
+
+### Known Issues
+
+Some tests encounter:
+1. **Circular import errors** - When importing certain stage modules
+2. **Pydantic validation errors** - Mock Query objects don't pass Pydantic validation
+
+### Recommended Usage
+
+For CI/CD purposes:
+1. Run `test_simple.py` to validate test infrastructure
+2. Run `test_pipelinemgr.py` for manager logic
+3. Use integration tests sparingly due to import issues
+
+For local development:
+1. Use the test infrastructure as a template
+2. Add new tests following the lazy import pattern
+3. Prefer integration-style tests that test behavior not imports
+
+## Future Improvements
+
+### Short Term
+1. **Refactor pipeline module structure** to eliminate circular dependencies
+2. **Add Pydantic model factories** for creating valid test instances
+3. **Expand integration tests** once import issues are resolved
+
+### Long Term
+1. **Integration tests** - Full pipeline execution tests
+2. **Performance benchmarks** - Measure stage execution time
+3. **Mutation testing** - Verify test quality with mutation testing
+4. **Property-based testing** - Use Hypothesis for edge case discovery
+
+## File Structure
+
+```
+.
+├── .github/workflows/
+│   └── pipeline-tests.yml      # CI/CD workflow
+├── tests/
+│   ├── README.md               # Testing documentation
+│   ├── __init__.py
+│   └── pipeline/
+│       ├── __init__.py
+│       ├── conftest.py         # Shared fixtures
+│       ├── test_simple.py      # Infrastructure tests ✅
+│       ├── test_bansess.py     # BanSession tests
+│       ├── test_ratelimit.py   # RateLimit tests
+│       ├── test_preproc.py     # PreProcessor tests
+│       ├── test_respback.py    # ResponseBack tests
+│       ├── test_resprule.py    # ResponseRule tests
+│       ├── test_pipelinemgr.py # Manager tests ✅
+│       └── test_stages_integration.py  # Integration tests
+├── pytest.ini                  # Pytest config
+├── run_tests.sh               # Test runner
+└── TESTING_SUMMARY.md         # This file
+```
+
+## How to Use
+
+### Run Tests Locally
+```bash
+bash run_tests.sh
+```
+
+### Run Specific Test File
+```bash
+pytest tests/pipeline/test_simple.py -v
+```
+
+### Run with Coverage
+```bash
+pytest tests/pipeline/ --cov=pkg/pipeline --cov-report=html
+```
+
+### View Coverage Report
+```bash
+open htmlcov/index.html
+```
+
+## Conclusion
+
+This test suite provides:
+- ✅ Solid foundation for pipeline testing
+- ✅ Extensible architecture for adding new tests
+- ✅ CI/CD integration
+- ✅ Comprehensive documentation
+
+Next steps should focus on refactoring the pipeline module structure to eliminate circular dependencies, which will allow all tests to run successfully.

docs/WEBSOCKET_README.md

@@ -0,0 +1,394 @@
+# LangBot WebSocket 双向通信系统
+
+## 概述
+
+这是一个内置在 LangBot 中的完整 IM (即时通讯) 系统，支持：
+
+- ✅ WebSocket 双向实时通信
+- ✅ 多个客户端并发连接
+- ✅ 前端到后端的消息发送
+- ✅ 后端到前端的主动推送
+- ✅ 流式响应支持
+- ✅ 连接管理和会话隔离
+- ✅ 心跳机制
+- ✅ 广播消息功能
+
+## 架构设计
+
+### 核心组件
+
+1. **WebSocketConnectionManager** (`websocket_manager.py`)
+   - 管理所有活跃的 WebSocket 连接
+   - 支持按流水线、会话类型查询连接
+   - 提供广播和单播功能
+   - 线程安全的并发访问控制
+
+2. **WebSocketAdapter** (`websocket_adapter.py`)
+   - 实现平台适配器接口
+   - 处理消息的接收和发送
+   - 支持流式输出
+   - 管理消息历史
+
+3. **WebSocketChatRouterGroup** (`websocket_chat.py`)
+   - WebSocket 路由控制器
+   - 处理连接建立、消息收发
+   - 实现心跳机制
+   - 提供 REST API 接口
+
+## API 接口
+
+### WebSocket 连接
+
+#### 建立连接
+
+```
+ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
+```
+
+**参数:**
+- `pipeline_uuid`: 流水线 UUID (必需)
+- `session_type`: 会话类型，可选 `person` 或 `group` (默认: `person`)
+
+**连接成功响应:**
+```json
+{
+  "type": "connected",
+  "connection_id": "550e8400-e29b-41d4-a716-446655440000",
+  "pipeline_uuid": "your-pipeline-uuid",
+  "session_type": "person",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+### 消息格式
+
+#### 客户端发送消息
+
+**发送聊天消息:**
+```json
+{
+  "type": "message",
+  "message": [
+    {
+      "type": "Plain",
+      "text": "你好，这是一条测试消息"
+    }
+  ]
+}
+```
+
+**发送心跳:**
+```json
+{
+  "type": "ping"
+}
+```
+
+**主动断开连接:**
+```json
+{
+  "type": "disconnect"
+}
+```
+
+#### 服务器响应消息
+
+**聊天响应 (流式):**
+```json
+{
+  "type": "response",
+  "data": {
+    "id": 1,
+    "role": "assistant",
+    "content": "这是机器人的回复",
+    "message_chain": [...],
+    "timestamp": "2025-01-28T12:00:00",
+    "is_final": false,
+    "connection_id": "..."
+  }
+}
+```
+
+**心跳响应:**
+```json
+{
+  "type": "pong",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+**广播消息:**
+```json
+{
+  "type": "broadcast",
+  "message": "这是一条广播消息",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+**错误消息:**
+```json
+{
+  "type": "error",
+  "message": "错误描述"
+}
+```
+
+### REST API 接口
+
+#### 1. 获取消息历史
+
+```http
+GET /api/v1/pipelines/<pipeline_uuid>/ws/messages/<session_type>
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "messages": [...]
+  }
+}
+```
+
+#### 2. 重置会话
+
+```http
+POST /api/v1/pipelines/<pipeline_uuid>/ws/reset/<session_type>
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "message": "Session reset successfully"
+  }
+}
+```
+
+#### 3. 获取连接统计
+
+```http
+GET /api/v1/pipelines/<pipeline_uuid>/ws/connections
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "stats": {
+      "total_connections": 5,
+      "pipelines": 2,
+      "connections_by_pipeline": {
+        "pipeline-1": 3,
+        "pipeline-2": 2
+      },
+      "connections_by_session_type": {
+        "person": 4,
+        "group": 1
+      }
+    },
+    "connections": [
+      {
+        "connection_id": "...",
+        "session_type": "person",
+        "created_at": "2025-01-28T12:00:00",
+        "last_active": "2025-01-28T12:05:00",
+        "is_active": true
+      }
+    ]
+  }
+}
+```
+
+#### 4. 广播消息 (后端主动推送)
+
+```http
+POST /api/v1/pipelines/<pipeline_uuid>/ws/broadcast
+Content-Type: application/json
+
+{
+  "message": "这是一条广播消息"
+}
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "message": "Broadcast sent successfully"
+  }
+}
+```
+
+## 使用示例
+
+### Python 客户端示例
+
+使用提供的测试客户端：
+
+```bash
+# 安装依赖
+pip install websockets
+
+# 单个连接测试
+python test_websocket_client.py <pipeline_uuid>
+
+# 指定会话类型
+python test_websocket_client.py <pipeline_uuid> --session-type group
+
+# 多连接并发测试
+python test_websocket_client.py <pipeline_uuid> --multi 5
+```
+
+### JavaScript 客户端示例
+
+```javascript
+// 建立 WebSocket 连接
+const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/your-pipeline-uuid/ws/connect?session_type=person');
+
+// 连接建立
+ws.onopen = () => {
+  console.log('WebSocket 连接已建立');
+
+  // 发送消息
+  ws.send(JSON.stringify({
+    type: 'message',
+    message: [
+      {
+        type: 'Plain',
+        text: '你好'
+      }
+    ]
+  }));
+};
+
+// 接收消息
+ws.onmessage = (event) => {
+  const data = JSON.parse(event.data);
+
+  if (data.type === 'connected') {
+    console.log('连接成功:', data.connection_id);
+  } else if (data.type === 'response') {
+    console.log('机器人回复:', data.data.content);
+    if (data.data.is_final) {
+      console.log('响应完成');
+    }
+  } else if (data.type === 'broadcast') {
+    console.log('收到广播:', data.message);
+  }
+};
+
+// 连接关闭
+ws.onclose = () => {
+  console.log('WebSocket 连接已关闭');
+};
+
+// 错误处理
+ws.onerror = (error) => {
+  console.error('WebSocket 错误:', error);
+};
+
+// 发送心跳
+setInterval(() => {
+  if (ws.readyState === WebSocket.OPEN) {
+    ws.send(JSON.stringify({ type: 'ping' }));
+  }
+}, 30000); // 每 30 秒发送一次心跳
+```
+
+## 特性说明
+
+### 1. 多连接支持
+
+系统支持同时建立多个 WebSocket 连接，每个连接都有唯一的 `connection_id`。连接按照流水线和会话类型进行分组管理。
+
+### 2. 双向通信
+
+- **前端 → 后端**: 客户端可以主动发送消息给服务器
+- **后端 → 前端**: 服务器可以通过广播 API 主动推送消息给客户端
+
+### 3. 流式响应
+
+支持流式输出，机器人的响应会分块发送，客户端可以实时显示部分响应内容。
+
+### 4. 会话隔离
+
+支持 `person` 和 `group` 两种会话类型，不同类型的会话消息历史互不影响。
+
+### 5. 连接管理
+
+- 自动追踪连接状态
+- 记录最后活跃时间
+- 支持连接统计查询
+- 连接断开时自动清理资源
+
+### 6. 心跳机制
+
+客户端可以定期发送 `ping` 消息，服务器会响应 `pong`，用于保持连接活跃和检测连接状态。
+
+## 架构优势
+
+1. **高并发**: 使用 asyncio 异步架构，支持大量并发连接
+2. **可扩展**: 模块化设计，易于扩展新功能
+3. **线程安全**: 连接管理器使用锁机制保证并发安全
+4. **消息队列**: 每个连接独立的发送队列，避免消息混乱
+5. **灵活路由**: 支持按流水线、会话类型灵活路由消息
+
+## 注意事项
+
+1. **认证**: 当前 WebSocket 连接不需要认证，生产环境建议添加认证机制
+2. **心跳**: 建议客户端实现心跳机制，避免连接超时
+3. **重连**: 客户端应实现断线重连逻辑
+4. **消息大小**: 注意控制单条消息大小，避免内存溢出
+5. **连接数限制**: 生产环境建议设置最大连接数限制
+
+## 故障排查
+
+### 连接失败
+
+1. 检查流水线 UUID 是否正确
+2. 检查服务器是否正常运行
+3. 检查防火墙设置
+
+### 消息发送失败
+
+1. 检查消息格式是否正确
+2. 检查连接是否仍然活跃
+3. 查看服务器日志获取详细错误信息
+
+### 性能问题
+
+1. 检查并发连接数是否过多
+2. 检查消息处理速度
+3. 考虑使用连接池或负载均衡
+
+## 开发调试
+
+启用详细日志：
+
+```python
+import logging
+logging.getLogger('langbot.pkg.platform.sources.websocket_adapter').setLevel(logging.DEBUG)
+logging.getLogger('langbot.pkg.platform.sources.websocket_manager').setLevel(logging.DEBUG)
+logging.getLogger('langbot.pkg.api.http.controller.groups.pipelines.websocket_chat').setLevel(logging.DEBUG)
+```
+
+## 后续改进建议
+
+1. 添加用户认证和授权机制
+2. 实现消息持久化
+3. 添加消息加密
+4. 实现更丰富的消息类型 (图片、文件等)
+5. 添加消息已读/未读状态
+6. 实现群组聊天功能
+7. 添加在线状态显示
+8. 实现消息撤回功能

docs/development/workflow-system.md

@@ -0,0 +1,713 @@
+# Workflow 系统开发者文档
+
+本文档面向 LangBot 开发者，详细介绍 Workflow 系统的技术架构、核心组件和扩展方法。
+
+## 目录
+
+- [系统架构概述](#系统架构概述)
+- [目录结构](#目录结构)
+- [核心组件](#核心组件)
+  - [后端模块](#后端模块)
+  - [前端组件](#前端组件)
+- [数据库表结构](#数据库表结构)
+- [API 接口文档](#api-接口文档)
+- [如何添加新节点类型](#如何添加新节点类型)
+- [调试功能实现](#调试功能实现)
+
+---
+
+## 系统架构概述
+
+Workflow 系统采用前后端分离架构，主要包含以下层次：
+
+```
+┌─────────────────────────────────────────────────────────────┐
+│                      前端层 (React)                          │
+│  ┌─────────────┬──────────────┬──────────────┬───────────┐  │
+│  │ 可视化编辑器 │   节点面板    │   属性面板   │  调试器   │  │
+│  │ ReactFlow   │  NodePalette │ PropertyPanel│ Debugger  │  │
+│  └─────────────┴──────────────┴──────────────┴───────────┘  │
+├─────────────────────────────────────────────────────────────┤
+│                      API 层 (Quart)                          │
+│  ┌─────────────┬──────────────┬──────────────────────────┐  │
+│  │ Workflow API│  Debug API   │     Node Types API       │  │
+│  └─────────────┴──────────────┴──────────────────────────┘  │
+├─────────────────────────────────────────────────────────────┤
+│                     核心引擎层 (Python)                       │
+│  ┌─────────────┬──────────────┬──────────────┬───────────┐  │
+│  │ Executor    │   Registry   │    Node      │ Entities  │  │
+│  │ 执行引擎     │  节点注册表   │   节点基类   │  数据结构  │  │
+│  └─────────────┴──────────────┴──────────────┴───────────┘  │
+├─────────────────────────────────────────────────────────────┤
+│                      存储层 (SQLAlchemy)                     │
+│  ┌─────────────┬──────────────┬──────────────────────────┐  │
+│  │  Workflow   │  Executions  │        Triggers          │  │
+│  └─────────────┴──────────────┴──────────────────────────┘  │
+└─────────────────────────────────────────────────────────────┘
+```
+
+---
+
+## 目录结构
+
+### 后端代码结构
+
+```
+LangBot/src/langbot/pkg/
+├── workflow/                      # Workflow 核心模块
+│   ├── __init__.py               # 模块初始化，导出公共接口
+│   ├── entities.py               # 数据实体定义
+│   ├── executor.py               # 执行引擎
+│   ├── node.py                   # 节点基类和装饰器
+│   ├── registry.py               # 节点类型注册表
+│   └── nodes/                    # 内置节点实现
+│       ├── __init__.py           # 注册所有内置节点
+│       ├── trigger.py            # 触发节点
+│       ├── process.py            # 处理节点
+│       ├── control.py            # 控制节点
+│       └── action.py             # 动作节点
+├── entity/persistence/
+│   └── workflow.py               # 数据库模型
+├── api/http/
+│   ├── controller/groups/workflows/
+│   │   └── workflows.py          # API 路由控制器
+│   └── service/
+│       └── workflow.py           # 业务逻辑服务
+└── persistence/migrations/
+    └── dbm026_workflow_tables.py # 数据库迁移
+```
+
+### 前端代码结构
+
+```
+LangBot/web/src/app/home/workflows/
+├── page.tsx                      # Workflow 列表页
+├── WorkflowDetailContent.tsx     # 详情页内容
+├── store/
+│   └── useWorkflowStore.ts       # Zustand 状态管理
+└── components/
+    ├── workflow-editor/          # 可视化编辑器
+    │   ├── index.ts              # 导出
+    │   ├── WorkflowEditorComponent.tsx  # 主编辑器组件
+    │   ├── WorkflowNodeComponent.tsx    # 自定义节点组件
+    │   ├── NodePalette.tsx       # 节点面板
+    │   ├── PropertyPanel.tsx     # 属性面板
+    │   └── node-configs/         # 节点配置元数据
+    │       ├── types.ts          # 配置类型定义
+    │       ├── trigger-configs.ts
+    │       ├── ai-configs.ts
+    │       ├── process-configs.ts
+    │       ├── control-configs.ts
+    │       ├── action-configs.ts
+    │       ├── integration-configs.ts
+    │       └── index.ts          # 配置汇总
+    ├── workflow-debugger/        # 调试器组件
+    │   ├── index.ts
+    │   └── WorkflowDebugger.tsx
+    ├── workflow-form/            # 表单组件
+    │   └── WorkflowFormComponent.tsx
+    └── workflow-executions/      # 执行历史组件
+        └── WorkflowExecutionsTab.tsx
+```
+
+---
+
+## 核心组件
+
+### 后端模块
+
+#### 1. 执行引擎 (WorkflowExecutor)
+
+位置：[`executor.py`](../../src/langbot/pkg/workflow/executor.py)
+
+执行引擎负责工作流的实际执行，包括：
+
+- **拓扑排序**：确定节点执行顺序
+- **节点执行**：调用各节点的 execute 方法
+- **控制流处理**：处理条件分支、循环、并行执行
+- **错误处理**：支持重试机制
+
+```python
+class WorkflowExecutor:
+    async def execute(
+        self, 
+        workflow: WorkflowDefinition, 
+        context: ExecutionContext,
+        start_node_id: Optional[str] = None
+    ) -> ExecutionContext:
+        """执行工作流"""
+        # 1. 构建执行图
+        # 2. 初始化节点状态
+        # 3. 找到起始节点
+        # 4. 按拓扑顺序执行
+```
+
+**调试执行器 (DebugWorkflowExecutor)**
+
+继承自 WorkflowExecutor，增加了调试支持：
+
+- 断点支持
+- 单步执行
+- 暂停/继续
+- 实时日志
+
+```python
+class DebugWorkflowExecutor(WorkflowExecutor):
+    async def execute_debug(
+        self,
+        workflow: WorkflowDefinition,
+        context: ExecutionContext,
+        debug_state: DebugExecutionState,
+    ) -> ExecutionContext:
+        """调试模式执行"""
+```
+
+#### 2. 节点注册表 (NodeTypeRegistry)
+
+位置：[`registry.py`](../../src/langbot/pkg/workflow/registry.py)
+
+单例模式管理所有节点类型：
+
+```python
+class NodeTypeRegistry:
+    _instance: Optional['NodeTypeRegistry'] = None
+    
+    def register(self, node_type: str, node_class: type[WorkflowNode]):
+        """注册节点类型"""
+        
+    def create_instance(self, node_type: str, node_id: str, config: dict) -> WorkflowNode:
+        """创建节点实例"""
+        
+    def list_all(self) -> list[dict]:
+        """获取所有节点类型的 Schema"""
+```
+
+#### 3. 节点基类 (WorkflowNode)
+
+位置：[`node.py`](../../src/langbot/pkg/workflow/node.py)
+
+所有节点必须继承此基类：
+
+```python
+class WorkflowNode(abc.ABC):
+    # 节点元数据
+    type_name: str = ""
+    name: str = ""
+    description: str = ""
+    category: str = "misc"
+    icon: str = ""
+    
+    # 端口定义
+    inputs: list[NodePort] = []
+    outputs: list[NodePort] = []
+    
+    # 配置 Schema
+    config_schema: list[NodeConfig] = []
+    
+    @abc.abstractmethod
+    async def execute(
+        self, 
+        inputs: dict[str, Any], 
+        context: ExecutionContext
+    ) -> dict[str, Any]:
+        """执行节点逻辑"""
+        pass
+```
+
+#### 4. 数据实体 (entities.py)
+
+主要数据结构：
+
+```python
+class WorkflowDefinition:
+    """工作流定义"""
+    uuid: str
+    name: str
+    nodes: list[NodeDefinition]
+    edges: list[EdgeDefinition]
+    settings: WorkflowSettings
+    
+class ExecutionContext:
+    """执行上下文"""
+    execution_id: str
+    workflow_id: str
+    status: ExecutionStatus
+    variables: dict
+    node_states: dict[str, NodeState]
+    history: list[ExecutionStep]
+```
+
+### 前端组件
+
+#### 1. WorkflowEditorComponent
+
+主编辑器组件，基于 React Flow 实现：
+
+- **画布交互**：拖拽、缩放、平移
+- **节点连接**：自动验证端口类型
+- **撤销/重做**：基于历史记录栈
+- **复制/粘贴**：支持多选复制
+
+关键功能：
+
+```tsx
+function WorkflowEditorInner() {
+  const { nodes, edges, onNodesChange, onEdgesChange, onConnect } = useWorkflowStore();
+  
+  // 拖放添加节点
+  const onDrop = useCallback((event: React.DragEvent) => {
+    const type = event.dataTransfer.getData('application/reactflow');
+    const position = screenToFlowPosition({ x: event.clientX, y: event.clientY });
+    addNode(type, position);
+  }, []);
+  
+  // 复制粘贴
+  const handleCopy = useCallback(() => { ... }, []);
+  const handlePaste = useCallback(() => { ... }, []);
+}
+```
+
+#### 2. NodePalette
+
+节点面板组件，展示可用节点类型：
+
+```tsx
+function NodePalette() {
+  // 按类别组织节点
+  const categories = [
+    { id: 'trigger', name: '触发节点', icon: Zap },
+    { id: 'ai', name: 'AI 节点', icon: Brain },
+    { id: 'process', name: '处理节点', icon: Cpu },
+    { id: 'control', name: '控制节点', icon: GitBranch },
+    { id: 'action', name: '动作节点', icon: Send },
+    { id: 'integration', name: '集成节点', icon: Plug },
+  ];
+  
+  // 拖拽开始
+  const onDragStart = (event: React.DragEvent, nodeType: string) => {
+    event.dataTransfer.setData('application/reactflow', nodeType);
+  };
+}
+```
+
+#### 3. PropertyPanel
+
+属性面板组件，动态渲染节点配置表单：
+
+```tsx
+function PropertyPanel() {
+  const { selectedNodeId, nodes, updateNodeData } = useWorkflowStore();
+  
+  // 根据节点类型获取配置元数据
+  const selectedNode = nodes.find(n => n.id === selectedNodeId);
+  const nodeConfig = getNodeConfig(selectedNode?.data?.nodeType);
+  
+  // 动态渲染配置字段
+  return (
+    <div>
+      {nodeConfig?.fields.map(field => (
+        <ConfigField key={field.name} field={field} />
+      ))}
+    </div>
+  );
+}
+```
+
+#### 4. WorkflowDebugger
+
+调试器组件，支持实时调试：
+
+```tsx
+function WorkflowDebugger({ workflowUuid, workflow }) {
+  const [debugState, setDebugState] = useState<DebugState>('idle');
+  const [executionId, setExecutionId] = useState<string>('');
+  const [logs, setLogs] = useState<ExecutionLog[]>([]);
+  
+  // 启动调试
+  const startDebug = async () => {
+    const result = await backendClient.post(
+      `/api/v1/workflows/${workflowUuid}/debug/start`,
+      { context, variables, breakpoints }
+    );
+    setExecutionId(result.execution_id);
+  };
+  
+  // 轮询状态
+  useEffect(() => {
+    if (debugState === 'running') {
+      const interval = setInterval(fetchState, 500);
+      return () => clearInterval(interval);
+    }
+  }, [debugState]);
+}
+```
+
+#### 5. useWorkflowStore
+
+Zustand 状态管理：
+
+```typescript
+interface WorkflowState {
+  nodes: WorkflowNode[];
+  edges: WorkflowEdge[];
+  selectedNodeId: string | null;
+  history: HistoryEntry[];
+  historyIndex: number;
+  isDirty: boolean;
+  
+  // Actions
+  addNode: (type: string, position: XYPosition) => void;
+  updateNodeData: (nodeId: string, data: Partial<NodeData>) => void;
+  deleteNode: (nodeId: string) => void;
+  undo: () => void;
+  redo: () => void;
+}
+
+export const useWorkflowStore = create<WorkflowState>((set, get) => ({
+  // ... state and actions
+}));
+```
+
+---
+
+## 数据库表结构
+
+### workflows 表
+
+```sql
+CREATE TABLE workflows (
+    uuid VARCHAR(255) PRIMARY KEY,
+    name VARCHAR(255) NOT NULL,
+    description TEXT,
+    emoji VARCHAR(10) DEFAULT '🔄',
+    version INTEGER DEFAULT 1,
+    is_enabled BOOLEAN DEFAULT TRUE,
+    definition JSON NOT NULL,        -- 节点和边定义
+    global_config JSON DEFAULT '{}', -- 全局配置
+    extensions_preferences JSON,     -- 插件和 MCP 配置
+    created_at TIMESTAMP,
+    updated_at TIMESTAMP
+);
+```
+
+### workflow_versions 表
+
+```sql
+CREATE TABLE workflow_versions (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    workflow_uuid VARCHAR(255) NOT NULL,
+    version INTEGER NOT NULL,
+    definition JSON NOT NULL,
+    global_config JSON DEFAULT '{}',
+    created_at TIMESTAMP,
+    created_by VARCHAR(255),
+    UNIQUE(workflow_uuid, version)
+);
+```
+
+### workflow_executions 表
+
+```sql
+CREATE TABLE workflow_executions (
+    uuid VARCHAR(255) PRIMARY KEY,
+    workflow_uuid VARCHAR(255) NOT NULL,
+    workflow_version INTEGER NOT NULL,
+    status VARCHAR(20) NOT NULL,  -- pending/running/completed/failed/cancelled
+    trigger_type VARCHAR(50),
+    trigger_data JSON,
+    variables JSON,
+    start_time TIMESTAMP,
+    end_time TIMESTAMP,
+    error TEXT,
+    created_at TIMESTAMP
+);
+```
+
+### workflow_node_executions 表
+
+```sql
+CREATE TABLE workflow_node_executions (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    execution_uuid VARCHAR(255) NOT NULL,
+    node_id VARCHAR(100) NOT NULL,
+    node_type VARCHAR(50) NOT NULL,
+    status VARCHAR(20) NOT NULL,
+    inputs JSON,
+    outputs JSON,
+    start_time TIMESTAMP,
+    end_time TIMESTAMP,
+    error TEXT,
+    retry_count INTEGER DEFAULT 0
+);
+```
+
+### workflow_triggers 表
+
+```sql
+CREATE TABLE workflow_triggers (
+    uuid VARCHAR(255) PRIMARY KEY,
+    workflow_uuid VARCHAR(255) NOT NULL,
+    type VARCHAR(50) NOT NULL,  -- message/cron/event/webhook
+    config JSON NOT NULL,
+    is_enabled BOOLEAN DEFAULT TRUE,
+    priority INTEGER DEFAULT 0,
+    created_at TIMESTAMP,
+    updated_at TIMESTAMP
+);
+```
+
+---
+
+## API 接口文档
+
+### Workflow CRUD
+
+| 方法 | 路径 | 描述 |
+|-----|------|------|
+| GET | `/api/v1/workflows` | 获取工作流列表 |
+| POST | `/api/v1/workflows` | 创建工作流 |
+| GET | `/api/v1/workflows/:uuid` | 获取单个工作流 |
+| PUT | `/api/v1/workflows/:uuid` | 更新工作流 |
+| DELETE | `/api/v1/workflows/:uuid` | 删除工作流 |
+| POST | `/api/v1/workflows/:uuid/copy` | 复制工作流 |
+
+### 执行相关
+
+| 方法 | 路径 | 描述 |
+|-----|------|------|
+| POST | `/api/v1/workflows/:uuid/execute` | 手动执行工作流 |
+| GET | `/api/v1/workflows/:uuid/executions` | 获取执行记录 |
+
+### 版本管理
+
+| 方法 | 路径 | 描述 |
+|-----|------|------|
+| GET | `/api/v1/workflows/:uuid/versions` | 获取版本列表 |
+| POST | `/api/v1/workflows/:uuid/rollback/:version` | 回滚到指定版本 |
+
+### 调试 API
+
+| 方法 | 路径 | 描述 |
+|-----|------|------|
+| POST | `/api/v1/workflows/:uuid/debug/start` | 启动调试 |
+| POST | `/api/v1/workflows/:uuid/debug/:exec_id/pause` | 暂停执行 |
+| POST | `/api/v1/workflows/:uuid/debug/:exec_id/resume` | 继续执行 |
+| POST | `/api/v1/workflows/:uuid/debug/:exec_id/stop` | 停止执行 |
+| POST | `/api/v1/workflows/:uuid/debug/:exec_id/step` | 单步执行 |
+| GET | `/api/v1/workflows/:uuid/debug/:exec_id/state` | 获取调试状态 |
+
+### 节点类型
+
+| 方法 | 路径 | 描述 |
+|-----|------|------|
+| GET | `/api/v1/workflows/_/node-types` | 获取所有节点类型 |
+| GET | `/api/v1/workflows/_/node-types/categories` | 按类别获取节点类型 |
+
+---
+
+## 如何添加新节点类型
+
+### 步骤 1：创建节点类
+
+在 `LangBot/src/langbot/pkg/workflow/nodes/` 下创建或修改文件：
+
+```python
+from ..node import WorkflowNode, NodePort, NodeConfig, workflow_node
+from ..entities import ExecutionContext
+
+@workflow_node('my_custom_node')
+class MyCustomNode(WorkflowNode):
+    """自定义节点"""
+    
+    # 元数据
+    type_name = 'my_custom_node'
+    name = '我的自定义节点'
+    description = '这是一个自定义节点'
+    category = 'process'  # trigger/process/control/action/integration
+    icon = '🔧'
+    
+    # 输入端口
+    inputs = [
+        NodePort(name='input', type='string', description='输入数据', required=True),
+    ]
+    
+    # 输出端口
+    outputs = [
+        NodePort(name='output', type='string', description='输出数据'),
+    ]
+    
+    # 配置字段
+    config_schema = [
+        NodeConfig(
+            name='option',
+            type='select',
+            required=True,
+            options=['选项A', '选项B'],
+            description='选择一个选项'
+        ),
+        NodeConfig(
+            name='value',
+            type='string',
+            required=False,
+            default='默认值',
+            description='配置值'
+        ),
+    ]
+    
+    async def execute(
+        self, 
+        inputs: dict[str, Any], 
+        context: ExecutionContext
+    ) -> dict[str, Any]:
+        """执行节点逻辑"""
+        input_data = inputs.get('input', '')
+        option = self.get_config('option')
+        value = self.get_config('value', '')
+        
+        # 处理逻辑
+        result = f"处理: {input_data} with {option} and {value}"
+        
+        return {'output': result}
+```
+
+### 步骤 2：注册节点
+
+在 `LangBot/src/langbot/pkg/workflow/nodes/__init__.py` 中导入：
+
+```python
+from .process import (
+    CodeExecutorNode,
+    HttpRequestNode,
+    DataTransformNode,
+    MyCustomNode,  # 添加新节点
+)
+```
+
+### 步骤 3：添加前端配置
+
+在 `LangBot/web/src/app/home/workflows/components/workflow-editor/node-configs/` 目录下添加配置：
+
+```typescript
+// process-configs.ts
+export const processNodeConfigs: NodeConfigMap = {
+  // ... 其他配置
+  
+  my_custom_node: {
+    type: 'my_custom_node',
+    label: 'workflows.nodes.myCustomNode',
+    description: 'workflows.nodes.myCustomNodeDesc',
+    icon: 'Wrench',
+    category: 'process',
+    fields: [
+      {
+        name: 'option',
+        type: 'select',
+        label: 'workflows.fields.option',
+        required: true,
+        options: [
+          { value: '选项A', label: '选项 A' },
+          { value: '选项B', label: '选项 B' },
+        ],
+      },
+      {
+        name: 'value',
+        type: 'string',
+        label: 'workflows.fields.value',
+        required: false,
+        defaultValue: '默认值',
+      },
+    ],
+  },
+};
+```
+
+### 步骤 4：添加国际化
+
+在 `LangBot/web/src/i18n/locales/` 中添加翻译：
+
+```typescript
+// zh-Hans.ts
+workflows: {
+  nodes: {
+    myCustomNode: '我的自定义节点',
+    myCustomNodeDesc: '这是一个自定义节点',
+  },
+  fields: {
+    option: '选项',
+    value: '值',
+  },
+}
+```
+
+---
+
+## 调试功能实现
+
+### 后端调试状态管理
+
+```python
+class DebugExecutionState:
+    """调试执行状态"""
+    
+    def __init__(self, execution_id: str, breakpoints: list[str] = None):
+        self.execution_id = execution_id
+        self.status: str = 'running'
+        self.is_paused: bool = False
+        self.is_stopped: bool = False
+        self.breakpoints: set[str] = set(breakpoints or [])
+        self.logs: list[ExecutionLog] = []
+        self._pause_event = asyncio.Event()
+    
+    def pause(self):
+        """暂停执行"""
+        self.is_paused = True
+        self._pause_event.clear()
+    
+    def resume(self):
+        """继续执行"""
+        self.is_paused = False
+        self._pause_event.set()
+    
+    async def wait_if_paused(self):
+        """如果暂停则等待"""
+        if self.is_paused:
+            await self._pause_event.wait()
+```
+
+### 前端调试流程
+
+1. **设置断点**：点击节点设置断点
+2. **启动调试**：调用 `/debug/start` 启动调试执行
+3. **轮询状态**：定期调用 `/debug/:id/state` 获取状态
+4. **控制执行**：调用 pause/resume/step/stop 控制执行
+5. **查看日志**：实时显示执行日志和节点状态
+
+```typescript
+// 调试状态轮询
+const fetchDebugState = async () => {
+  const state = await backendClient.get(
+    `/api/v1/workflows/${workflowUuid}/debug/${executionId}/state`
+  );
+  
+  // 更新节点状态
+  setNodeStates(state.node_states);
+  
+  // 追加新日志
+  if (state.new_logs.length > 0) {
+    setLogs(prev => [...prev, ...state.new_logs]);
+  }
+  
+  // 检查完成状态
+  if (state.status === 'completed' || state.status === 'error') {
+    setDebugState('idle');
+  }
+};
+```
+
+---
+
+## 扩展阅读
+
+- [Workflow 功能设计文档](../../../plans/langbot-workflow-design.md)
+- [用户使用指南](../user-guide/workflow-guide.md)
+- [API 认证文档](../API_KEY_AUTH.md)

docs/user-guide/workflow-guide.md

@@ -0,0 +1,425 @@
+# Workflow 用户指南
+
+本文档帮助您了解和使用 LangBot 的 Workflow（工作流）功能，通过可视化方式构建自动化的对话处理流程。
+
+## 目录
+
+- [功能介绍](#功能介绍)
+- [快速入门](#快速入门)
+- [节点类型说明](#节点类型说明)
+- [编辑器使用指南](#编辑器使用指南)
+- [调试功能](#调试功能)
+- [常见问题解答](#常见问题解答)
+
+---
+
+## 功能介绍
+
+### 什么是 Workflow？
+
+Workflow（工作流）是 LangBot 提供的可视化自动化编排系统。通过拖拽节点、连接边的方式，您可以：
+
+- 📝 **构建复杂的对话流程**：使用条件分支、循环等控制节点
+- 🤖 **调用 AI 能力**：集成 LLM、知识库检索、参数提取
+- 🔗 **连接外部服务**：集成 Dify、n8n、Coze 等平台
+- ⚡ **自动化任务执行**：消息触发、定时触发、Webhook 触发
+
+### Workflow vs Pipeline
+
+| 对比项 | Pipeline | Workflow |
+|-------|----------|----------|
+| 配置方式 | 表单配置 | 可视化拖拽 |
+| 流程控制 | 线性执行 | 支持分支、循环、并行 |
+| 适用场景 | 简单对话 | 复杂流程 |
+| 学习曲线 | 低 | 中等 |
+
+---
+
+## 快速入门
+
+### 第一步：创建 Workflow
+
+1. 在侧边栏点击 **Workflow** 进入工作流列表
+2. 点击右上角 **创建工作流** 按钮
+3. 填写基本信息：
+   - **名称**：给工作流起一个描述性的名字
+   - **描述**：可选，说明工作流的用途
+   - **图标**：选择一个 emoji 作为标识
+
+### 第二步：添加节点
+
+进入编辑器后，左侧是节点面板，中间是画布区域，右侧是属性面板。
+
+1. **添加触发节点**：从左侧面板拖拽一个"消息触发"节点到画布
+2. **添加 AI 节点**：拖拽一个"LLM 调用"节点
+3. **添加回复节点**：拖拽一个"回复消息"节点
+
+### 第三步：连接节点
+
+1. 将鼠标悬停在触发节点的输出端口（右侧小圆点）
+2. 按住鼠标拖拽到 LLM 节点的输入端口（左侧小圆点）
+3. 同样方式连接 LLM 节点和回复节点
+
+```
+[消息触发] ──▶ [LLM 调用] ──▶ [回复消息]
+```
+
+### 第四步：配置节点
+
+点击 LLM 调用节点，在右侧属性面板配置：
+
+- **运行方式**：选择"本地 Agent"
+- **系统提示词**：描述 AI 的角色和行为
+- **模型**：选择要使用的 LLM 模型
+
+点击回复消息节点配置：
+
+- **消息内容**：设置为 `{{nodes.llm_call.outputs.response}}`（引用 LLM 输出）
+
+### 第五步：保存并绑定
+
+1. 点击工具栏的 **保存** 按钮
+2. 返回 Bot 配置页面
+3. 在 Bot 的绑定设置中选择 **Workflow**，然后选择刚创建的工作流
+
+恭喜！您已经创建了第一个 Workflow。
+
+---
+
+## 节点类型说明
+
+### 触发节点 (Trigger)
+
+触发节点是工作流的入口，定义何时启动执行。
+
+| 节点 | 说明 | 输出 |
+|-----|------|------|
+| 消息触发 | 收到消息时触发 | message, sender_id, platform |
+| 定时触发 | 按 Cron 表达式定时触发 | timestamp |
+| Webhook 触发 | 收到 HTTP 请求时触发 | request_body, headers |
+| 事件触发 | 系统事件触发 | event_type, event_data |
+
+**消息触发配置示例**：
+
+```yaml
+触发条件:
+  - 关键词匹配: ["帮助", "help"]
+  - 平台: ["wechat", "qq"]
+```
+
+### AI 节点
+
+AI 节点用于调用各种 AI 能力。
+
+| 节点 | 说明 | 典型用途 |
+|-----|------|---------|
+| LLM 调用 | 调用大语言模型 | 生成回复、理解意图 |
+| 问题分类器 | 对用户问题分类 | 路由到不同处理分支 |
+| 参数提取器 | 从文本提取结构化数据 | 提取订单号、日期等 |
+| 知识库检索 | 查询知识库 | RAG 增强回复 |
+
+**LLM 调用配置示例**：
+
+```yaml
+运行方式: 本地 Agent
+模型: gpt-4
+系统提示词: |
+  你是一个友好的客服助手。
+  请根据用户的问题提供帮助。
+温度: 0.7
+最大 Token 数: 2000
+```
+
+### 处理节点 (Process)
+
+处理节点用于数据处理和外部调用。
+
+| 节点 | 说明 | 典型用途 |
+|-----|------|---------|
+| 代码执行 | 执行 Python/JavaScript 代码 | 数据处理、格式转换 |
+| HTTP 请求 | 发送 HTTP 请求 | 调用外部 API |
+| 数据转换 | JSON/模板转换 | 数据格式化 |
+
+**HTTP 请求配置示例**：
+
+```yaml
+URL: https://api.example.com/data
+方法: POST
+请求头:
+  Content-Type: application/json
+  Authorization: Bearer {{variables.api_key}}
+请求体: |
+  {"query": "{{message.content}}"}
+```
+
+### 控制节点 (Control)
+
+控制节点用于流程控制。
+
+| 节点 | 说明 | 用途 |
+|-----|------|------|
+| 条件分支 | 二选一分支 | if-else 逻辑 |
+| 多路分支 | 多选一分支 | switch-case 逻辑 |
+| 循环 | 遍历数组 | 批量处理 |
+| 并行 | 同时执行多分支 | 并发处理 |
+| 等待 | 暂停执行 | 延时处理 |
+| 合并 | 合并多个分支 | 汇总结果 |
+
+**条件分支配置示例**：
+
+```yaml
+条件表达式: "{{nodes.classifier.outputs.category}}" == "complaint"
+真分支: 投诉处理
+假分支: 普通咨询
+```
+
+### 动作节点 (Action)
+
+动作节点执行具体操作。
+
+| 节点 | 说明 | 用途 |
+|-----|------|------|
+| 发送消息 | 主动发送消息 | 通知、推送 |
+| 回复消息 | 回复当前消息 | 对话回复 |
+| 存储数据 | 保存数据到存储 | 持久化 |
+| 调用 Pipeline | 调用现有 Pipeline | 复用现有流程 |
+
+**回复消息配置示例**：
+
+```yaml
+消息内容: |
+  感谢您的咨询！
+  
+  {{nodes.llm_call.outputs.response}}
+  
+  如有其他问题，随时联系我。
+```
+
+### 集成节点 (Integration)
+
+集成节点连接外部平台。
+
+| 节点 | 说明 | 平台 |
+|-----|------|------|
+| Dify 工作流 | 调用 Dify 应用 | Dify |
+| Dify 知识库 | 查询 Dify 知识库 | Dify |
+| n8n 工作流 | 调用 n8n 流程 | n8n |
+| Langflow | 调用 Langflow 流程 | Langflow |
+| Coze Bot | 调用扣子 Bot | Coze |
+
+**Dify 工作流配置示例**：
+
+```yaml
+API 地址: https://api.dify.ai/v1
+API Key: sk-xxxxx
+应用类型: workflow
+同步对话历史: true
+```
+
+---
+
+## 编辑器使用指南
+
+### 画布操作
+
+| 操作 | 方式 |
+|-----|------|
+| 平移画布 | 按住鼠标中键/空格+左键 拖拽 |
+| 缩放画布 | 鼠标滚轮 / 工具栏按钮 |
+| 框选多个节点 | 按住 Shift + 拖拽框选 |
+| 适应视图 | 点击工具栏"适应"按钮 |
+
+### 节点操作
+
+| 操作 | 方式 |
+|-----|------|
+| 添加节点 | 从左侧面板拖拽到画布 |
+| 移动节点 | 点击节点拖拽 |
+| 删除节点 | 选中后按 Delete / 点击工具栏删除 |
+| 复制节点 | 选中后 Ctrl+C / 工具栏复制 |
+| 粘贴节点 | Ctrl+V / 工具栏粘贴 |
+
+### 连接操作
+
+| 操作 | 方式 |
+|-----|------|
+| 创建连接 | 从输出端口拖拽到输入端口 |
+| 删除连接 | 点击连接线后按 Delete |
+| 选中连接 | 点击连接线 |
+
+### 快捷键
+
+| 快捷键 | 功能 |
+|-------|------|
+| Ctrl + Z | 撤销 |
+| Ctrl + Shift + Z | 重做 |
+| Ctrl + C | 复制 |
+| Ctrl + V | 粘贴 |
+| Delete | 删除选中 |
+| Ctrl + S | 保存 |
+
+### 工具栏功能
+
+```
+[撤销] [重做] | [放大] [缩小] [适应] | [复制] [粘贴] [删除] | [保存] [调试]
+```
+
+---
+
+## 调试功能
+
+### 启动调试
+
+1. 点击工具栏的 **调试** 按钮
+2. 在调试面板中配置初始数据：
+   - **输入消息**：模拟用户发送的消息
+   - **会话 ID**：可选，用于测试会话变量
+   - **变量**：设置初始变量值
+
+3. 点击 **开始调试** 按钮
+
+### 调试控制
+
+| 按钮 | 功能 |
+|-----|------|
+| ▶️ 开始/继续 | 开始或继续执行 |
+| ⏸️ 暂停 | 暂停执行 |
+| ⏹️ 停止 | 停止执行 |
+| ⏭️ 单步 | 执行下一个节点 |
+
+### 断点
+
+- **设置断点**：点击节点上的断点图标
+- **断点触发**：执行到断点时自动暂停
+- **查看状态**：在暂停时查看节点的输入输出
+
+### 执行日志
+
+调试面板下方显示实时日志：
+
+```
+[INFO] 2024-01-15 10:30:00 - Starting debug execution
+[INFO] 2024-01-15 10:30:00 - Executing node: message_trigger
+[DEBUG] 2024-01-15 10:30:00 - Node inputs: {"message": "你好"}
+[INFO] 2024-01-15 10:30:01 - Node completed in 50ms
+[INFO] 2024-01-15 10:30:01 - Executing node: llm_call
+...
+```
+
+### 节点状态颜色
+
+| 颜色 | 状态 |
+|-----|------|
+| 灰色 | 待执行 |
+| 蓝色 | 执行中 |
+| 绿色 | 已完成 |
+| 红色 | 失败 |
+| 黄色 | 已跳过 |
+
+---
+
+## 常见问题解答
+
+### Q1：如何在节点间传递数据？
+
+使用表达式语法引用其他节点的输出：
+
+```
+{{nodes.节点ID.outputs.输出名称}}
+```
+
+例如：
+- `{{nodes.llm_call.outputs.response}}` - 引用 LLM 节点的响应
+- `{{nodes.http_request.outputs.body}}` - 引用 HTTP 请求的响应体
+
+### Q2：如何使用变量？
+
+Workflow 支持三种变量类型：
+
+1. **工作流变量**：`{{variables.变量名}}`
+2. **会话变量**：`{{conversation_variables.变量名}}`
+3. **消息上下文**：`{{message.content}}`、`{{message.sender_id}}`
+
+### Q3：条件分支如何写条件表达式？
+
+支持以下运算符：
+
+- 比较：`==`, `!=`, `>`, `<`, `>=`, `<=`
+- 逻辑：`and`, `or`, `not`
+- 包含：`in`
+
+示例：
+```python
+# 字符串比较
+"{{nodes.classifier.outputs.intent}}" == "purchase"
+
+# 数值比较
+{{nodes.extractor.outputs.amount}} > 1000
+
+# 包含检查
+"退款" in "{{message.content}}"
+```
+
+### Q4：如何处理错误？
+
+1. **节点级重试**：在节点配置中设置重试次数
+2. **全局错误处理**：在 Workflow 设置中配置错误处理策略
+3. **条件分支**：使用条件节点检查上一节点的状态
+
+### Q5：如何查看执行历史？
+
+1. 进入 Workflow 详情页
+2. 点击 **执行历史** 标签
+3. 查看每次执行的状态、耗时、输入输出
+
+### Q6：Workflow 可以被多个 Bot 使用吗？
+
+是的。一个 Workflow 可以被多个 Bot 绑定使用，但每个 Bot 只能绑定一个处理单元（Pipeline 或 Workflow）。
+
+### Q7：如何复制现有的 Workflow？
+
+在 Workflow 列表页，点击工作流卡片右上角的菜单，选择"复制"即可创建副本。
+
+### Q8：支持版本回滚吗？
+
+支持。每次保存都会创建新版本。在 Workflow 详情页可以查看版本历史并回滚到指定版本。
+
+---
+
+## 最佳实践
+
+### 1. 合理命名
+
+- 为节点和 Workflow 使用描述性名称
+- 使用统一的命名规范
+
+### 2. 模块化设计
+
+- 将复杂流程拆分为多个小 Workflow
+- 使用"调用 Pipeline"节点复用现有流程
+
+### 3. 错误处理
+
+- 为关键节点设置重试机制
+- 使用条件分支处理异常情况
+- 添加日志记录便于排查问题
+
+### 4. 测试先行
+
+- 使用调试功能充分测试
+- 准备多种测试场景
+- 检查边界情况
+
+### 5. 性能优化
+
+- 避免不必要的节点
+- 使用并行节点提高效率
+- 合理设置超时时间
+
+---
+
+## 更多资源
+
+- [开发者文档](../development/workflow-system.md)
+- [设计文档](../../../plans/langbot-workflow-design.md)
+- [API 文档](../service-api-openapi.json)

libs/dify_service_api/test.py

@@ -1,53 +0,0 @@
-from v1 import client
-
-import asyncio
-
-import os
-import json
-
-
-class TestDifyClient:
-    async def test_chat_messages(self):
-        cln = client.AsyncDifyServiceClient(
-            api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL')
-        )
-
-        async for chunk in cln.chat_messages(
-            inputs={}, query='调用工具查看现在几点？', user='test'
-        ):
-            print(json.dumps(chunk, ensure_ascii=False, indent=4))
-
-    async def test_upload_file(self):
-        cln = client.AsyncDifyServiceClient(
-            api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL')
-        )
-
-        file_bytes = open('img.png', 'rb').read()
-
-        print(type(file_bytes))
-
-        file = ('img2.png', file_bytes, 'image/png')
-
-        resp = await cln.upload_file(file=file, user='test')
-        print(json.dumps(resp, ensure_ascii=False, indent=4))
-
-    async def test_workflow_run(self):
-        cln = client.AsyncDifyServiceClient(
-            api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL')
-        )
-
-        # resp = await cln.workflow_run(inputs={}, user="test")
-        # # print(json.dumps(resp, ensure_ascii=False, indent=4))
-        # print(resp)
-        chunks = []
-
-        ignored_events = ['text_chunk']
-        async for chunk in cln.workflow_run(inputs={}, user='test'):
-            if chunk['event'] in ignored_events:
-                continue
-            chunks.append(chunk)
-        print(json.dumps(chunks, ensure_ascii=False, indent=4))
-
-
-if __name__ == '__main__':
-    asyncio.run(TestDifyClient().test_chat_messages())

libs/dingtalk_api/api.py

@@ -1,246 +0,0 @@
-import base64
-import json
-import time
-from typing import Callable
-import dingtalk_stream
-from .EchoHandler import EchoTextHandler
-from .dingtalkevent import DingTalkEvent
-import httpx
-import traceback
-
-
-class DingTalkClient:
-    def __init__(
-        self,
-        client_id: str,
-        client_secret: str,
-        robot_name: str,
-        robot_code: str,
-        markdown_card: bool,
-    ):
-        """初始化 WebSocket 连接并自动启动"""
-        self.credential = dingtalk_stream.Credential(client_id, client_secret)
-        self.client = dingtalk_stream.DingTalkStreamClient(self.credential)
-        self.key = client_id
-        self.secret = client_secret
-        # 在 DingTalkClient 中传入自己作为参数，避免循环导入
-        self.EchoTextHandler = EchoTextHandler(self)
-        self.client.register_callback_handler(dingtalk_stream.chatbot.ChatbotMessage.TOPIC, self.EchoTextHandler)
-        self._message_handlers = {
-            'example': [],
-        }
-        self.access_token = ''
-        self.robot_name = robot_name
-        self.robot_code = robot_code
-        self.access_token_expiry_time = ''
-        self.markdown_card = markdown_card
-
-    async def get_access_token(self):
-        url = 'https://api.dingtalk.com/v1.0/oauth2/accessToken'
-        headers = {'Content-Type': 'application/json'}
-        data = {'appKey': self.key, 'appSecret': self.secret}
-        async with httpx.AsyncClient() as client:
-            try:
-                response = await client.post(url, json=data, headers=headers)
-                if response.status_code == 200:
-                    response_data = response.json()
-                    self.access_token = response_data.get('accessToken')
-                    expires_in = int(response_data.get('expireIn', 7200))
-                    self.access_token_expiry_time = time.time() + expires_in - 60
-            except Exception as e:
-                raise Exception(e)
-
-    async def is_token_expired(self):
-        """检查token是否过期"""
-        if self.access_token_expiry_time is None:
-            return True
-        return time.time() > self.access_token_expiry_time
-
-    async def check_access_token(self):
-        if not self.access_token or await self.is_token_expired():
-            return False
-        return bool(self.access_token and self.access_token.strip())
-
-    async def download_image(self, download_code: str):
-        if not await self.check_access_token():
-            await self.get_access_token()
-        url = 'https://api.dingtalk.com/v1.0/robot/messageFiles/download'
-        params = {'downloadCode': download_code, 'robotCode': self.robot_code}
-        headers = {'x-acs-dingtalk-access-token': self.access_token}
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, headers=headers, json=params)
-            if response.status_code == 200:
-                result = response.json()
-                download_url = result.get('downloadUrl')
-            else:
-                raise Exception(f'Error: {response.status_code}, {response.text}')
-
-        if download_url:
-            return await self.download_url_to_base64(download_url)
-
-    async def download_url_to_base64(self, download_url):
-        async with httpx.AsyncClient() as client:
-            response = await client.get(download_url)
-
-            if response.status_code == 200:
-                file_bytes = response.content
-                base64_str = base64.b64encode(file_bytes).decode('utf-8')  # 返回字符串格式
-                return base64_str
-            else:
-                raise Exception('获取文件失败')
-
-    async def get_audio_url(self, download_code: str):
-        if not await self.check_access_token():
-            await self.get_access_token()
-        url = 'https://api.dingtalk.com/v1.0/robot/messageFiles/download'
-        params = {'downloadCode': download_code, 'robotCode': self.robot_code}
-        headers = {'x-acs-dingtalk-access-token': self.access_token}
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, headers=headers, json=params)
-            if response.status_code == 200:
-                result = response.json()
-                download_url = result.get('downloadUrl')
-                if download_url:
-                    return await self.download_url_to_base64(download_url)
-                else:
-                    raise Exception('获取音频失败')
-            else:
-                raise Exception(f'Error: {response.status_code}, {response.text}')
-
-    async def update_incoming_message(self, message):
-        """异步更新 DingTalkClient 中的 incoming_message"""
-        message_data = await self.get_message(message)
-        if message_data:
-            event = DingTalkEvent.from_payload(message_data)
-            if event:
-                await self._handle_message(event)
-
-    async def send_message(self, content: str, incoming_message,at:bool):
-        if self.markdown_card:
-            if at:
-                self.EchoTextHandler.reply_markdown(
-                    title='@'+incoming_message.sender_nick+' '+content,
-                    text='@'+incoming_message.sender_nick+' '+content,
-                    incoming_message=incoming_message,
-                )
-            else:
-                self.EchoTextHandler.reply_markdown(
-                    title=content,
-                    text=content,
-                    incoming_message=incoming_message,
-                )
-        else:
-            self.EchoTextHandler.reply_text(content, incoming_message)
-
-    async def get_incoming_message(self):
-        """获取收到的消息"""
-        return await self.EchoTextHandler.get_incoming_message()
-
-    def on_message(self, msg_type: str):
-        def decorator(func: Callable[[DingTalkEvent], None]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-    async def _handle_message(self, event: DingTalkEvent):
-        """
-        处理消息事件。
-        """
-        msg_type = event.conversation
-        if msg_type in self._message_handlers:
-            for handler in self._message_handlers[msg_type]:
-                await handler(event)
-
-    async def get_message(self, incoming_message: dingtalk_stream.chatbot.ChatbotMessage):
-        try:
-            # print(json.dumps(incoming_message.to_dict(), indent=4, ensure_ascii=False))
-            message_data = {
-                'IncomingMessage': incoming_message,
-            }
-            if str(incoming_message.conversation_type) == '1':
-                message_data['conversation_type'] = 'FriendMessage'
-            elif str(incoming_message.conversation_type) == '2':
-                message_data['conversation_type'] = 'GroupMessage'
-
-            if incoming_message.message_type == 'richText':
-                data = incoming_message.rich_text_content.to_dict()
-                for item in data['richText']:
-                    if 'text' in item:
-                        message_data['Content'] = item['text']
-                    if incoming_message.get_image_list()[0]:
-                        message_data['Picture'] = await self.download_image(incoming_message.get_image_list()[0])
-                message_data['Type'] = 'text'
-
-            elif incoming_message.message_type == 'text':
-                message_data['Content'] = incoming_message.get_text_list()[0]
-
-                message_data['Type'] = 'text'
-            elif incoming_message.message_type == 'picture':
-                message_data['Picture'] = await self.download_image(incoming_message.get_image_list()[0])
-
-                message_data['Type'] = 'image'
-            elif incoming_message.message_type == 'audio':
-                message_data['Audio'] = await self.get_audio_url(incoming_message.to_dict()['content']['downloadCode'])
-
-                message_data['Type'] = 'audio'
-
-            copy_message_data = message_data.copy()
-            del copy_message_data['IncomingMessage']
-            # print("message_data:", json.dumps(copy_message_data, indent=4, ensure_ascii=False))
-        except Exception:
-            traceback.print_exc()
-
-        return message_data
-
-    async def send_proactive_message_to_one(self, target_id: str, content: str):
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = 'https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend'
-
-        headers = {
-            'x-acs-dingtalk-access-token': self.access_token,
-            'Content-Type': 'application/json',
-        }
-
-        data = {
-            'robotCode': self.robot_code,
-            'userIds': [target_id],
-            'msgKey': 'sampleText',
-            'msgParam': json.dumps({'content': content}),
-        }
-        try:
-            async with httpx.AsyncClient() as client:
-                await client.post(url, headers=headers, json=data)
-        except Exception:
-            traceback.print_exc()
-
-    async def send_proactive_message_to_group(self, target_id: str, content: str):
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = 'https://api.dingtalk.com/v1.0/robot/groupMessages/send'
-
-        headers = {
-            'x-acs-dingtalk-access-token': self.access_token,
-            'Content-Type': 'application/json',
-        }
-
-        data = {
-            'robotCode': self.robot_code,
-            'openConversationId': target_id,
-            'msgKey': 'sampleText',
-            'msgParam': json.dumps({'content': content}),
-        }
-        try:
-            async with httpx.AsyncClient() as client:
-                await client.post(url, headers=headers, json=data)
-        except Exception:
-            traceback.print_exc()
-
-    async def start(self):
-        """启动 WebSocket 连接，监听消息"""
-        await self.client.start()

libs/qq_official_api/api.py

@@ -1,256 +0,0 @@
-import time
-from quart import request
-import httpx
-from quart import Quart
-from typing import Callable, Dict, Any
-from pkg.platform.types import events as platform_events
-from .qqofficialevent import QQOfficialEvent
-import json
-import traceback
-from cryptography.hazmat.primitives.asymmetric import ed25519
-
-
-def handle_validation(body: dict, bot_secret: str):
-    # bot正确的secert是32位的，此处仅为了适配演示demo
-    while len(bot_secret) < 32:
-        bot_secret = bot_secret * 2
-    bot_secret = bot_secret[:32]
-    # 实际使用场景中以上三行内容可清除
-
-    seed_bytes = bot_secret.encode()
-
-    signing_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed_bytes)
-
-    msg = body['d']['event_ts'] + body['d']['plain_token']
-    msg_bytes = msg.encode()
-
-    signature = signing_key.sign(msg_bytes)
-
-    signature_hex = signature.hex()
-
-    response = {'plain_token': body['d']['plain_token'], 'signature': signature_hex}
-
-    return response
-
-
-class QQOfficialClient:
-    def __init__(self, secret: str, token: str, app_id: str):
-        self.app = Quart(__name__)
-        self.app.add_url_rule(
-            '/callback/command',
-            'handle_callback',
-            self.handle_callback_request,
-            methods=['GET', 'POST'],
-        )
-        self.secret = secret
-        self.token = token
-        self.app_id = app_id
-        self._message_handlers = {}
-        self.base_url = 'https://api.sgroup.qq.com'
-        self.access_token = ''
-        self.access_token_expiry_time = None
-
-    async def check_access_token(self):
-        """检查access_token是否存在"""
-        if not self.access_token or await self.is_token_expired():
-            return False
-        return bool(self.access_token and self.access_token.strip())
-
-    async def get_access_token(self):
-        """获取access_token"""
-        url = 'https://bots.qq.com/app/getAppAccessToken'
-        async with httpx.AsyncClient() as client:
-            params = {
-                'appId': self.app_id,
-                'clientSecret': self.secret,
-            }
-            headers = {
-                'content-type': 'application/json',
-            }
-            try:
-                response = await client.post(url, json=params, headers=headers)
-                if response.status_code == 200:
-                    response_data = response.json()
-                access_token = response_data.get('access_token')
-                expires_in = int(response_data.get('expires_in', 7200))
-                self.access_token_expiry_time = time.time() + expires_in - 60
-                if access_token:
-                    self.access_token = access_token
-            except Exception as e:
-                raise Exception(f'获取access_token失败: {e}')
-
-    async def handle_callback_request(self):
-        """处理回调请求"""
-        try:
-            # 读取请求数据
-            body = await request.get_data()
-            payload = json.loads(body)
-
-            # 验证是否为回调验证请求
-            if payload.get('op') == 13:
-                # 生成签名
-                response = handle_validation(payload, self.secret)
-
-                return response
-
-            if payload.get('op') == 0:
-                message_data = await self.get_message(payload)
-                if message_data:
-                    event = QQOfficialEvent.from_payload(message_data)
-                    await self._handle_message(event)
-
-            return {'code': 0, 'message': 'success'}
-
-        except Exception as e:
-            traceback.print_exc()
-            return {'error': str(e)}, 400
-
-    async def run_task(self, host: str, port: int, *args, **kwargs):
-        """启动 Quart 应用"""
-        await self.app.run_task(host=host, port=port, *args, **kwargs)
-
-    def on_message(self, msg_type: str):
-        """注册消息类型处理器"""
-
-        def decorator(func: Callable[[platform_events.Event], None]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-    async def _handle_message(self, event: QQOfficialEvent):
-        """处理消息事件"""
-        msg_type = event.t
-        if msg_type in self._message_handlers:
-            for handler in self._message_handlers[msg_type]:
-                await handler(event)
-
-    async def get_message(self, msg: dict) -> Dict[str, Any]:
-        """获取消息"""
-        message_data = {
-            't': msg.get('t', {}),
-            'user_openid': msg.get('d', {}).get('author', {}).get('user_openid', {}),
-            'timestamp': msg.get('d', {}).get('timestamp', {}),
-            'd_author_id': msg.get('d', {}).get('author', {}).get('id', {}),
-            'content': msg.get('d', {}).get('content', {}),
-            'd_id': msg.get('d', {}).get('id', {}),
-            'id': msg.get('id', {}),
-            'channel_id': msg.get('d', {}).get('channel_id', {}),
-            'username': msg.get('d', {}).get('author', {}).get('username', {}),
-            'guild_id': msg.get('d', {}).get('guild_id', {}),
-            'member_openid': msg.get('d', {}).get('author', {}).get('openid', {}),
-            'group_openid': msg.get('d', {}).get('group_openid', {}),
-        }
-        attachments = msg.get('d', {}).get('attachments', [])
-        image_attachments = [attachment['url'] for attachment in attachments if await self.is_image(attachment)]
-        image_attachments_type = [
-            attachment['content_type'] for attachment in attachments if await self.is_image(attachment)
-        ]
-        if image_attachments:
-            message_data['image_attachments'] = image_attachments[0]
-            message_data['content_type'] = image_attachments_type[0]
-        else:
-            message_data['image_attachments'] = None
-
-        return message_data
-
-    async def is_image(self, attachment: dict) -> bool:
-        """判断是否为图片附件"""
-        content_type = attachment.get('content_type', '')
-        return content_type.startswith('image/')
-
-    async def send_private_text_msg(self, user_openid: str, content: str, msg_id: str):
-        """发送私聊消息"""
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = self.base_url + '/v2/users/' + user_openid + '/messages'
-        async with httpx.AsyncClient() as client:
-            headers = {
-                'Authorization': f'QQBot {self.access_token}',
-                'Content-Type': 'application/json',
-            }
-            data = {
-                'content': content,
-                'msg_type': 0,
-                'msg_id': msg_id,
-            }
-            response = await client.post(url, headers=headers, json=data)
-            if response.status_code == 200:
-                return
-            else:
-                raise ValueError(response)
-
-    async def send_group_text_msg(self, group_openid: str, content: str, msg_id: str):
-        """发送群聊消息"""
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = self.base_url + '/v2/groups/' + group_openid + '/messages'
-        async with httpx.AsyncClient() as client:
-            headers = {
-                'Authorization': f'QQBot {self.access_token}',
-                'Content-Type': 'application/json',
-            }
-            data = {
-                'content': content,
-                'msg_type': 0,
-                'msg_id': msg_id,
-            }
-            response = await client.post(url, headers=headers, json=data)
-            if response.status_code == 200:
-                return
-            else:
-                raise Exception(response.read().decode())
-
-    async def send_channle_group_text_msg(self, channel_id: str, content: str, msg_id: str):
-        """发送频道群聊消息"""
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = self.base_url + '/channels/' + channel_id + '/messages'
-        async with httpx.AsyncClient() as client:
-            headers = {
-                'Authorization': f'QQBot {self.access_token}',
-                'Content-Type': 'application/json',
-            }
-            params = {
-                'content': content,
-                'msg_type': 0,
-                'msg_id': msg_id,
-            }
-            response = await client.post(url, headers=headers, json=params)
-            if response.status_code == 200:
-                return True
-            else:
-                raise Exception(response)
-
-    async def send_channle_private_text_msg(self, guild_id: str, content: str, msg_id: str):
-        """发送频道私聊消息"""
-        if not await self.check_access_token():
-            await self.get_access_token()
-
-        url = self.base_url + '/dms/' + guild_id + '/messages'
-        async with httpx.AsyncClient() as client:
-            headers = {
-                'Authorization': f'QQBot {self.access_token}',
-                'Content-Type': 'application/json',
-            }
-            params = {
-                'content': content,
-                'msg_type': 0,
-                'msg_id': msg_id,
-            }
-            response = await client.post(url, headers=headers, json=params)
-            if response.status_code == 200:
-                return True
-            else:
-                raise Exception(response)
-
-    async def is_token_expired(self):
-        """检查token是否过期"""
-        if self.access_token_expiry_time is None:
-            return True
-        return time.time() > self.access_token_expiry_time

libs/wechatpad_api/__init__.py

@@ -1 +0,0 @@
-from .client import WeChatPadClient

libs/wechatpad_api/api/message.py

@@ -1,123 +0,0 @@
-
-from libs.wechatpad_api.util.http_util import async_request, post_json
-
-
-class MessageApi:
-    def __init__(self, base_url, token):
-        self.base_url = base_url
-        self.token = token
-
-    def post_text(self, to_wxid, content, ats: list= []):
-        '''
-
-        Args:
-            app_id: 微信id
-            to_wxid: 发送方的微信id
-            content: 内容
-            ats: at
-
-        Returns:
-
-        '''
-        url = self.base_url + "/message/SendTextMessage"
-        """发送文字消息"""
-        json_data = {
-                      "MsgItem": [
-                        {
-                          "AtWxIDList": ats,
-                          "ImageContent": "",
-                          "MsgType": 0,
-                          "TextContent": content,
-                          "ToUserName": to_wxid
-                        }
-                      ]
-                    }
-        return  post_json(base_url=url, token=self.token, data=json_data)
-
-
-
-
-    def post_image(self, to_wxid, img_url, ats: list= []):
-        """发送图片消息"""
-        # 这里好像可以尝试发送多个暂时未测试
-        json_data = {
-            "MsgItem": [
-                {
-                    "AtWxIDList": ats,
-                    "ImageContent": img_url,
-                    "MsgType": 0,
-                    "TextContent": '',
-                    "ToUserName": to_wxid
-                }
-            ]
-        }
-        url = self.base_url + "/message/SendImageMessage"
-        return post_json(base_url=url, token=self.token, data=json_data)
-
-    def post_voice(self, to_wxid, voice_data, voice_forma, voice_duration):
-        """发送语音消息"""
-        json_data = {
-            "ToUserName": to_wxid,
-            "VoiceData": voice_data,
-            "VoiceFormat": voice_forma,
-            "VoiceSecond": voice_duration
-        }
-        url = self.base_url + "/message/SendVoice"
-        return post_json(base_url=url, token=self.token, data=json_data)
-
-
-
-
-
-    def post_name_card(self, alias, to_wxid, nick_name, name_card_wxid, flag):
-        """发送名片消息"""
-        param = {
-                "CardAlias": alias,
-                "CardFlag": flag,
-                "CardNickName": nick_name,
-                "CardWxId": name_card_wxid,
-                "ToUserName": to_wxid
-        }
-        url = f"{self.base_url}/message/ShareCardMessage"
-        return post_json(base_url=url, token=self.token, data=param)
-
-    def post_emoji(self, to_wxid, emoji_md5, emoji_size:int=0):
-        """发送emoji消息"""
-        json_data = {
-            "EmojiList": [
-                {
-                    "EmojiMd5": emoji_md5,
-                    "EmojiSize": emoji_size,
-                    "ToUserName": to_wxid
-                }
-            ]
-        }
-        url = f"{self.base_url}/message/SendEmojiMessage"
-        return post_json(base_url=url, token=self.token, data=json_data)
-
-    def post_app_msg(self, to_wxid,xml_data, contenttype:int=0):
-        """发送appmsg消息"""
-        json_data = {
-            "AppList": [
-                {
-                    "ContentType": contenttype,
-                    "ContentXML": xml_data,
-                    "ToUserName": to_wxid
-                }
-            ]
-        }
-        url = f"{self.base_url}/message/SendAppMessage"
-        return post_json(base_url=url, token=self.token, data=json_data)
-
-
-
-    def revoke_msg(self, to_wxid, msg_id, new_msg_id, create_time):
-        """撤回消息"""
-        param = {
-              "ClientMsgId": msg_id,
-              "CreateTime": create_time,
-              "NewMsgId": new_msg_id,
-              "ToUserName": to_wxid
-            }
-        url = f"{self.base_url}/message/RevokeMsg"
-        return post_json(base_url=url, token=self.token, data=param)

libs/wechatpad_api/util/http_util.py

@@ -1,92 +0,0 @@
-import requests
-
-def post_json(base_url, token, data=None):
-    headers = {
-        'Content-Type': 'application/json'
-    }
-
-
-    url = base_url + f'?key={token}'
-
-    try:
-        response = requests.post(url, json=data, headers=headers, timeout=60)
-        response.raise_for_status()
-        result = response.json()
-
-        if result:
-            return result
-        else:
-            raise RuntimeError(response.text)
-    except Exception as e:
-        print(f"http请求失败, url={url}, exception={e}")
-        raise RuntimeError(str(e))
-
-def get_json(base_url, token):
-    headers = {
-        'Content-Type': 'application/json'
-    }
-
-
-    url = base_url + f'?key={token}'
-
-    try:
-        response = requests.get(url, headers=headers, timeout=60)
-        response.raise_for_status()
-        result = response.json()
-
-        if result:
-            return result
-        else:
-            raise RuntimeError(response.text)
-    except Exception as e:
-        print(f"http请求失败, url={url}, exception={e}")
-        raise RuntimeError(str(e))
-
-import aiohttp
-import asyncio
-
-
-async def async_request(
-        base_url: str,
-        token_key: str,
-        method: str = 'POST',
-        params: dict = None,
-        # headers: dict = None,
-        data: dict = None,
-        json: dict = None
-):
-    """
-    通用异步请求函数
-
-    :param base_url: 请求URL
-    :param token_key: 请求token
-    :param method: HTTP方法 (GET, POST, PUT, DELETE等)
-    :param params: URL查询参数
-    # :param headers: 请求头
-    :param data: 表单数据
-    :param json: JSON数据
-    :return: 响应文本
-    """
-    headers = {
-        'Content-Type': 'application/json'
-    }
-    url = f"{base_url}?key={token_key}"
-    async with aiohttp.ClientSession() as session:
-        async with session.request(
-                method=method,
-                url=url,
-                params=params,
-                headers=headers,
-                data=data,
-                json=json
-        ) as response:
-            response.raise_for_status()  # 如果状态码不是200，抛出异常
-            result = await response.json()
-            # print(result)
-            return result
-            # if result.get('Code') == 200:
-            #
-            #     return await result
-            # else:
-            #     raise RuntimeError("请求失败",response.text)
-

libs/wecom_api/api.py

@@ -1,331 +0,0 @@
-from quart import request
-from .WXBizMsgCrypt3 import WXBizMsgCrypt
-import base64
-import binascii
-import httpx
-from quart import Quart
-import xml.etree.ElementTree as ET
-from typing import Callable, Dict, Any
-from .wecomevent import WecomEvent
-from pkg.platform.types import message as platform_message
-import aiofiles
-
-
-class WecomClient:
-    def __init__(
-        self,
-        corpid: str,
-        secret: str,
-        token: str,
-        EncodingAESKey: str,
-        contacts_secret: str,
-    ):
-        self.corpid = corpid
-        self.secret = secret
-        self.access_token_for_contacts = ''
-        self.token = token
-        self.aes = EncodingAESKey
-        self.base_url = 'https://qyapi.weixin.qq.com/cgi-bin'
-        self.access_token = ''
-        self.secret_for_contacts = contacts_secret
-        self.app = Quart(__name__)
-        self.app.add_url_rule(
-            '/callback/command',
-            'handle_callback',
-            self.handle_callback_request,
-            methods=['GET', 'POST'],
-        )
-        self._message_handlers = {
-            'example': [],
-        }
-
-    # access——token操作
-    async def check_access_token(self):
-        return bool(self.access_token and self.access_token.strip())
-
-    async def check_access_token_for_contacts(self):
-        return bool(self.access_token_for_contacts and self.access_token_for_contacts.strip())
-
-    async def get_access_token(self, secret):
-        url = f'https://qyapi.weixin.qq.com/cgi-bin/gettoken?corpid={self.corpid}&corpsecret={secret}'
-        async with httpx.AsyncClient() as client:
-            response = await client.get(url)
-            data = response.json()
-            if 'access_token' in data:
-                return data['access_token']
-            else:
-                raise Exception(f'未获取access token: {data}')
-
-    async def get_users(self):
-        if not self.check_access_token_for_contacts():
-            self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)
-
-        url = self.base_url + '/user/list_id?access_token=' + self.access_token_for_contacts
-        async with httpx.AsyncClient() as client:
-            params = {
-                'cursor': '',
-                'limit': 10000,
-            }
-            response = await client.post(url, json=params)
-            data = response.json()
-            if data['errcode'] == 0:
-                dept_users = data['dept_user']
-                userid = []
-                for user in dept_users:
-                    userid.append(user['userid'])
-                return userid
-            else:
-                raise Exception('未获取用户')
-
-    async def send_to_all(self, content: str, agent_id: int):
-        if not self.check_access_token_for_contacts():
-            self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)
-
-            url = self.base_url + '/message/send?access_token=' + self.access_token_for_contacts
-            user_ids = await self.get_users()
-            user_ids_string = '|'.join(user_ids)
-            async with httpx.AsyncClient() as client:
-                params = {
-                    'touser': user_ids_string,
-                    'msgtype': 'text',
-                    'agentid': agent_id,
-                    'text': {
-                        'content': content,
-                    },
-                    'safe': 0,
-                    'enable_id_trans': 0,
-                    'enable_duplicate_check': 0,
-                    'duplicate_check_interval': 1800,
-                }
-                response = await client.post(url, json=params)
-                data = response.json()
-                if data['errcode'] != 0:
-                    raise Exception('Failed to send message: ' + str(data))
-
-    async def send_image(self, user_id: str, agent_id: int, media_id: str):
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-        url = self.base_url + '/media/upload?access_token=' + self.access_token
-        async with httpx.AsyncClient() as client:
-            params = {
-                'touser': user_id,
-                'toparty': '',
-                'totag': '',
-                'agentid': agent_id,
-                'msgtype': 'image',
-                'image': {
-                    'media_id': media_id,
-                },
-                'safe': 0,
-                'enable_id_trans': 0,
-                'enable_duplicate_check': 0,
-                'duplicate_check_interval': 1800,
-            }
-            try:
-                response = await client.post(url, json=params)
-                data = response.json()
-            except Exception as e:
-                raise Exception('Failed to send image: ' + str(e))
-
-            # 企业微信错误码40014和42001，代表accesstoken问题
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.send_image(user_id, agent_id, media_id)
-
-            if data['errcode'] != 0:
-                raise Exception('Failed to send image: ' + str(data))
-
-    async def send_private_msg(self, user_id: str, agent_id: int, content: str):
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = self.base_url + '/message/send?access_token=' + self.access_token
-        async with httpx.AsyncClient() as client:
-            params = {
-                'touser': user_id,
-                'msgtype': 'text',
-                'agentid': agent_id,
-                'text': {
-                    'content': content,
-                },
-                'safe': 0,
-                'enable_id_trans': 0,
-                'enable_duplicate_check': 0,
-                'duplicate_check_interval': 1800,
-            }
-            response = await client.post(url, json=params)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.send_private_msg(user_id, agent_id, content)
-            if data['errcode'] != 0:
-                raise Exception('Failed to send message: ' + str(data))
-
-    async def handle_callback_request(self):
-        """
-        处理回调请求，包括 GET 验证和 POST 消息接收。
-        """
-        try:
-            msg_signature = request.args.get('msg_signature')
-            timestamp = request.args.get('timestamp')
-            nonce = request.args.get('nonce')
-
-            wxcpt = WXBizMsgCrypt(self.token, self.aes, self.corpid)
-            if request.method == 'GET':
-                echostr = request.args.get('echostr')
-                ret, reply_echo_str = wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
-                if ret != 0:
-                    raise Exception(f'验证失败，错误码: {ret}')
-                return reply_echo_str
-
-            elif request.method == 'POST':
-                encrypt_msg = await request.data
-                ret, xml_msg = wxcpt.DecryptMsg(encrypt_msg, msg_signature, timestamp, nonce)
-                if ret != 0:
-                    raise Exception(f'消息解密失败，错误码: {ret}')
-
-                # 解析消息并处理
-                message_data = await self.get_message(xml_msg)
-                if message_data:
-                    event = WecomEvent.from_payload(message_data)  # 转换为 WecomEvent 对象
-                    if event:
-                        await self._handle_message(event)
-
-                return 'success'
-        except Exception as e:
-            return f'Error processing request: {str(e)}', 400
-
-    async def run_task(self, host: str, port: int, *args, **kwargs):
-        """
-        启动 Quart 应用。
-        """
-        await self.app.run_task(host=host, port=port, *args, **kwargs)
-
-    def on_message(self, msg_type: str):
-        """
-        注册消息类型处理器。
-        """
-
-        def decorator(func: Callable[[WecomEvent], None]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-    async def _handle_message(self, event: WecomEvent):
-        """
-        处理消息事件。
-        """
-        msg_type = event.type
-        if msg_type in self._message_handlers:
-            for handler in self._message_handlers[msg_type]:
-                await handler(event)
-
-    async def get_message(self, xml_msg: str) -> Dict[str, Any]:
-        """
-        解析微信返回的 XML 消息并转换为字典。
-        """
-        root = ET.fromstring(xml_msg)
-        message_data = {
-            'ToUserName': root.find('ToUserName').text,
-            'FromUserName': root.find('FromUserName').text,
-            'CreateTime': int(root.find('CreateTime').text),
-            'MsgType': root.find('MsgType').text,
-            'Content': root.find('Content').text if root.find('Content') is not None else None,
-            'MsgId': int(root.find('MsgId').text) if root.find('MsgId') is not None else None,
-            'AgentID': int(root.find('AgentID').text) if root.find('AgentID') is not None else None,
-        }
-        if message_data['MsgType'] == 'image':
-            message_data['MediaId'] = root.find('MediaId').text if root.find('MediaId') is not None else None
-            message_data['PicUrl'] = root.find('PicUrl').text if root.find('PicUrl') is not None else None
-
-        return message_data
-
-    @staticmethod
-    async def get_image_type(image_bytes: bytes) -> str:
-        """
-        通过图片的magic numbers判断图片类型
-        """
-        magic_numbers = {
-            b'\xff\xd8\xff': 'jpg',
-            b'\x89\x50\x4e\x47': 'png',
-            b'\x47\x49\x46': 'gif',
-            b'\x42\x4d': 'bmp',
-            b'\x00\x00\x01\x00': 'ico',
-        }
-
-        for magic, ext in magic_numbers.items():
-            if image_bytes.startswith(magic):
-                return ext
-        return 'jpg'  # 默认返回jpg
-
-    async def upload_to_work(self, image: platform_message.Image):
-        """
-        获取 media_id
-        """
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
-        file_bytes = None
-        file_name = 'uploaded_file.txt'
-
-        # 获取文件的二进制数据
-        if image.path:
-            async with aiofiles.open(image.path, 'rb') as f:
-                file_bytes = await f.read()
-                file_name = image.path.split('/')[-1]
-        elif image.url:
-            file_bytes = await self.download_image_to_bytes(image.url)
-            file_name = image.url.split('/')[-1]
-        elif image.base64:
-            try:
-                base64_data = image.base64
-                if ',' in base64_data:
-                    base64_data = base64_data.split(',', 1)[1]
-                padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
-                padded_base64 = base64_data + '=' * padding
-                file_bytes = base64.b64decode(padded_base64)
-            except binascii.Error as e:
-                raise ValueError(f'Invalid base64 string: {str(e)}')
-        else:
-            raise ValueError('image对象出错')
-
-        # 设置 multipart/form-data 格式的文件
-        boundary = '-------------------------acebdf13572468'
-        headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
-        body = (
-            (
-                f'--{boundary}\r\n'
-                f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
-                f'Content-Type: application/octet-stream\r\n\r\n'
-            ).encode('utf-8')
-            + file_bytes
-            + f'\r\n--{boundary}--\r\n'.encode('utf-8')
-        )
-
-        # 上传文件
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, headers=headers, content=body)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                media_id = await self.upload_to_work(image)
-            if data.get('errcode', 0) != 0:
-                raise Exception('failed to upload file')
-
-            media_id = data.get('media_id')
-            return media_id
-
-    async def download_image_to_bytes(self, url: str) -> bytes:
-        async with httpx.AsyncClient() as client:
-            response = await client.get(url)
-            response.raise_for_status()
-            return response.content
-
-    # 进行media_id的获取
-    async def get_media_id(self, image: platform_message.Image):
-        media_id = await self.upload_to_work(image=image)
-        return media_id

main.py

@@ -1,99 +1,3 @@
-import asyncio
-# LangBot 终端启动入口
-# 在此层级解决依赖项检查。
-# LangBot/main.py
+import langbot.__main__
 
-asciiart = r"""
- _                   ___      _   
-| |   __ _ _ _  __ _| _ ) ___| |_ 
-| |__/ _` | ' \/ _` | _ \/ _ \  _|
-|____\__,_|_||_\__, |___/\___/\__|
-               |___/              
-
-⭐️ Open Source 开源地址: https://github.com/RockChinQ/LangBot
-📖 Documentation 文档地址: https://docs.langbot.app
-"""
-
-
-async def main_entry(loop: asyncio.AbstractEventLoop):
-    print(asciiart)
-
-    import sys
-
-    # 检查依赖
-
-    from pkg.core.bootutils import deps
-
-    missing_deps = await deps.check_deps()
-
-    if missing_deps:
-        print('以下依赖包未安装，将自动安装，请完成后重启程序：')
-        print(
-            'These dependencies are missing, they will be installed automatically, please restart the program after completion:'
-        )
-        for dep in missing_deps:
-            print('-', dep)
-        await deps.install_deps(missing_deps)
-        print('已自动安装缺失的依赖包，请重启程序。')
-        print('The missing dependencies have been installed automatically, please restart the program.')
-        sys.exit(0)
-
-    # check plugin deps
-    await deps.precheck_plugin_deps()
-
-    # 检查pydantic版本，如果没有 pydantic.v1，则把 pydantic 映射为 v1
-    import pydantic.version
-
-    if pydantic.version.VERSION < '2.0':
-        import pydantic
-
-        sys.modules['pydantic.v1'] = pydantic
-
-    # 检查配置文件
-
-    from pkg.core.bootutils import files
-
-    generated_files = await files.generate_files()
-
-    if generated_files:
-        print('以下文件不存在，已自动生成：')
-        print('Following files do not exist and have been automatically generated:')
-        for file in generated_files:
-            print('-', file)
-
-    from pkg.core import boot
-
-    await boot.main(loop)
-
-
-if __name__ == '__main__':
-    import os
-    import sys
-
-    # 必须大于 3.10.1
-    if sys.version_info < (3, 10, 1):
-        print('需要 Python 3.10.1 及以上版本，当前 Python 版本为：', sys.version)
-        input('按任意键退出...')
-        print('Your Python version is not supported. Please exit the program by pressing any key.')
-        exit(1)
-
-    # Check if the current directory is the LangBot project root directory
-    invalid_pwd = False
-
-    if not os.path.exists('main.py'):
-        invalid_pwd = True
-    else:
-        with open('main.py', 'r', encoding='utf-8') as f:
-            content = f.read()
-            if 'LangBot/main.py' not in content:
-                invalid_pwd = True
-    if invalid_pwd:
-        print('请在 LangBot 项目根目录下以命令形式运行此程序。')
-        input('按任意键退出...')
-        print('Please run this program in the LangBot project root directory in command form.')
-        print('Press any key to exit...')
-        exit(1)
-
-    loop = asyncio.new_event_loop()
-
-    loop.run_until_complete(main_entry(loop))
+langbot.__main__.main()

pkg/api/http/controller/group.py

@@ -1,125 +0,0 @@
-from __future__ import annotations
-
-import abc
-import typing
-import enum
-import quart
-import traceback
-from quart.typing import RouteCallable
-
-from ....core import app
-
-
-preregistered_groups: list[type[RouterGroup]] = []
-"""RouterGroup 的预注册列表"""
-
-
-def group_class(name: str, path: str) -> None:
-    """注册一个 RouterGroup"""
-
-    def decorator(cls: typing.Type[RouterGroup]) -> typing.Type[RouterGroup]:
-        cls.name = name
-        cls.path = path
-        preregistered_groups.append(cls)
-        return cls
-
-    return decorator
-
-
-class AuthType(enum.Enum):
-    """认证类型"""
-
-    NONE = 'none'
-    USER_TOKEN = 'user-token'
-
-
-class RouterGroup(abc.ABC):
-    name: str
-
-    path: str
-
-    ap: app.Application
-
-    quart_app: quart.Quart
-
-    def __init__(self, ap: app.Application, quart_app: quart.Quart) -> None:
-        self.ap = ap
-        self.quart_app = quart_app
-
-    @abc.abstractmethod
-    async def initialize(self) -> None:
-        pass
-
-    def route(
-        self,
-        rule: str,
-        auth_type: AuthType = AuthType.USER_TOKEN,
-        **options: typing.Any,
-    ) -> typing.Callable[[RouteCallable], RouteCallable]:  # decorator
-        """注册一个路由"""
-
-        def decorator(f: RouteCallable) -> RouteCallable:
-            nonlocal rule
-            rule = self.path + rule
-
-            async def handler_error(*args, **kwargs):
-                if auth_type == AuthType.USER_TOKEN:
-                    # 从Authorization头中获取token
-                    token = quart.request.headers.get('Authorization', '').replace('Bearer ', '')
-
-                    if not token:
-                        return self.http_status(401, -1, '未提供有效的用户令牌')
-
-                    try:
-                        user_email = await self.ap.user_service.verify_jwt_token(token)
-
-                        # check if this account exists
-                        user = await self.ap.user_service.get_user_by_email(user_email)
-                        if not user:
-                            return self.http_status(401, -1, '用户不存在')
-
-                        # 检查f是否接受user_email参数
-                        if 'user_email' in f.__code__.co_varnames:
-                            kwargs['user_email'] = user_email
-                    except Exception as e:
-                        return self.http_status(401, -1, str(e))
-
-                try:
-                    return await f(*args, **kwargs)
-                except Exception:  # 自动 500
-                    traceback.print_exc()
-                    # return self.http_status(500, -2, str(e))
-                    return self.http_status(500, -2, 'internal server error')
-
-            new_f = handler_error
-            new_f.__name__ = (self.name + rule).replace('/', '__')
-            new_f.__doc__ = f.__doc__
-
-            self.quart_app.route(rule, **options)(new_f)
-            return f
-
-        return decorator
-
-    def success(self, data: typing.Any = None) -> quart.Response:
-        """返回一个 200 响应"""
-        return quart.jsonify(
-            {
-                'code': 0,
-                'msg': 'ok',
-                'data': data,
-            }
-        )
-
-    def fail(self, code: int, msg: str) -> quart.Response:
-        """返回一个异常响应"""
-
-        return quart.jsonify(
-            {
-                'code': code,
-                'msg': msg,
-            }
-        )
-
-    def http_status(self, status: int, code: int, msg: str) -> quart.Response:
-        """返回一个指定状态码的响应"""
-        return self.fail(code, msg), status

pkg/api/http/controller/groups/pipelines.py

@@ -1,44 +0,0 @@
-from __future__ import annotations
-
-import quart
-
-from .. import group
-
-
-@group.group_class('pipelines', '/api/v1/pipelines')
-class PipelinesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'pipelines': await self.ap.pipeline_service.get_pipelines()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-
-                pipeline_uuid = await self.ap.pipeline_service.create_pipeline(json_data)
-
-                return self.success(data={'uuid': pipeline_uuid})
-
-        @self.route('/_/metadata', methods=['GET'])
-        async def _() -> str:
-            return self.success(data={'configs': await self.ap.pipeline_service.get_pipeline_metadata()})
-
-        @self.route('/<pipeline_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(pipeline_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                pipeline = await self.ap.pipeline_service.get_pipeline(pipeline_uuid)
-
-                if pipeline is None:
-                    return self.http_status(404, -1, 'pipeline not found')
-
-                return self.success(data={'pipeline': pipeline})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-
-                await self.ap.pipeline_service.update_pipeline(pipeline_uuid, json_data)
-
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.pipeline_service.delete_pipeline(pipeline_uuid)
-
-                return self.success()

pkg/api/http/controller/groups/platform/adapters.py

@@ -1,34 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('adapters', '/api/v1/platform/adapters')
-class AdaptersRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'])
-        async def _() -> str:
-            return self.success(data={'adapters': self.ap.platform_mgr.get_available_adapters_info()})
-
-        @self.route('/<adapter_name>', methods=['GET'])
-        async def _(adapter_name: str) -> str:
-            adapter_info = self.ap.platform_mgr.get_available_adapter_info_by_name(adapter_name)
-
-            if adapter_info is None:
-                return self.http_status(404, -1, 'adapter not found')
-
-            return self.success(data={'adapter': adapter_info})
-
-        @self.route('/<adapter_name>/icon', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _(adapter_name: str) -> quart.Response:
-            adapter_manifest = self.ap.platform_mgr.get_available_adapter_manifest_by_name(adapter_name)
-
-            if adapter_manifest is None:
-                return self.http_status(404, -1, 'adapter not found')
-
-            icon_path = adapter_manifest.icon_rel_path
-
-            if icon_path is None:
-                return self.http_status(404, -1, 'icon not found')
-
-            return await quart.send_file(icon_path)

pkg/api/http/controller/groups/platform/bots.py

@@ -1,31 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('bots', '/api/v1/platform/bots')
-class BotsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'bots': await self.ap.bot_service.get_bots()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-                bot_uuid = await self.ap.bot_service.create_bot(json_data)
-                return self.success(data={'uuid': bot_uuid})
-
-        @self.route('/<bot_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(bot_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                bot = await self.ap.bot_service.get_bot(bot_uuid)
-                if bot is None:
-                    return self.http_status(404, -1, 'bot not found')
-                return self.success(data={'bot': bot})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-                await self.ap.bot_service.update_bot(bot_uuid, json_data)
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.bot_service.delete_bot(bot_uuid)
-                return self.success()

pkg/api/http/controller/groups/plugins.py

@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-
-import quart
-
-from .....core import taskmgr
-from .. import group
-
-
-@group.group_class('plugins', '/api/v1/plugins')
-class PluginsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            plugins = self.ap.plugin_mgr.plugins()
-
-            plugins_data = [plugin.model_dump() for plugin in plugins]
-
-            return self.success(data={'plugins': plugins_data})
-
-        @self.route(
-            '/<author>/<plugin_name>/toggle',
-            methods=['PUT'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            data = await quart.request.json
-            target_enabled = data.get('target_enabled')
-            await self.ap.plugin_mgr.update_plugin_switch(plugin_name, target_enabled)
-            return self.success()
-
-        @self.route(
-            '/<author>/<plugin_name>/update',
-            methods=['POST'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_mgr.update_plugin(plugin_name, task_context=ctx),
-                kind='plugin-operation',
-                name=f'plugin-update-{plugin_name}',
-                label=f'更新插件 {plugin_name}',
-                context=ctx,
-            )
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>',
-            methods=['GET', 'DELETE'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            if quart.request.method == 'GET':
-                plugin = self.ap.plugin_mgr.get_plugin(author, plugin_name)
-                if plugin is None:
-                    return self.http_status(404, -1, 'plugin not found')
-                return self.success(data={'plugin': plugin.model_dump()})
-            elif quart.request.method == 'DELETE':
-                ctx = taskmgr.TaskContext.new()
-                wrapper = self.ap.task_mgr.create_user_task(
-                    self.ap.plugin_mgr.uninstall_plugin(plugin_name, task_context=ctx),
-                    kind='plugin-operation',
-                    name=f'plugin-remove-{plugin_name}',
-                    label=f'删除插件 {plugin_name}',
-                    context=ctx,
-                )
-
-                return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>/config',
-            methods=['GET', 'PUT'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> quart.Response:
-            plugin = self.ap.plugin_mgr.get_plugin(author, plugin_name)
-            if plugin is None:
-                return self.http_status(404, -1, 'plugin not found')
-            if quart.request.method == 'GET':
-                return self.success(data={'config': plugin.plugin_config})
-            elif quart.request.method == 'PUT':
-                data = await quart.request.json
-
-                await self.ap.plugin_mgr.set_plugin_config(plugin, data)
-
-                return self.success(data={})
-
-        @self.route('/reorder', methods=['PUT'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-            await self.ap.plugin_mgr.reorder_plugins(data.get('plugins'))
-            return self.success()
-
-        @self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-
-            ctx = taskmgr.TaskContext.new()
-            short_source_str = data['source'][-8:]
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_mgr.install_plugin(data['source'], task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-github',
-                label=f'安装插件 ...{short_source_str}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})

pkg/api/http/controller/groups/provider/models.py

@@ -1,46 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('models/llm', '/api/v1/provider/models/llm')
-class LLMModelsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'models': await self.ap.model_service.get_llm_models()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-
-                model_uuid = await self.ap.model_service.create_llm_model(json_data)
-
-                return self.success(data={'uuid': model_uuid})
-
-        @self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(model_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                model = await self.ap.model_service.get_llm_model(model_uuid)
-
-                if model is None:
-                    return self.http_status(404, -1, 'model not found')
-
-                return self.success(data={'model': model})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-
-                await self.ap.model_service.update_llm_model(model_uuid, json_data)
-
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.model_service.delete_llm_model(model_uuid)
-
-                return self.success()
-
-        @self.route('/<model_uuid>/test', methods=['POST'])
-        async def _(model_uuid: str) -> str:
-            json_data = await quart.request.json
-
-            await self.ap.model_service.test_llm_model(model_uuid, json_data)
-
-            return self.success()

pkg/api/http/controller/groups/system.py

@@ -1,56 +0,0 @@
-import quart
-
-from .. import group
-from .....utils import constants
-
-
-@group.group_class('system', '/api/v1/system')
-class SystemRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/info', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            return self.success(
-                data={
-                    'version': constants.semantic_version,
-                    'debug': constants.debug_mode,
-                    'enabled_platform_count': len(self.ap.platform_mgr.get_running_adapters()),
-                }
-            )
-
-        @self.route('/tasks', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            task_type = quart.request.args.get('type')
-
-            if task_type == '':
-                task_type = None
-
-            return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type))
-
-        @self.route('/tasks/<task_id>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(task_id: str) -> str:
-            task = self.ap.task_mgr.get_task_by_id(int(task_id))
-
-            if task is None:
-                return self.http_status(404, 404, 'Task not found')
-
-            return self.success(data=task.to_dict())
-
-        @self.route('/reload', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            json_data = await quart.request.json
-
-            scope = json_data.get('scope')
-
-            await self.ap.reload(scope=scope)
-            return self.success()
-
-        @self.route('/_debug/exec', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            if not constants.debug_mode:
-                return self.http_status(403, 403, 'Forbidden')
-
-            py_code = await quart.request.data
-
-            ap = self.ap
-
-            return self.success(data=exec(py_code, {'ap': ap}))

pkg/api/http/controller/groups/user.py

@@ -1,42 +0,0 @@
-import quart
-import argon2
-
-from .. import group
-
-
-@group.group_class('user', '/api/v1/user')
-class UserRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/init', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'initialized': await self.ap.user_service.is_initialized()})
-
-            if await self.ap.user_service.is_initialized():
-                return self.fail(1, '系统已初始化')
-
-            json_data = await quart.request.json
-
-            user_email = json_data['user']
-            password = json_data['password']
-
-            await self.ap.user_service.create_user(user_email, password)
-
-            return self.success()
-
-        @self.route('/auth', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            json_data = await quart.request.json
-
-            try:
-                token = await self.ap.user_service.authenticate(json_data['user'], json_data['password'])
-            except argon2.exceptions.VerifyMismatchError:
-                return self.fail(1, '用户名或密码错误')
-
-            return self.success(data={'token': token})
-
-        @self.route('/check-token', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            token = await self.ap.user_service.generate_jwt_token(user_email)
-
-            return self.success(data={'token': token})

pkg/api/http/service/bot.py

@@ -1,100 +0,0 @@
-from __future__ import annotations
-
-import uuid
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import bot as persistence_bot
-from ....entity.persistence import pipeline as persistence_pipeline
-
-
-class BotService:
-    """机器人服务"""
-
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_bots(self) -> list[dict]:
-        """获取所有机器人"""
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_bot.Bot))
-
-        bots = result.all()
-
-        return [self.ap.persistence_mgr.serialize_model(persistence_bot.Bot, bot) for bot in bots]
-
-    async def get_bot(self, bot_uuid: str) -> dict | None:
-        """获取机器人"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_bot.Bot).where(persistence_bot.Bot.uuid == bot_uuid)
-        )
-
-        bot = result.first()
-
-        if bot is None:
-            return None
-
-        return self.ap.persistence_mgr.serialize_model(persistence_bot.Bot, bot)
-
-    async def create_bot(self, bot_data: dict) -> str:
-        """创建机器人"""
-        # TODO: 检查配置信息格式
-        bot_data['uuid'] = str(uuid.uuid4())
-
-        # checkout the default pipeline
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
-                persistence_pipeline.LegacyPipeline.is_default == True
-            )
-        )
-        pipeline = result.first()
-        if pipeline is not None:
-            bot_data['use_pipeline_uuid'] = pipeline.uuid
-            bot_data['use_pipeline_name'] = pipeline.name
-
-        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_bot.Bot).values(bot_data))
-
-        bot = await self.get_bot(bot_data['uuid'])
-
-        await self.ap.platform_mgr.load_bot(bot)
-
-        return bot_data['uuid']
-
-    async def update_bot(self, bot_uuid: str, bot_data: dict) -> None:
-        """更新机器人"""
-        if 'uuid' in bot_data:
-            del bot_data['uuid']
-
-        # set use_pipeline_name
-        if 'use_pipeline_uuid' in bot_data:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
-                    persistence_pipeline.LegacyPipeline.uuid == bot_data['use_pipeline_uuid']
-                )
-            )
-            pipeline = result.first()
-            if pipeline is not None:
-                bot_data['use_pipeline_name'] = pipeline.name
-            else:
-                raise Exception('Pipeline not found')
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_bot.Bot).values(bot_data).where(persistence_bot.Bot.uuid == bot_uuid)
-        )
-        await self.ap.platform_mgr.remove_bot(bot_uuid)
-
-        # select from db
-        bot = await self.get_bot(bot_uuid)
-
-        runtime_bot = await self.ap.platform_mgr.load_bot(bot)
-
-        if runtime_bot.enable:
-            await runtime_bot.run()
-
-    async def delete_bot(self, bot_uuid: str) -> None:
-        """删除机器人"""
-        await self.ap.platform_mgr.remove_bot(bot_uuid)
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.delete(persistence_bot.Bot).where(persistence_bot.Bot.uuid == bot_uuid)
-        )

pkg/api/http/service/model.py

@@ -1,105 +0,0 @@
-from __future__ import annotations
-
-import uuid
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import model as persistence_model
-from ....entity.persistence import pipeline as persistence_pipeline
-from ....provider.modelmgr import requester as model_requester
-from ....provider import entities as llm_entities
-
-
-class ModelsService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_llm_models(self) -> list[dict]:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
-
-        models = result.all()
-        return [self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model) for model in models]
-
-    async def create_llm_model(self, model_data: dict) -> str:
-        model_data['uuid'] = str(uuid.uuid4())
-
-        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_model.LLMModel).values(**model_data))
-
-        llm_model = await self.get_llm_model(model_data['uuid'])
-
-        await self.ap.model_mgr.load_llm_model(llm_model)
-
-        # check if default pipeline has no model bound
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
-                persistence_pipeline.LegacyPipeline.is_default == True
-            )
-        )
-        pipeline = result.first()
-        if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
-            pipeline_config = pipeline.config
-            pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
-            pipeline_data = {'config': pipeline_config}
-            await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
-
-        return model_data['uuid']
-
-    async def get_llm_model(self, model_uuid: str) -> dict | None:
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
-        )
-
-        model = result.first()
-
-        if model is None:
-            return None
-
-        return self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
-
-    async def update_llm_model(self, model_uuid: str, model_data: dict) -> None:
-        if 'uuid' in model_data:
-            del model_data['uuid']
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_model.LLMModel)
-            .where(persistence_model.LLMModel.uuid == model_uuid)
-            .values(**model_data)
-        )
-
-        await self.ap.model_mgr.remove_llm_model(model_uuid)
-
-        llm_model = await self.get_llm_model(model_uuid)
-
-        await self.ap.model_mgr.load_llm_model(llm_model)
-
-    async def delete_llm_model(self, model_uuid: str) -> None:
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.delete(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
-        )
-
-        await self.ap.model_mgr.remove_llm_model(model_uuid)
-
-    async def test_llm_model(self, model_uuid: str, model_data: dict) -> None:
-        runtime_llm_model: model_requester.RuntimeLLMModel | None = None
-
-        if model_uuid != '_':
-            for model in self.ap.model_mgr.llm_models:
-                if model.model_entity.uuid == model_uuid:
-                    runtime_llm_model = model
-                    break
-
-            if runtime_llm_model is None:
-                raise Exception('model not found')
-
-        else:
-            runtime_llm_model = await self.ap.model_mgr.init_runtime_llm_model(model_data)
-
-        await runtime_llm_model.requester.invoke_llm(
-            query=None,
-            model=runtime_llm_model,
-            messages=[llm_entities.Message(role='user', content='Hello, world!')],
-            funcs=[],
-            extra_args={},
-        )

pkg/api/http/service/pipeline.py

@@ -1,121 +0,0 @@
-from __future__ import annotations
-
-import uuid
-import json
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import pipeline as persistence_pipeline
-
-
-default_stage_order = [
-    'GroupRespondRuleCheckStage',  # 群响应规则检查
-    'BanSessionCheckStage',  # 封禁会话检查
-    'PreContentFilterStage',  # 内容过滤前置阶段
-    'PreProcessor',  # 预处理器
-    'ConversationMessageTruncator',  # 会话消息截断器
-    'RequireRateLimitOccupancy',  # 请求速率限制占用
-    'MessageProcessor',  # 处理器
-    'ReleaseRateLimitOccupancy',  # 释放速率限制占用
-    'PostContentFilterStage',  # 内容过滤后置阶段
-    'ResponseWrapper',  # 响应包装器
-    'LongTextProcessStage',  # 长文本处理
-    'SendResponseBackStage',  # 发送响应
-]
-
-
-class PipelineService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_pipeline_metadata(self) -> dict:
-        return [
-            self.ap.pipeline_config_meta_trigger.data,
-            self.ap.pipeline_config_meta_safety.data,
-            self.ap.pipeline_config_meta_ai.data,
-            self.ap.pipeline_config_meta_output.data,
-        ]
-
-    async def get_pipelines(self) -> list[dict]:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        pipelines = result.all()
-        return [
-            self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-            for pipeline in pipelines
-        ]
-
-    async def get_pipeline(self, pipeline_uuid: str) -> dict | None:
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
-                persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid
-            )
-        )
-
-        pipeline = result.first()
-
-        if pipeline is None:
-            return None
-
-        return self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-    async def create_pipeline(self, pipeline_data: dict, default: bool = False) -> str:
-        pipeline_data['uuid'] = str(uuid.uuid4())
-        pipeline_data['for_version'] = self.ap.ver_mgr.get_current_version()
-        pipeline_data['stages'] = default_stage_order.copy()
-        pipeline_data['is_default'] = default
-        pipeline_data['config'] = json.load(open('templates/default-pipeline-config.json', 'r', encoding='utf-8'))
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(persistence_pipeline.LegacyPipeline).values(**pipeline_data)
-        )
-
-        pipeline = await self.get_pipeline(pipeline_data['uuid'])
-
-        await self.ap.pipeline_mgr.load_pipeline(pipeline)
-
-        return pipeline_data['uuid']
-
-    async def update_pipeline(self, pipeline_uuid: str, pipeline_data: dict) -> None:
-        if 'uuid' in pipeline_data:
-            del pipeline_data['uuid']
-        if 'for_version' in pipeline_data:
-            del pipeline_data['for_version']
-        if 'stages' in pipeline_data:
-            del pipeline_data['stages']
-        if 'is_default' in pipeline_data:
-            del pipeline_data['is_default']
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_pipeline.LegacyPipeline)
-            .where(persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid)
-            .values(**pipeline_data)
-        )
-
-        pipeline = await self.get_pipeline(pipeline_uuid)
-
-        if 'name' in pipeline_data:
-            from ....entity.persistence import bot as persistence_bot
-
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(persistence_bot.Bot).where(persistence_bot.Bot.use_pipeline_uuid == pipeline_uuid)
-            )
-
-            bots = result.all()
-
-            for bot in bots:
-                bot_data = {'use_pipeline_name': pipeline_data['name']}
-                await self.ap.bot_service.update_bot(bot.uuid, bot_data)
-
-        await self.ap.pipeline_mgr.remove_pipeline(pipeline_uuid)
-        await self.ap.pipeline_mgr.load_pipeline(pipeline)
-
-    async def delete_pipeline(self, pipeline_uuid: str) -> None:
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.delete(persistence_pipeline.LegacyPipeline).where(
-                persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid
-            )
-        )
-        await self.ap.pipeline_mgr.remove_pipeline(pipeline_uuid)

pkg/api/http/service/user.py

@@ -1,75 +0,0 @@
-from __future__ import annotations
-
-import sqlalchemy
-import argon2
-import jwt
-import datetime
-
-from ....core import app
-from ....entity.persistence import user
-from ....utils import constants
-
-
-class UserService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def is_initialized(self) -> bool:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
-
-        result_list = result.all()
-        return result_list is not None and len(result_list) > 0
-
-    async def create_user(self, user_email: str, password: str) -> None:
-        ph = argon2.PasswordHasher()
-
-        hashed_password = ph.hash(password)
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password)
-        )
-
-    async def get_user_by_email(self, user_email: str) -> user.User | None:
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(user.User).where(user.User.user == user_email)
-        )
-
-        result_list = result.all()
-        return result_list[0] if result_list is not None and len(result_list) > 0 else None
-
-    async def authenticate(self, user_email: str, password: str) -> str | None:
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(user.User).where(user.User.user == user_email)
-        )
-
-        result_list = result.all()
-
-        if result_list is None or len(result_list) == 0:
-            raise ValueError('用户不存在')
-
-        user_obj = result_list[0]
-
-        ph = argon2.PasswordHasher()
-
-        ph.verify(user_obj.password, password)
-
-        return await self.generate_jwt_token(user_email)
-
-    async def generate_jwt_token(self, user_email: str) -> str:
-        jwt_secret = self.ap.instance_config.data['system']['jwt']['secret']
-        jwt_expire = self.ap.instance_config.data['system']['jwt']['expire']
-
-        payload = {
-            'user': user_email,
-            'iss': 'LangBot-' + constants.edition,
-            'exp': datetime.datetime.now() + datetime.timedelta(seconds=jwt_expire),
-        }
-
-        return jwt.encode(payload, jwt_secret, algorithm='HS256')
-
-    async def verify_jwt_token(self, token: str) -> str:
-        jwt_secret = self.ap.instance_config.data['system']['jwt']['secret']
-
-        return jwt.decode(token, jwt_secret, algorithms=['HS256'])['user']

pkg/command/cmdmgr.py

@@ -1,114 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from ..core import app, entities as core_entities
-from . import entities, operator, errors
-from ..utils import importutil
-
-# 引入所有算子以便注册
-from . import operators
-
-importutil.import_modules_in_pkg(operators)
-
-
-class CommandManager:
-    """命令管理器"""
-
-    ap: app.Application
-
-    cmd_list: list[operator.CommandOperator]
-    """
-    运行时命令列表，扁平存储，各个对象包含对应的子节点引用
-    """
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def initialize(self):
-        # 设置各个类的路径
-        def set_path(cls: operator.CommandOperator, ancestors: list[str]):
-            cls.path = '.'.join(ancestors + [cls.name])
-            for op in operator.preregistered_operators:
-                if op.parent_class == cls:
-                    set_path(op, ancestors + [cls.name])
-
-        for cls in operator.preregistered_operators:
-            if cls.parent_class is None:
-                set_path(cls, [])
-
-        # 应用命令权限配置
-        for cls in operator.preregistered_operators:
-            if cls.path in self.ap.instance_config.data['command']['privilege']:
-                cls.lowest_privilege = self.ap.instance_config.data['command']['privilege'][cls.path]
-
-        # 实例化所有类
-        self.cmd_list = [cls(self.ap) for cls in operator.preregistered_operators]
-
-        # 设置所有类的子节点
-        for cmd in self.cmd_list:
-            cmd.children = [child for child in self.cmd_list if child.parent_class == cmd.__class__]
-
-        # 初始化所有类
-        for cmd in self.cmd_list:
-            await cmd.initialize()
-
-    async def _execute(
-        self,
-        context: entities.ExecuteContext,
-        operator_list: list[operator.CommandOperator],
-        operator: operator.CommandOperator = None,
-    ) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        """执行命令"""
-
-        found = False
-        if len(context.crt_params) > 0:  # 查找下一个参数是否对应此节点的某个子节点名
-            for oper in operator_list:
-                if (context.crt_params[0] == oper.name or context.crt_params[0] in oper.alias) and (
-                    oper.parent_class is None or oper.parent_class == operator.__class__
-                ):
-                    found = True
-
-                    context.crt_command = context.crt_params[0]
-                    context.crt_params = context.crt_params[1:]
-
-                    async for ret in self._execute(context, oper.children, oper):
-                        yield ret
-                    break
-
-        if not found:  # 如果下一个参数未在此节点的子节点中找到，则执行此节点或者报错
-            if operator is None:
-                yield entities.CommandReturn(error=errors.CommandNotFoundError(context.crt_params[0]))
-            else:
-                if operator.lowest_privilege > context.privilege:
-                    yield entities.CommandReturn(error=errors.CommandPrivilegeError(operator.name))
-                else:
-                    async for ret in operator.execute(context):
-                        yield ret
-
-    async def execute(
-        self,
-        command_text: str,
-        query: core_entities.Query,
-        session: core_entities.Session,
-    ) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        """执行命令"""
-
-        privilege = 1
-
-        if f'{query.launcher_type.value}_{query.launcher_id}' in self.ap.instance_config.data['admins']:
-            privilege = 2
-
-        ctx = entities.ExecuteContext(
-            query=query,
-            session=session,
-            command_text=command_text,
-            command='',
-            crt_command='',
-            params=command_text.split(' '),
-            crt_params=command_text.split(' '),
-            privilege=privilege,
-        )
-
-        async for ret in self._execute(ctx, self.cmd_list):
-            yield ret

pkg/command/entities.py

@@ -1,74 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-import pydantic.v1 as pydantic
-
-from ..core import entities as core_entities
-from . import errors
-from ..platform.types import message as platform_message
-
-
-class CommandReturn(pydantic.BaseModel):
-    """命令返回值"""
-
-    text: typing.Optional[str] = None
-    """文本
-    """
-
-    image: typing.Optional[platform_message.Image] = None
-    """弃用"""
-
-    image_url: typing.Optional[str] = None
-    """图片链接
-    """
-
-    error: typing.Optional[errors.CommandError] = None
-    """错误
-    """
-
-    class Config:
-        arbitrary_types_allowed = True
-
-
-class ExecuteContext(pydantic.BaseModel):
-    """单次命令执行上下文"""
-
-    query: core_entities.Query
-    """本次消息的请求对象"""
-
-    session: core_entities.Session
-    """本次消息所属的会话对象"""
-
-    command_text: str
-    """命令完整文本"""
-
-    command: str
-    """命令名称"""
-
-    crt_command: str
-    """当前命令
-    
-    多级命令中crt_command为当前命令，command为根命令。
-    例如：!plugin on Webwlkr
-    处理到plugin时，command为plugin，crt_command为plugin
-    处理到on时，command为plugin，crt_command为on
-    """
-
-    params: list[str]
-    """命令参数
-    
-    整个命令以空格分割后的参数列表
-    """
-
-    crt_params: list[str]
-    """当前命令参数
-
-    多级命令中crt_params为当前命令参数，params为根命令参数。
-    例如：!plugin on Webwlkr
-    处理到plugin时，params为['on', 'Webwlkr']，crt_params为['on', 'Webwlkr']
-    处理到on时，params为['on', 'Webwlkr']，crt_params为['Webwlkr']
-    """
-
-    privilege: int
-    """发起人权限"""

pkg/command/errors.py

@@ -1,26 +0,0 @@
-class CommandError(Exception):
-    def __init__(self, message: str = None):
-        self.message = message
-
-    def __str__(self):
-        return self.message
-
-
-class CommandNotFoundError(CommandError):
-    def __init__(self, message: str = None):
-        super().__init__('未知命令: ' + message)
-
-
-class CommandPrivilegeError(CommandError):
-    def __init__(self, message: str = None):
-        super().__init__('权限不足: ' + message)
-
-
-class ParamNotEnoughError(CommandError):
-    def __init__(self, message: str = None):
-        super().__init__('参数不足: ' + message)
-
-
-class CommandOperationError(CommandError):
-    def __init__(self, message: str = None):
-        super().__init__('操作失败: ' + message)

pkg/command/operators/cmd.py

@@ -1,41 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='cmd', help='显示命令列表', usage='!cmd\n!cmd <命令名称>')
-class CmdOperator(operator.CommandOperator):
-    """命令列表"""
-
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        """执行"""
-        if len(context.crt_params) == 0:
-            reply_str = '当前所有命令: \n\n'
-
-            for cmd in self.ap.cmd_mgr.cmd_list:
-                if cmd.parent_class is None:
-                    reply_str += f'{cmd.name}: {cmd.help}\n'
-
-            reply_str += '\n使用 !cmd <命令名称> 查看命令的详细帮助'
-
-            yield entities.CommandReturn(text=reply_str.strip())
-
-        else:
-            cmd_name = context.crt_params[0]
-
-            cmd = None
-
-            for _cmd in self.ap.cmd_mgr.cmd_list:
-                if (cmd_name == _cmd.name or cmd_name in _cmd.alias) and (_cmd.parent_class is None):
-                    cmd = _cmd
-                    break
-
-            if cmd is None:
-                yield entities.CommandReturn(error=errors.CommandNotFoundError(cmd_name))
-            else:
-                reply_str = f'{cmd.name}: {cmd.help}\n\n'
-                reply_str += f'使用方法: \n{cmd.usage}'
-
-                yield entities.CommandReturn(text=reply_str.strip())

pkg/command/operators/delc.py

@@ -1,43 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='del', help='删除当前会话的历史记录', usage='!del <序号>\n!del all')
-class DelOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if context.session.conversations:
-            delete_index = 0
-            if len(context.crt_params) > 0:
-                try:
-                    delete_index = int(context.crt_params[0])
-                except Exception:
-                    yield entities.CommandReturn(error=errors.CommandOperationError('索引必须是整数'))
-                    return
-
-            if delete_index < 0 or delete_index >= len(context.session.conversations):
-                yield entities.CommandReturn(error=errors.CommandOperationError('索引超出范围'))
-                return
-
-            # 倒序
-            to_delete_index = len(context.session.conversations) - 1 - delete_index
-
-            if context.session.conversations[to_delete_index] == context.session.using_conversation:
-                context.session.using_conversation = None
-
-            del context.session.conversations[to_delete_index]
-
-            yield entities.CommandReturn(text=f'已删除对话: {delete_index}')
-        else:
-            yield entities.CommandReturn(error=errors.CommandOperationError('当前没有对话'))
-
-
-@operator.operator_class(name='all', help='删除此会话的所有历史记录', parent_class=DelOperator)
-class DelAllOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        context.session.conversations = []
-        context.session.using_conversation = None
-
-        yield entities.CommandReturn(text='已删除所有对话')

pkg/command/operators/func.py

@@ -1,26 +0,0 @@
-from __future__ import annotations
-from typing import AsyncGenerator
-
-from .. import operator, entities
-
-
-@operator.operator_class(name='func', help='查看所有已注册的内容函数', usage='!func')
-class FuncOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> AsyncGenerator[entities.CommandReturn, None]:
-        reply_str = '当前已启用的内容函数: \n\n'
-
-        index = 1
-
-        all_functions = await self.ap.tool_mgr.get_all_functions(
-            plugin_enabled=True,
-        )
-
-        for func in all_functions:
-            reply_str += '{}. {}:\n{}\n\n'.format(
-                index,
-                func.name,
-                func.description,
-            )
-            index += 1
-
-        yield entities.CommandReturn(text=reply_str)

pkg/command/operators/help.py

@@ -1,15 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities
-
-
-@operator.operator_class(name='help', help='显示帮助', usage='!help\n!help <命令名称>')
-class HelpOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        help = 'LangBot - 大语言模型原生即时通信机器人平台\n链接：https://langbot.app'
-
-        help += '\n发送命令 !cmd 可查看命令列表'
-
-        yield entities.CommandReturn(text=help)

pkg/command/operators/last.py

@@ -1,28 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='last', help='切换到前一个对话', usage='!last')
-class LastOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if context.session.conversations:
-            # 找到当前会话的上一个会话
-            for index in range(len(context.session.conversations) - 1, -1, -1):
-                if context.session.conversations[index] == context.session.using_conversation:
-                    if index == 0:
-                        yield entities.CommandReturn(error=errors.CommandOperationError('已经是第一个对话了'))
-                        return
-                    else:
-                        context.session.using_conversation = context.session.conversations[index - 1]
-                        time_str = context.session.using_conversation.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-                        yield entities.CommandReturn(
-                            text=f'已切换到上一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].readable_str()}'
-                        )
-                        return
-        else:
-            yield entities.CommandReturn(error=errors.CommandOperationError('当前没有对话'))

pkg/command/operators/list.py

@@ -1,48 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='list', help='列出此会话中的所有历史对话', usage='!list\n!list <页码>')
-class ListOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        page = 0
-
-        if len(context.crt_params) > 0:
-            try:
-                page = int(context.crt_params[0] - 1)
-            except Exception:
-                yield entities.CommandReturn(error=errors.CommandOperationError('页码应为整数'))
-                return
-
-        record_per_page = 10
-
-        content = ''
-
-        index = 0
-
-        using_conv_index = 0
-
-        for conv in context.session.conversations[::-1]:
-            time_str = conv.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-            if conv == context.session.using_conversation:
-                using_conv_index = index
-
-            if index >= page * record_per_page and index < (page + 1) * record_per_page:
-                content += (
-                    f'{index} {time_str}: {conv.messages[0].readable_str() if len(conv.messages) > 0 else "无内容"}\n'
-                )
-            index += 1
-
-        if content == '':
-            content = '无'
-        else:
-            if context.session.using_conversation is None:
-                content += '\n当前处于新会话'
-            else:
-                content += f'\n当前会话: {using_conv_index} {context.session.using_conversation.create_time.strftime("%Y-%m-%d %H:%M:%S")}: {context.session.using_conversation.messages[0].readable_str() if len(context.session.using_conversation.messages) > 0 else "无内容"}'
-
-        yield entities.CommandReturn(text=f'第 {page + 1} 页 (时间倒序):\n{content}')

pkg/command/operators/next.py

@@ -1,27 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='next', help='切换到后一个对话', usage='!next')
-class NextOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if context.session.conversations:
-            # 找到当前会话的下一个会话
-            for index in range(len(context.session.conversations)):
-                if context.session.conversations[index] == context.session.using_conversation:
-                    if index == len(context.session.conversations) - 1:
-                        yield entities.CommandReturn(error=errors.CommandOperationError('已经是最后一个对话了'))
-                        return
-                    else:
-                        context.session.using_conversation = context.session.conversations[index + 1]
-                        time_str = context.session.using_conversation.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-                        yield entities.CommandReturn(
-                            text=f'已切换到后一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].content}'
-                        )
-                        return
-        else:
-            yield entities.CommandReturn(error=errors.CommandOperationError('当前没有对话'))

pkg/command/operators/plugin.py

@@ -1,156 +0,0 @@
-from __future__ import annotations
-import typing
-import traceback
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(
-    name='plugin',
-    help='插件操作',
-    usage='!plugin\n!plugin get <插件仓库地址>\n!plugin update\n!plugin del <插件名>\n!plugin on <插件名>\n!plugin off <插件名>',
-)
-class PluginOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        plugin_list = self.ap.plugin_mgr.plugins()
-        reply_str = '所有插件({}):\n'.format(len(plugin_list))
-        idx = 0
-        for plugin in plugin_list:
-            reply_str += '\n#{} {} {}\n{}\nv{}\n作者: {}\n'.format(
-                (idx + 1),
-                plugin.plugin_name,
-                '[已禁用]' if not plugin.enabled else '',
-                plugin.plugin_description,
-                plugin.plugin_version,
-                plugin.plugin_author,
-            )
-
-            idx += 1
-
-        yield entities.CommandReturn(text=reply_str)
-
-
-@operator.operator_class(name='get', help='安装插件', privilege=2, parent_class=PluginOperator)
-class PluginGetOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供插件仓库地址'))
-        else:
-            repo = context.crt_params[0]
-
-            yield entities.CommandReturn(text='正在安装插件...')
-
-            try:
-                await self.ap.plugin_mgr.install_plugin(repo)
-                yield entities.CommandReturn(text='插件安装成功，请重启程序以加载插件')
-            except Exception as e:
-                traceback.print_exc()
-                yield entities.CommandReturn(error=errors.CommandError('插件安装失败: ' + str(e)))
-
-
-@operator.operator_class(name='update', help='更新插件', privilege=2, parent_class=PluginOperator)
-class PluginUpdateOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-
-                if plugin_container is not None:
-                    yield entities.CommandReturn(text='正在更新插件...')
-                    await self.ap.plugin_mgr.update_plugin(plugin_name)
-                    yield entities.CommandReturn(text='插件更新成功，请重启程序以加载插件')
-                else:
-                    yield entities.CommandReturn(error=errors.CommandError('插件更新失败: 未找到插件'))
-            except Exception as e:
-                traceback.print_exc()
-                yield entities.CommandReturn(error=errors.CommandError('插件更新失败: ' + str(e)))
-
-
-@operator.operator_class(name='all', help='更新所有插件', privilege=2, parent_class=PluginUpdateOperator)
-class PluginUpdateAllOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        try:
-            plugins = [p.plugin_name for p in self.ap.plugin_mgr.plugins()]
-
-            if plugins:
-                yield entities.CommandReturn(text='正在更新插件...')
-                updated = []
-                try:
-                    for plugin_name in plugins:
-                        await self.ap.plugin_mgr.update_plugin(plugin_name)
-                        updated.append(plugin_name)
-                except Exception as e:
-                    traceback.print_exc()
-                    yield entities.CommandReturn(error=errors.CommandError('插件更新失败: ' + str(e)))
-                yield entities.CommandReturn(text='已更新插件: {}'.format(', '.join(updated)))
-            else:
-                yield entities.CommandReturn(text='没有可更新的插件')
-        except Exception as e:
-            traceback.print_exc()
-            yield entities.CommandReturn(error=errors.CommandError('插件更新失败: ' + str(e)))
-
-
-@operator.operator_class(name='del', help='删除插件', privilege=2, parent_class=PluginOperator)
-class PluginDelOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-
-                if plugin_container is not None:
-                    yield entities.CommandReturn(text='正在删除插件...')
-                    await self.ap.plugin_mgr.uninstall_plugin(plugin_name)
-                    yield entities.CommandReturn(text='插件删除成功，请重启程序以加载插件')
-                else:
-                    yield entities.CommandReturn(error=errors.CommandError('插件删除失败: 未找到插件'))
-            except Exception as e:
-                traceback.print_exc()
-                yield entities.CommandReturn(error=errors.CommandError('插件删除失败: ' + str(e)))
-
-
-@operator.operator_class(name='on', help='启用插件', privilege=2, parent_class=PluginOperator)
-class PluginEnableOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                if await self.ap.plugin_mgr.update_plugin_switch(plugin_name, True):
-                    yield entities.CommandReturn(text='已启用插件: {}'.format(plugin_name))
-                else:
-                    yield entities.CommandReturn(
-                        error=errors.CommandError('插件状态修改失败: 未找到插件 {}'.format(plugin_name))
-                    )
-            except Exception as e:
-                traceback.print_exc()
-                yield entities.CommandReturn(error=errors.CommandError('插件状态修改失败: ' + str(e)))
-
-
-@operator.operator_class(name='off', help='禁用插件', privilege=2, parent_class=PluginOperator)
-class PluginDisableOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                if await self.ap.plugin_mgr.update_plugin_switch(plugin_name, False):
-                    yield entities.CommandReturn(text='已禁用插件: {}'.format(plugin_name))
-                else:
-                    yield entities.CommandReturn(
-                        error=errors.CommandError('插件状态修改失败: 未找到插件 {}'.format(plugin_name))
-                    )
-            except Exception as e:
-                traceback.print_exc()
-                yield entities.CommandReturn(error=errors.CommandError('插件状态修改失败: ' + str(e)))

pkg/command/operators/prompt.py

@@ -1,20 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='prompt', help='查看当前对话的前文', usage='!prompt')
-class PromptOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        """执行"""
-        if context.session.using_conversation is None:
-            yield entities.CommandReturn(error=errors.CommandOperationError('当前没有对话'))
-        else:
-            reply_str = '当前对话所有内容:\n\n'
-
-            for msg in context.session.using_conversation.messages:
-                reply_str += f'{msg.role}: {msg.content}\n'
-
-            yield entities.CommandReturn(text=reply_str)

pkg/command/operators/resend.py

@@ -1,26 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities, errors
-
-
-@operator.operator_class(name='resend', help='重发当前会话的最后一条消息', usage='!resend')
-class ResendOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        # 回滚到最后一条用户message前
-        if context.session.using_conversation is None:
-            yield entities.CommandReturn(error=errors.CommandError('当前没有对话'))
-        else:
-            conv_msg = context.session.using_conversation.messages
-
-            # 倒序一直删到最后一条用户message
-            while len(conv_msg) > 0 and conv_msg[-1].role != 'user':
-                conv_msg.pop()
-
-            if len(conv_msg) > 0:
-                # 删除最后一条用户message
-                conv_msg.pop()
-
-            # 不重发了，提示用户已删除就行了
-            yield entities.CommandReturn(text='已删除最后一次请求记录')

pkg/command/operators/reset.py

@@ -1,14 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities
-
-
-@operator.operator_class(name='reset', help='重置当前会话', usage='!reset')
-class ResetOperator(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        """执行"""
-        context.session.using_conversation = None
-
-        yield entities.CommandReturn(text='已重置当前会话')

pkg/command/operators/update.py

@@ -1,11 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities
-
-
-@operator.operator_class(name='update', help='更新程序', usage='!update', privilege=2)
-class UpdateCommand(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        yield entities.CommandReturn(text='不再支持通过命令更新，请查看 LangBot 文档。')

pkg/command/operators/version.py

@@ -1,19 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator, entities
-
-
-@operator.operator_class(name='version', help='显示版本信息', usage='!version')
-class VersionCommand(operator.CommandOperator):
-    async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
-        reply_str = f'当前版本: \n{self.ap.ver_mgr.get_current_version()}'
-
-        try:
-            if await self.ap.ver_mgr.is_new_version_available():
-                reply_str += '\n\n有新版本可用。'
-        except Exception:
-            pass
-
-        yield entities.CommandReturn(text=reply_str.strip())

pkg/core/app.py

@@ -1,238 +0,0 @@
-from __future__ import annotations
-
-import logging
-import asyncio
-import traceback
-import sys
-import os
-
-from ..platform import botmgr as im_mgr
-from ..provider.session import sessionmgr as llm_session_mgr
-from ..provider.modelmgr import modelmgr as llm_model_mgr
-from ..provider.tools import toolmgr as llm_tool_mgr
-from ..config import manager as config_mgr
-from ..command import cmdmgr
-from ..plugin import manager as plugin_mgr
-from ..pipeline import pool
-from ..pipeline import controller, pipelinemgr
-from ..utils import version as version_mgr, proxy as proxy_mgr, announce as announce_mgr
-from ..persistence import mgr as persistencemgr
-from ..api.http.controller import main as http_controller
-from ..api.http.service import user as user_service
-from ..api.http.service import model as model_service
-from ..api.http.service import pipeline as pipeline_service
-from ..api.http.service import bot as bot_service
-from ..discover import engine as discover_engine
-from ..utils import logcache
-from . import taskmgr
-from . import entities as core_entities
-
-
-class Application:
-    """运行时应用对象和上下文"""
-
-    event_loop: asyncio.AbstractEventLoop = None
-
-    # asyncio_tasks: list[asyncio.Task] = []
-    task_mgr: taskmgr.AsyncTaskManager = None
-
-    discover: discover_engine.ComponentDiscoveryEngine = None
-
-    platform_mgr: im_mgr.PlatformManager = None
-
-    cmd_mgr: cmdmgr.CommandManager = None
-
-    sess_mgr: llm_session_mgr.SessionManager = None
-
-    model_mgr: llm_model_mgr.ModelManager = None
-
-    # TODO 移动到 pipeline 里
-    tool_mgr: llm_tool_mgr.ToolManager = None
-
-    # ======= 配置管理器 =======
-
-    command_cfg: config_mgr.ConfigManager = None  # deprecated
-
-    pipeline_cfg: config_mgr.ConfigManager = None  # deprecated
-
-    platform_cfg: config_mgr.ConfigManager = None  # deprecated
-
-    provider_cfg: config_mgr.ConfigManager = None  # deprecated
-
-    system_cfg: config_mgr.ConfigManager = None  # deprecated
-
-    instance_config: config_mgr.ConfigManager = None
-
-    # ======= 元数据配置管理器 =======
-
-    sensitive_meta: config_mgr.ConfigManager = None
-
-    pipeline_config_meta_trigger: config_mgr.ConfigManager = None
-    pipeline_config_meta_safety: config_mgr.ConfigManager = None
-    pipeline_config_meta_ai: config_mgr.ConfigManager = None
-    pipeline_config_meta_output: config_mgr.ConfigManager = None
-
-    # =========================
-
-    plugin_mgr: plugin_mgr.PluginManager = None
-
-    query_pool: pool.QueryPool = None
-
-    ctrl: controller.Controller = None
-
-    pipeline_mgr: pipelinemgr.PipelineManager = None
-
-    ver_mgr: version_mgr.VersionManager = None
-
-    ann_mgr: announce_mgr.AnnouncementManager = None
-
-    proxy_mgr: proxy_mgr.ProxyManager = None
-
-    logger: logging.Logger = None
-
-    persistence_mgr: persistencemgr.PersistenceManager = None
-
-    http_ctrl: http_controller.HTTPController = None
-
-    log_cache: logcache.LogCache = None
-
-    # ========= HTTP Services =========
-
-    user_service: user_service.UserService = None
-
-    model_service: model_service.ModelsService = None
-
-    pipeline_service: pipeline_service.PipelineService = None
-
-    bot_service: bot_service.BotService = None
-
-    def __init__(self):
-        pass
-
-    async def initialize(self):
-        pass
-
-    async def run(self):
-        try:
-            await self.plugin_mgr.initialize_plugins()
-
-            # 后续可能会允许动态重启其他任务
-            # 故为了防止程序在非 Ctrl-C 情况下退出，这里创建一个不会结束的协程
-            async def never_ending():
-                while True:
-                    await asyncio.sleep(1)
-
-            self.task_mgr.create_task(
-                self.platform_mgr.run(),
-                name='platform-manager',
-                scopes=[
-                    core_entities.LifecycleControlScope.APPLICATION,
-                    core_entities.LifecycleControlScope.PLATFORM,
-                ],
-            )
-            self.task_mgr.create_task(
-                self.ctrl.run(),
-                name='query-controller',
-                scopes=[core_entities.LifecycleControlScope.APPLICATION],
-            )
-            self.task_mgr.create_task(
-                self.http_ctrl.run(),
-                name='http-api-controller',
-                scopes=[core_entities.LifecycleControlScope.APPLICATION],
-            )
-            self.task_mgr.create_task(
-                never_ending(),
-                name='never-ending-task',
-                scopes=[core_entities.LifecycleControlScope.APPLICATION],
-            )
-
-            await self.print_web_access_info()
-            await self.task_mgr.wait_all()
-        except asyncio.CancelledError:
-            pass
-        except Exception as e:
-            self.logger.error(f'应用运行致命异常: {e}')
-            self.logger.debug(f'Traceback: {traceback.format_exc()}')
-
-    async def print_web_access_info(self):
-        """打印访问 webui 的提示"""
-
-        if not os.path.exists(os.path.join('.', 'web/out')):
-            self.logger.warning('WebUI 文件缺失，请根据文档部署：https://docs.langbot.app/zh')
-            self.logger.warning(
-                'WebUI files are missing, please deploy according to the documentation: https://docs.langbot.app/en'
-            )
-            return
-
-        host_ip = '127.0.0.1'
-
-        port = self.instance_config.data['api']['port']
-
-        tips = f"""
-=======================================
-✨ Access WebUI / 访问管理面板
-
-🏠 Local Address: http://{host_ip}:{port}/
-🌐 Public Address: http://<Your Public IP>:{port}/
-
-📌 Running this program in a container? Please ensure that the {port} port is exposed
-=======================================
-""".strip()
-        for line in tips.split('\n'):
-            self.logger.info(line)
-
-    async def reload(
-        self,
-        scope: core_entities.LifecycleControlScope,
-    ):
-        match scope:
-            case core_entities.LifecycleControlScope.PLATFORM.value:
-                self.logger.info('执行热重载 scope=' + scope)
-                await self.platform_mgr.shutdown()
-
-                self.platform_mgr = im_mgr.PlatformManager(self)
-
-                await self.platform_mgr.initialize()
-
-                self.task_mgr.create_task(
-                    self.platform_mgr.run(),
-                    name='platform-manager',
-                    scopes=[
-                        core_entities.LifecycleControlScope.APPLICATION,
-                        core_entities.LifecycleControlScope.PLATFORM,
-                    ],
-                )
-            case core_entities.LifecycleControlScope.PLUGIN.value:
-                self.logger.info('执行热重载 scope=' + scope)
-                await self.plugin_mgr.destroy_plugins()
-
-                # 删除 sys.module 中所有的 plugins/* 下的模块
-                for mod in list(sys.modules.keys()):
-                    if mod.startswith('plugins.'):
-                        del sys.modules[mod]
-
-                self.plugin_mgr = plugin_mgr.PluginManager(self)
-                await self.plugin_mgr.initialize()
-
-                await self.plugin_mgr.initialize_plugins()
-
-                await self.plugin_mgr.load_plugins()
-                await self.plugin_mgr.initialize_plugins()
-            case core_entities.LifecycleControlScope.PROVIDER.value:
-                self.logger.info('执行热重载 scope=' + scope)
-
-                await self.tool_mgr.shutdown()
-
-                llm_model_mgr_inst = llm_model_mgr.ModelManager(self)
-                await llm_model_mgr_inst.initialize()
-                self.model_mgr = llm_model_mgr_inst
-
-                llm_session_mgr_inst = llm_session_mgr.SessionManager(self)
-                await llm_session_mgr_inst.initialize()
-                self.sess_mgr = llm_session_mgr_inst
-
-                llm_tool_mgr_inst = llm_tool_mgr.ToolManager(self)
-                await llm_tool_mgr_inst.initialize()
-                self.tool_mgr = llm_tool_mgr_inst
-            case _:
-                pass

pkg/core/entities.py

@@ -1,170 +0,0 @@
-from __future__ import annotations
-
-import enum
-import typing
-import datetime
-import asyncio
-
-import pydantic.v1 as pydantic
-
-from ..provider import entities as llm_entities
-from ..provider.modelmgr import requester
-from ..provider.tools import entities as tools_entities
-from ..platform import adapter as msadapter
-from ..platform.types import message as platform_message
-from ..platform.types import events as platform_events
-
-
-class LifecycleControlScope(enum.Enum):
-    APPLICATION = 'application'
-    PLATFORM = 'platform'
-    PLUGIN = 'plugin'
-    PROVIDER = 'provider'
-
-
-class LauncherTypes(enum.Enum):
-    """一个请求的发起者类型"""
-
-    PERSON = 'person'
-    """私聊"""
-
-    GROUP = 'group'
-    """群聊"""
-
-
-class Query(pydantic.BaseModel):
-    """一次请求的信息封装"""
-
-    query_id: int
-    """请求ID，添加进请求池时生成"""
-
-    launcher_type: LauncherTypes
-    """会话类型，platform处理阶段设置"""
-
-    launcher_id: typing.Union[int, str]
-    """会话ID，platform处理阶段设置"""
-
-    sender_id: typing.Union[int, str]
-    """发送者ID，platform处理阶段设置"""
-
-    message_event: platform_events.MessageEvent
-    """事件，platform收到的原始事件"""
-
-    message_chain: platform_message.MessageChain
-    """消息链，platform收到的原始消息链"""
-
-    bot_uuid: typing.Optional[str] = None
-    """机器人UUID。"""
-
-    pipeline_uuid: typing.Optional[str] = None
-    """流水线UUID。"""
-
-    pipeline_config: typing.Optional[dict[str, typing.Any]] = None
-    """流水线配置，由 Pipeline 在运行开始时设置。"""
-
-    adapter: msadapter.MessagePlatformAdapter
-    """消息平台适配器对象，单个app中可能启用了多个消息平台适配器，此对象表明发起此query的适配器"""
-
-    session: typing.Optional[Session] = None
-    """会话对象，由前置处理器阶段设置"""
-
-    messages: typing.Optional[list[llm_entities.Message]] = []
-    """历史消息列表，由前置处理器阶段设置"""
-
-    prompt: typing.Optional[llm_entities.Prompt] = None
-    """情景预设内容，由前置处理器阶段设置"""
-
-    user_message: typing.Optional[llm_entities.Message] = None
-    """此次请求的用户消息对象，由前置处理器阶段设置"""
-
-    variables: typing.Optional[dict[str, typing.Any]] = None
-    """变量，由前置处理器阶段设置。在prompt中嵌入或由 Runner 传递到 LLMOps 平台。"""
-
-    use_llm_model: typing.Optional[requester.RuntimeLLMModel] = None
-    """使用的对话模型，由前置处理器阶段设置"""
-
-    use_funcs: typing.Optional[list[tools_entities.LLMFunction]] = None
-    """使用的函数，由前置处理器阶段设置"""
-
-    resp_messages: (
-        typing.Optional[list[llm_entities.Message]] | typing.Optional[list[platform_message.MessageChain]]
-    ) = []
-    """由Process阶段生成的回复消息对象列表"""
-
-    resp_message_chain: typing.Optional[list[platform_message.MessageChain]] = None
-    """回复消息链，从resp_messages包装而得"""
-
-    # ======= 内部保留 =======
-    current_stage: typing.Optional['pkg.pipeline.pipelinemgr.StageInstContainer'] = None
-    """当前所处阶段"""
-
-    class Config:
-        arbitrary_types_allowed = True
-
-    # ========== 插件可调用的 API（请求 API） ==========
-
-    def set_variable(self, key: str, value: typing.Any):
-        """设置变量"""
-        if self.variables is None:
-            self.variables = {}
-        self.variables[key] = value
-
-    def get_variable(self, key: str) -> typing.Any:
-        """获取变量"""
-        if self.variables is None:
-            return None
-        return self.variables.get(key)
-
-    def get_variables(self) -> dict[str, typing.Any]:
-        """获取所有变量"""
-        if self.variables is None:
-            return {}
-        return self.variables
-
-
-class Conversation(pydantic.BaseModel):
-    """对话，包含于 Session 中，一个 Session 可以有多个历史 Conversation，但只有一个当前使用的 Conversation"""
-
-    prompt: llm_entities.Prompt
-
-    messages: list[llm_entities.Message]
-
-    create_time: typing.Optional[datetime.datetime] = pydantic.Field(default_factory=datetime.datetime.now)
-
-    update_time: typing.Optional[datetime.datetime] = pydantic.Field(default_factory=datetime.datetime.now)
-
-    use_llm_model: typing.Optional[requester.RuntimeLLMModel] = None
-
-    use_funcs: typing.Optional[list[tools_entities.LLMFunction]]
-
-    uuid: typing.Optional[str] = None
-    """该对话的 uuid，在创建时不会自动生成。而是当使用 Dify API 等由外部管理对话信息的服务时，用于绑定外部的会话。具体如何使用，取决于 Runner。"""
-
-    class Config:
-        arbitrary_types_allowed = True
-
-
-class Session(pydantic.BaseModel):
-    """会话，一个 Session 对应一个 {launcher_type.value}_{launcher_id}"""
-
-    launcher_type: LauncherTypes
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Optional[typing.Union[int, str]] = 0
-
-    use_prompt_name: typing.Optional[str] = 'default'
-
-    using_conversation: typing.Optional[Conversation] = None
-
-    conversations: typing.Optional[list[Conversation]] = pydantic.Field(default_factory=list)
-
-    create_time: typing.Optional[datetime.datetime] = pydantic.Field(default_factory=datetime.datetime.now)
-
-    update_time: typing.Optional[datetime.datetime] = pydantic.Field(default_factory=datetime.datetime.now)
-
-    semaphore: typing.Optional[asyncio.Semaphore] = None
-    """当前会话的信号量，用于限制并发"""
-
-    class Config:
-        arbitrary_types_allowed = True

pkg/core/stages/build_app.py

@@ -1,103 +0,0 @@
-from __future__ import annotations
-
-
-from .. import stage, app
-from ...utils import version, proxy, announce
-from ...pipeline import pool, controller, pipelinemgr
-from ...plugin import manager as plugin_mgr
-from ...command import cmdmgr
-from ...provider.session import sessionmgr as llm_session_mgr
-from ...provider.modelmgr import modelmgr as llm_model_mgr
-from ...provider.tools import toolmgr as llm_tool_mgr
-from ...platform import botmgr as im_mgr
-from ...persistence import mgr as persistencemgr
-from ...api.http.controller import main as http_controller
-from ...api.http.service import user as user_service
-from ...api.http.service import model as model_service
-from ...api.http.service import pipeline as pipeline_service
-from ...api.http.service import bot as bot_service
-from ...discover import engine as discover_engine
-from ...utils import logcache
-from .. import taskmgr
-
-
-@stage.stage_class('BuildAppStage')
-class BuildAppStage(stage.BootingStage):
-    """构建应用阶段"""
-
-    async def run(self, ap: app.Application):
-        """构建app对象的各个组件对象并初始化"""
-        ap.task_mgr = taskmgr.AsyncTaskManager(ap)
-
-        discover = discover_engine.ComponentDiscoveryEngine(ap)
-        discover.discover_blueprint('components.yaml')
-        ap.discover = discover
-
-        proxy_mgr = proxy.ProxyManager(ap)
-        await proxy_mgr.initialize()
-        ap.proxy_mgr = proxy_mgr
-
-        ver_mgr = version.VersionManager(ap)
-        await ver_mgr.initialize()
-        ap.ver_mgr = ver_mgr
-
-        # 发送公告
-        ann_mgr = announce.AnnouncementManager(ap)
-        ap.ann_mgr = ann_mgr
-
-        ap.query_pool = pool.QueryPool()
-
-        log_cache = logcache.LogCache()
-        ap.log_cache = log_cache
-
-        persistence_mgr_inst = persistencemgr.PersistenceManager(ap)
-        ap.persistence_mgr = persistence_mgr_inst
-        await persistence_mgr_inst.initialize()
-
-        plugin_mgr_inst = plugin_mgr.PluginManager(ap)
-        await plugin_mgr_inst.initialize()
-        ap.plugin_mgr = plugin_mgr_inst
-        await plugin_mgr_inst.load_plugins()
-
-        cmd_mgr_inst = cmdmgr.CommandManager(ap)
-        await cmd_mgr_inst.initialize()
-        ap.cmd_mgr = cmd_mgr_inst
-
-        llm_model_mgr_inst = llm_model_mgr.ModelManager(ap)
-        await llm_model_mgr_inst.initialize()
-        ap.model_mgr = llm_model_mgr_inst
-
-        llm_session_mgr_inst = llm_session_mgr.SessionManager(ap)
-        await llm_session_mgr_inst.initialize()
-        ap.sess_mgr = llm_session_mgr_inst
-
-        llm_tool_mgr_inst = llm_tool_mgr.ToolManager(ap)
-        await llm_tool_mgr_inst.initialize()
-        ap.tool_mgr = llm_tool_mgr_inst
-
-        im_mgr_inst = im_mgr.PlatformManager(ap=ap)
-        await im_mgr_inst.initialize()
-        ap.platform_mgr = im_mgr_inst
-
-        pipeline_mgr = pipelinemgr.PipelineManager(ap)
-        await pipeline_mgr.initialize()
-        ap.pipeline_mgr = pipeline_mgr
-
-        http_ctrl = http_controller.HTTPController(ap)
-        await http_ctrl.initialize()
-        ap.http_ctrl = http_ctrl
-
-        user_service_inst = user_service.UserService(ap)
-        ap.user_service = user_service_inst
-
-        model_service_inst = model_service.ModelsService(ap)
-        ap.model_service = model_service_inst
-
-        pipeline_service_inst = pipeline_service.PipelineService(ap)
-        ap.pipeline_service = pipeline_service_inst
-
-        bot_service_inst = bot_service.BotService(ap)
-        ap.bot_service = bot_service_inst
-
-        ctrl = controller.Controller(ap)
-        ap.ctrl = ctrl

pkg/core/stages/load_config.py

@@ -1,79 +0,0 @@
-from __future__ import annotations
-
-import os
-
-from .. import stage, app
-from ..bootutils import config
-
-
-@stage.stage_class('LoadConfigStage')
-class LoadConfigStage(stage.BootingStage):
-    """加载配置文件阶段"""
-
-    async def run(self, ap: app.Application):
-        """启动"""
-
-        # ======= deprecated =======
-        if os.path.exists('data/config/command.json'):
-            ap.command_cfg = await config.load_json_config(
-                'data/config/command.json',
-                'templates/legacy/command.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/pipeline.json'):
-            ap.pipeline_cfg = await config.load_json_config(
-                'data/config/pipeline.json',
-                'templates/legacy/pipeline.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/platform.json'):
-            ap.platform_cfg = await config.load_json_config(
-                'data/config/platform.json',
-                'templates/legacy/platform.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/provider.json'):
-            ap.provider_cfg = await config.load_json_config(
-                'data/config/provider.json',
-                'templates/legacy/provider.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/system.json'):
-            ap.system_cfg = await config.load_json_config(
-                'data/config/system.json',
-                'templates/legacy/system.json',
-                completion=False,
-            )
-
-        # ======= deprecated =======
-
-        ap.instance_config = await config.load_yaml_config(
-            'data/config.yaml', 'templates/config.yaml', completion=False
-        )
-        await ap.instance_config.dump_config()
-
-        ap.sensitive_meta = await config.load_json_config(
-            'data/metadata/sensitive-words.json',
-            'templates/metadata/sensitive-words.json',
-        )
-        await ap.sensitive_meta.dump_config()
-
-        ap.pipeline_config_meta_trigger = await config.load_yaml_config(
-            'templates/metadata/pipeline/trigger.yaml',
-            'templates/metadata/pipeline/trigger.yaml',
-        )
-        ap.pipeline_config_meta_safety = await config.load_yaml_config(
-            'templates/metadata/pipeline/safety.yaml',
-            'templates/metadata/pipeline/safety.yaml',
-        )
-        ap.pipeline_config_meta_ai = await config.load_yaml_config(
-            'templates/metadata/pipeline/ai.yaml', 'templates/metadata/pipeline/ai.yaml'
-        )
-        ap.pipeline_config_meta_output = await config.load_yaml_config(
-            'templates/metadata/pipeline/output.yaml',
-            'templates/metadata/pipeline/output.yaml',
-        )

pkg/entity/persistence/user.py

@@ -1,18 +0,0 @@
-import sqlalchemy
-
-from .base import Base
-
-
-class User(Base):
-    __tablename__ = 'users'
-
-    id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
-    user = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    password = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
-    updated_at = sqlalchemy.Column(
-        sqlalchemy.DateTime,
-        nullable=False,
-        server_default=sqlalchemy.func.now(),
-        onupdate=sqlalchemy.func.now(),
-    )

pkg/persistence/databases/sqlite.py

@@ -1,14 +0,0 @@
-from __future__ import annotations
-
-import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
-
-from .. import database
-
-
-@database.manager_class('sqlite')
-class SQLiteDatabaseManager(database.BaseDatabaseManager):
-    """SQLite 数据库管理类"""
-
-    async def initialize(self) -> None:
-        sqlite_path = 'data/langbot.db'
-        self.engine = sqlalchemy_asyncio.create_async_engine(f'sqlite+aiosqlite:///{sqlite_path}')

pkg/persistence/migrations/dbm002_combine_quote_msg_config.py

@@ -1,36 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(2)
-class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
-    """引用消息合并配置"""
-
-    async def upgrade(self):
-        """升级"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'misc' not in config['trigger']:
-                config['trigger']['misc'] = {}
-
-            if 'combine-quote-message' not in config['trigger']['misc']:
-                config['trigger']['misc']['combine-quote-message'] = False
-
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
-                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
-                .values({'config': config, 'for_version': self.ap.ver_mgr.get_current_version()})
-            )
-
-    async def downgrade(self):
-        """降级"""
-        pass

pkg/pipeline/cntfilter/filter.py

@@ -1,76 +0,0 @@
-# 内容过滤器的抽象类
-from __future__ import annotations
-import abc
-import typing
-
-from ...core import app, entities as core_entities
-from . import entities
-
-
-preregistered_filters: list[typing.Type[ContentFilter]] = []
-
-
-def filter_class(
-    name: str,
-) -> typing.Callable[[typing.Type[ContentFilter]], typing.Type[ContentFilter]]:
-    """内容过滤器类装饰器
-
-    Args:
-        name (str): 过滤器名称
-
-    Returns:
-        typing.Callable[[typing.Type[ContentFilter]], typing.Type[ContentFilter]]: 装饰器
-    """
-
-    def decorator(cls: typing.Type[ContentFilter]) -> typing.Type[ContentFilter]:
-        assert issubclass(cls, ContentFilter)
-
-        cls.name = name
-
-        preregistered_filters.append(cls)
-
-        return cls
-
-    return decorator
-
-
-class ContentFilter(metaclass=abc.ABCMeta):
-    """内容过滤器抽象类"""
-
-    name: str
-
-    ap: app.Application
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    @property
-    def enable_stages(self):
-        """启用的阶段
-
-        默认为消息请求AI前后的两个阶段。
-
-        entity.EnableStage.PRE: 消息请求AI前，此时需要检查的内容是用户的输入消息。
-        entity.EnableStage.POST: 消息请求AI后，此时需要检查的内容是AI的回复消息。
-        """
-        return [entities.EnableStage.PRE, entities.EnableStage.POST]
-
-    async def initialize(self):
-        """初始化过滤器"""
-        pass
-
-    @abc.abstractmethod
-    async def process(self, query: core_entities.Query, message: str = None, image_url=None) -> entities.FilterResult:
-        """处理消息
-
-        分为前后阶段，具体取决于 enable_stages 的值。
-        对于内容过滤器来说，不需要考虑消息所处的阶段，只需要检查消息内容即可。
-
-        Args:
-            message (str): 需要检查的内容
-            image_url (str): 要检查的图片的 URL
-
-        Returns:
-            entities.FilterResult: 过滤结果，具体内容请查看 entities.FilterResult 类的文档
-        """
-        raise NotImplementedError

pkg/pipeline/cntfilter/filters/baiduexamine.py

@@ -1,65 +0,0 @@
-from __future__ import annotations
-
-import aiohttp
-
-from .. import entities
-from .. import filter as filter_model
-from ....core import entities as core_entities
-
-
-BAIDU_EXAMINE_URL = 'https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined?access_token={}'
-BAIDU_EXAMINE_TOKEN_URL = 'https://aip.baidubce.com/oauth/2.0/token'
-
-
-@filter_model.filter_class('baidu-cloud-examine')
-class BaiduCloudExamine(filter_model.ContentFilter):
-    """百度云内容审核"""
-
-    async def _get_token(self) -> str:
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                BAIDU_EXAMINE_TOKEN_URL,
-                params={
-                    'grant_type': 'client_credentials',
-                    'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
-                    'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
-                },
-            ) as resp:
-                return (await resp.json())['access_token']
-
-    async def process(self, query: core_entities.Query, message: str) -> entities.FilterResult:
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                BAIDU_EXAMINE_URL.format(await self._get_token()),
-                headers={
-                    'Content-Type': 'application/x-www-form-urlencoded',
-                    'Accept': 'application/json',
-                },
-                data=f'text={message}'.encode('utf-8'),
-            ) as resp:
-                result = await resp.json()
-
-                if 'error_code' in result:
-                    return entities.FilterResult(
-                        level=entities.ResultLevel.BLOCK,
-                        replacement=message,
-                        user_notice='',
-                        console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
-                    )
-                else:
-                    conclusion = result['conclusion']
-
-                    if conclusion in ('合规'):
-                        return entities.FilterResult(
-                            level=entities.ResultLevel.PASS,
-                            replacement=message,
-                            user_notice='',
-                            console_notice=f'百度云判定结果：{conclusion}',
-                        )
-                    else:
-                        return entities.FilterResult(
-                            level=entities.ResultLevel.BLOCK,
-                            replacement=message,
-                            user_notice='消息中存在不合适的内容, 请修改',
-                            console_notice=f'百度云判定结果：{conclusion}',
-                        )

pkg/pipeline/longtext/strategies/forward.py

@@ -1,35 +0,0 @@
-# 转发消息组件
-from __future__ import annotations
-
-
-from .. import strategy as strategy_model
-from ....core import entities as core_entities
-from ....platform.types import message as platform_message
-
-
-ForwardMessageDiaplay = platform_message.ForwardMessageDiaplay
-Forward = platform_message.Forward
-
-
-@strategy_model.strategy_class('forward')
-class ForwardComponentStrategy(strategy_model.LongTextStrategy):
-    async def process(self, message: str, query: core_entities.Query) -> list[platform_message.MessageComponent]:
-        display = ForwardMessageDiaplay(
-            title='群聊的聊天记录',
-            brief='[聊天记录]',
-            source='聊天记录',
-            preview=['QQ用户: ' + message],
-            summary='查看1条转发消息',
-        )
-
-        node_list = [
-            platform_message.ForwardMessageNode(
-                sender_id=query.adapter.bot_account_id,
-                sender_name='QQ用户',
-                message_chain=platform_message.MessageChain([message]),
-            )
-        ]
-
-        forward = Forward(display=display, node_list=node_list)
-
-        return [forward]

pkg/pipeline/pipelinemgr.py

@@ -1,269 +0,0 @@
-from __future__ import annotations
-
-import typing
-import traceback
-
-import sqlalchemy
-
-from ..core import app, entities
-from . import entities as pipeline_entities
-from ..entity.persistence import pipeline as persistence_pipeline
-from . import stage
-from ..platform.types import message as platform_message, events as platform_events
-from ..plugin import events
-from ..utils import importutil
-
-from . import (
-    resprule,
-    bansess,
-    cntfilter,
-    process,
-    longtext,
-    respback,
-    wrapper,
-    preproc,
-    ratelimit,
-    msgtrun,
-)
-
-importutil.import_modules_in_pkgs(
-    [
-        resprule,
-        bansess,
-        cntfilter,
-        process,
-        longtext,
-        respback,
-        wrapper,
-        preproc,
-        ratelimit,
-        msgtrun,
-    ]
-)
-
-
-class StageInstContainer:
-    """阶段实例容器"""
-
-    inst_name: str
-
-    inst: stage.PipelineStage
-
-    def __init__(self, inst_name: str, inst: stage.PipelineStage):
-        self.inst_name = inst_name
-        self.inst = inst
-
-
-class RuntimePipeline:
-    """运行时流水线"""
-
-    ap: app.Application
-
-    pipeline_entity: persistence_pipeline.LegacyPipeline
-    """流水线实体"""
-
-    stage_containers: list[StageInstContainer]
-    """阶段实例容器"""
-
-    def __init__(
-        self,
-        ap: app.Application,
-        pipeline_entity: persistence_pipeline.LegacyPipeline,
-        stage_containers: list[StageInstContainer],
-    ):
-        self.ap = ap
-        self.pipeline_entity = pipeline_entity
-        self.stage_containers = stage_containers
-
-    async def run(self, query: entities.Query):
-        query.pipeline_config = self.pipeline_entity.config
-        await self.process_query(query)
-
-    async def _check_output(self, query: entities.Query, result: pipeline_entities.StageProcessResult):
-        """检查输出"""
-        if result.user_notice:
-            # 处理str类型
-
-            if isinstance(result.user_notice, str):
-                result.user_notice = platform_message.MessageChain(platform_message.Plain(result.user_notice))
-            elif isinstance(result.user_notice, list):
-                result.user_notice = platform_message.MessageChain(*result.user_notice)
-
-            if query.pipeline_config['output']['misc']['at-sender'] and isinstance(
-                query.message_event, platform_events.GroupMessage
-            ):
-                result.user_notice.insert(0, platform_message.At(query.message_event.sender.id))
-
-            await query.adapter.reply_message(
-                message_source=query.message_event,
-                message=result.user_notice,
-                quote_origin=query.pipeline_config['output']['misc']['quote-origin'],
-            )
-        if result.debug_notice:
-            self.ap.logger.debug(result.debug_notice)
-        if result.console_notice:
-            self.ap.logger.info(result.console_notice)
-        if result.error_notice:
-            self.ap.logger.error(result.error_notice)
-
-    async def _execute_from_stage(
-        self,
-        stage_index: int,
-        query: entities.Query,
-    ):
-        """从指定阶段开始执行，实现了责任链模式和基于生成器的阶段分叉功能。
-
-        如何看懂这里为什么这么写？
-        去问 GPT-4:
-            Q1: 现在有一个责任链，其中有多个stage，query对象在其中传递，stage.process可能返回Result也有可能返回typing.AsyncGenerator[Result, None]，
-                如果返回的是生成器，需要挨个生成result，检查是否result中是否要求继续，如果要求继续就进行下一个stage。如果此次生成器产生的result处理完了，就继续生成下一个result，
-                调用后续的stage，直到该生成器全部生成完。责任链中可能有多个stage会返回生成器
-            Q2: 不是这样的，你可能理解有误。如果我们责任链上有这些Stage：
-
-                A B C D E F G
-
-                如果所有的stage都返回Result，且所有Result都要求继续，那么执行顺序是：
-
-                A B C D E F G
-
-                现在假设C返回的是AsyncGenerator，那么执行顺序是：
-
-                A B C D E F G C D E F G C D E F G ...
-            Q3: 但是如果不止一个stage会返回生成器呢？
-        """
-        i = stage_index
-
-        while i < len(self.stage_containers):
-            stage_container = self.stage_containers[i]
-
-            query.current_stage = stage_container  # 标记到 Query 对象里
-
-            result = stage_container.inst.process(query, stage_container.inst_name)
-
-            if isinstance(result, typing.Coroutine):
-                result = await result
-
-            if isinstance(result, pipeline_entities.StageProcessResult):  # 直接返回结果
-                self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} res {result}')
-                await self._check_output(query, result)
-
-                if result.result_type == pipeline_entities.ResultType.INTERRUPT:
-                    self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query}')
-                    break
-                elif result.result_type == pipeline_entities.ResultType.CONTINUE:
-                    query = result.new_query
-            elif isinstance(result, typing.AsyncGenerator):  # 生成器
-                self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} gen')
-
-                async for sub_result in result:
-                    self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} res {sub_result}')
-                    await self._check_output(query, sub_result)
-
-                    if sub_result.result_type == pipeline_entities.ResultType.INTERRUPT:
-                        self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query}')
-                        break
-                    elif sub_result.result_type == pipeline_entities.ResultType.CONTINUE:
-                        query = sub_result.new_query
-                        await self._execute_from_stage(i + 1, query)
-                break
-
-            i += 1
-
-    async def process_query(self, query: entities.Query):
-        """处理请求"""
-        try:
-            # ======== 触发 MessageReceived 事件 ========
-            event_type = (
-                events.PersonMessageReceived
-                if query.launcher_type == entities.LauncherTypes.PERSON
-                else events.GroupMessageReceived
-            )
-
-            event_ctx = await self.ap.plugin_mgr.emit_event(
-                event=event_type(
-                    launcher_type=query.launcher_type.value,
-                    launcher_id=query.launcher_id,
-                    sender_id=query.sender_id,
-                    message_chain=query.message_chain,
-                    query=query,
-                )
-            )
-
-            if event_ctx.is_prevented_default():
-                return
-
-            self.ap.logger.debug(f'Processing query {query}')
-
-            await self._execute_from_stage(0, query)
-        except Exception as e:
-            inst_name = query.current_stage.inst_name if query.current_stage else 'unknown'
-            self.ap.logger.error(f'处理请求时出错 query_id={query.query_id} stage={inst_name} : {e}')
-            self.ap.logger.error(f'Traceback: {traceback.format_exc()}')
-        finally:
-            self.ap.logger.debug(f'Query {query} processed')
-
-
-class PipelineManager:
-    """流水线管理器"""
-
-    # ====== 4.0 ======
-
-    ap: app.Application
-
-    pipelines: list[RuntimePipeline]
-
-    stage_dict: dict[str, type[stage.PipelineStage]]
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.pipelines = []
-
-    async def initialize(self):
-        self.stage_dict = {name: cls for name, cls in stage.preregistered_stages.items()}
-
-        await self.load_pipelines_from_db()
-
-    async def load_pipelines_from_db(self):
-        self.ap.logger.info('Loading pipelines from db...')
-
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        pipelines = result.all()
-
-        # load pipelines
-        for pipeline in pipelines:
-            await self.load_pipeline(pipeline)
-
-    async def load_pipeline(
-        self,
-        pipeline_entity: persistence_pipeline.LegacyPipeline
-        | sqlalchemy.Row[persistence_pipeline.LegacyPipeline]
-        | dict,
-    ):
-        if isinstance(pipeline_entity, sqlalchemy.Row):
-            pipeline_entity = persistence_pipeline.LegacyPipeline(**pipeline_entity._mapping)
-        elif isinstance(pipeline_entity, dict):
-            pipeline_entity = persistence_pipeline.LegacyPipeline(**pipeline_entity)
-
-        # initialize stage containers according to pipeline_entity.stages
-        stage_containers: list[StageInstContainer] = []
-        for stage_name in pipeline_entity.stages:
-            stage_containers.append(StageInstContainer(inst_name=stage_name, inst=self.stage_dict[stage_name](self.ap)))
-
-        for stage_container in stage_containers:
-            await stage_container.inst.initialize(pipeline_entity.config)
-
-        runtime_pipeline = RuntimePipeline(self.ap, pipeline_entity, stage_containers)
-        self.pipelines.append(runtime_pipeline)
-
-    async def get_pipeline_by_uuid(self, uuid: str) -> RuntimePipeline | None:
-        for pipeline in self.pipelines:
-            if pipeline.pipeline_entity.uuid == uuid:
-                return pipeline
-        return None
-
-    async def remove_pipeline(self, uuid: str):
-        for pipeline in self.pipelines:
-            if pipeline.pipeline_entity.uuid == uuid:
-                self.pipelines.remove(pipeline)
-                return

pkg/pipeline/preproc/preproc.py

@@ -1,127 +0,0 @@
-from __future__ import annotations
-
-import datetime
-
-from .. import stage, entities
-from ...core import entities as core_entities
-from ...provider import entities as llm_entities
-from ...plugin import events
-from ...platform.types import message as platform_message
-
-
-@stage.stage_class('PreProcessor')
-class PreProcessor(stage.PipelineStage):
-    """请求预处理阶段
-
-    签出会话、prompt、上文、模型、内容函数。
-
-    改写：
-        - session
-        - prompt
-        - messages
-        - user_message
-        - use_model
-        - use_funcs
-    """
-
-    async def process(
-        self,
-        query: core_entities.Query,
-        stage_inst_name: str,
-    ) -> entities.StageProcessResult:
-        """处理"""
-        selected_runner = query.pipeline_config['ai']['runner']['runner']
-
-        session = await self.ap.sess_mgr.get_session(query)
-
-
-        # 非 local-agent 时，llm_model 为 None
-        llm_model = (
-            await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
-            if selected_runner == 'local-agent'
-            else None
-        )
-
-        conversation = await self.ap.sess_mgr.get_conversation(
-            query,
-            session,
-            query.pipeline_config['ai']['local-agent']['prompt'],
-        )
-
-        conversation.use_llm_model = llm_model
-
-        # 设置query
-        query.session = session
-        query.prompt = conversation.prompt.copy()
-        query.messages = conversation.messages.copy()
-
-        query.use_llm_model = llm_model
-
-        if selected_runner == 'local-agent':
-            query.use_funcs = (
-                conversation.use_funcs if query.use_llm_model.model_entity.abilities.__contains__('tool_call') else None
-            )
-
-        query.variables = {
-            'session_id': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-            'conversation_id': conversation.uuid,
-            'msg_create_time': (
-                int(query.message_event.time) if query.message_event.time else int(datetime.datetime.now().timestamp())
-            ),
-        }
-
-        # Check if this model supports vision, if not, remove all images
-        # TODO this checking should be performed in runner, and in this stage, the image should be reserved
-        if selected_runner == 'local-agent' and not query.use_llm_model.model_entity.abilities.__contains__('vision'):
-            for msg in query.messages:
-                if isinstance(msg.content, list):
-                    for me in msg.content:
-                        if me.type == 'image_url':
-                            msg.content.remove(me)
-
-        content_list = []
-
-        plain_text = ''
-        qoute_msg = query.pipeline_config["trigger"].get("misc",'').get("combine-quote-message")
-
-        for me in query.message_chain:
-            if isinstance(me, platform_message.Plain):
-                content_list.append(llm_entities.ContentElement.from_text(me.text))
-                plain_text += me.text
-            elif isinstance(me, platform_message.Image):
-                if selected_runner != 'local-agent' or query.use_llm_model.model_entity.abilities.__contains__(
-                    'vision'
-                ):
-                    if me.base64 is not None:
-                        content_list.append(llm_entities.ContentElement.from_image_base64(me.base64))
-            elif isinstance(me, platform_message.Quote) and qoute_msg:
-                for msg in me.origin:
-                    if isinstance(msg, platform_message.Plain):
-                        content_list.append(llm_entities.ContentElement.from_text(msg.text))
-                    elif isinstance(msg, platform_message.Image):
-                        if selected_runner != 'local-agent' or query.use_llm_model.model_entity.abilities.__contains__(
-                                'vision'
-                        ):
-                            if msg.base64 is not None:
-                                content_list.append(llm_entities.ContentElement.from_image_base64(msg.base64))
-
-
-
-        query.variables['user_message_text'] = plain_text
-
-        query.user_message = llm_entities.Message(role='user', content=content_list)
-        # =========== 触发事件 PromptPreProcessing
-
-        event_ctx = await self.ap.plugin_mgr.emit_event(
-            event=events.PromptPreProcessing(
-                session_name=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-                default_prompt=query.prompt.messages,
-                prompt=query.messages,
-                query=query,
-            )
-        )
-
-        query.prompt.messages = event_ctx.event.default_prompt
-        query.messages = event_ctx.event.prompt
-
-        return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)

pkg/pipeline/process/handlers/chat.py

@@ -1,96 +0,0 @@
-from __future__ import annotations
-
-import typing
-import traceback
-
-
-from .. import handler
-from ... import entities
-from ....core import entities as core_entities
-from ....provider import runner as runner_module
-from ....plugin import events
-
-from ....platform.types import message as platform_message
-from ....utils import importutil
-from ....provider import runners
-
-importutil.import_modules_in_pkg(runners)
-
-
-class ChatMessageHandler(handler.MessageHandler):
-    async def handle(
-        self,
-        query: core_entities.Query,
-    ) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
-        """处理"""
-        # 调API
-        #   生成器
-
-        # 触发插件事件
-        event_class = (
-            events.PersonNormalMessageReceived
-            if query.launcher_type == core_entities.LauncherTypes.PERSON
-            else events.GroupNormalMessageReceived
-        )
-
-        event_ctx = await self.ap.plugin_mgr.emit_event(
-            event=event_class(
-                launcher_type=query.launcher_type.value,
-                launcher_id=query.launcher_id,
-                sender_id=query.sender_id,
-                text_message=str(query.message_chain),
-                query=query,
-            )
-        )
-
-        if event_ctx.is_prevented_default():
-            if event_ctx.event.reply is not None:
-                mc = platform_message.MessageChain(event_ctx.event.reply)
-
-                query.resp_messages.append(mc)
-
-                yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-            else:
-                yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
-        else:
-            if event_ctx.event.alter is not None:
-                # if isinstance(event_ctx.event, str):  # 现在暂时不考虑多模态alter
-                query.user_message.content = event_ctx.event.alter
-
-            text_length = 0
-
-            try:
-                for r in runner_module.preregistered_runners:
-                    if r.name == query.pipeline_config['ai']['runner']['runner']:
-                        runner = r(self.ap, query.pipeline_config)
-                        break
-                else:
-                    raise ValueError(f'未找到请求运行器: {query.pipeline_config["ai"]["runner"]["runner"]}')
-
-                async for result in runner.run(query):
-                    query.resp_messages.append(result)
-
-                    self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
-
-                    if result.content is not None:
-                        text_length += len(result.content)
-
-                    yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-
-                query.session.using_conversation.messages.append(query.user_message)
-                query.session.using_conversation.messages.extend(query.resp_messages)
-            except Exception as e:
-                self.ap.logger.error(f'对话({query.query_id})请求失败: {type(e).__name__} {str(e)}')
-
-                hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
-
-                yield entities.StageProcessResult(
-                    result_type=entities.ResultType.INTERRUPT,
-                    new_query=query,
-                    user_notice='请求失败' if hide_exception_info else f'{e}',
-                    error_notice=f'{e}',
-                    debug_notice=traceback.format_exc(),
-                )
-            finally:
-                # TODO statistics
-                pass

pkg/pipeline/process/handlers/command.py

@@ -1,96 +0,0 @@
-from __future__ import annotations
-import typing
-
-
-from .. import handler
-from ... import entities
-from ....core import entities as core_entities
-from ....provider import entities as llm_entities
-from ....plugin import events
-from ....platform.types import message as platform_message
-
-
-class CommandHandler(handler.MessageHandler):
-    async def handle(
-        self,
-        query: core_entities.Query,
-    ) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
-        """处理"""
-
-        command_text = str(query.message_chain).strip()[1:]
-
-        privilege = 1
-
-        if f'{query.launcher_type.value}_{query.launcher_id}' in self.ap.instance_config.data['admins']:
-            privilege = 2
-
-        spt = command_text.split(' ')
-
-        event_class = (
-            events.PersonCommandSent
-            if query.launcher_type == core_entities.LauncherTypes.PERSON
-            else events.GroupCommandSent
-        )
-
-        event_ctx = await self.ap.plugin_mgr.emit_event(
-            event=event_class(
-                launcher_type=query.launcher_type.value,
-                launcher_id=query.launcher_id,
-                sender_id=query.sender_id,
-                command=spt[0],
-                params=spt[1:] if len(spt) > 1 else [],
-                text_message=str(query.message_chain),
-                is_admin=(privilege == 2),
-                query=query,
-            )
-        )
-
-        if event_ctx.is_prevented_default():
-            if event_ctx.event.reply is not None:
-                mc = platform_message.MessageChain(event_ctx.event.reply)
-
-                query.resp_messages.append(mc)
-
-                yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-            else:
-                yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
-
-        else:
-            if event_ctx.event.alter is not None:
-                query.message_chain = platform_message.MessageChain([platform_message.Plain(event_ctx.event.alter)])
-
-            session = await self.ap.sess_mgr.get_session(query)
-
-            async for ret in self.ap.cmd_mgr.execute(command_text=command_text, query=query, session=session):
-                if ret.error is not None:
-                    query.resp_messages.append(
-                        llm_entities.Message(
-                            role='command',
-                            content=str(ret.error),
-                        )
-                    )
-
-                    self.ap.logger.info(f'命令({query.query_id})报错: {self.cut_str(str(ret.error))}')
-
-                    yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-                elif ret.text is not None or ret.image_url is not None:
-                    content: list[llm_entities.ContentElement] = []
-
-                    if ret.text is not None:
-                        content.append(llm_entities.ContentElement.from_text(ret.text))
-
-                    if ret.image_url is not None:
-                        content.append(llm_entities.ContentElement.from_image_url(ret.image_url))
-
-                    query.resp_messages.append(
-                        llm_entities.Message(
-                            role='command',
-                            content=content,
-                        )
-                    )
-
-                    self.ap.logger.info(f'命令返回: {self.cut_str(str(content[0]))}')
-
-                    yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-                else:
-                    yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)

pkg/pipeline/respback/respback.py

@@ -1,45 +0,0 @@
-from __future__ import annotations
-
-import random
-import asyncio
-
-
-from ...platform.types import events as platform_events
-from ...platform.types import message as platform_message
-
-from .. import stage, entities
-from ...core import entities as core_entities
-
-
-@stage.stage_class('SendResponseBackStage')
-class SendResponseBackStage(stage.PipelineStage):
-    """发送响应消息"""
-
-    async def process(self, query: core_entities.Query, stage_inst_name: str) -> entities.StageProcessResult:
-        """处理"""
-
-        random_range = (
-            query.pipeline_config['output']['force-delay']['min'],
-            query.pipeline_config['output']['force-delay']['max'],
-        )
-
-        random_delay = random.uniform(*random_range)
-
-        self.ap.logger.debug('根据规则强制延迟回复: %s s', random_delay)
-
-        await asyncio.sleep(random_delay)
-
-        if query.pipeline_config['output']['misc']['at-sender'] and isinstance(
-            query.message_event, platform_events.GroupMessage
-        ):
-            query.resp_message_chain[-1].insert(0, platform_message.At(query.message_event.sender.id))
-
-        quote_origin = query.pipeline_config['output']['misc']['quote-origin']
-
-        await query.adapter.reply_message(
-            message_source=query.message_event,
-            message=query.resp_message_chain[-1],
-            quote_origin=quote_origin,
-        )
-
-        return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)

pkg/pipeline/resprule/rules/atbot.py

@@ -1,32 +0,0 @@
-from __future__ import annotations
-
-
-from .. import rule as rule_model
-from .. import entities
-from ....core import entities as core_entities
-from ....platform.types import message as platform_message
-
-
-@rule_model.rule_class('at-bot')
-class AtBotRule(rule_model.GroupRespondRule):
-    async def match(
-        self,
-        message_text: str,
-        message_chain: platform_message.MessageChain,
-        rule_dict: dict,
-        query: core_entities.Query,
-    ) -> entities.RuleJudgeResult:
-        if message_chain.has(platform_message.At(query.adapter.bot_account_id)) and rule_dict['at']:
-            message_chain.remove(platform_message.At(query.adapter.bot_account_id))
-
-            if message_chain.has(
-                platform_message.At(query.adapter.bot_account_id)
-            ):  # 回复消息时会at两次，检查并删除重复的
-                message_chain.remove(platform_message.At(query.adapter.bot_account_id))
-
-            return entities.RuleJudgeResult(
-                matching=True,
-                replacement=message_chain,
-            )
-
-        return entities.RuleJudgeResult(matching=False, replacement=message_chain)