docs: Add multilingual README files (Spanish, French, Korean, Russian, Vietnamese) (#1794)

* Initial plan

* Add multilingual README files (ES, FR, KO, RU, VI)

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

.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
 

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

@@ -1,10 +1,9 @@
 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]
+  workflow_dispatch:
 jobs:
   publish-docker-image:
     runs-on: ubuntu-latest
@@ -41,5 +40,9 @@ jobs:
         run: docker login --username=${{ secrets.DOCKER_USERNAME }} --password ${{ secrets.DOCKER_PASSWORD }}
       - name: Create Buildx
         run: docker buildx create --name mybuilder --use
-      - name: Build  # image name: rockchin/langbot:<VERSION>
-        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Release # only relase, exlude pre-release
+        if: ${{ github.event.release.prerelease == false }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Pre-release # no update for latest tag
+        if: ${{ github.event.release.prerelease == true }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.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/out
+          cp -r out ../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 +1,71 @@
+name: Unit Tests
+
+on:
+  pull_request:
+    types: [opened, ready_for_review, synchronize]
+    paths:
+      - 'pkg/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'run_tests.sh'
+  push:
+    branches:
+      - master
+      - develop
+    paths:
+      - 'pkg/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'run_tests.sh'
+
+jobs:
+  test:
+    name: Run Unit Tests
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.10', '3.11', '3.12']
+      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: ${{ matrix.python-version }}
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Install dependencies
+        run: |
+          uv sync --dev
+
+      - name: Run unit tests
+        run: |
+          bash run_tests.sh
+
+      - name: Upload coverage to Codecov
+        if: matrix.python-version == '3.12'
+        uses: codecov/codecov-action@v5
+        with:
+          files: ./coverage.xml
+          flags: unit-tests
+          name: unit-tests-coverage
+          fail_ci_if_error: false
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+
+      - 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

.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

.gitignore

@@ -22,7 +22,7 @@ tips.py
 venv*
 bin/
 .vscode
-test_*
+/test_*
 venv/
 hugchat.json
 qcapi
@@ -43,4 +43,13 @@ test.py
 /web_ui
 .venv/
 uv.lock
-/test
+/test
+plugins.bak
+coverage.xml
+.coverage
+src/langbot/web/
+
+# Build artifacts
+/dist
+/build
+*.egg-info

AGENTS.md

@@ -0,0 +1,86 @@
+# 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:
+
+- `./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.
+
+## 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

LICENSE

@@ -1,661 +1,201 @@
-                    GNU AFFERO GENERAL PUBLIC LICENSE
-                       Version 3, 19 November 2007
-
- Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
- Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
-
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-software and other kinds of works, specifically designed to ensure
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-            How to Apply These Terms to Your New Programs
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-
-Also add information on how to contact you by electronic and paper mail.
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-  If your software can interact with users remotely through a computer
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-For more information on this, and how to apply and follow the GNU AGPL, see
-<https://www.gnu.org/licenses/>.
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+   END OF TERMS AND CONDITIONS
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+   APPENDIX: How to apply the Apache License to your work.
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+      To apply the Apache License to your work, attach the following
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+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

README.md

@@ -8,7 +8,7 @@
 
 <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>
 
-[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+[English](README_EN.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%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
@@ -31,11 +31,21 @@ LangBot 是一个开源的大语言模型原生即时通信机器人开发平台
 
 ## 📦 开始使用
 
+#### 快速部署
+
+使用 `uvx` 一键启动（需要先安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)）：
+
+```bash
+uvx langbot
+```
+
+访问 http://localhost:5300 即可开始使用。
+
 #### Docker Compose 部署
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
-cd LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -61,6 +71,10 @@ docker compose up -d
 
 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)。
 
+#### Kubernetes 部署
+
+参考 [Kubernetes 部署](./docker/README_K8S.md) 文档。
+
 ## 😎 保持更新
 
 点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
@@ -89,6 +103,7 @@ docker compose up -d
 | 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 | ✅ |  |
+| 企微智能机器人 | ✅ |  |
 | 个人微信 | ✅ |  |
 | 微信公众号 | ✅ |  |
 | 飞书 | ✅ |  |
@@ -96,6 +111,7 @@ docker compose up -d
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
+| LINE | ✅ |  |
 
 ### 大模型能力
 
@@ -107,8 +123,10 @@ docker compose up -d
 | [Anthropic](https://www.anthropic.com/) | ✅ |  |
 | [xAI](https://x.ai/) | ✅ |  |
 | [智谱AI](https://open.bigmodel.cn/) | ✅ |  |
+| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 全球大模型都可调用（友情推荐） |
 | [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，专注全球大模型接入 |
 | [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
@@ -116,10 +134,12 @@ docker compose up -d
 | [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 |
+| [小马算力](https://www.tokenpony.cn/453z1) | ✅ | 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 |
+| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台，每月免费10亿大模型Token |
 
 ### TTS
 
@@ -142,3 +162,9 @@ docker compose up -d
 <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

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+English / [简体中文](README.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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
@@ -25,11 +25,21 @@ LangBot is an open-source LLM native instant messaging robot development platfor
 
 ## 📦 Getting Started
 
+#### Quick Start
+
+Use `uvx` to start with one command (need to install [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Visit http://localhost:5300 to start using it.
+
 #### Docker Compose Deployment
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
-cd LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -55,6 +65,10 @@ Community contributed Zeabur template.
 
 Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
 
+#### Kubernetes Deployment
+
+Refer to the [Kubernetes Deployment](./docker/README_K8S.md) documentation.
+
 ## 😎 Stay Ahead
 
 Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
@@ -79,16 +93,18 @@ Or visit the demo environment: https://demo.langbot.dev/
 
 | Platform | Status | Remarks |
 | --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
 | Personal QQ | ✅ |  |
 | QQ Official API | ✅ |  |
 | WeCom | ✅ |  |
 | WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
 | Personal WeChat | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
 
 ### LLMs
 
@@ -103,6 +119,8 @@ Or visit the demo environment: https://demo.langbot.dev/
 | [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform |
 | [Dify](https://dify.ai) | ✅ | LLMOps platform |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLM aggregation platform, dedicated to global LLMs |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform |
 | [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |

README_ES.md

@@ -0,0 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+[English](README_EN.md) / [简体中文](README.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">
+
+<a href="https://langbot.app">Inicio</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Despliegue</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/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">Enviar Plugin</a>
+
+</div>
+
+</p>
+
+LangBot es una plataforma de desarrollo de robots de mensajería instantánea nativa de LLM de código abierto, con el objetivo de proporcionar una experiencia de desarrollo de robots de mensajería instantánea lista para usar, con funciones de aplicación LLM como Agent, RAG, MCP, adaptándose a plataformas de mensajería instantánea globales y proporcionando interfaces API ricas, compatible con desarrollo personalizado.
+
+## 📦 Comenzar
+
+#### Inicio Rápido
+
+Use `uvx` para iniciar con un comando (necesita instalar [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Visite http://localhost:5300 para comenzar a usarlo.
+
+#### Despliegue con Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+Visite http://localhost:5300 para comenzar a usarlo.
+
+Documentación detallada [Despliegue con Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Despliegue con un clic en BTPanel
+
+LangBot ha sido listado en BTPanel. Si tiene BTPanel instalado, puede usar la [documentación](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) para usarlo.
+
+#### Despliegue en la Nube Zeabur
+
+Plantilla de Zeabur contribuida por la comunidad.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Despliegue en la Nube Railway
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### Otros Métodos de Despliegue
+
+Use directamente la versión publicada para ejecutar, consulte la documentación de [Despliegue Manual](https://docs.langbot.app/en/deploy/langbot/manual.html).
+
+#### Despliegue en Kubernetes
+
+Consulte la documentación de [Despliegue en Kubernetes](./docker/README_K8S.md).
+
+## 😎 Manténgase Actualizado
+
+Haga clic en los botones Star y Watch en la esquina superior derecha del repositorio para obtener las últimas actualizaciones.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Características
+
+- 💬 Chat con LLM / Agent: Compatible con múltiples LLMs, adaptado para chats grupales y privados; Admite conversaciones de múltiples rondas, llamadas a herramientas, capacidades multimodales y de salida en streaming. Implementación RAG (base de conocimientos) incorporada, e integración profunda con [Dify](https://dify.ai).
+- 🤖 Soporte Multiplataforma: Actualmente compatible con QQ, QQ Channel, WeCom, WeChat personal, Lark, DingTalk, Discord, Telegram, etc.
+- 🛠️ Alta Estabilidad, Rico en Funciones: Control de acceso nativo, limitación de velocidad, filtrado de palabras sensibles, etc.; Fácil de usar, admite múltiples métodos de despliegue. Compatible con múltiples configuraciones de pipeline, diferentes bots para diferentes escenarios.
+- 🧩 Extensión de Plugin, Comunidad Activa: Compatible con mecanismos de plugin impulsados por eventos, extensión de componentes, etc.; Integración del protocolo [MCP](https://modelcontextprotocol.io/) de Anthropic; Actualmente cuenta con cientos de plugins.
+- 😻 Interfaz Web: Admite la gestión de instancias de LangBot a través del navegador. No es necesario escribir archivos de configuración manualmente.
+
+Para especificaciones más detalladas, consulte la [documentación](https://docs.langbot.app/en/insight/features.html).
+
+O visite el entorno de demostración: https://demo.langbot.dev/
+  - Información de inicio de sesión: Correo electrónico: `demo@langbot.app` Contraseña: `langbot123456`
+  - Nota: Solo para demostración de WebUI, por favor no ingrese información confidencial en el entorno público.
+
+### Plataformas de Mensajería
+
+| Plataforma | Estado | Observaciones |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Personal | ✅ |  |
+| QQ API Oficial | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personal | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | Estado | Observaciones |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Disponible para cualquier modelo con formato de interfaz OpenAI |
+| [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/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Plataforma de recursos LLM y GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Plataforma de recursos LLM y GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Plataforma de agregación LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Plataforma de recursos LLM y GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Gateway LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Plataforma LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Plataforma de ejecución de LLM local |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Plataforma de ejecución de LLM local |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Gateway de interfaz LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Gateway LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Gateway LLM (MaaS), plataforma LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Gateway LLM (MaaS), plataforma LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Gateway LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Compatible con acceso a herramientas a través del protocolo MCP |
+
+## 🤝 Contribución de la Comunidad
+
+Gracias a los siguientes [contribuidores de código](https://github.com/langbot-app/LangBot/graphs/contributors) y otros miembros de la comunidad por sus contribuciones a 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+[English](README_EN.md) / [简体中文](README.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">
+
+<a href="https://langbot.app">Accueil</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Déploiement</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/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">Soumettre un Plugin</a>
+
+</div>
+
+</p>
+
+LangBot est une plateforme de développement de robots de messagerie instantanée native LLM open source, visant à fournir une expérience de développement de robots de messagerie instantanée prête à l'emploi, avec des fonctionnalités d'application LLM telles qu'Agent, RAG, MCP, s'adaptant aux plateformes de messagerie instantanée mondiales et fournissant des interfaces API riches, prenant en charge le développement personnalisé.
+
+## 📦 Commencer
+
+#### Démarrage Rapide
+
+Utilisez `uvx` pour démarrer avec une commande (besoin d'installer [uv](https://docs.astral.sh/uv/getting-started/installation/)) :
+
+```bash
+uvx langbot
+```
+
+Visitez http://localhost:5300 pour commencer à l'utiliser.
+
+#### Déploiement avec Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+Visitez http://localhost:5300 pour commencer à l'utiliser.
+
+Documentation détaillée [Déploiement Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Déploiement en un clic sur BTPanel
+
+LangBot a été répertorié sur BTPanel. Si vous avez installé BTPanel, vous pouvez utiliser la [documentation](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) pour l'utiliser.
+
+#### Déploiement Cloud Zeabur
+
+Modèle Zeabur contribué par la communauté.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Déploiement Cloud Railway
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### Autres Méthodes de Déploiement
+
+Utilisez directement la version publiée pour exécuter, consultez la documentation de [Déploiement Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html).
+
+#### Déploiement Kubernetes
+
+Consultez la documentation de [Déploiement Kubernetes](./docker/README_K8S.md).
+
+## 😎 Restez à Jour
+
+Cliquez sur les boutons Star et Watch dans le coin supérieur droit du dépôt pour obtenir les dernières mises à jour.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Fonctionnalités
+
+- 💬 Chat avec LLM / Agent : Prend en charge plusieurs LLM, adapté aux chats de groupe et privés ; Prend en charge les conversations multi-tours, les appels d'outils, les capacités multimodales et de sortie en streaming. Implémentation RAG (base de connaissances) intégrée, et intégration profonde avec [Dify](https://dify.ai).
+- 🤖 Support Multi-plateforme : Actuellement compatible avec QQ, QQ Channel, WeCom, WeChat personnel, Lark, DingTalk, Discord, Telegram, etc.
+- 🛠️ Haute Stabilité, Riche en Fonctionnalités : Contrôle d'accès natif, limitation de débit, filtrage de mots sensibles, etc. ; Facile à utiliser, prend en charge plusieurs méthodes de déploiement. Prend en charge plusieurs configurations de pipeline, différents bots pour différents scénarios.
+- 🧩 Extension de Plugin, Communauté Active : Prend en charge les mécanismes de plugin pilotés par événements, l'extension de composants, etc. ; Intégration du protocole [MCP](https://modelcontextprotocol.io/) d'Anthropic ; Dispose actuellement de centaines de plugins.
+- 😻 Interface Web : Prend en charge la gestion des instances LangBot via le navigateur. Pas besoin d'écrire manuellement les fichiers de configuration.
+
+Pour des spécifications plus détaillées, veuillez consulter la [documentation](https://docs.langbot.app/en/insight/features.html).
+
+Ou visitez l'environnement de démonstration : https://demo.langbot.dev/
+  - Informations de connexion : Email : `demo@langbot.app` Mot de passe : `langbot123456`
+  - Note : Pour la démonstration WebUI uniquement, veuillez ne pas entrer d'informations sensibles dans l'environnement public.
+
+### Plateformes de Messagerie
+
+| Plateforme | Statut | Remarques |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Personnel | ✅ |  |
+| API Officielle QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personnel | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | Statut | Remarques |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Disponible pour tout modèle au format d'interface OpenAI |
+| [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/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Plateforme de ressources LLM et GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Plateforme de ressources LLM et GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Plateforme d'agrégation LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Plateforme de ressources LLM et GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Passerelle LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Plateforme LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Plateforme d'exécution LLM locale |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Plateforme d'exécution LLM locale |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Passerelle d'interface LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Passerelle LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Passerelle LLM (MaaS), plateforme LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Passerelle LLM (MaaS), plateforme LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Passerelle LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Prend en charge l'accès aux outils via le protocole MCP |
+
+## 🤝 Contribution de la Communauté
+
+Merci aux [contributeurs de code](https://github.com/langbot-app/LangBot/graphs/contributors) suivants et aux autres membres de la communauté pour leurs contributions à 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

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / (PR for your language)
+[English](README_EN.md) / [简体中文](README.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/langbot-app/LangBot)
@@ -25,11 +25,21 @@ LangBot は、エージェント、RAG、MCP などの LLM アプリケーショ
 
 ## 📦 始め方
 
+#### クイックスタート
+
+`uvx` を使用した迅速なデプロイ（[uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です）：
+
+```bash
+uvx langbot
+```
+
+http://localhost:5300 にアクセスして使用を開始します。
+
 #### Docker Compose デプロイ
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
-cd LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -55,6 +65,10 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 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。
 
+#### Kubernetes デプロイ
+
+[Kubernetes デプロイ](./docker/README_K8S.md) ドキュメントを参照してください。
+
 ## 😎 最新情報を入手
 
 リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
@@ -79,16 +93,18 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 | プラットフォーム | ステータス | 備考 |
 | --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
 | 個人QQ | ✅ |  |
 | QQ公式API | ✅ |  |
 | WeCom | ✅ |  |
 | WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
 | 個人WeChat | ✅ | |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
 
 ### LLMs
 
@@ -102,6 +118,8 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 | [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
 | [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
 | [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 |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLMゲートウェイ(MaaS) |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム |
 | [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |

README_KO.md

@@ -0,0 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+[English](README_EN.md) / [简体中文](README.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">
+
+<a href="https://langbot.app">홈</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">배포</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">플러그인</a> ｜
+<a href="https://github.com/langbot-app/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">플러그인 제출</a>
+
+</div>
+
+</p>
+
+LangBot은 오픈 소스 LLM 네이티브 인스턴트 메시징 로봇 개발 플랫폼으로, Agent, RAG, MCP 등 다양한 LLM 애플리케이션 기능을 갖춘 즉시 사용 가능한 IM 로봇 개발 경험을 제공하며, 글로벌 인스턴트 메시징 플랫폼에 적응하고 풍부한 API 인터페이스를 제공하여 맞춤형 개발을 지원합니다.
+
+## 📦 시작하기
+
+#### 빠른 시작
+
+`uvx`를 사용하여 한 명령으로 시작하세요 ([uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요):
+
+```bash
+uvx langbot
+```
+
+http://localhost:5300을 방문하여 사용을 시작하세요.
+
+#### Docker Compose 배포
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+http://localhost:5300을 방문하여 사용을 시작하세요.
+
+자세한 문서는 [Docker 배포](https://docs.langbot.app/en/deploy/langbot/docker.html)를 참조하세요.
+
+#### BTPanel 원클릭 배포
+
+LangBot은 BTPanel에 등록되어 있습니다. BTPanel을 설치한 경우 [문서](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)를 사용하여 사용할 수 있습니다.
+
+#### Zeabur 클라우드 배포
+
+커뮤니티에서 제공하는 Zeabur 템플릿입니다.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Railway 클라우드 배포
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### 기타 배포 방법
+
+릴리스 버전을 직접 사용하여 실행하려면 [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) 문서를 참조하세요.
+
+#### Kubernetes 배포
+
+[Kubernetes 배포](./docker/README_K8S.md) 문서를 참조하세요.
+
+## 😎 최신 정보 받기
+
+리포지토리 오른쪽 상단의 Star 및 Watch 버튼을 클릭하여 최신 업데이트를 받으세요.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 기능
+
+- 💬 LLM / Agent와 채팅: 여러 LLM을 지원하며 그룹 채팅 및 개인 채팅에 적응; 멀티 라운드 대화, 도구 호출, 멀티모달, 스트리밍 출력 기능을 지원합니다. 내장된 RAG(지식 베이스) 구현 및 [Dify](https://dify.ai)와 깊이 통합됩니다.
+- 🤖 다중 플랫폼 지원: 현재 QQ, QQ Channel, WeCom, 개인 WeChat, Lark, DingTalk, Discord, Telegram 등을 지원합니다.
+- 🛠️ 높은 안정성, 풍부한 기능: 네이티브 액세스 제어, 속도 제한, 민감한 단어 필터링 등의 메커니즘; 사용하기 쉽고 여러 배포 방법을 지원합니다. 여러 파이프라인 구성을 지원하며 다양한 시나리오에 대해 다른 봇을 사용할 수 있습니다.
+- 🧩 플러그인 확장, 활발한 커뮤니티: 이벤트 기반, 컴포넌트 확장 등의 플러그인 메커니즘을 지원; Anthropic [MCP 프로토콜](https://modelcontextprotocol.io/) 통합; 현재 수백 개의 플러그인이 있습니다.
+- 😻 웹 UI: 브라우저를 통해 LangBot 인스턴스 관리를 지원합니다. 구성 파일을 수동으로 작성할 필요가 없습니다.
+
+더 자세한 사양은 [문서](https://docs.langbot.app/en/insight/features.html)를 참조하세요.
+
+또는 데모 환경을 방문하세요: https://demo.langbot.dev/
+  - 로그인 정보: 이메일: `demo@langbot.app` 비밀번호: `langbot123456`
+  - 참고: WebUI 데모 전용이므로 공개 환경에서는 민감한 정보를 입력하지 마세요.
+
+### 메시징 플랫폼
+
+| 플랫폼 | 상태 | 비고 |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| 개인 QQ | ✅ |  |
+| QQ 공식 API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| 개인 WeChat | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | 상태 | 비고 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 모든 OpenAI 인터페이스 형식 모델에 사용 가능 |
+| [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/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLM 집계 플랫폼 |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM 게이트웨이(MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOps 플랫폼 |
+| [Ollama](https://ollama.com/) | ✅ | 로컬 LLM 실행 플랫폼 |
+| [LMStudio](https://lmstudio.ai/) | ✅ | 로컬 LLM 실행 플랫폼 |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM 인터페이스 게이트웨이(MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM 게이트웨이(MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM 게이트웨이(MaaS), LLMOps 플랫폼 |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM 게이트웨이(MaaS), LLMOps 플랫폼 |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM 게이트웨이(MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | MCP 프로토콜을 통한 도구 액세스 지원 |
+
+## 🤝 커뮤니티 기여
+
+다음 [코드 기여자](https://github.com/langbot-app/LangBot/graphs/contributors) 및 커뮤니티의 다른 구성원들의 LangBot 기여에 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+[English](README_EN.md) / [简体中文](README.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">
+
+<a href="https://langbot.app">Главная</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Развертывание</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Плагин</a> ｜
+<a href="https://github.com/langbot-app/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">Отправить плагин</a>
+
+</div>
+
+</p>
+
+LangBot — это платформа разработки ботов для мгновенных сообщений на основе LLM с открытым исходным кодом, целью которой является предоставление готового к использованию опыта разработки ботов для IM, с функциями приложений LLM, такими как Agent, RAG, MCP, адаптацией к глобальным платформам мгновенных сообщений и предоставлением богатых API-интерфейсов, поддерживающих пользовательскую разработку.
+
+## 📦 Начало работы
+
+#### Быстрый старт
+
+Используйте `uvx` для запуска одной командой (требуется установка [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Посетите http://localhost:5300, чтобы начать использование.
+
+#### Развертывание с Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+Посетите http://localhost:5300, чтобы начать использование.
+
+Подробная документация [Развертывание Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Развертывание одним кликом на BTPanel
+
+LangBot добавлен в BTPanel. Если у вас установлен BTPanel, вы можете использовать [документацию](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) для его использования.
+
+#### Облачное развертывание Zeabur
+
+Шаблон Zeabur, предоставленный сообществом.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Облачное развертывание Railway
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### Другие методы развертывания
+
+Используйте выпущенную версию напрямую для запуска, см. документацию [Ручное развертывание](https://docs.langbot.app/en/deploy/langbot/manual.html).
+
+#### Развертывание Kubernetes
+
+См. документацию [Развертывание Kubernetes](./docker/README_K8S.md).
+
+## 😎 Оставайтесь в курсе
+
+Нажмите кнопки Star и Watch в правом верхнем углу репозитория, чтобы получать последние обновления.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Функции
+
+- 💬 Чат с LLM / Agent: Поддержка нескольких LLM, адаптация к групповым и личным чатам; Поддержка многораундовых разговоров, вызовов инструментов, мультимодальных возможностей и потоковой передачи. Встроенная реализация RAG (база знаний) и глубокая интеграция с [Dify](https://dify.ai).
+- 🤖 Многоплатформенная поддержка: В настоящее время поддерживает QQ, QQ Channel, WeCom, личный WeChat, Lark, DingTalk, Discord, Telegram и т.д.
+- 🛠️ Высокая стабильность, богатство функций: Нативный контроль доступа, ограничение скорости, фильтрация чувствительных слов и т.д.; Простота в использовании, поддержка нескольких методов развертывания. Поддержка нескольких конфигураций конвейера, разные боты для разных сценариев.
+- 🧩 Расширение плагинов, активное сообщество: Поддержка механизмов плагинов, управляемых событиями, расширения компонентов и т.д.; Интеграция протокола [MCP](https://modelcontextprotocol.io/) от Anthropic; В настоящее время сотни плагинов.
+- 😻 Веб-интерфейс: Поддержка управления экземплярами LangBot через браузер. Нет необходимости вручную писать конфигурационные файлы.
+
+Для более подробных спецификаций обратитесь к [документации](https://docs.langbot.app/en/insight/features.html).
+
+Или посетите демонстрационную среду: https://demo.langbot.dev/
+  - Информация для входа: Email: `demo@langbot.app` Пароль: `langbot123456`
+  - Примечание: Только для демонстрации WebUI, пожалуйста, не вводите конфиденциальную информацию в общедоступной среде.
+
+### Платформы обмена сообщениями
+
+| Платформа | Статус | Примечания |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| Личный QQ | ✅ |  |
+| Официальный API QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| Личный WeChat | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | Статус | Примечания |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Доступна для любой модели формата интерфейса OpenAI |
+| [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/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Платформа ресурсов LLM и GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Платформа ресурсов LLM и GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Платформа агрегации LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Платформа ресурсов LLM и GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Шлюз LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Платформа LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Платформа локального запуска LLM |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Платформа локального запуска LLM |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Шлюз интерфейса LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Шлюз LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Шлюз LLM (MaaS), платформа LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Шлюз LLM (MaaS), платформа LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Шлюз LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Поддержка доступа к инструментам через протокол MCP |
+
+## 🤝 Вклад сообщества
+
+Спасибо следующим [контрибьюторам кода](https://github.com/langbot-app/LangBot/graphs/contributors) и другим членам сообщества за их вклад в LangBot:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_TW.md

@@ -5,7 +5,7 @@
 
 <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>
 
-[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / (PR for your language)
+[English](README_EN.md) / [简体中文](README.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)
@@ -27,11 +27,21 @@ LangBot 是一個開源的大語言模型原生即時通訊機器人開發平台
 
 ## 📦 開始使用
 
+#### 快速部署
+
+使用 `uvx` 一鍵啟動（需要先安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/) ）：
+
+```bash
+uvx langbot
+```
+
+訪問 http://localhost:5300 即可開始使用。
+
 #### Docker Compose 部署
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
-cd LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -57,6 +67,10 @@ docker compose up -d
 
 直接使用發行版運行，查看文件[手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
 
+#### Kubernetes 部署
+
+參考 [Kubernetes 部署](./docker/README_K8S.md) 文件。
+
 ## 😎 保持更新
 
 點擊倉庫右上角 Star 和 Watch 按鈕，獲取最新動態。
@@ -81,16 +95,18 @@ docker compose up -d
 
 | 平台 | 狀態 | 備註 |
 | --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
 | QQ 個人號 | ✅ | QQ 個人號私聊、群聊 |
 | QQ 官方機器人 | ✅ | QQ 官方機器人，支援頻道、私聊、群聊 |
 | 微信 | ✅ |  |
 | 企微對外客服 | ✅ |  |
+| 企微智能機器人 | ✅ |  |
 | 微信公眾號 | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
 
 ### 大模型能力
 
@@ -102,8 +118,10 @@ docker compose up -d
 | [Anthropic](https://www.anthropic.com/) | ✅ |  |
 | [xAI](https://x.ai/) | ✅ |  |
 | [智譜AI](https://open.bigmodel.cn/) | ✅ |  |
+| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 |
 | [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，專注全球大模型接入 |
 | [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Dify](https://dify.ai) | ✅ | LLMOps 平台 |

README_VI.md

@@ -0,0 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+[English](README_EN.md) / [简体中文](README.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">
+
+<a href="https://langbot.app">Trang chủ</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Triển khai</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/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">Gửi Plugin</a>
+
+</div>
+
+</p>
+
+LangBot là một nền tảng phát triển robot nhắn tin tức thời gốc LLM mã nguồn mở, nhằm mục đích cung cấp trải nghiệm phát triển robot IM sẵn sàng sử dụng, với các chức năng ứng dụng LLM như Agent, RAG, MCP, thích ứng với các nền tảng nhắn tin tức thời toàn cầu và cung cấp giao diện API phong phú, hỗ trợ phát triển tùy chỉnh.
+
+## 📦 Bắt đầu
+
+#### Khởi động Nhanh
+
+Sử dụng `uvx` để khởi động bằng một lệnh (cần cài đặt [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Truy cập http://localhost:5300 để bắt đầu sử dụng.
+
+#### Triển khai Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+Truy cập http://localhost:5300 để bắt đầu sử dụng.
+
+Tài liệu chi tiết [Triển khai Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Triển khai Một cú nhấp chuột trên BTPanel
+
+LangBot đã được liệt kê trên BTPanel. Nếu bạn đã cài đặt BTPanel, bạn có thể sử dụng [tài liệu](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) để sử dụng nó.
+
+#### Triển khai Cloud Zeabur
+
+Mẫu Zeabur được đóng góp bởi cộng đồng.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Triển khai Cloud Railway
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### Các Phương pháp Triển khai Khác
+
+Sử dụng trực tiếp phiên bản phát hành để chạy, xem tài liệu [Triển khai Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html).
+
+#### Triển khai Kubernetes
+
+Tham khảo tài liệu [Triển khai Kubernetes](./docker/README_K8S.md).
+
+## 😎 Cập nhật Mới nhất
+
+Nhấp vào các nút Star và Watch ở góc trên bên phải của kho lưu trữ để nhận các bản cập nhật mới nhất.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Tính năng
+
+- 💬 Chat với LLM / Agent: Hỗ trợ nhiều LLM, thích ứng với chat nhóm và chat riêng tư; Hỗ trợ các cuộc trò chuyện nhiều vòng, gọi công cụ, khả năng đa phương thức và đầu ra streaming. Triển khai RAG (cơ sở kiến thức) tích hợp sẵn và tích hợp sâu với [Dify](https://dify.ai).
+- 🤖 Hỗ trợ Đa nền tảng: Hiện hỗ trợ QQ, QQ Channel, WeCom, WeChat cá nhân, Lark, DingTalk, Discord, Telegram, v.v.
+- 🛠️ Độ ổn định Cao, Tính năng Phong phú: Kiểm soát truy cập gốc, giới hạn tốc độ, lọc từ nhạy cảm, v.v.; Dễ sử dụng, hỗ trợ nhiều phương pháp triển khai. Hỗ trợ nhiều cấu hình pipeline, các bot khác nhau cho các kịch bản khác nhau.
+- 🧩 Mở rộng Plugin, Cộng đồng Hoạt động: Hỗ trợ các cơ chế plugin hướng sự kiện, mở rộng thành phần, v.v.; Tích hợp giao thức [MCP](https://modelcontextprotocol.io/) của Anthropic; Hiện có hàng trăm plugin.
+- 😻 Giao diện Web: Hỗ trợ quản lý các phiên bản LangBot thông qua trình duyệt. Không cần viết tệp cấu hình thủ công.
+
+Để biết thêm thông số kỹ thuật chi tiết, vui lòng tham khảo [tài liệu](https://docs.langbot.app/en/insight/features.html).
+
+Hoặc truy cập môi trường demo: https://demo.langbot.dev/
+  - Thông tin đăng nhập: Email: `demo@langbot.app` Mật khẩu: `langbot123456`
+  - Lưu ý: Chỉ dành cho demo WebUI, vui lòng không nhập bất kỳ thông tin nhạy cảm nào trong môi trường công cộng.
+
+### Nền tảng Nhắn tin
+
+| Nền tảng | Trạng thái | Ghi chú |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Cá nhân | ✅ |  |
+| QQ API Chính thức | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Cá nhân | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | Trạng thái | Ghi chú |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Có sẵn cho bất kỳ mô hình định dạng giao diện OpenAI nào |
+| [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/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Nền tảng tổng hợp LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Cổng LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Nền tảng LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Nền tảng chạy LLM cục bộ |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Nền tảng chạy LLM cục bộ |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Cổng giao diện LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Cổng LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Cổng LLM (MaaS), nền tảng LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Cổng LLM (MaaS), nền tảng LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Cổng LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Hỗ trợ truy cập công cụ qua giao thức MCP |
+
+## 🤝 Đóng góp Cộng đồng
+
+Cảm ơn các [người đóng góp mã](https://github.com/langbot-app/LangBot/graphs/contributors) sau đây và các thành viên khác trong cộng đồng vì những đóng góp của họ cho LangBot:
+
+<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

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://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [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://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [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 +1,40 @@
+# 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
+    platform: linux/amd64 # For Apple Silicon compatibility
+    volumes:
+      - ./data/plugins:/app/data/plugins
+    ports:
+      - 5401:5401
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+    networks:
+      - langbot_network
+
+  langbot:
+    image: rockchin/langbot:latest
+    container_name: langbot
+    platform: linux/amd64 # For Apple Silicon compatibility
+    volumes:
+      - ./data:/app/data
+      - ./plugins:/app/plugins
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    ports:
+      - 5300:5300  # For web ui
+      - 2280-2290:2280-2290  # For platform webhook
+    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/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/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.

libs/dify_service_api/test.py

@@ -1,45 +0,0 @@
-from v1 import client  # type: ignore
-
-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())

main.py

@@ -1,105 +1,3 @@
-import asyncio
-import argparse
-# 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/langbot-app/LangBot
-📖 Documentation 文档地址: https://docs.langbot.app
-"""
-
-
-async def main_entry(loop: asyncio.AbstractEventLoop):
-    parser = argparse.ArgumentParser(description='LangBot')
-    parser.add_argument('--skip-plugin-deps-check', action='store_true', help='跳过插件依赖项检查', default=False)
-    args = parser.parse_args()
-
-    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
-    if not args.skip_plugin_deps_check:
-        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/groups/pipelines/pipelines.py

@@ -1,48 +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':
-                sort_by = quart.request.args.get('sort_by', 'created_at')
-                sort_order = quart.request.args.get('sort_order', 'DESC')
-                return self.success(
-                    data={'pipelines': await self.ap.pipeline_service.get_pipelines(sort_by, sort_order)}
-                )
-            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/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'Updating plugin {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'Removing plugin {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'Installing plugin ...{short_source_str}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})

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/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/entities.py

@@ -1,178 +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]]
-        | typing.Optional[list[llm_entities.MessageChunk]]
-    ) = []
-    """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]]
-
-    pipeline_uuid: str
-    """流水线UUID。"""
-
-    bot_uuid: str
-    """机器人UUID。"""
-
-    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/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):
-    """Load config file stage"""
-
-    async def run(self, ap: app.Application):
-        """Load config file"""
-
-        # ======= 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/pipeline/preproc/preproc.py

@@ -1,129 +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):
-    """Request pre-processing stage
-
-    Check out session, prompt, context, model, and content functions.
-
-    Rewrite:
-        - session
-        - prompt
-        - messages
-        - user_message
-        - use_model
-        - use_funcs
-    """
-
-    async def process(
-        self,
-        query: core_entities.Query,
-        stage_inst_name: str,
-    ) -> entities.StageProcessResult:
-        """Process"""
-        selected_runner = query.pipeline_config['ai']['runner']['runner']
-
-        session = await self.ap.sess_mgr.get_session(query)
-
-        # When not local-agent, llm_model is 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'],
-            query.pipeline_uuid,
-            query.bot_uuid,
-        )
-
-        conversation.use_llm_model = llm_model
-
-        # Set 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__('func_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: list[llm_entities.ContentElement] = []
-
-        plain_text = ''
-        qoute_msg = query.pipeline_config['trigger'].get('misc', '').get('combine-quote-message')
-
-        # tidy the content_list
-        # combine all text content into one, and put it in the first position
-        for me in query.message_chain:
-            if isinstance(me, platform_message.Plain):
-                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))
-
-        content_list.insert(0, llm_entities.ContentElement.from_text(plain_text))
-
-        query.variables['user_message_text'] = plain_text
-
-        query.user_message = llm_entities.Message(role='user', content=content_list)
-        # =========== Trigger event 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/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]:
-        """Process"""
-
-        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'Command({query.query_id}) error: {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'Command returned: {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/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)

pkg/platform/adapter.py

@@ -1,190 +0,0 @@
-from __future__ import annotations
-
-# MessageSource的适配器
-import typing
-import abc
-
-
-from ..core import app
-from .types import message as platform_message
-from .types import events as platform_events
-from .logger import EventLogger
-
-
-class MessagePlatformAdapter(metaclass=abc.ABCMeta):
-    """消息平台适配器基类"""
-
-    name: str
-
-    bot_account_id: int
-    """机器人账号ID，需要在初始化时设置"""
-
-    config: dict
-
-    ap: app.Application
-
-    logger: EventLogger
-
-    def __init__(self, config: dict, ap: app.Application, logger: EventLogger):
-        """初始化适配器
-
-        Args:
-            config (dict): 对应的配置
-            ap (app.Application): 应用上下文
-        """
-        self.config = config
-        self.ap = ap
-        self.logger = logger
-
-    async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        """主动发送消息
-
-        Args:
-            target_type (str): 目标类型，`person`或`group`
-            target_id (str): 目标ID
-            message (platform.types.MessageChain): 消息链
-        """
-        raise NotImplementedError
-
-    async def reply_message(
-        self,
-        message_source: platform_events.MessageEvent,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-    ):
-        """回复消息
-
-        Args:
-            message_source (platform.types.MessageEvent): 消息源事件
-            message (platform.types.MessageChain): 消息链
-            quote_origin (bool, optional): 是否引用原消息. Defaults to False.
-        """
-        raise NotImplementedError
-
-    async def reply_message_chunk(
-        self,
-        message_source: platform_events.MessageEvent,
-        bot_message: dict,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-        is_final: bool = False,
-    ):
-        """回复消息（流式输出）
-        Args:
-            message_source (platform.types.MessageEvent): 消息源事件
-            message_id (int): 消息ID
-            message (platform.types.MessageChain): 消息链
-            quote_origin (bool, optional): 是否引用原消息. Defaults to False.
-            is_final (bool, optional): 流式是否结束. Defaults to False.
-        """
-        raise NotImplementedError
-
-    async def create_message_card(self, message_id: typing.Type[str, int], event: platform_events.MessageEvent) -> bool:
-        """创建卡片消息
-        Args:
-            message_id (str): 消息ID
-            event (platform_events.MessageEvent): 消息源事件
-        """
-        return False
-
-    async def is_muted(self, group_id: int) -> bool:
-        """获取账号是否在指定群被禁言"""
-        raise NotImplementedError
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[[platform_events.Event, MessagePlatformAdapter], None],
-    ):
-        """注册事件监听器
-
-        Args:
-            event_type (typing.Type[platform.types.Event]): 事件类型
-            callback (typing.Callable[[platform.types.Event], None]): 回调函数，接收一个参数，为事件
-        """
-        raise NotImplementedError
-
-    def unregister_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[[platform_events.Event, MessagePlatformAdapter], None],
-    ):
-        """注销事件监听器
-
-        Args:
-            event_type (typing.Type[platform.types.Event]): 事件类型
-            callback (typing.Callable[[platform.types.Event], None]): 回调函数，接收一个参数，为事件
-        """
-        raise NotImplementedError
-
-    async def run_async(self):
-        """异步运行"""
-        raise NotImplementedError
-
-    async def is_stream_output_supported(self) -> bool:
-        """是否支持流式输出"""
-        return False
-
-    async def kill(self) -> bool:
-        """关闭适配器
-
-        Returns:
-            bool: 是否成功关闭，热重载时若此函数返回False则不会重载MessageSource底层
-        """
-        raise NotImplementedError
-
-
-class MessageConverter:
-    """消息链转换器基类"""
-
-    @staticmethod
-    def yiri2target(message_chain: platform_message.MessageChain):
-        """将源平台消息链转换为目标平台消息链
-
-        Args:
-            message_chain (platform.types.MessageChain): 源平台消息链
-
-        Returns:
-            typing.Any: 目标平台消息链
-        """
-        raise NotImplementedError
-
-    @staticmethod
-    def target2yiri(message_chain: typing.Any) -> platform_message.MessageChain:
-        """将目标平台消息链转换为源平台消息链
-
-        Args:
-            message_chain (typing.Any): 目标平台消息链
-
-        Returns:
-            platform.types.MessageChain: 源平台消息链
-        """
-        raise NotImplementedError
-
-
-class EventConverter:
-    """事件转换器基类"""
-
-    @staticmethod
-    def yiri2target(event: typing.Type[platform_events.Event]):
-        """将源平台事件转换为目标平台事件
-
-        Args:
-            event (typing.Type[platform.types.Event]): 源平台事件
-
-        Returns:
-            typing.Any: 目标平台事件
-        """
-        raise NotImplementedError
-
-    @staticmethod
-    def target2yiri(event: typing.Any) -> platform_events.Event:
-        """将目标平台事件的调用参数转换为源平台的事件参数对象
-
-        Args:
-            event (typing.Any): 目标平台事件
-
-        Returns:
-            typing.Type[platform.types.Event]: 源平台事件
-        """
-        raise NotImplementedError

pkg/platform/adapter.yaml

@@ -1,14 +0,0 @@
-apiVersion: v1
-kind: ComponentTemplate
-metadata:
-  name: MessagePlatformAdapter
-  label:
-    en_US: Message Platform Adapter
-    zh_Hans: 消息平台适配器模板类
-spec:
-  type:
-    - python
-execution:
-  python:
-    path: ./adapter.py
-    attr: MessagePlatformAdapter

pkg/platform/types/__init__.py

@@ -1,3 +0,0 @@
-from .entities import *
-from .events import *
-from .message import *

pkg/platform/types/base.py

@@ -1,107 +0,0 @@
-from typing import Dict, List, Type
-
-import pydantic.v1.main as pdm
-from pydantic.v1 import BaseModel
-
-
-class PlatformMetaclass(pdm.ModelMetaclass):
-    """此类是平台中使用的 pydantic 模型的元类的基类。"""
-
-
-def to_camel(name: str) -> str:
-    """将下划线命名风格转换为小驼峰命名。"""
-    if name[:2] == '__':  # 不处理双下划线开头的特殊命名。
-        return name
-    name_parts = name.split('_')
-    return ''.join(name_parts[:1] + [x.title() for x in name_parts[1:]])
-
-
-class PlatformBaseModel(BaseModel, metaclass=PlatformMetaclass):
-    """模型基类。
-
-    启用了三项配置：
-    1. 允许解析时传入额外的值，并将额外值保存在模型中。
-    2. 允许通过别名访问字段。
-    3. 自动生成小驼峰风格的别名。
-    """
-
-    def __init__(self, *args, **kwargs):
-        """"""
-        super().__init__(*args, **kwargs)
-
-    def __repr__(self) -> str:
-        return (
-            self.__class__.__name__ + '(' + ', '.join((f'{k}={repr(v)}' for k, v in self.__dict__.items() if v)) + ')'
-        )
-
-    class Config:
-        extra = 'allow'
-        allow_population_by_field_name = True
-        alias_generator = to_camel
-
-
-class PlatformIndexedMetaclass(PlatformMetaclass):
-    """可以通过子类名获取子类的类的元类。"""
-
-    __indexedbases__: List[Type['PlatformIndexedModel']] = []
-    __indexedmodel__ = None
-
-    def __new__(cls, name, bases, attrs, **kwargs):
-        new_cls = super().__new__(cls, name, bases, attrs, **kwargs)
-        # 第一类：PlatformIndexedModel
-        if name == 'PlatformIndexedModel':
-            cls.__indexedmodel__ = new_cls
-            new_cls.__indexes__ = {}
-            return new_cls
-        # 第二类：PlatformIndexedModel 的直接子类，这些是可以通过子类名获取子类的类。
-        if cls.__indexedmodel__ in bases:
-            cls.__indexedbases__.append(new_cls)
-            new_cls.__indexes__ = {}
-            return new_cls
-        # 第三类：PlatformIndexedModel 的直接子类的子类，这些添加到直接子类的索引中。
-        for base in cls.__indexedbases__:
-            if issubclass(new_cls, base):
-                base.__indexes__[name] = new_cls
-                return new_cls
-
-    def __getitem__(cls, name):
-        return cls.get_subtype(name)
-
-
-class PlatformIndexedModel(PlatformBaseModel, metaclass=PlatformIndexedMetaclass):
-    """可以通过子类名获取子类的类。"""
-
-    __indexes__: Dict[str, Type['PlatformIndexedModel']]
-
-    @classmethod
-    def get_subtype(cls, name: str) -> Type['PlatformIndexedModel']:
-        """根据类名称，获取相应的子类类型。
-
-        Args:
-            name: 类名称。
-
-        Returns:
-            Type['PlatformIndexedModel']: 子类类型。
-        """
-        try:
-            type_ = cls.__indexes__.get(name)
-            if not (type_ and issubclass(type_, cls)):
-                raise ValueError(f'`{name}` 不是 `{cls.__name__}` 的子类！')
-            return type_
-        except AttributeError:
-            raise ValueError(f'`{name}` 不是 `{cls.__name__}` 的子类！') from None
-
-    @classmethod
-    def parse_subtype(cls, obj: dict) -> 'PlatformIndexedModel':
-        """通过字典，构造对应的模型对象。
-
-        Args:
-            obj: 一个字典，包含了模型对象的属性。
-
-        Returns:
-            PlatformIndexedModel: 构造的对象。
-        """
-        if cls in PlatformIndexedModel.__subclasses__():
-            ModelType = cls.get_subtype(obj['type'])
-            return ModelType.parse_obj(obj)
-        return super().parse_obj(obj)

pkg/platform/types/entities.py

@@ -1,88 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-此模块提供实体和配置项模型。
-"""
-
-import abc
-from datetime import datetime
-from enum import Enum
-import typing
-
-import pydantic.v1 as pydantic
-
-
-class Entity(pydantic.BaseModel):
-    """实体，表示一个用户或群。"""
-
-    id: int
-    """ID。"""
-
-    @abc.abstractmethod
-    def get_name(self) -> str:
-        """名称。"""
-
-
-class Friend(Entity):
-    """私聊对象。"""
-
-    id: typing.Union[int, str]
-    """ID。"""
-    nickname: typing.Optional[str]
-    """昵称。"""
-    remark: typing.Optional[str]
-    """备注。"""
-
-    def get_name(self) -> str:
-        return self.nickname or self.remark or ''
-
-
-class Permission(str, Enum):
-    """群成员身份权限。"""
-
-    Member = 'MEMBER'
-    """成员。"""
-    Administrator = 'ADMINISTRATOR'
-    """管理员。"""
-    Owner = 'OWNER'
-    """群主。"""
-
-    def __repr__(self) -> str:
-        return repr(self.value)
-
-
-class Group(Entity):
-    """群。"""
-
-    id: typing.Union[int, str]
-    """群号。"""
-    name: str
-    """群名称。"""
-    permission: Permission
-    """Bot 在群中的权限。"""
-
-    def get_name(self) -> str:
-        return self.name
-
-
-class GroupMember(Entity):
-    """群成员。"""
-
-    id: typing.Union[int, str]
-    """群员 ID。"""
-    member_name: str
-    """群员名称。"""
-    permission: Permission
-    """在群中的权限。"""
-    group: Group
-    """群。"""
-    special_title: str = ''
-    """群头衔。"""
-    join_timestamp: datetime = datetime.utcfromtimestamp(0)
-    """加入群的时间。"""
-    last_speak_timestamp: datetime = datetime.utcfromtimestamp(0)
-    """最后一次发言的时间。"""
-    mute_time_remaining: int = 0
-    """禁言剩余时间。"""
-
-    def get_name(self) -> str:
-        return self.member_name

pkg/platform/types/events.py

@@ -1,106 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-此模块提供事件模型。
-"""
-
-import typing
-
-import pydantic.v1 as pydantic
-
-from . import entities as platform_entities
-from . import message as platform_message
-
-
-class Event(pydantic.BaseModel):
-    """事件基类。
-
-    Args:
-        type: 事件名。
-    """
-
-    type: str
-    """事件名。"""
-
-    def __repr__(self):
-        return (
-            self.__class__.__name__
-            + '('
-            + ', '.join((f'{k}={repr(v)}' for k, v in self.__dict__.items() if k != 'type' and v))
-            + ')'
-        )
-
-    @classmethod
-    def parse_subtype(cls, obj: dict) -> 'Event':
-        try:
-            return typing.cast(Event, super().parse_subtype(obj))
-        except ValueError:
-            return Event(type=obj['type'])
-
-    @classmethod
-    def get_subtype(cls, name: str) -> typing.Type['Event']:
-        try:
-            return typing.cast(typing.Type[Event], super().get_subtype(name))
-        except ValueError:
-            return Event
-
-
-###############################
-# Message Event
-class MessageEvent(Event):
-    """消息事件。
-
-    Args:
-        type: 事件名。
-        message_chain: 消息内容。
-    """
-
-    type: str
-    """事件名。"""
-    message_chain: platform_message.MessageChain
-    """消息内容。"""
-
-    time: float | None = None
-    """消息发送时间戳。"""
-
-    source_platform_object: typing.Optional[typing.Any] = None
-    """原消息平台对象。
-    供消息平台适配器开发者使用，如果回复用户时需要使用原消息事件对象的信息，
-    那么可以将其存到这个字段以供之后取出使用。"""
-
-
-class FriendMessage(MessageEvent):
-    """私聊消息。
-
-    Args:
-        type: 事件名。
-        sender: 发送消息的好友。
-        message_chain: 消息内容。
-    """
-
-    type: str = 'FriendMessage'
-    """事件名。"""
-    sender: platform_entities.Friend
-    """发送消息的好友。"""
-    message_chain: platform_message.MessageChain
-    """消息内容。"""
-
-
-class GroupMessage(MessageEvent):
-    """群消息。
-
-    Args:
-        type: 事件名。
-        sender: 发送消息的群成员。
-        message_chain: 消息内容。
-    """
-
-    type: str = 'GroupMessage'
-    """事件名。"""
-    sender: platform_entities.GroupMember
-    """发送消息的群成员。"""
-    message_chain: platform_message.MessageChain
-    """消息内容。"""
-
-    @property
-    def group(self) -> platform_entities.Group:
-        return self.sender.group

pkg/platform/types/message.py

@@ -1,978 +0,0 @@
-import itertools
-import logging
-import typing
-from datetime import datetime
-from pathlib import Path
-import base64
-
-import aiofiles
-import httpx
-import pydantic.v1 as pydantic
-
-from . import entities as platform_entities
-from .base import PlatformBaseModel, PlatformIndexedMetaclass, PlatformIndexedModel
-
-logger = logging.getLogger(__name__)
-
-
-class MessageComponentMetaclass(PlatformIndexedMetaclass):
-    """消息组件元类。"""
-
-    __message_component__ = None
-
-    def __new__(cls, name, bases, attrs, **kwargs):
-        new_cls = super().__new__(cls, name, bases, attrs, **kwargs)
-        if name == 'MessageComponent':
-            cls.__message_component__ = new_cls
-
-        if not cls.__message_component__:
-            return new_cls
-
-        for base in bases:
-            if issubclass(base, cls.__message_component__):
-                # 获取字段名
-                if hasattr(new_cls, '__fields__'):
-                    # 忽略 type 字段
-                    new_cls.__parameter_names__ = list(new_cls.__fields__)[1:]
-                else:
-                    new_cls.__parameter_names__ = []
-                break
-
-        return new_cls
-
-
-class MessageComponent(PlatformIndexedModel, metaclass=MessageComponentMetaclass):
-    """消息组件。"""
-
-    type: str
-    """消息组件类型。"""
-
-    def __str__(self):
-        return ''
-
-    def __repr__(self):
-        return (
-            self.__class__.__name__
-            + '('
-            + ', '.join((f'{k}={repr(v)}' for k, v in self.__dict__.items() if k != 'type' and v))
-            + ')'
-        )
-
-    def __init__(self, *args, **kwargs):
-        # 解析参数列表，将位置参数转化为具名参数
-        parameter_names = self.__parameter_names__
-        if len(args) > len(parameter_names):
-            raise TypeError(f'`{self.type}`需要{len(parameter_names)}个参数，但传入了{len(args)}个。')
-        for name, value in zip(parameter_names, args):
-            if name in kwargs:
-                raise TypeError(f'在 `{self.type}` 中，具名参数 `{name}` 与位置参数重复。')
-            kwargs[name] = value
-
-        super().__init__(**kwargs)
-
-
-TMessageComponent = typing.TypeVar('TMessageComponent', bound=MessageComponent)
-
-
-class MessageChain(PlatformBaseModel):
-    """消息链。
-
-    一个构造消息链的例子：
-    ```py
-    message_chain = MessageChain([
-        AtAll(),
-        Plain("Hello World!"),
-    ])
-    ```
-
-    `Plain` 可以省略。
-    ```py
-    message_chain = MessageChain([
-        AtAll(),
-        "Hello World!",
-    ])
-    ```
-
-    在调用 API 时，参数中需要 MessageChain 的，也可以使用 `List[MessageComponent]` 代替。
-    例如，以下两种写法是等价的：
-    ```py
-    await bot.send_friend_message(12345678, [
-        Plain("Hello World!")
-    ])
-    ```
-    ```py
-    await bot.send_friend_message(12345678, MessageChain([
-        Plain("Hello World!")
-    ]))
-    ```
-
-    可以使用 `in` 运算检查消息链中：
-    1. 是否有某个消息组件。
-    2. 是否有某个类型的消息组件。
-
-    ```py
-    if AtAll in message_chain:
-        print('AtAll')
-
-    if At(bot.qq) in message_chain:
-        print('At Me')
-    ```
-
-    """
-
-    __root__: typing.List[MessageComponent]
-
-    @staticmethod
-    def _parse_message_chain(msg_chain: typing.Iterable):
-        result = []
-        for msg in msg_chain:
-            if isinstance(msg, dict):
-                result.append(MessageComponent.parse_subtype(msg))
-            elif isinstance(msg, MessageComponent):
-                result.append(msg)
-            elif isinstance(msg, str):
-                result.append(Plain(msg))
-            else:
-                raise TypeError(f'消息链中元素需为 dict 或 str 或 MessageComponent，当前类型：{type(msg)}')
-        return result
-
-    @pydantic.validator('__root__', always=True, pre=True)
-    def _parse_component(cls, msg_chain):
-        if isinstance(msg_chain, (str, MessageComponent)):
-            msg_chain = [msg_chain]
-        if not msg_chain:
-            msg_chain = []
-        return cls._parse_message_chain(msg_chain)
-
-    @classmethod
-    def parse_obj(cls, msg_chain: typing.Iterable):
-        """通过列表形式的消息链，构造对应的 `MessageChain` 对象。
-
-        Args:
-            msg_chain: 列表形式的消息链。
-        """
-        result = cls._parse_message_chain(msg_chain)
-        return cls(__root__=result)
-
-    def __init__(self, __root__: typing.Iterable[MessageComponent] = None):
-        super().__init__(__root__=__root__)
-
-    def __str__(self):
-        return ''.join(str(component) for component in self.__root__)
-
-    def __repr__(self):
-        return f'{self.__class__.__name__}({self.__root__!r})'
-
-    def __iter__(self):
-        yield from self.__root__
-
-    def get_first(self, t: typing.Type[TMessageComponent]) -> typing.Optional[TMessageComponent]:
-        """获取消息链中第一个符合类型的消息组件。"""
-        for component in self:
-            if isinstance(component, t):
-                return component
-        return None
-
-    @typing.overload
-    def __getitem__(self, index: int) -> MessageComponent: ...
-
-    @typing.overload
-    def __getitem__(self, index: slice) -> typing.List[MessageComponent]: ...
-
-    @typing.overload
-    def __getitem__(self, index: typing.Type[TMessageComponent]) -> typing.List[TMessageComponent]: ...
-
-    @typing.overload
-    def __getitem__(
-        self, index: typing.Tuple[typing.Type[TMessageComponent], int]
-    ) -> typing.List[TMessageComponent]: ...
-
-    def __getitem__(
-        self,
-        index: typing.Union[
-            int,
-            slice,
-            typing.Type[TMessageComponent],
-            typing.Tuple[typing.Type[TMessageComponent], int],
-        ],
-    ) -> typing.Union[MessageComponent, typing.List[MessageComponent], typing.List[TMessageComponent]]:
-        return self.get(index)
-
-    def __setitem__(
-        self,
-        key: typing.Union[int, slice],
-        value: typing.Union[MessageComponent, str, typing.Iterable[typing.Union[MessageComponent, str]]],
-    ):
-        if isinstance(value, str):
-            value = Plain(value)
-        if isinstance(value, typing.Iterable):
-            value = (Plain(c) if isinstance(c, str) else c for c in value)
-        self.__root__[key] = value  # type: ignore
-
-    def __delitem__(self, key: typing.Union[int, slice]):
-        del self.__root__[key]
-
-    def __reversed__(self) -> typing.Iterable[MessageComponent]:
-        return reversed(self.__root__)
-
-    def has(
-        self,
-        sub: typing.Union[MessageComponent, typing.Type[MessageComponent], 'MessageChain', str],
-    ) -> bool:
-        """判断消息链中：
-        1. 是否有某个消息组件。
-        2. 是否有某个类型的消息组件。
-
-        Args:
-            sub (`Union[MessageComponent, Type[MessageComponent], 'MessageChain', str]`):
-                若为 `MessageComponent`，则判断该组件是否在消息链中。
-                若为 `Type[MessageComponent]`，则判断该组件类型是否在消息链中。
-
-        Returns:
-            bool: 是否找到。
-        """
-        if isinstance(sub, type):  # 检测消息链中是否有某种类型的对象
-            for i in self:
-                if type(i) is sub:
-                    return True
-            return False
-        if isinstance(sub, MessageComponent):  # 检查消息链中是否有某个组件
-            for i in self:
-                if i == sub:
-                    return True
-            return False
-        raise TypeError(f'类型不匹配，当前类型：{type(sub)}')
-
-    def __contains__(self, sub) -> bool:
-        return self.has(sub)
-
-    def __ge__(self, other):
-        return other in self
-
-    def __len__(self) -> int:
-        return len(self.__root__)
-
-    def __add__(self, other: typing.Union['MessageChain', MessageComponent, str]) -> 'MessageChain':
-        if isinstance(other, MessageChain):
-            return self.__class__(self.__root__ + other.__root__)
-        if isinstance(other, str):
-            return self.__class__(self.__root__ + [Plain(other)])
-        if isinstance(other, MessageComponent):
-            return self.__class__(self.__root__ + [other])
-        return NotImplemented
-
-    def __radd__(self, other: typing.Union[MessageComponent, str]) -> 'MessageChain':
-        if isinstance(other, MessageComponent):
-            return self.__class__([other] + self.__root__)
-        if isinstance(other, str):
-            return self.__class__([typing.cast(MessageComponent, Plain(other))] + self.__root__)
-        return NotImplemented
-
-    def __mul__(self, other: int):
-        if isinstance(other, int):
-            return self.__class__(self.__root__ * other)
-        return NotImplemented
-
-    def __rmul__(self, other: int):
-        return self.__mul__(other)
-
-    def __iadd__(self, other: typing.Iterable[typing.Union[MessageComponent, str]]):
-        self.extend(other)
-
-    def __imul__(self, other: int):
-        if isinstance(other, int):
-            self.__root__ *= other
-        return NotImplemented
-
-    def index(
-        self,
-        x: typing.Union[MessageComponent, typing.Type[MessageComponent]],
-        i: int = 0,
-        j: int = -1,
-    ) -> int:
-        """返回 x 在消息链中首次出现项的索引号（索引号在 i 或其后且在 j 之前）。
-
-        Args:
-            x (`Union[MessageComponent, Type[MessageComponent]]`):
-                要查找的消息元素或消息元素类型。
-            i: 从哪个位置开始查找。
-            j: 查找到哪个位置结束。
-
-        Returns:
-            int: 如果找到，则返回索引号。
-
-        Raises:
-            ValueError: 没有找到。
-            TypeError: 类型不匹配。
-        """
-        if isinstance(x, type):
-            l = len(self)
-            if i < 0:
-                i += l
-            if i < 0:
-                i = 0
-            if j < 0:
-                j += l
-            if j > l:
-                j = l
-            for index in range(i, j):
-                if type(self[index]) is x:
-                    return index
-            raise ValueError('消息链中不存在该类型的组件。')
-        if isinstance(x, MessageComponent):
-            return self.__root__.index(x, i, j)
-        raise TypeError(f'类型不匹配，当前类型：{type(x)}')
-
-    def count(self, x: typing.Union[MessageComponent, typing.Type[MessageComponent]]) -> int:
-        """返回消息链中 x 出现的次数。
-
-        Args:
-            x (`Union[MessageComponent, Type[MessageComponent]]`):
-                要查找的消息元素或消息元素类型。
-
-        Returns:
-            int: 次数。
-        """
-        if isinstance(x, type):
-            return sum(1 for i in self if type(i) is x)
-        if isinstance(x, MessageComponent):
-            return self.__root__.count(x)
-        raise TypeError(f'类型不匹配，当前类型：{type(x)}')
-
-    def extend(self, x: typing.Iterable[typing.Union[MessageComponent, str]]):
-        """将另一个消息链中的元素添加到消息链末尾。
-
-        Args:
-            x: 另一个消息链，也可为消息元素或字符串元素的序列。
-        """
-        self.__root__.extend(Plain(c) if isinstance(c, str) else c for c in x)
-
-    def append(self, x: typing.Union[MessageComponent, str]):
-        """将一个消息元素或字符串元素添加到消息链末尾。
-
-        Args:
-            x: 消息元素或字符串元素。
-        """
-        self.__root__.append(Plain(x) if isinstance(x, str) else x)
-
-    def insert(self, i: int, x: typing.Union[MessageComponent, str]):
-        """将一个消息元素或字符串添加到消息链中指定位置。
-
-        Args:
-            i: 插入位置。
-            x: 消息元素或字符串元素。
-        """
-        self.__root__.insert(i, Plain(x) if isinstance(x, str) else x)
-
-    def pop(self, i: int = -1) -> MessageComponent:
-        """从消息链中移除并返回指定位置的元素。
-
-        Args:
-            i: 移除位置。默认为末尾。
-
-        Returns:
-            MessageComponent: 移除的元素。
-        """
-        return self.__root__.pop(i)
-
-    def remove(self, x: typing.Union[MessageComponent, typing.Type[MessageComponent]]):
-        """从消息链中移除指定元素或指定类型的一个元素。
-
-        Args:
-            x: 指定的元素或元素类型。
-        """
-        if isinstance(x, type):
-            self.pop(self.index(x))
-        if isinstance(x, MessageComponent):
-            self.__root__.remove(x)
-
-    def exclude(
-        self,
-        x: typing.Union[MessageComponent, typing.Type[MessageComponent]],
-        count: int = -1,
-    ) -> 'MessageChain':
-        """返回移除指定元素或指定类型的元素后剩余的消息链。
-
-        Args:
-            x: 指定的元素或元素类型。
-            count: 至多移除的数量。默认为全部移除。
-
-        Returns:
-            MessageChain: 剩余的消息链。
-        """
-
-        def _exclude():
-            nonlocal count
-            x_is_type = isinstance(x, type)
-            for c in self:
-                if count > 0 and ((x_is_type and type(c) is x) or c == x):
-                    count -= 1
-                    continue
-                yield c
-
-        return self.__class__(_exclude())
-
-    def reverse(self):
-        """将消息链原地翻转。"""
-        self.__root__.reverse()
-
-    @classmethod
-    def join(cls, *args: typing.Iterable[typing.Union[str, MessageComponent]]):
-        return cls(Plain(c) if isinstance(c, str) else c for c in itertools.chain(*args))
-
-    @property
-    def source(self) -> typing.Optional['Source']:
-        """获取消息链中的 `Source` 对象。"""
-        return self.get_first(Source)
-
-    @property
-    def message_id(self) -> int:
-        """获取消息链的 message_id，若无法获取，返回 -1。"""
-        source = self.source
-        return source.id if source else -1
-
-
-TMessage = typing.Union[
-    MessageChain,
-    typing.Iterable[typing.Union[MessageComponent, str]],
-    MessageComponent,
-    str,
-]
-"""可以转化为 MessageChain 的类型。"""
-
-
-class Source(MessageComponent):
-    """源。包含消息的基本信息。"""
-
-    type: str = 'Source'
-    """消息组件类型。"""
-    id: typing.Union[int, str]
-    """消息的识别号，用于引用回复（Source 类型永远为 MessageChain 的第一个元素）。"""
-    time: datetime
-    """消息时间。"""
-
-
-class Plain(MessageComponent):
-    """纯文本。"""
-
-    type: str = 'Plain'
-    """消息组件类型。"""
-    text: str
-    """文字消息。"""
-
-    def __str__(self):
-        return self.text
-
-    def __repr__(self):
-        return f'Plain({self.text!r})'
-
-
-class Quote(MessageComponent):
-    """引用。"""
-
-    type: str = 'Quote'
-    """消息组件类型。"""
-    id: typing.Optional[int] = None
-    """被引用回复的原消息的 message_id。"""
-    group_id: typing.Optional[typing.Union[int, str]] = None
-    """被引用回复的原消息所接收的群号，当为好友消息时为0。"""
-    sender_id: typing.Optional[typing.Union[int, str]] = None
-    """被引用回复的原消息的发送者的ID。"""
-    target_id: typing.Optional[typing.Union[int, str]] = None
-    """被引用回复的原消息的接收者者的ID或群ID。"""
-    origin: MessageChain
-    """被引用回复的原消息的消息链对象。"""
-
-    @pydantic.validator('origin', always=True, pre=True)
-    def origin_formater(cls, v):
-        return MessageChain.parse_obj(v)
-
-
-class At(MessageComponent):
-    """At某人。"""
-
-    type: str = 'At'
-    """消息组件类型。"""
-    target: typing.Union[int, str]
-    """群员 ID。"""
-    display: typing.Optional[str] = None
-    """At时显示的文字，发送消息时无效，自动使用群名片。"""
-
-    def __eq__(self, other):
-        return isinstance(other, At) and self.target == other.target
-
-    def __str__(self):
-        return f'@{self.display or self.target}'
-
-
-class AtAll(MessageComponent):
-    """At全体。"""
-
-    type: str = 'AtAll'
-    """消息组件类型。"""
-
-    def __str__(self):
-        return '@全体成员'
-
-
-class Image(MessageComponent):
-    """图片。"""
-
-    type: str = 'Image'
-    """消息组件类型。"""
-    image_id: typing.Optional[str] = None
-    """图片的 image_id，不为空时将忽略 url 属性。"""
-    url: typing.Optional[pydantic.HttpUrl] = None
-    """图片的 URL，发送时可作网络图片的链接；接收时为图片的链接，可用于图片下载。"""
-    path: typing.Union[str, Path, None] = None
-    """图片的路径，发送本地图片。"""
-    base64: typing.Optional[str] = None
-    """图片的 Base64 编码。"""
-
-    def __eq__(self, other):
-        return isinstance(other, Image) and self.type == other.type and self.uuid == other.uuid
-
-    def __str__(self):
-        return '[图片]'
-
-    @pydantic.validator('path')
-    def validate_path(cls, path: typing.Union[str, Path, None]):
-        """修复 path 参数的行为，使之相对于 LangBot 的启动路径。"""
-        if path:
-            try:
-                return str(Path(path).resolve(strict=True))
-            except FileNotFoundError:
-                raise ValueError(f'无效路径：{path}')
-        else:
-            return path
-
-    @property
-    def uuid(self):
-        image_id = self.image_id
-        if image_id[0] == '{':  # 群图片
-            image_id = image_id[1:37]
-        elif image_id[0] == '/':  # 好友图片
-            image_id = image_id[1:]
-        return image_id
-
-    async def get_bytes(self) -> typing.Tuple[bytes, str]:
-        """获取图片的 bytes 和 mime type"""
-        if self.url:
-            async with httpx.AsyncClient() as client:
-                response = await client.get(self.url)
-                response.raise_for_status()
-                return response.content, response.headers.get('Content-Type')
-        elif self.base64:
-            mime_type = 'image/jpeg'
-
-            split_index = self.base64.find(';base64,')
-            if split_index == -1:
-                raise ValueError('Invalid base64 string')
-
-            mime_type = self.base64[5:split_index]
-            base64_data = self.base64[split_index + 8 :]
-
-            return base64.b64decode(base64_data), mime_type
-        elif self.path:
-            async with aiofiles.open(self.path, 'rb') as f:
-                return await f.read(), 'image/jpeg'
-        else:
-            raise ValueError('Can not get bytes from image')
-
-    @classmethod
-    async def from_local(
-        cls,
-        filename: typing.Union[str, Path, None] = None,
-        content: typing.Optional[bytes] = None,
-    ) -> 'Image':
-        """从本地文件路径加载图片，以 base64 的形式传递。
-
-        Args:
-            filename: 从本地文件路径加载图片，与 `content` 二选一。
-            content: 从本地文件内容加载图片，与 `filename` 二选一。
-
-        Returns:
-            Image: 图片对象。
-        """
-        if content:
-            pass
-        elif filename:
-            path = Path(filename)
-            import aiofiles
-
-            async with aiofiles.open(path, 'rb') as f:
-                content = await f.read()
-        else:
-            raise ValueError('请指定图片路径或图片内容！')
-        import base64
-
-        img = cls(base64=base64.b64encode(content).decode())
-        return img
-
-    @classmethod
-    def from_unsafe_path(cls, path: typing.Union[str, Path]) -> 'Image':
-        """从不安全的路径加载图片。
-
-        Args:
-            path: 从不安全的路径加载图片。
-
-        Returns:
-            Image: 图片对象。
-        """
-        return cls.construct(path=str(path))
-
-
-class Unknown(MessageComponent):
-    """未知。"""
-
-    type: str = 'Unknown'
-    """消息组件类型。"""
-    text: str
-    """文本。"""
-
-    def __str__(self):
-        return f'Unknown Message: {self.text}'
-
-
-class Voice(MessageComponent):
-    """语音。"""
-
-    type: str = 'Voice'
-    """消息组件类型。"""
-    voice_id: typing.Optional[str] = None
-    """语音的 voice_id，不为空时将忽略 url 属性。"""
-    url: typing.Optional[str] = None
-    """语音的 URL，发送时可作网络语音的链接；接收时为语音文件的链接，可用于语音下载。"""
-    path: typing.Optional[str] = None
-    """语音的路径，发送本地语音。"""
-    base64: typing.Optional[str] = None
-    """语音的 Base64 编码。"""
-    length: typing.Optional[int] = None
-    """语音的长度，单位为秒。"""
-
-    @pydantic.validator('path')
-    def validate_path(cls, path: typing.Optional[str]):
-        """修复 path 参数的行为，使之相对于 LangBot 的启动路径。"""
-        if path:
-            try:
-                return str(Path(path).resolve(strict=True))
-            except FileNotFoundError:
-                raise ValueError(f'无效路径：{path}')
-        else:
-            return path
-
-    def __str__(self):
-        return '[语音]'
-
-    async def download(
-        self,
-        filename: typing.Union[str, Path, None] = None,
-        directory: typing.Union[str, Path, None] = None,
-    ):
-        """下载语音到本地。
-
-        Args:
-            filename: 下载到本地的文件路径。与 `directory` 二选一。
-            directory: 下载到本地的文件夹路径。与 `filename` 二选一。
-        """
-        if not self.url:
-            logger.warning(f'语音 `{self.voice_id}` 无 url 参数，下载失败。')
-            return
-
-        import httpx
-
-        async with httpx.AsyncClient() as client:
-            response = await client.get(self.url)
-            response.raise_for_status()
-            content = response.content
-
-            if filename:
-                path = Path(filename)
-                path.parent.mkdir(parents=True, exist_ok=True)
-            elif directory:
-                path = Path(directory)
-                path.mkdir(parents=True, exist_ok=True)
-                path = path / f'{self.voice_id}.silk'
-            else:
-                raise ValueError('请指定文件路径或文件夹路径！')
-
-            import aiofiles
-
-            async with aiofiles.open(path, 'wb') as f:
-                await f.write(content)
-
-    @classmethod
-    async def from_local(
-        cls,
-        filename: typing.Union[str, Path, None] = None,
-        content: typing.Optional[bytes] = None,
-    ) -> 'Voice':
-        """从本地文件路径加载语音，以 base64 的形式传递。
-
-        Args:
-            filename: 从本地文件路径加载语音，与 `content` 二选一。
-            content: 从本地文件内容加载语音，与 `filename` 二选一。
-        """
-        if content:
-            pass
-        if filename:
-            path = Path(filename)
-            import aiofiles
-
-            async with aiofiles.open(path, 'rb') as f:
-                content = await f.read()
-        else:
-            raise ValueError('请指定语音路径或语音内容！')
-        import base64
-
-        img = cls(base64=base64.b64encode(content).decode())
-        return img
-
-
-class ForwardMessageNode(pydantic.BaseModel):
-    """合并转发中的一条消息。"""
-
-    sender_id: typing.Optional[typing.Union[int, str]] = None
-    """发送人ID。"""
-    sender_name: typing.Optional[str] = None
-    """显示名称。"""
-    message_chain: typing.Optional[MessageChain] = None
-    """消息内容。"""
-    message_id: typing.Optional[int] = None
-    """消息的 message_id。"""
-    time: typing.Optional[datetime] = None
-    """发送时间。"""
-
-    @pydantic.validator('message_chain', check_fields=False)
-    def _validate_message_chain(cls, value: typing.Union[MessageChain, list]):
-        if isinstance(value, list):
-            return MessageChain.parse_obj(value)
-        return value
-
-    @classmethod
-    def create(
-        cls,
-        sender: typing.Union[platform_entities.Friend, platform_entities.GroupMember],
-        message: MessageChain,
-    ) -> 'ForwardMessageNode':
-        """从消息链生成转发消息。
-
-        Args:
-            sender: 发送人。
-            message: 消息内容。
-
-        Returns:
-            ForwardMessageNode: 生成的一条消息。
-        """
-        return ForwardMessageNode(sender_id=sender.id, sender_name=sender.get_name(), message_chain=message)
-
-
-class ForwardMessageDiaplay(pydantic.BaseModel):
-    title: str = '群聊的聊天记录'
-    brief: str = '[聊天记录]'
-    source: str = '聊天记录'
-    preview: typing.List[str] = []
-    summary: str = '查看x条转发消息'
-
-
-class Forward(MessageComponent):
-    """合并转发。"""
-
-    type: str = 'Forward'
-    """消息组件类型。"""
-    display: ForwardMessageDiaplay
-    """显示信息"""
-    node_list: typing.List[ForwardMessageNode]
-    """转发消息节点列表。"""
-
-    def __init__(self, *args, **kwargs):
-        if len(args) == 1:
-            self.node_list = args[0]
-            super().__init__(**kwargs)
-        super().__init__(*args, **kwargs)
-
-    def __str__(self):
-        return '[聊天记录]'
-
-
-class File(MessageComponent):
-    """文件。"""
-
-    type: str = 'File'
-    """消息组件类型。"""
-    id: str = ''
-    """文件识别 ID。"""
-    name: str
-    """文件名称。"""
-    size: int = 0
-    """文件大小。"""
-    url: str
-    """文件路径"""
-
-    def __str__(self):
-        return f'[文件]{self.name}'
-
-
-class Face(MessageComponent):
-    """系统表情
-    此处将超级表情骰子/划拳，一同归类于face
-    当face_type为rps(划拳)时 face_id 对应的是手势
-    当face_type为dice(骰子)时 face_id 对应的是点数
-    """
-
-    type: str = 'Face'
-    """表情类型"""
-    face_type: str = 'face'
-    """表情id"""
-    face_id: int = 0
-    """表情名"""
-    face_name: str = ''
-
-    def __str__(self):
-        if self.face_type == 'face':
-            return f'[表情]{self.face_name}'
-        elif self.face_type == 'dice':
-            return f'[表情]{self.face_id}点的{self.face_name}'
-        elif self.face_type == 'rps':
-            return f'[表情]{self.face_name}({self.rps_data(self.face_id)})'
-
-    def rps_data(self, face_id):
-        rps_dict = {
-            1: '布',
-            2: '剪刀',
-            3: '石头',
-        }
-        return rps_dict[face_id]
-
-
-# ================ 个人微信专用组件 ================
-
-
-class WeChatMiniPrograms(MessageComponent):
-    """小程序。个人微信专用组件。"""
-
-    type: str = 'WeChatMiniPrograms'
-    """小程序id"""
-    mini_app_id: str
-    """小程序归属用户id"""
-    user_name: str
-    """小程序名称"""
-    display_name: typing.Optional[str] = ''
-    """打开地址"""
-    page_path: typing.Optional[str] = ''
-    """小程序标题"""
-    title: typing.Optional[str] = ''
-    """首页图片"""
-    image_url: typing.Optional[str] = ''
-
-
-class WeChatForwardMiniPrograms(MessageComponent):
-    """转发小程序。个人微信专用组件。"""
-
-    type: str = 'WeChatForwardMiniPrograms'
-    """xml数据"""
-    xml_data: str
-    """首页图片"""
-    image_url: typing.Optional[str] = None
-
-    def __str__(self):
-        return self.xml_data
-
-
-class WeChatEmoji(MessageComponent):
-    """emoji表情。个人微信专用组件。"""
-
-    type: str = 'WeChatEmoji'
-    """emojimd5"""
-    emoji_md5: str
-    """emoji大小"""
-    emoji_size: int
-
-
-class WeChatLink(MessageComponent):
-    """发送链接。个人微信专用组件。"""
-
-    type: str = 'WeChatLink'
-    """标题"""
-    link_title: str = ''
-    """链接描述"""
-    link_desc: str = ''
-    """链接地址"""
-    link_url: str = ''
-    """链接略缩图"""
-    link_thumb_url: str = ''
-
-
-class WeChatForwardLink(MessageComponent):
-    """转发链接。个人微信专用组件。"""
-
-    type: str = 'WeChatForwardLink'
-    """xml数据"""
-    xml_data: str
-
-    def __str__(self):
-        return self.xml_data
-
-
-class WeChatForwardImage(MessageComponent):
-    """转发图片。个人微信专用组件。"""
-
-    type: str = 'WeChatForwardImage'
-    """xml数据"""
-    xml_data: str
-
-    def __str__(self):
-        return self.xml_data
-
-
-class WeChatForwardFile(MessageComponent):
-    """转发文件。个人微信专用组件。"""
-
-    type: str = 'WeChatForwardFile'
-    """xml数据"""
-    xml_data: str
-
-    def __str__(self):
-        return self.xml_data
-
-
-class WeChatAppMsg(MessageComponent):
-    """通用appmsg发送。个人微信专用组件。"""
-
-    type: str = 'WeChatAppMsg'
-    """xml数据"""
-    app_msg: str
-
-    def __str__(self):
-        return self.app_msg
-
-
-class WeChatForwardQuote(MessageComponent):
-    """转发引用消息。个人微信专用组件。"""
-
-    type: str = 'WeChatForwardQuote'
-    """xml数据"""
-    app_msg: str
-
-    def __str__(self):
-        return self.app_msg
-
-
-class WeChatFile(MessageComponent):
-    """文件。"""
-
-    type: str = 'File'
-    """消息组件类型。"""
-    file_id: str = ''
-    """文件识别 ID。"""
-    file_name: str = ''
-    """文件名称。"""
-    file_size: int = 0
-    """文件大小。"""
-    file_path: str = ''
-    """文件地址"""
-    file_base64: str = ''
-    """base64"""
-
-    def __str__(self):
-        return f'[文件]{self.file_name}'

pkg/plugin/context.py

@@ -1,388 +0,0 @@
-from __future__ import annotations
-
-import typing
-import abc
-import pydantic.v1 as pydantic
-import enum
-
-from . import events
-from ..provider.tools import entities as tools_entities
-from ..core import app
-from ..discover import engine as discover_engine
-from ..platform.types import message as platform_message
-from ..platform import adapter as platform_adapter
-
-
-def register(
-    name: str, description: str, version: str, author: str
-) -> typing.Callable[[typing.Type[BasePlugin]], typing.Type[BasePlugin]]:
-    """注册插件类
-
-    使用示例：
-
-    @register(
-        name="插件名称",
-        description="插件描述",
-        version="插件版本",
-        author="插件作者"
-    )
-    class MyPlugin(BasePlugin):
-        pass
-    """
-    pass
-
-
-def handler(
-    event: typing.Type[events.BaseEventModel],
-) -> typing.Callable[[typing.Callable], typing.Callable]:
-    """注册事件监听器
-
-    使用示例：
-
-    class MyPlugin(BasePlugin):
-
-        @handler(NormalMessageResponded)
-        async def on_normal_message_responded(self, ctx: EventContext):
-            pass
-    """
-    pass
-
-
-def llm_func(
-    name: str = None,
-) -> typing.Callable:
-    """注册内容函数
-
-    使用示例：
-
-    class MyPlugin(BasePlugin):
-
-        @llm_func("access_the_web_page")
-        async def _(self, query, url: str, brief_len: int):
-            \"""Call this function to search about the question before you answer any questions.
-            - Do not search through google.com at any time.
-            - If you need to search somthing, visit https://www.sogou.com/web?query=<something>.
-            - If user ask you to open a url (start with http:// or https://), visit it directly.
-            - Summary the plain content result by yourself, DO NOT directly output anything in the result you got.
-
-            Args:
-                url(str): url to visit
-                brief_len(int): max length of the plain text content, recommend 1024-4096, prefer 4096
-
-            Returns:
-                str: plain text content of the web page or error message(starts with 'error:')
-            \"""
-    """
-    pass
-
-
-class BasePlugin(metaclass=abc.ABCMeta):
-    """插件基类"""
-
-    host: APIHost
-    """API宿主"""
-
-    ap: app.Application
-    """应用程序对象"""
-
-    config: dict
-    """插件配置"""
-
-    def __init__(self, host: APIHost):
-        """初始化阶段被调用"""
-        self.host = host
-        self.config = {}
-
-    async def initialize(self):
-        """初始化阶段被调用"""
-        pass
-
-    async def destroy(self):
-        """释放/禁用插件时被调用"""
-        pass
-
-    def __del__(self):
-        """释放/禁用插件时被调用"""
-        pass
-
-
-class APIHost:
-    """LangBot API 宿主"""
-
-    ap: app.Application
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def initialize(self):
-        pass
-
-    # ========== 插件可调用的 API（主程序API） ==========
-
-    def get_platform_adapters(self) -> list[platform_adapter.MessagePlatformAdapter]:
-        """获取已启用的消息平台适配器列表
-
-        Returns:
-            list[platform.adapter.MessageSourceAdapter]: 已启用的消息平台适配器列表
-        """
-        return self.ap.platform_mgr.get_running_adapters()
-
-    async def send_active_message(
-        self,
-        adapter: platform_adapter.MessagePlatformAdapter,
-        target_type: str,
-        target_id: str,
-        message: platform_message.MessageChain,
-    ):
-        """发送主动消息
-
-        Args:
-            adapter (platform.adapter.MessageSourceAdapter): 消息平台适配器对象，调用 host.get_platform_adapters() 获取并取用其中某个
-            target_type (str): 目标类型，`person`或`group`
-            target_id (str): 目标ID
-            message (platform.types.MessageChain): 消息链
-        """
-        await adapter.send_message(
-            target_type=target_type,
-            target_id=target_id,
-            message=message,
-        )
-
-    def require_ver(
-        self,
-        ge: str,
-        le: str = 'v999.999.999',
-    ) -> bool:
-        """插件版本要求装饰器
-
-        Args:
-            ge (str): 最低版本要求
-            le (str, optional): 最高版本要求
-
-        Returns:
-            bool: 是否满足要求, False时为无法获取版本号，True时为满足要求，报错为不满足要求
-        """
-        langbot_version = ''
-
-        try:
-            langbot_version = self.ap.ver_mgr.get_current_version()  # 从updater模块获取版本号
-        except Exception:
-            return False
-
-        if self.ap.ver_mgr.compare_version_str(langbot_version, ge) < 0 or (
-            self.ap.ver_mgr.compare_version_str(langbot_version, le) > 0
-        ):
-            raise Exception(
-                'LangBot 版本不满足要求，某些功能（可能是由插件提供的）无法正常使用。（要求版本：{}-{}，但当前版本：{}）'.format(
-                    ge, le, langbot_version
-                )
-            )
-
-        return True
-
-
-class EventContext:
-    """事件上下文, 保存此次事件运行的信息"""
-
-    eid = 0
-    """事件编号"""
-
-    host: APIHost = None
-    """API宿主"""
-
-    event: events.BaseEventModel = None
-    """此次事件的对象，具体类型为handler注册时指定监听的类型，可查看events.py中的定义"""
-
-    __prevent_default__ = False
-    """是否阻止默认行为"""
-
-    __prevent_postorder__ = False
-    """是否阻止后续插件的执行"""
-
-    __return_value__ = {}
-    """ 返回值 
-    示例:
-    {
-        "example": [
-            'value1',
-            'value2',
-            3,
-            4,
-            {
-                'key1': 'value1',
-            },
-            ['value1', 'value2']
-        ]
-    }
-    """
-
-    # ========== 插件可调用的 API ==========
-
-    def add_return(self, key: str, ret):
-        """添加返回值"""
-        if key not in self.__return_value__:
-            self.__return_value__[key] = []
-        self.__return_value__[key].append(ret)
-
-    async def reply(self, message_chain: platform_message.MessageChain):
-        """回复此次消息请求
-
-        Args:
-            message_chain (platform.types.MessageChain): 源平台的消息链，若用户使用的不是源平台适配器，程序也能自动转换为目标平台消息链
-        """
-        # TODO 添加 at_sender 和 quote_origin 参数
-        await self.event.query.adapter.reply_message(
-            message_source=self.event.query.message_event, message=message_chain
-        )
-
-    async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        """主动发送消息
-
-        Args:
-            target_type (str): 目标类型，`person`或`group`
-            target_id (str): 目标ID
-            message (platform.types.MessageChain): 源平台的消息链，若用户使用的不是源平台适配器，程序也能自动转换为目标平台消息链
-        """
-        await self.event.query.adapter.send_message(target_type=target_type, target_id=target_id, message=message)
-
-    def prevent_postorder(self):
-        """阻止后续插件执行"""
-        self.__prevent_postorder__ = True
-
-    def prevent_default(self):
-        """阻止默认行为"""
-        self.__prevent_default__ = True
-
-    # ========== 以下是内部保留方法，插件不应调用 ==========
-
-    def get_return(self, key: str) -> list:
-        """获取key的所有返回值"""
-        if key in self.__return_value__:
-            return self.__return_value__[key]
-        return None
-
-    def get_return_value(self, key: str):
-        """获取key的首个返回值"""
-        if key in self.__return_value__:
-            return self.__return_value__[key][0]
-        return None
-
-    def is_prevented_default(self):
-        """是否阻止默认行为"""
-        return self.__prevent_default__
-
-    def is_prevented_postorder(self):
-        """是否阻止后序插件执行"""
-        return self.__prevent_postorder__
-
-    def __init__(self, host: APIHost, event: events.BaseEventModel):
-        self.eid = EventContext.eid
-        self.host = host
-        self.event = event
-        self.__prevent_default__ = False
-        self.__prevent_postorder__ = False
-        self.__return_value__ = {}
-        EventContext.eid += 1
-
-
-class RuntimeContainerStatus(enum.Enum):
-    """插件容器状态"""
-
-    MOUNTED = 'mounted'
-    """已加载进内存，所有位于运行时记录中的 RuntimeContainer 至少是这个状态"""
-
-    INITIALIZED = 'initialized'
-    """已初始化"""
-
-
-class RuntimeContainer(pydantic.BaseModel):
-    """运行时的插件容器
-
-    运行期间存储单个插件的信息
-    """
-
-    plugin_name: str
-    """插件名称"""
-
-    plugin_label: discover_engine.I18nString
-    """插件标签"""
-
-    plugin_description: discover_engine.I18nString
-    """插件描述"""
-
-    plugin_version: str
-    """插件版本"""
-
-    plugin_author: str
-    """插件作者"""
-
-    plugin_repository: str
-    """插件源码地址"""
-
-    main_file: str
-    """插件主文件路径"""
-
-    pkg_path: str
-    """插件包路径"""
-
-    plugin_class: typing.Type[BasePlugin] = None
-    """插件类"""
-
-    enabled: typing.Optional[bool] = True
-    """是否启用"""
-
-    priority: typing.Optional[int] = 0
-    """优先级"""
-
-    config_schema: typing.Optional[list[dict]] = []
-    """插件配置模板"""
-
-    plugin_config: typing.Optional[dict] = {}
-    """插件配置"""
-
-    plugin_inst: typing.Optional[BasePlugin] = None
-    """插件实例"""
-
-    event_handlers: dict[
-        typing.Type[events.BaseEventModel],
-        typing.Callable[[BasePlugin, EventContext], typing.Awaitable[None]],
-    ] = {}
-    """事件处理器"""
-
-    tools: list[tools_entities.LLMFunction] = []
-    """内容函数"""
-
-    status: RuntimeContainerStatus = RuntimeContainerStatus.MOUNTED
-    """插件状态"""
-
-    class Config:
-        arbitrary_types_allowed = True
-
-    def model_dump(self, *args, **kwargs):
-        return {
-            'name': self.plugin_name,
-            'label': self.plugin_label.to_dict(),
-            'description': self.plugin_description.to_dict(),
-            'version': self.plugin_version,
-            'author': self.plugin_author,
-            'repository': self.plugin_repository,
-            'main_file': self.main_file,
-            'pkg_path': self.pkg_path,
-            'enabled': self.enabled,
-            'priority': self.priority,
-            'config_schema': self.config_schema,
-            'event_handlers': {
-                event_name.__name__: handler.__name__ for event_name, handler in self.event_handlers.items()
-            },
-            'tools': [
-                {
-                    'name': function.name,
-                    'human_desc': function.human_desc,
-                    'description': function.description,
-                    'parameters': function.parameters,
-                    'func': function.func.__name__,
-                }
-                for function in self.tools
-            ],
-            'status': self.status.value,
-        }

pkg/plugin/errors.py

@@ -1,21 +0,0 @@
-from __future__ import annotations
-
-
-class PluginSystemError(Exception):
-    message: str
-
-    def __init__(self, message: str):
-        self.message = message
-
-    def __str__(self):
-        return self.message
-
-
-class PluginNotFoundError(PluginSystemError):
-    def __init__(self, message: str):
-        super().__init__(f'未找到插件: {message}')
-
-
-class PluginInstallerError(PluginSystemError):
-    def __init__(self, message: str):
-        super().__init__(f'安装器操作错误: {message}')

pkg/plugin/events.py

@@ -1,170 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-import pydantic.v1 as pydantic
-
-from ..core import entities as core_entities
-from ..provider import entities as llm_entities
-from ..platform.types import message as platform_message
-
-
-class BaseEventModel(pydantic.BaseModel):
-    """事件模型基类"""
-
-    query: typing.Union[core_entities.Query, None]
-    """此次请求的query对象，非请求过程的事件时为None"""
-
-    class Config:
-        arbitrary_types_allowed = True
-
-
-class PersonMessageReceived(BaseEventModel):
-    """收到任何私聊消息时"""
-
-    launcher_type: str
-    """发起对象类型(group/person)"""
-
-    launcher_id: typing.Union[int, str]
-    """发起对象ID(群号/QQ号)"""
-
-    sender_id: typing.Union[int, str]
-    """发送者ID(QQ号)"""
-
-    message_chain: platform_message.MessageChain
-
-
-class GroupMessageReceived(BaseEventModel):
-    """收到任何群聊消息时"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    message_chain: platform_message.MessageChain
-
-
-class PersonNormalMessageReceived(BaseEventModel):
-    """判断为应该处理的私聊普通消息时触发"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    text_message: str
-
-    alter: typing.Optional[str] = None
-    """修改后的消息文本"""
-
-    reply: typing.Optional[list] = None
-    """回复消息组件列表"""
-
-
-class PersonCommandSent(BaseEventModel):
-    """判断为应该处理的私聊命令时触发"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    command: str
-
-    params: list[str]
-
-    text_message: str
-
-    is_admin: bool
-
-    alter: typing.Optional[str] = None
-    """修改后的完整命令文本"""
-
-    reply: typing.Optional[list] = None
-    """回复消息组件列表"""
-
-
-class GroupNormalMessageReceived(BaseEventModel):
-    """判断为应该处理的群聊普通消息时触发"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    text_message: str
-
-    alter: typing.Optional[str] = None
-    """修改后的消息文本"""
-
-    reply: typing.Optional[list] = None
-    """回复消息组件列表"""
-
-
-class GroupCommandSent(BaseEventModel):
-    """判断为应该处理的群聊命令时触发"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    command: str
-
-    params: list[str]
-
-    text_message: str
-
-    is_admin: bool
-
-    alter: typing.Optional[str] = None
-    """修改后的完整命令文本"""
-
-    reply: typing.Optional[list] = None
-    """回复消息组件列表"""
-
-
-class NormalMessageResponded(BaseEventModel):
-    """回复普通消息时触发"""
-
-    launcher_type: str
-
-    launcher_id: typing.Union[int, str]
-
-    sender_id: typing.Union[int, str]
-
-    session: core_entities.Session
-    """会话对象"""
-
-    prefix: str
-    """回复消息的前缀"""
-
-    response_text: str
-    """回复消息的文本"""
-
-    finish_reason: str
-    """响应结束原因"""
-
-    funcs_called: list[str]
-    """调用的函数列表"""
-
-    reply: typing.Optional[list] = None
-    """回复消息组件列表"""
-
-
-class PromptPreProcessing(BaseEventModel):
-    """会话中的Prompt预处理时触发"""
-
-    session_name: str
-
-    default_prompt: list[llm_entities.Message]
-    """此对话的情景预设，可修改"""
-
-    prompt: list[llm_entities.Message]
-    """此对话现有消息记录，可修改"""

pkg/plugin/host.py

@@ -1,9 +0,0 @@
-# 此模块已过时
-# 请从 pkg.plugin.context 引入 BasePlugin, EventContext 和 APIHost
-# 最早将于 v3.4 移除此模块
-
-from .events import *
-
-
-def emit(*args, **kwargs):
-    print('插件调用了已弃用的函数 pkg.plugin.host.emit()')

pkg/plugin/installer.py

@@ -1,45 +0,0 @@
-from __future__ import annotations
-
-import abc
-
-from ..core import app, taskmgr
-
-
-class PluginInstaller(metaclass=abc.ABCMeta):
-    """插件安装器抽象类"""
-
-    ap: app.Application
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def initialize(self):
-        pass
-
-    @abc.abstractmethod
-    async def install_plugin(
-        self,
-        plugin_source: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """安装插件"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    async def uninstall_plugin(
-        self,
-        plugin_name: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """卸载插件"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    async def update_plugin(
-        self,
-        plugin_name: str,
-        plugin_source: str = None,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """更新插件"""
-        raise NotImplementedError

pkg/plugin/installers/github.py

@@ -1,143 +0,0 @@
-from __future__ import annotations
-
-import re
-import os
-import zipfile
-import ssl
-import certifi
-
-import aiohttp
-import aiofiles
-import aiofiles.os as aiofiles_os
-import aioshutil
-
-from .. import installer, errors
-from ...utils import pkgmgr
-from ...core import taskmgr
-
-
-class GitHubRepoInstaller(installer.PluginInstaller):
-    """GitHub仓库插件安装器"""
-
-    def get_github_plugin_repo_label(self, repo_url: str) -> list[str]:
-        """获取username, repo"""
-        repo = re.findall(
-            r'(?:https?://github\.com/|git@github\.com:)([^/]+/[^/]+?)(?:\.git|/|$)',
-            repo_url,
-        )
-        if len(repo) > 0:
-            return repo[0].split('/')
-        else:
-            return None
-
-    async def download_plugin_source_code(
-        self,
-        repo_url: str,
-        target_path: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ) -> str:
-        """下载插件源码（全异步）"""
-        repo = self.get_github_plugin_repo_label(repo_url)
-        if repo is None:
-            raise errors.PluginInstallerError('仅支持GitHub仓库地址')
-
-        target_path += repo[1]
-        self.ap.logger.debug('正在下载源码...')
-        task_context.trace('下载源码...', 'download-plugin-source-code')
-
-        zipball_url = f'https://api.github.com/repos/{"/".join(repo)}/zipball/HEAD'
-        zip_resp: bytes = None
-
-        # 创建自定义SSL上下文，使用certifi提供的根证书
-        ssl_context = ssl.create_default_context(cafile=certifi.where())
-
-        async with aiohttp.ClientSession(trust_env=True) as session:
-            async with session.get(
-                url=zipball_url,
-                timeout=aiohttp.ClientTimeout(total=300),
-                ssl=ssl_context,  # 使用自定义SSL上下文来验证证书
-            ) as resp:
-                if resp.status != 200:
-                    raise errors.PluginInstallerError(f'下载源码失败: {await resp.text()}')
-                zip_resp = await resp.read()
-
-        if await aiofiles_os.path.exists('temp/' + target_path):
-            await aioshutil.rmtree('temp/' + target_path)
-
-        if await aiofiles_os.path.exists(target_path):
-            await aioshutil.rmtree(target_path)
-
-        await aiofiles_os.makedirs('temp/' + target_path)
-
-        async with aiofiles.open('temp/' + target_path + '/source.zip', 'wb') as f:
-            await f.write(zip_resp)
-
-        self.ap.logger.debug('解压中...')
-        task_context.trace('解压中...', 'unzip-plugin-source-code')
-
-        with zipfile.ZipFile('temp/' + target_path + '/source.zip', 'r') as zip_ref:
-            zip_ref.extractall('temp/' + target_path)
-        await aiofiles_os.remove('temp/' + target_path + '/source.zip')
-
-        import glob
-
-        unzip_dir = glob.glob('temp/' + target_path + '/*')[0]
-        await aioshutil.copytree(unzip_dir, target_path + '/')
-        await aioshutil.rmtree(unzip_dir)
-
-        self.ap.logger.debug('源码下载完成。')
-        return repo[1]
-
-    async def install_requirements(self, path: str):
-        if os.path.exists(path + '/requirements.txt'):
-            pkgmgr.install_requirements(path + '/requirements.txt')
-
-    async def install_plugin(
-        self,
-        plugin_source: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """安装插件"""
-        task_context.trace('下载插件源码...', 'install-plugin')
-        repo_label = await self.download_plugin_source_code(plugin_source, 'plugins/', task_context)
-        task_context.trace('安装插件依赖...', 'install-plugin')
-        await self.install_requirements('plugins/' + repo_label)
-        task_context.trace('完成.', 'install-plugin')
-
-        # Caution: in the v4.0, plugin without manifest will not be able to be updated
-        # await self.ap.plugin_mgr.setting.record_installed_plugin_source(
-        #     "plugins/" + repo_label + '/', plugin_source
-        # )
-
-    async def uninstall_plugin(
-        self,
-        plugin_name: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """卸载插件"""
-        plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-        if plugin_container is None:
-            raise errors.PluginInstallerError('插件不存在或未成功加载')
-        else:
-            task_context.trace('删除插件目录...', 'uninstall-plugin')
-            await aioshutil.rmtree(plugin_container.pkg_path)
-            task_context.trace('完成, 重新加载以生效.', 'uninstall-plugin')
-
-    async def update_plugin(
-        self,
-        plugin_name: str,
-        plugin_source: str = None,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """更新插件"""
-        task_context.trace('更新插件...', 'update-plugin')
-        plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-        if plugin_container is None:
-            raise errors.PluginInstallerError('插件不存在或未成功加载')
-        else:
-            if plugin_container.plugin_repository:
-                plugin_source = plugin_container.plugin_repository
-                task_context.trace('转交安装任务.', 'update-plugin')
-                await self.install_plugin(plugin_source, task_context)
-            else:
-                raise errors.PluginInstallerError('插件无源码信息，无法更新')

pkg/plugin/loader.py

@@ -1,25 +0,0 @@
-from __future__ import annotations
-
-import abc
-
-from ..core import app
-from . import context
-
-
-class PluginLoader(metaclass=abc.ABCMeta):
-    """插件加载器抽象类"""
-
-    ap: app.Application
-
-    plugins: list[context.RuntimeContainer]
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.plugins = []
-
-    async def initialize(self):
-        pass
-
-    @abc.abstractmethod
-    async def load_plugins(self):
-        pass

pkg/plugin/loaders/classic.py

@@ -1,198 +0,0 @@
-from __future__ import annotations
-
-import typing
-import pkgutil
-import importlib
-import traceback
-
-from .. import loader, events, context, models
-from ...core import entities as core_entities
-from ...provider.tools import entities as tools_entities
-from ...utils import funcschema
-from ...discover import engine as discover_engine
-
-
-class PluginLoader(loader.PluginLoader):
-    """加载 plugins/ 目录下的插件"""
-
-    _current_pkg_path = ''
-
-    _current_module_path = ''
-
-    _current_container: context.RuntimeContainer = None
-
-    plugins: list[context.RuntimeContainer] = []
-
-    def __init__(self, ap):
-        self.ap = ap
-        self.plugins = []
-        self._current_pkg_path = ''
-        self._current_module_path = ''
-        self._current_container = None
-
-    async def initialize(self):
-        """初始化"""
-
-    def register(
-        self, name: str, description: str, version: str, author: str
-    ) -> typing.Callable[[typing.Type[context.BasePlugin]], typing.Type[context.BasePlugin]]:
-        self.ap.logger.debug(f'注册插件 {name} {version} by {author}')
-        container = context.RuntimeContainer(
-            plugin_name=name,
-            plugin_label=discover_engine.I18nString(en_US=name, zh_Hans=name),
-            plugin_description=discover_engine.I18nString(en_US=description, zh_Hans=description),
-            plugin_version=version,
-            plugin_author=author,
-            plugin_repository='',
-            pkg_path=self._current_pkg_path,
-            main_file=self._current_module_path,
-            event_handlers={},
-            tools=[],
-        )
-
-        self._current_container = container
-
-        def wrapper(cls: context.BasePlugin) -> typing.Type[context.BasePlugin]:
-            container.plugin_class = cls
-            return cls
-
-        return wrapper
-
-    # 过时
-    # 最早将于 v3.4 版本移除
-    def on(self, event: typing.Type[events.BaseEventModel]) -> typing.Callable[[typing.Callable], typing.Callable]:
-        """注册过时的事件处理器"""
-        self.ap.logger.debug(f'注册事件处理器 {event.__name__}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            async def handler(plugin: context.BasePlugin, ctx: context.EventContext) -> None:
-                args = {
-                    'host': ctx.host,
-                    'event': ctx,
-                }
-
-                # 把 ctx.event 所有的属性都放到 args 里
-                # for k, v in ctx.event.dict().items():
-                #     args[k] = v
-                for attr_name in ctx.event.__dict__.keys():
-                    args[attr_name] = getattr(ctx.event, attr_name)
-
-                func(plugin, **args)
-
-            self._current_container.event_handlers[event] = handler
-
-            return func
-
-        return wrapper
-
-    # 过时
-    # 最早将于 v3.4 版本移除
-    def func(
-        self,
-        name: str = None,
-    ) -> typing.Callable:
-        """注册过时的内容函数"""
-        self.ap.logger.debug(f'注册内容函数 {name}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            function_schema = funcschema.get_func_schema(func)
-            function_name = self._current_container.plugin_name + '-' + (func.__name__ if name is None else name)
-
-            async def handler(plugin: context.BasePlugin, query: core_entities.Query, *args, **kwargs):
-                return func(*args, **kwargs)
-
-            llm_function = tools_entities.LLMFunction(
-                name=function_name,
-                human_desc='',
-                description=function_schema['description'],
-                parameters=function_schema['parameters'],
-                func=handler,
-            )
-
-            self._current_container.tools.append(llm_function)
-
-            return func
-
-        return wrapper
-
-    def handler(self, event: typing.Type[events.BaseEventModel]) -> typing.Callable[[typing.Callable], typing.Callable]:
-        """注册事件处理器"""
-        self.ap.logger.debug(f'注册事件处理器 {event.__name__}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            if (
-                self._current_container is None
-            ):  # None indicates this plugin is registered through manifest, so ignore it here
-                return func
-
-            self._current_container.event_handlers[event] = func
-
-            return func
-
-        return wrapper
-
-    def llm_func(
-        self,
-        name: str = None,
-    ) -> typing.Callable:
-        """注册内容函数"""
-        self.ap.logger.debug(f'注册内容函数 {name}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            if (
-                self._current_container is None
-            ):  # None indicates this plugin is registered through manifest, so ignore it here
-                return func
-
-            function_schema = funcschema.get_func_schema(func)
-            function_name = self._current_container.plugin_name + '-' + (func.__name__ if name is None else name)
-
-            llm_function = tools_entities.LLMFunction(
-                name=function_name,
-                human_desc='',
-                description=function_schema['description'],
-                parameters=function_schema['parameters'],
-                func=func,
-            )
-
-            self._current_container.tools.append(llm_function)
-
-            return func
-
-        return wrapper
-
-    async def _walk_plugin_path(self, module, prefix='', path_prefix=''):
-        """遍历插件路径"""
-        for item in pkgutil.iter_modules(module.__path__):
-            if item.ispkg:
-                await self._walk_plugin_path(
-                    __import__(module.__name__ + '.' + item.name, fromlist=['']),
-                    prefix + item.name + '.',
-                    path_prefix + item.name + '/',
-                )
-            else:
-                try:
-                    self._current_pkg_path = 'plugins/' + path_prefix
-                    self._current_module_path = 'plugins/' + path_prefix + item.name + '.py'
-
-                    self._current_container = None
-
-                    importlib.import_module(module.__name__ + '.' + item.name)
-
-                    if self._current_container is not None:
-                        self.plugins.append(self._current_container)
-                        self.ap.logger.debug(f'插件 {self._current_container} 已加载')
-                except Exception:
-                    self.ap.logger.error(f'加载插件模块 {prefix + item.name} 时发生错误')
-                    traceback.print_exc()
-
-    async def load_plugins(self):
-        """加载插件"""
-        setattr(models, 'register', self.register)
-        setattr(models, 'on', self.on)
-        setattr(models, 'func', self.func)
-
-        setattr(context, 'register', self.register)
-        setattr(context, 'handler', self.handler)
-        setattr(context, 'llm_func', self.llm_func)
-        await self._walk_plugin_path(__import__('plugins', fromlist=['']))

pkg/plugin/loaders/manifest.py

@@ -1,96 +0,0 @@
-from __future__ import annotations
-
-import typing
-import os
-import traceback
-
-from ...core import app
-from .. import context, events
-from .. import loader
-from ...utils import funcschema
-from ...provider.tools import entities as tools_entities
-
-
-class PluginManifestLoader(loader.PluginLoader):
-    """通过插件清单发现插件"""
-
-    _current_container: context.RuntimeContainer = None
-
-    def __init__(self, ap: app.Application):
-        super().__init__(ap)
-
-    def handler(self, event: typing.Type[events.BaseEventModel]) -> typing.Callable[[typing.Callable], typing.Callable]:
-        """注册事件处理器"""
-        self.ap.logger.debug(f'注册事件处理器 {event.__name__}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            self._current_container.event_handlers[event] = func
-
-            return func
-
-        return wrapper
-
-    def llm_func(
-        self,
-        name: str = None,
-    ) -> typing.Callable:
-        """注册内容函数"""
-        self.ap.logger.debug(f'注册内容函数 {name}')
-
-        def wrapper(func: typing.Callable) -> typing.Callable:
-            function_schema = funcschema.get_func_schema(func)
-            function_name = self._current_container.plugin_name + '-' + (func.__name__ if name is None else name)
-
-            llm_function = tools_entities.LLMFunction(
-                name=function_name,
-                human_desc='',
-                description=function_schema['description'],
-                parameters=function_schema['parameters'],
-                func=func,
-            )
-
-            self._current_container.tools.append(llm_function)
-
-            return func
-
-        return wrapper
-
-    async def load_plugins(self):
-        """加载插件"""
-        setattr(context, 'handler', self.handler)
-        setattr(context, 'llm_func', self.llm_func)
-
-        plugin_manifests = self.ap.discover.get_components_by_kind('Plugin')
-
-        for plugin_manifest in plugin_manifests:
-            try:
-                config_schema = plugin_manifest.spec['config'] if 'config' in plugin_manifest.spec else []
-
-                current_plugin_container = context.RuntimeContainer(
-                    plugin_name=plugin_manifest.metadata.name,
-                    plugin_label=plugin_manifest.metadata.label,
-                    plugin_description=plugin_manifest.metadata.description,
-                    plugin_version=plugin_manifest.metadata.version,
-                    plugin_author=plugin_manifest.metadata.author,
-                    plugin_repository=plugin_manifest.metadata.repository,
-                    main_file=os.path.join(plugin_manifest.rel_dir, plugin_manifest.execution.python.path),
-                    pkg_path=plugin_manifest.rel_dir,
-                    config_schema=config_schema,
-                    event_handlers={},
-                    tools=[],
-                )
-
-                self._current_container = current_plugin_container
-
-                # extract the plugin class
-                # this step will load the plugin module,
-                # so the event handlers and tools will be registered
-                plugin_class = plugin_manifest.get_python_component_class()
-                current_plugin_container.plugin_class = plugin_class
-
-                # TODO load component extensions
-
-                self.plugins.append(current_plugin_container)
-            except Exception:
-                self.ap.logger.error(f'加载插件 {plugin_manifest.metadata.name} 时发生错误')
-                traceback.print_exc()

pkg/plugin/manager.py

@@ -1,308 +0,0 @@
-from __future__ import annotations
-
-import traceback
-
-import sqlalchemy
-
-from ..core import app, taskmgr
-from . import context, loader, events, installer, models
-from .loaders import classic, manifest
-from .installers import github
-from ..entity.persistence import plugin as persistence_plugin
-
-
-class PluginManager:
-    """插件管理器"""
-
-    ap: app.Application
-
-    loaders: list[loader.PluginLoader]
-
-    installer: installer.PluginInstaller
-
-    api_host: context.APIHost
-
-    plugin_containers: list[context.RuntimeContainer]
-
-    def plugins(
-        self,
-        enabled: bool = None,
-        status: context.RuntimeContainerStatus = None,
-    ) -> list[context.RuntimeContainer]:
-        """获取插件列表"""
-        plugins = self.plugin_containers
-
-        if enabled is not None:
-            plugins = [plugin for plugin in plugins if plugin.enabled == enabled]
-
-        if status is not None:
-            plugins = [plugin for plugin in plugins if plugin.status == status]
-
-        return plugins
-
-    def get_plugin(
-        self,
-        author: str,
-        plugin_name: str,
-    ) -> context.RuntimeContainer:
-        """通过作者和插件名获取插件"""
-        for plugin in self.plugins():
-            if plugin.plugin_author == author and plugin.plugin_name == plugin_name:
-                return plugin
-        return None
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.loaders = [
-            classic.PluginLoader(ap),
-            manifest.PluginManifestLoader(ap),
-        ]
-        self.installer = github.GitHubRepoInstaller(ap)
-        self.api_host = context.APIHost(ap)
-        self.plugin_containers = []
-
-    async def initialize(self):
-        for loader in self.loaders:
-            await loader.initialize()
-        await self.installer.initialize()
-        await self.api_host.initialize()
-
-        setattr(models, 'require_ver', self.api_host.require_ver)
-
-    async def load_plugins(self):
-        self.ap.logger.info('Loading all plugins...')
-
-        for loader in self.loaders:
-            await loader.load_plugins()
-            self.plugin_containers.extend(loader.plugins)
-
-        await self.load_plugin_settings(self.plugin_containers)
-
-        # 按优先级倒序
-        self.plugin_containers.sort(key=lambda x: x.priority, reverse=False)
-
-        self.ap.logger.debug(f'优先级排序后的插件列表 {self.plugin_containers}')
-
-    async def load_plugin_settings(self, plugin_containers: list[context.RuntimeContainer]):
-        for plugin_container in plugin_containers:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(persistence_plugin.PluginSetting)
-                .where(persistence_plugin.PluginSetting.plugin_author == plugin_container.plugin_author)
-                .where(persistence_plugin.PluginSetting.plugin_name == plugin_container.plugin_name)
-            )
-
-            setting = result.first()
-
-            if setting is None:
-                new_setting_data = {
-                    'plugin_author': plugin_container.plugin_author,
-                    'plugin_name': plugin_container.plugin_name,
-                    'enabled': plugin_container.enabled,
-                    'priority': plugin_container.priority,
-                    'config': plugin_container.plugin_config,
-                }
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.insert(persistence_plugin.PluginSetting).values(**new_setting_data)
-                )
-                continue
-            else:
-                plugin_container.enabled = setting.enabled
-                plugin_container.priority = setting.priority
-                plugin_container.plugin_config = setting.config
-
-    async def dump_plugin_container_setting(self, plugin_container: context.RuntimeContainer):
-        """保存单个插件容器的设置到数据库"""
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_plugin.PluginSetting)
-            .where(persistence_plugin.PluginSetting.plugin_author == plugin_container.plugin_author)
-            .where(persistence_plugin.PluginSetting.plugin_name == plugin_container.plugin_name)
-            .values(
-                enabled=plugin_container.enabled,
-                priority=plugin_container.priority,
-                config=plugin_container.plugin_config,
-            )
-        )
-
-    async def initialize_plugin(self, plugin: context.RuntimeContainer):
-        self.ap.logger.debug(f'初始化插件 {plugin.plugin_name}')
-        plugin.plugin_inst = plugin.plugin_class(self.api_host)
-        plugin.plugin_inst.config = plugin.plugin_config
-        plugin.plugin_inst.ap = self.ap
-        plugin.plugin_inst.host = self.api_host
-        await plugin.plugin_inst.initialize()
-        plugin.status = context.RuntimeContainerStatus.INITIALIZED
-
-    async def initialize_plugins(self):
-        for plugin in self.plugins():
-            if not plugin.enabled:
-                self.ap.logger.debug(f'插件 {plugin.plugin_name} 未启用，跳过初始化')
-                continue
-            try:
-                await self.initialize_plugin(plugin)
-            except Exception as e:
-                self.ap.logger.error(f'插件 {plugin.plugin_name} 初始化失败: {e}')
-                self.ap.logger.exception(e)
-                continue
-
-    async def destroy_plugin(self, plugin: context.RuntimeContainer):
-        if plugin.status != context.RuntimeContainerStatus.INITIALIZED:
-            return
-
-        self.ap.logger.debug(f'释放插件 {plugin.plugin_name}')
-        plugin.plugin_inst.__del__()
-        await plugin.plugin_inst.destroy()
-        plugin.plugin_inst = None
-        plugin.status = context.RuntimeContainerStatus.MOUNTED
-
-    async def destroy_plugins(self):
-        for plugin in self.plugins():
-            if plugin.status != context.RuntimeContainerStatus.INITIALIZED:
-                self.ap.logger.debug(f'插件 {plugin.plugin_name} 未初始化，跳过释放')
-                continue
-
-            try:
-                await self.destroy_plugin(plugin)
-            except Exception as e:
-                self.ap.logger.error(f'插件 {plugin.plugin_name} 释放失败: {e}')
-                self.ap.logger.exception(e)
-                continue
-
-    async def install_plugin(
-        self,
-        plugin_source: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """安装插件"""
-        await self.installer.install_plugin(plugin_source, task_context)
-
-        # TODO statistics
-
-        task_context.trace('重载插件..', 'reload-plugin')
-        await self.ap.reload(scope='plugin')
-
-    async def uninstall_plugin(
-        self,
-        plugin_name: str,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """卸载插件"""
-
-        plugin_container = self.get_plugin_by_name(plugin_name)
-
-        if plugin_container is None:
-            raise ValueError(f'插件 {plugin_name} 不存在')
-
-        await self.destroy_plugin(plugin_container)
-        await self.installer.uninstall_plugin(plugin_name, task_context)
-
-        # TODO statistics
-
-        task_context.trace('重载插件..', 'reload-plugin')
-        await self.ap.reload(scope='plugin')
-
-    async def update_plugin(
-        self,
-        plugin_name: str,
-        plugin_source: str = None,
-        task_context: taskmgr.TaskContext = taskmgr.TaskContext.placeholder(),
-    ):
-        """更新插件"""
-        await self.installer.update_plugin(plugin_name, plugin_source, task_context)
-
-        # TODO statistics
-
-        task_context.trace('重载插件..', 'reload-plugin')
-        await self.ap.reload(scope='plugin')
-
-    def get_plugin_by_name(self, plugin_name: str) -> context.RuntimeContainer:
-        """通过插件名获取插件"""
-        for plugin in self.plugins():
-            if plugin.plugin_name == plugin_name:
-                return plugin
-        return None
-
-    async def emit_event(self, event: events.BaseEventModel) -> context.EventContext:
-        """触发事件"""
-
-        ctx = context.EventContext(host=self.api_host, event=event)
-
-        emitted_plugins: list[context.RuntimeContainer] = []
-
-        for plugin in self.plugins(enabled=True, status=context.RuntimeContainerStatus.INITIALIZED):
-            if event.__class__ in plugin.event_handlers:
-                self.ap.logger.debug(f'插件 {plugin.plugin_name} 处理事件 {event.__class__.__name__}')
-
-                is_prevented_default_before_call = ctx.is_prevented_default()
-
-                try:
-                    await plugin.event_handlers[event.__class__](plugin.plugin_inst, ctx)
-                except Exception as e:
-                    self.ap.logger.error(
-                        f'插件 {plugin.plugin_name} 处理事件 {event.__class__.__name__} 时发生错误: {e}'
-                    )
-                    self.ap.logger.debug(f'Traceback: {traceback.format_exc()}')
-
-                emitted_plugins.append(plugin)
-
-                if not is_prevented_default_before_call and ctx.is_prevented_default():
-                    self.ap.logger.debug(f'插件 {plugin.plugin_name} 阻止了默认行为执行')
-
-                if ctx.is_prevented_postorder():
-                    self.ap.logger.debug(f'插件 {plugin.plugin_name} 阻止了后序插件的执行')
-                    break
-
-        for key in ctx.__return_value__.keys():
-            if hasattr(ctx.event, key):
-                setattr(ctx.event, key, ctx.__return_value__[key][0])
-
-        self.ap.logger.debug(f'事件 {event.__class__.__name__}({ctx.eid}) 处理完成，返回值 {ctx.__return_value__}')
-
-        # TODO statistics
-
-        return ctx
-
-    async def update_plugin_switch(self, plugin_name: str, new_status: bool):
-        if self.get_plugin_by_name(plugin_name) is not None:
-            for plugin in self.plugins():
-                if plugin.plugin_name == plugin_name:
-                    if plugin.enabled == new_status:
-                        return False
-
-                    # 初始化/释放插件
-                    if new_status:
-                        await self.initialize_plugin(plugin)
-                    else:
-                        await self.destroy_plugin(plugin)
-
-                    plugin.enabled = new_status
-
-                    await self.dump_plugin_container_setting(plugin)
-
-                    break
-
-            return True
-        else:
-            return False
-
-    async def reorder_plugins(self, plugins: list[dict]):
-        for plugin in plugins:
-            plugin_name = plugin.get('name')
-            plugin_priority = plugin.get('priority')
-
-            for plugin in self.plugin_containers:
-                if plugin.plugin_name == plugin_name:
-                    plugin.priority = plugin_priority
-                    break
-
-        self.plugin_containers.sort(key=lambda x: x.priority, reverse=False)
-
-        for plugin in self.plugin_containers:
-            await self.dump_plugin_container_setting(plugin)
-
-    async def set_plugin_config(self, plugin_container: context.RuntimeContainer, new_config: dict):
-        plugin_container.plugin_config = new_config
-
-        plugin_container.plugin_inst.config = new_config
-
-        await self.dump_plugin_container_setting(plugin_container)

pkg/plugin/models.py

@@ -1,28 +0,0 @@
-# 此模块已过时，请引入 pkg.plugin.context 中的 register, handler 和 llm_func 来注册插件、事件处理函数和内容函数
-# 各个事件模型请从 pkg.plugin.events 引入
-# 最早将于 v3.4 移除此模块
-
-from __future__ import annotations
-
-import typing
-
-from .context import BasePlugin as Plugin
-from .events import *
-
-
-def register(
-    name: str, description: str, version: str, author
-) -> typing.Callable[[typing.Type[Plugin]], typing.Type[Plugin]]:
-    pass
-
-
-def on(
-    event: typing.Type[BaseEventModel],
-) -> typing.Callable[[typing.Callable], typing.Callable]:
-    pass
-
-
-def func(
-    name: str = None,
-) -> typing.Callable:
-    pass

pkg/provider/entities.py

@@ -1,224 +0,0 @@
-from __future__ import annotations
-
-import typing
-import pydantic.v1 as pydantic
-
-from pkg.provider import entities
-
-
-from ..platform.types import message as platform_message
-
-
-class FunctionCall(pydantic.BaseModel):
-    name: str
-
-    arguments: str
-
-
-class ToolCall(pydantic.BaseModel):
-    id: str
-
-    type: str
-
-    function: FunctionCall
-
-
-class ImageURLContentObject(pydantic.BaseModel):
-    url: str
-
-    def __str__(self):
-        return self.url[:128] + ('...' if len(self.url) > 128 else '')
-
-
-class ContentElement(pydantic.BaseModel):
-    type: str
-    """内容类型"""
-
-    text: typing.Optional[str] = None
-
-    image_url: typing.Optional[ImageURLContentObject] = None
-
-    image_base64: typing.Optional[str] = None
-
-    def __str__(self):
-        if self.type == 'text':
-            return self.text
-        elif self.type == 'image_url':
-            return f'[图片]({self.image_url})'
-        else:
-            return '未知内容'
-
-    @classmethod
-    def from_text(cls, text: str):
-        return cls(type='text', text=text)
-
-    @classmethod
-    def from_image_url(cls, image_url: str):
-        return cls(type='image_url', image_url=ImageURLContentObject(url=image_url))
-
-    @classmethod
-    def from_image_base64(cls, image_base64: str):
-        return cls(type='image_base64', image_base64=image_base64)
-
-
-class Message(pydantic.BaseModel):
-    """消息"""
-
-    role: str  # user, system, assistant, tool, command, plugin
-    """消息的角色"""
-
-    name: typing.Optional[str] = None
-    """名称，仅函数调用返回时设置"""
-
-    content: typing.Optional[list[ContentElement]] | typing.Optional[str] = None
-    """内容"""
-
-    tool_calls: typing.Optional[list[ToolCall]] = None
-    """工具调用"""
-
-    tool_call_id: typing.Optional[str] = None
-
-    def readable_str(self) -> str:
-        if self.content is not None:
-            return str(self.role) + ': ' + str(self.get_content_platform_message_chain())
-        elif self.tool_calls is not None:
-            return f'调用工具: {self.tool_calls[0].id}'
-        else:
-            return '未知消息'
-
-    def get_content_platform_message_chain(self, prefix_text: str = '') -> platform_message.MessageChain | None:
-        """将内容转换为平台消息 MessageChain 对象
-
-        Args:
-            prefix_text (str): 首个文字组件的前缀文本
-        """
-
-        if self.content is None:
-            return None
-        elif isinstance(self.content, str):
-            return platform_message.MessageChain([platform_message.Plain(prefix_text + self.content)])
-        elif isinstance(self.content, list):
-            mc = []
-            for ce in self.content:
-                if ce.type == 'text':
-                    mc.append(platform_message.Plain(ce.text))
-                elif ce.type == 'image_url':
-                    if ce.image_url.url.startswith('http'):
-                        mc.append(platform_message.Image(url=ce.image_url.url))
-                    else:  # base64
-                        b64_str = ce.image_url.url
-
-                        if b64_str.startswith('data:'):
-                            b64_str = b64_str.split(',')[1]
-
-                        mc.append(platform_message.Image(base64=b64_str))
-
-            # 找第一个文字组件
-            if prefix_text:
-                for i, c in enumerate(mc):
-                    if isinstance(c, platform_message.Plain):
-                        mc[i] = platform_message.Plain(prefix_text + c.text)
-                        break
-                else:
-                    mc.insert(0, platform_message.Plain(prefix_text))
-
-            return platform_message.MessageChain(mc)
-
-
-class MessageChunk(pydantic.BaseModel):
-    """消息"""
-
-    resp_message_id: typing.Optional[str] = None
-    """消息id"""
-
-    role: str  # user, system, assistant, tool, command, plugin
-    """消息的角色"""
-
-    name: typing.Optional[str] = None
-    """名称，仅函数调用返回时设置"""
-
-    all_content: typing.Optional[str] = None
-    """所有内容"""
-
-    content: typing.Optional[list[ContentElement]] | typing.Optional[str] = None
-    """内容"""
-
-    tool_calls: typing.Optional[list[ToolCall]] = None
-    """工具调用"""
-
-    tool_call_id: typing.Optional[str] = None
-
-    is_final: bool = False
-    """是否是结束"""
-
-    msg_sequence: int = 0
-    """消息迭代次数"""
-
-    def readable_str(self) -> str:
-        if self.content is not None:
-            return str(self.role) + ': ' + str(self.get_content_platform_message_chain())
-        elif self.tool_calls is not None:
-            return f'调用工具: {self.tool_calls[0].id}'
-        else:
-            return '未知消息'
-
-    def get_content_platform_message_chain(self, prefix_text: str = '') -> platform_message.MessageChain | None:
-        """将内容转换为平台消息 MessageChain 对象
-
-        Args:
-            prefix_text (str): 首个文字组件的前缀文本
-        """
-
-        if self.content is None:
-            return None
-        elif isinstance(self.content, str):
-            return platform_message.MessageChain([platform_message.Plain(prefix_text + self.content)])
-        elif isinstance(self.content, list):
-            mc = []
-            for ce in self.content:
-                if ce.type == 'text':
-                    mc.append(platform_message.Plain(ce.text))
-                elif ce.type == 'image_url':
-                    if ce.image_url.url.startswith('http'):
-                        mc.append(platform_message.Image(url=ce.image_url.url))
-                    else:  # base64
-                        b64_str = ce.image_url.url
-
-                        if b64_str.startswith('data:'):
-                            b64_str = b64_str.split(',')[1]
-
-                        mc.append(platform_message.Image(base64=b64_str))
-
-            # 找第一个文字组件
-            if prefix_text:
-                for i, c in enumerate(mc):
-                    if isinstance(c, platform_message.Plain):
-                        mc[i] = platform_message.Plain(prefix_text + c.text)
-                        break
-                else:
-                    mc.insert(0, platform_message.Plain(prefix_text))
-
-            return platform_message.MessageChain(mc)
-
-
-class ToolCallChunk(pydantic.BaseModel):
-    """工具调用"""
-
-    id: str
-    """工具调用ID"""
-
-    type: str
-    """工具调用类型"""
-
-    function: FunctionCall
-    """函数调用"""
-
-
-class Prompt(pydantic.BaseModel):
-    """供AI使用的Prompt"""
-
-    name: str
-    """名称"""
-
-    messages: list[entities.Message]
-    """消息列表"""

pkg/provider/modelmgr/requesters/302aichatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: 302-ai-chat-completions
-  label:
-    en_US: 302.AI
-    zh_Hans: 302.AI
-  icon: 302ai.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.302.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./302aichatcmpl.py
-    attr: AI302ChatCompletions

pkg/provider/modelmgr/requesters/anthropicmsgs.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: anthropic-messages
-  label:
-    en_US: Anthropic
-    zh_Hans: Anthropic
-  icon: anthropic.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.anthropic.com"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./anthropicmsgs.py
-    attr: AnthropicMessages

pkg/provider/modelmgr/requesters/bailianchatcmpl.py

@@ -1,17 +0,0 @@
-from __future__ import annotations
-
-import typing
-import openai
-
-from . import modelscopechatcmpl
-
-
-class BailianChatCompletions(modelscopechatcmpl.ModelScopeChatCompletions):
-    """阿里云百炼大模型平台 ChatCompletion API 请求器"""
-
-    client: openai.AsyncClient
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
-        'timeout': 120,
-    }

pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: bailian-chat-completions
-  label:
-    en_US: Aliyun Bailian
-    zh_Hans: 阿里云百炼
-  icon: bailian.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://dashscope.aliyuncs.com/compatible-mode/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./bailianchatcmpl.py
-    attr: BailianChatCompletions

pkg/provider/modelmgr/requesters/chatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openai-chat-completions
-  label:
-    en_US: OpenAI
-    zh_Hans: OpenAI
-  icon: openai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.openai.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./chatcmpl.py
-    attr: OpenAIChatCompletions

pkg/provider/modelmgr/requesters/compsharechatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: compshare-chat-completions
-  label:
-    en_US: CompShare
-    zh_Hans: 优云智算
-  icon: compshare.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.modelverse.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./compsharechatcmpl.py
-    attr: CompShareChatCompletions

pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: deepseek-chat-completions
-  label:
-    en_US: DeepSeek
-    zh_Hans: DeepSeek
-  icon: deepseek.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.deepseek.com"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./deepseekchatcmpl.py
-    attr: DeepseekChatCompletions

pkg/provider/modelmgr/requesters/geminichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gemini-chat-completions
-  label:
-    en_US: Google Gemini
-    zh_Hans: Google Gemini
-  icon: gemini.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://generativelanguage.googleapis.com/v1beta/openai"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./geminichatcmpl.py
-    attr: GeminiChatCompletions

pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gitee-ai-chat-completions
-  label:
-    en_US: Gitee AI
-    zh_Hans: Gitee AI
-  icon: giteeai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ai.gitee.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./giteeaichatcmpl.py
-    attr: GiteeAIChatCompletions

pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: lmstudio-chat-completions
-  label:
-    en_US: LM Studio
-    zh_Hans: LM Studio
-  icon: lmstudio.webp
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:1234/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./lmstudiochatcmpl.py
-    attr: LmStudioChatCompletions

pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml

@@ -1,37 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: modelscope-chat-completions
-  label:
-    en_US: ModelScope
-    zh_Hans: 魔搭社区
-  icon: modelscope.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api-inference.modelscope.cn/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./modelscopechatcmpl.py
-    attr: ModelScopeChatCompletions

pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: moonshot-chat-completions
-  label:
-    en_US: Moonshot
-    zh_Hans: 月之暗面
-  icon: moonshot.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.moonshot.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./moonshotchatcmpl.py
-    attr: MoonshotChatCompletions

pkg/provider/modelmgr/requesters/newapichatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: new-api-chat-completions
-  label:
-    en_US: New API
-    zh_Hans: New API
-  icon: newapi.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://localhost:3000/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./newapichatcmpl.py
-    attr: NewAPIChatCompletions

pkg/provider/modelmgr/requesters/ollamachat.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ollama-chat
-  label:
-    en_US: Ollama
-    zh_Hans: Ollama
-  icon: ollama.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:11434"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./ollamachat.py
-    attr: OllamaChatCompletions

pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openrouter-chat-completions
-  label:
-    en_US: OpenRouter
-    zh_Hans: OpenRouter
-  icon: openrouter.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://openrouter.ai/api/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./openrouterchatcmpl.py
-    attr: OpenRouterChatCompletions

pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ppio-chat-completions
-  label:
-    en_US: ppio 
-    zh_Hans: 派欧云
-  icon: ppio.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.ppinfra.com/v3/openai"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./ppiochatcmpl.py
-    attr: PPIOChatCompletions

pkg/provider/modelmgr/requesters/qhaigcchatcmpl.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: qhaigc-chat-completions
-  label:
-    en_US: QH AI
-    zh_Hans: 启航 AI
-  icon: qhaigc.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.qhaigc.net/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./qhaigcchatcmpl.py
-    attr: QHAIGCChatCompletions

pkg/provider/modelmgr/requesters/shengsuanyun.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: shengsuanyun-chat-completions
-  label:
-    en_US: ShengSuanYun
-    zh_Hans: 胜算云
-  icon: shengsuanyun.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://router.shengsuanyun.com/api/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./shengsuanyun.py
-    attr: ShengSuanYunChatCompletions

pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: siliconflow-chat-completions
-  label:
-    en_US: SiliconFlow
-    zh_Hans: 硅基流动
-  icon: siliconflow.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.siliconflow.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./siliconflowchatcmpl.py
-    attr: SiliconFlowChatCompletions

pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: volcark-chat-completions
-  label:
-    en_US: Volc Engine Ark
-    zh_Hans: 火山方舟
-  icon: volcark.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ark.cn-beijing.volces.com/api/v3"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./volcarkchatcmpl.py
-    attr: VolcArkChatCompletions

pkg/provider/modelmgr/requesters/xaichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: xai-chat-completions
-  label:
-    en_US: xAI
-    zh_Hans: xAI
-  icon: xai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.x.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./xaichatcmpl.py
-    attr: XaiChatCompletions

pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: zhipuai-chat-completions
-  label:
-    en_US: ZhipuAI
-    zh_Hans: 智谱 AI
-  icon: zhipuai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://open.bigmodel.cn/api/paas/v4"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./zhipuaichatcmpl.py
-    attr: ZhipuAIChatCompletions

pkg/provider/tools/entities.py

@@ -1,31 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-import pydantic.v1 as pydantic
-
-
-class LLMFunction(pydantic.BaseModel):
-    """函数"""
-
-    name: str
-    """函数名"""
-
-    human_desc: str
-
-    description: str
-    """给LLM识别的函数描述"""
-
-    parameters: dict
-
-    func: typing.Callable
-    """供调用的python异步方法
-    
-    此异步方法第一个参数接收当前请求的query对象，可以从其中取出session等信息。
-    query参数不在parameters中，但在调用时会自动传入。
-    但在当前版本中，插件提供的内容函数都是同步的，且均为请求无关的，故在此版本的实现（以及考虑了向后兼容性的版本）中，
-    对插件的内容函数进行封装并存到这里来。
-    """
-
-    class Config:
-        arbitrary_types_allowed = True

pkg/provider/tools/loaders/mcp.py

@@ -1,157 +0,0 @@
-from __future__ import annotations
-
-import typing
-from contextlib import AsyncExitStack
-
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
-from mcp.client.sse import sse_client
-
-from .. import loader, entities as tools_entities
-from ....core import app, entities as core_entities
-
-
-class RuntimeMCPSession:
-    """运行时 MCP 会话"""
-
-    ap: app.Application
-
-    server_name: str
-
-    server_config: dict
-
-    session: ClientSession
-
-    exit_stack: AsyncExitStack
-
-    functions: list[tools_entities.LLMFunction] = []
-
-    def __init__(self, server_name: str, server_config: dict, ap: app.Application):
-        self.server_name = server_name
-        self.server_config = server_config
-        self.ap = ap
-
-        self.session = None
-
-        self.exit_stack = AsyncExitStack()
-        self.functions = []
-
-    async def _init_stdio_python_server(self):
-        server_params = StdioServerParameters(
-            command=self.server_config['command'],
-            args=self.server_config['args'],
-            env=self.server_config['env'],
-        )
-
-        stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
-
-        stdio, write = stdio_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(stdio, write))
-
-        await self.session.initialize()
-
-    async def _init_sse_server(self):
-        sse_transport = await self.exit_stack.enter_async_context(
-            sse_client(
-                self.server_config['url'],
-                headers=self.server_config.get('headers', {}),
-                timeout=self.server_config.get('timeout', 10),
-            )
-        )
-
-        sseio, write = sse_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(sseio, write))
-
-        await self.session.initialize()
-
-    async def initialize(self):
-        self.ap.logger.debug(f'初始化 MCP 会话: {self.server_name} {self.server_config}')
-
-        if self.server_config['mode'] == 'stdio':
-            await self._init_stdio_python_server()
-        elif self.server_config['mode'] == 'sse':
-            await self._init_sse_server()
-        else:
-            raise ValueError(f'无法识别 MCP 服务器类型: {self.server_name}: {self.server_config}')
-
-        tools = await self.session.list_tools()
-
-        self.ap.logger.debug(f'获取 MCP 工具: {tools}')
-
-        for tool in tools.tools:
-
-            async def func(query: core_entities.Query, *, _tool=tool, **kwargs):
-                result = await self.session.call_tool(_tool.name, kwargs)
-                if result.isError:
-                    raise Exception(result.content[0].text)
-                return result.content[0].text
-
-            func.__name__ = tool.name
-
-            self.functions.append(
-                tools_entities.LLMFunction(
-                    name=tool.name,
-                    human_desc=tool.description,
-                    description=tool.description,
-                    parameters=tool.inputSchema,
-                    func=func,
-                )
-            )
-
-    async def shutdown(self):
-        """关闭工具"""
-        await self.session._exit_stack.aclose()
-
-
-@loader.loader_class('mcp')
-class MCPLoader(loader.ToolLoader):
-    """MCP 工具加载器。
-
-    在此加载器中管理所有与 MCP Server 的连接。
-    """
-
-    sessions: dict[str, RuntimeMCPSession] = {}
-
-    _last_listed_functions: list[tools_entities.LLMFunction] = []
-
-    def __init__(self, ap: app.Application):
-        super().__init__(ap)
-        self.sessions = {}
-        self._last_listed_functions = []
-
-    async def initialize(self):
-        for server_config in self.ap.instance_config.data.get('mcp', {}).get('servers', []):
-            if not server_config['enable']:
-                continue
-            session = RuntimeMCPSession(server_config['name'], server_config, self.ap)
-            await session.initialize()
-            # self.ap.event_loop.create_task(session.initialize())
-            self.sessions[server_config['name']] = session
-
-    async def get_tools(self, enabled: bool = True) -> list[tools_entities.LLMFunction]:
-        all_functions = []
-
-        for session in self.sessions.values():
-            all_functions.extend(session.functions)
-
-        self._last_listed_functions = all_functions
-
-        return all_functions
-
-    async def has_tool(self, name: str) -> bool:
-        return name in [f.name for f in self._last_listed_functions]
-
-    async def invoke_tool(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
-        for server_name, session in self.sessions.items():
-            for function in session.functions:
-                if function.name == name:
-                    return await function.func(query, **parameters)
-
-        raise ValueError(f'未找到工具: {name}')
-
-    async def shutdown(self):
-        """关闭工具"""
-        for session in self.sessions.values():
-            await session.shutdown()

pkg/provider/tools/loaders/plugin.py

@@ -1,78 +0,0 @@
-from __future__ import annotations
-
-import typing
-import traceback
-
-from .. import loader, entities as tools_entities
-from ....core import entities as core_entities
-from ....plugin import context as plugin_context
-
-
-@loader.loader_class('plugin-tool-loader')
-class PluginToolLoader(loader.ToolLoader):
-    """插件工具加载器。
-
-    本加载器中不存储工具信息，仅负责从插件系统中获取工具信息。
-    """
-
-    async def get_tools(self, enabled: bool = True) -> list[tools_entities.LLMFunction]:
-        # 从插件系统获取工具（内容函数）
-        all_functions: list[tools_entities.LLMFunction] = []
-
-        for plugin in self.ap.plugin_mgr.plugins(
-            enabled=enabled, status=plugin_context.RuntimeContainerStatus.INITIALIZED
-        ):
-            all_functions.extend(plugin.tools)
-
-        return all_functions
-
-    async def has_tool(self, name: str) -> bool:
-        """检查工具是否存在"""
-        for plugin in self.ap.plugin_mgr.plugins(
-            enabled=True, status=plugin_context.RuntimeContainerStatus.INITIALIZED
-        ):
-            for function in plugin.tools:
-                if function.name == name:
-                    return True
-        return False
-
-    async def _get_function_and_plugin(
-        self, name: str
-    ) -> typing.Tuple[tools_entities.LLMFunction, plugin_context.BasePlugin]:
-        """获取函数和插件实例"""
-        for plugin in self.ap.plugin_mgr.plugins(
-            enabled=True, status=plugin_context.RuntimeContainerStatus.INITIALIZED
-        ):
-            for function in plugin.tools:
-                if function.name == name:
-                    return function, plugin.plugin_inst
-        return None, None
-
-    async def invoke_tool(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
-        try:
-            function, plugin = await self._get_function_and_plugin(name)
-            if function is None:
-                return None
-
-            parameters = parameters.copy()
-
-            parameters = {'query': query, **parameters}
-
-            return await function.func(plugin, **parameters)
-        except Exception as e:
-            self.ap.logger.error(f'执行函数 {name} 时发生错误: {e}')
-            traceback.print_exc()
-            return f'error occurred when executing function {name}: {e}'
-        finally:
-            plugin = None
-
-            for p in self.ap.plugin_mgr.plugins():
-                if function in p.tools:
-                    plugin = p
-                    break
-
-            # TODO statistics
-
-    async def shutdown(self):
-        """关闭工具"""
-        pass

pkg/storage/mgr.py

@@ -1,21 +0,0 @@
-from __future__ import annotations
-
-
-from ..core import app
-from . import provider
-from .providers import localstorage
-
-
-class StorageMgr:
-    """存储管理器"""
-
-    ap: app.Application
-
-    storage_provider: provider.StorageProvider
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.storage_provider = localstorage.LocalStorageProvider(ap)
-
-    async def initialize(self):
-        await self.storage_provider.initialize()

pkg/utils/announce.py

@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-import json
-import typing
-import os
-import base64
-import logging
-
-import pydantic.v1 as pydantic
-import requests
-
-from ..core import app
-
-
-class Announcement(pydantic.BaseModel):
-    """公告"""
-
-    id: int
-
-    time: str
-
-    timestamp: int
-
-    content: str
-
-    enabled: typing.Optional[bool] = True
-
-    def to_dict(self) -> dict:
-        return {
-            'id': self.id,
-            'time': self.time,
-            'timestamp': self.timestamp,
-            'content': self.content,
-            'enabled': self.enabled,
-        }
-
-
-class AnnouncementManager:
-    """公告管理器"""
-
-    ap: app.Application = None
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def fetch_all(self) -> list[Announcement]:
-        """获取所有公告"""
-        resp = requests.get(
-            url='https://api.github.com/repos/langbot-app/LangBot/contents/res/announcement.json',
-            proxies=self.ap.proxy_mgr.get_forward_proxies(),
-            timeout=5,
-        )
-        obj_json = resp.json()
-        b64_content = obj_json['content']
-        # 解码
-        content = base64.b64decode(b64_content).decode('utf-8')
-
-        return [Announcement(**item) for item in json.loads(content)]
-
-    async def fetch_saved(self) -> list[Announcement]:
-        if not os.path.exists('data/labels/announcement_saved.json'):
-            with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-                f.write('[]')
-
-        with open('data/labels/announcement_saved.json', 'r', encoding='utf-8') as f:
-            content = f.read()
-
-        if not content:
-            content = '[]'
-
-        return [Announcement(**item) for item in json.loads(content)]
-
-    async def write_saved(self, content: list[Announcement]):
-        with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-            f.write(json.dumps([item.to_dict() for item in content], indent=4, ensure_ascii=False))
-
-    async def fetch_new(self) -> list[Announcement]:
-        """获取新公告"""
-        all = await self.fetch_all()
-        saved = await self.fetch_saved()
-
-        to_show: list[Announcement] = []
-
-        for item in all:
-            # 遍历saved检查是否有相同id的公告
-            for saved_item in saved:
-                if saved_item.id == item.id:
-                    break
-            else:
-                if item.enabled:
-                    # 没有相同id的公告
-                    to_show.append(item)
-
-        await self.write_saved(all)
-        return to_show
-
-    async def show_announcements(self) -> typing.Tuple[str, int]:
-        """显示公告"""
-        try:
-            announcements = await self.fetch_new()
-            ann_text = ''
-            for ann in announcements:
-                ann_text += f'[公告] {ann.time}: {ann.content}\n'
-
-            # TODO statistics
-
-            return ann_text, logging.INFO
-        except Exception as e:
-            return f'获取公告时出错: {e}', logging.WARNING