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YAML 定义角色、目标和任务流程\n- 🔄 **多模式执行** - 顺序/并行/层级三种任务调度模式\n- 🛠️ **15+ 内置技能** - 搜索、绘图、代码执行、文档处理等\n- 🌐 **多 LLM 支持** - 智谱AI、OpenAI、DeepSeek、Moonshot、阿里云等\n- 🔒 **企业级安全** - Fernet 加密存储、Token 裁剪、访问控制\n- 💻 **三种交互方式** - CLI、REST API、现代化 Web 界面\n- 📱 **响应式设计** - 支持桌面端和移动端访问\n- 🌍 **多语言支持** - 完整的中英文国际化\n\n## 📁 项目结构\n\n```\nmy_ai_agent/\n├── 🎯 入口与脚本\n│   ├── main.py                 # 命令行入口\n│   ├── start.sh / start.bat    # 一键启动脚本\n│   └── stop.sh / stop.bat      # 停止服务脚本\n│\n├── 🖥️ 前端界面 (Next.js 14 + React 18)\n│   ├── src/\n│   │   ├── app/               # Next.js App Router\n│   │   ├── components/        # React 组件\n│   │   │   ├── chat/         # 聊天界面\n│   │   │   ├── office/       # Agent 办公室可视化\n│   │   │   └── settings/     # 设置面板\n│   │   ├── store/            # Zustand 状态管理\n│   │   └── lib/              # API 客户端\n│   └── package.json\n│\n├── ⚙️ 后端 API (FastAPI)\n│   ├── main.py               # API 服务入口\n│   ├── routes/               # 路由模块\n│   │   ├── chat.py          # 流式对话 (SSE)\n│   │   ├── sessions.py      # 会话管理\n│   │   ├── agents.py        # Agent 配置\n│   │   ├── skills.py        # 技能管理\n│   │   ├── models.py        # 模型配置\n│   │   ├── files.py         # 文件处理\n│   │   └── stats.py         # 用量统计\n│   └── schemas.py           # Pydantic 模型\n│\n├── 🧠 核心引擎\n│   ├── chat_engine.py       # 主对话引擎\n│   ├── worker_executor.py   # Worker 执行器\n│   ├── fc_dispatcher.py     # Function Calling 调度器\n│   ├── skill_executor.py    # 技能执行器\n│   ├── memory.py            # 内存管理 + Token 裁剪\n│   ├── security.py          # 安全加密模块\n│   ├── llm_factory.py       # LLM 工厂\n│   └── model_router.py      # 模型路由\n│\n├── 🛠️ 技能库 (15+ 内置技能)\n│   ├── search_report.py      # 智能搜索报告\n│   ├── image_generate.py    # AI 图像生成\n│   ├── code_execute.py      # 代码执行\n│   ├── doc_summary.py       # 文档摘要\n│   ├── doc_generator.py     # 文档生成\n│   ├── data_analysis.py     # 数据分析\n│   ├── translate.py         # 翻译\n│   ├── tts.py               # 文本转语音\n│   ├── web_scrape.py        # 网页抓取\n│   ├── email_send.py        # 邮件发送\n│   ├── reminder.py          # 提醒任务\n│   ├── knowledge_base.py    # 知识库\n│   ├── media_understand.py  # 媒体理解\n│   ├── prompt_optimizer.py  # 提示词优化\n│   └── task_manager.py      # 任务管理\n│\n├── 🔌 插件扩展\n│   ├── browser/             # 浏览器自动化\n│   ├── code_executor/       # 代码执行器\n│   └── bot/                 # 机器人扩展\n│\n├── ⚙️ 配置与部署\n│   ├── config.yaml          # 主配置文件\n│   ├── .env.example         # 环境变量模板\n│   ├── deploy.sh            # 部署脚本\n│   └── deploy/              # 部署配置\n│\n├── 🧪 测试\n│   └── tests/               # 测试套件 (68+ 测试用例)\n│\n└── 📚 文档\n    └── docs/                # 项目文档\n```\n\n## 🚀 快速开始\n\n### 环境要求\n\n- Python >= 3.10\n- Node.js >= 18 (前端需要)\n- 支持的操作系统：macOS / Linux / Windows\n\n### 1. 克隆项目\n\n```bash\ngit clone https://github.com/zbin0929/my_ai_agent.git\ncd my_ai_agent\n```\n\n### 2. 安装依赖\n\n```bash\n# 创建虚拟环境\npython -m venv venv\nsource venv/bin/activate  # Linux/Mac\n# 或: venv\\Scripts\\activate  # Windows\n\n# 安装 Python 依赖\npip install -r requirements.txt\n\n# 安装前端依赖（可选）\ncd frontend && npm install && cd ..\n```\n\n### 3. 配置环境变量\n\n```bash\ncp .env.example .env\n# 编辑 .env 填入你的 API Keys\n```\n\n### 4. 启动服务\n\n```bash\n# 方式一：一键启动所有服务（推荐）\n./start.sh\n\n# 方式二：单独启动\n# 启动 API 服务\nuvicorn api.main:app --host 0.0.0.0 --port 8000\n\n# 启动前端（新终端）\ncd frontend && npm run dev\n```\n\n访问 http://localhost:3000 使用 Web 界面\n\n## 🎯 使用指南\n\n### 命令行模式\n\n```bash\n# 基础用法\npython main.py\n\n# 指定研究主题\npython main.py --topic \"量子计算最新进展\"\n\n# 自定义参数\npython main.py \\\n  --topic \"AI智能体技术\" \\\n  --num-points 5 \\\n  --word-count 500 \\\n  --output-file \"report.txt\"\n\n# 仅验证配置\npython main.py --validate\n\n# 启用详细日志\npython main.py --verbose\n\n# 指定执行模式\npython main.py --mode hierarchical\n```\n\n### API 接口\n\n| 接口 | 方法 | 说明 |\n|------|------|------|\n| `/api/chat` | POST | 流式对话 (SSE) |\n| `/api/health` | GET | 健康检查 |\n| `/api/sessions` | GET | 会话列表 |\n| `/api/sessions/{id}` | GET/DELETE | 获取/删除会话 |\n| `/api/sessions/{id}/export` | GET | 导出 Markdown |\n| `/api/agents` | GET/POST | Agent 列表/配置 |\n| `/api/skills` | GET | 技能列表 |\n| `/api/models` | GET | 可用模型列表 |\n| `/api/stats` | GET | 用量统计 |\n\n### Web 界面功能\n\n- 💬 **智能对话** - 流式输出、思考过程可视化\n- 📁 **会话管理** - 置顶、重命名、导出 Markdown\n- ⚙️ **Agent 配置** - 可视化配置角色和目标\n- 🛠️ **技能管理** - 启用/禁用技能、参数配置\n- 🤖 **模型设置** - 多 LLM 切换、参数调优\n- 📊 **用量统计** - Token 消耗、API 调用统计\n- 🎮 **Agent 办公室** - 像素风格的可视化工作场景\n- 🌓 **深色模式** - 自动跟随系统或手动切换\n\n## ⚙️ 配置说明\n\n### Agent 配置示例 (`config.yaml`)\n\n```yaml\nagents:\n  - name: \"researcher\"\n    role: \"研究员\"\n    goal: \"搜索并总结关于 {topic} 的最新信息\"\n    backstory: \"你擅长使用搜索引擎查找最新资料，并提炼要点\"\n    tools: [\"search\"]\n    verbose: true\n\n  - name: \"writer\"\n    role: \"报告撰写员\"\n    goal: \"根据资料写出简洁的报告\"\n    backstory: \"你擅长把复杂内容变成易读的文字\"\n\n  - name: \"executor\"\n    role: \"执行员\"\n    goal: \"将最终报告保存到本地文件\"\n    backstory: \"你负责把报告写入文件，确保内容完整\"\n    tools: [\"file_writer\"]\n\ntasks:\n  - name: \"research\"\n    description: \"搜索关于 {topic} 的最新信息，总结出{num_points}个要点\"\n    agent: \"researcher\"\n    expected_output: \"要点总结\"\n    context: []\n\n  - name: \"write\"\n    description: \"根据研究资料，写一段{word_count}字左右的总结报告\"\n    agent: \"writer\"\n    expected_output: \"完整报告\"\n    context: [\"research\"]\n\n  - name: \"save\"\n    description: \"将最终报告保存到文件 '{output_file}' 中\"\n    agent: \"executor\"\n    expected_output: \"保存确认\"\n    context: [\"write\"]\n```\n\n### 环境变量\n\n| 变量 | 说明 | 必需 |\n|------|------|------|\n| `ZHIPU_API_KEY` | 智谱 AI API Key | ✅ 推荐 |\n| `OPENAI_API_KEY` | OpenAI API Key | ❌ 可选 |\n| `DEEPSEEK_API_KEY` | DeepSeek API Key | ❌ 可选 |\n| `MOONSHOT_API_KEY` | Moonshot API Key | ❌ 可选 |\n| `DASHSCOPE_API_KEY` | 阿里云百炼 API Key | ❌ 可选 |\n| `ENCRYPTION_KEY` | API Key 加密密钥 (Fernet) | ✅ 推荐 |\n| `ADMIN_TOKEN` | 管理接口认证令牌 | ✅ 生产环境 |\n| `LOG_LEVEL` | 日志级别 | ❌ 默认 INFO |\n\n## 🧪 测试\n\n```bash\n# 运行所有测试\npytest tests/ -v\n\n# 运行核心功能测试\npytest tests/test_p0_features.py -v\n\n# 生成覆盖率报告\npytest tests/ --cov=core --cov-report=html\n```\n\n## 📸 界面预览\n\n> Web 界面截图将在这里展示\n\n## 🤝 加入社区，一起建设\n\n**我们热切期待你的加入！** 无论你的技术水平如何，都可以为项目贡献力量。这是一个开放、友好的社区，欢迎各种形式的参与。\n\n### 🌟 你可以这样参与\n\n| 参与方式 | 适合人群 | 如何开始 |\n|---------|---------|---------|\n| 🐛 **报告 Bug** | 所有用户 | 发现问题时 [提交 Issue](https://github.com/zbin0929/my_ai_agent/issues) |\n| 💡 **提出需求** | 所有用户 | 有新想法？[告诉我们](https://github.com/zbin0929/my_ai_agent/issues/new?template=feature_request.md) |\n| 📝 **完善文档** | 技术写作者 | 改进 README、添加教程、翻译内容 |\n| 🔧 **贡献代码** | 开发者 | Fork → 开发 → 提交 Pull Request |\n| 🧪 **测试反馈** | 测试人员 | 试用新功能，反馈使用体验 |\n| 🌍 **翻译国际化** | 多语言者 | 帮助翻译成更多语言 |\n| 💬 **帮助答疑** | 资深用户 | 在 Issues 中帮助其他用户 |\n| ⭐ **推广项目** | 所有人 | 给项目 Star，分享给朋友 |\n\n### 🚀 快速开始贡献\n\n1. **Fork 本仓库** 到你的 GitHub 账号\n2. **创建特性分支** `git checkout -b feature/amazing-feature`\n3. **提交你的改动** `git commit -m 'Add some amazing feature'`\n4. **推送到分支** `git push origin feature/amazing-feature`\n5. **打开 Pull Request**，我们会尽快审核\n\n### 📋 贡献规范\n\n- 代码风格遵循 [PEP 8](https://pep8.org/)\n- 提交前请运行测试 `pytest tests/`\n- 新增功能请添加相应的测试用例\n- 文档更新与代码同步\n\n### 💬 交流渠道\n\n- 💻 [GitHub Issues](https://github.com/zbin0929/my_ai_agent/issues) - 问题反馈与讨论\n- 📧 发送邮件至作者：通过 GitHub 个人主页联系\n\n### 🙏 贡献者\n\n感谢所有为项目做出贡献的开发者！你们的每一份努力都让这个项目变得更好。\n\n<a href=\"https://github.com/zbin0929/my_ai_agent/graphs/contributors\">\n  <img src=\"https://contrib.rocks/image?repo=zbin0929/my_ai_agent\" alt=\"Contributors\" />\n</a>\n\n## 📄 开源协议\n\n本项目基于 [MIT License](LICENSE) 开源。\n\n## 👤 作者\n\n**zbin0929**\n\n- GitHub: [@zbin0929](https://github.com/zbin0929)\n- 项目主页: [https://github.com/zbin0929/my_ai_agent](https://github.com/zbin0929/my_ai_agent)\n\n---\n\n<div align=\"center\">\n\n⭐ 如果这个项目对你有帮助，请给它一个 Star！\n\n**[⬆ 返回顶部](#-my-ai-agent)**\n\n</div>\n","readmeExcerpt":"<div align=\"center\"> 🤖 My AI Agent **基于 CrewAI 的模块化多 Agent 智能协作系统** $1 $1 $1 $1 $1 $1 | 中文 </div> 📖 简介 My AI Agent 是一个**企业级多 Agent 智能协作平台**，通过配置化方式定义智能体角色、目标和工作流程。系统提供三种交互模式（命令行、REST API、Web 界面），支持多种主流 LLM，内置丰富的技能工具，帮助团队高效完成复杂任务。 ✨ 核心亮点 - 🎯 **配置化 Agent 系统** - YAML 定义角色、目标和任务流程 - 🔄 **多模式执行** - 顺序/并行/层级三种任务调度模式 - 🛠️ **15+ 内置技能** - 搜索、绘图、代码执行、文档处理等 - 🌐 **多 LLM 支持** - 智谱AI、OpenAI、DeepSeek、Moonshot、阿里云等 - 🔒 **企业级安全","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"my_ai_agent/\n├── 🎯 入口与脚本\n│   ├── main.py                 # 命令行入口\n│   ├── start.sh / start.bat    # 一键启动脚本\n│   └── stop.sh / stop.bat      # 停止服务脚本\n│\n├── 🖥️ 前端界面 (Next.js 14 + React 18)\n│   ├── src/\n│   │   ├── app/               # Next.js App Router\n│   │   ├── components/        # React 组件\n│   │   │   ├── chat/         # 聊天界面\n│   │   │   ├── office/       # Agent 办公室可视化\n│   │   │   └── settings/     # 设置面板\n│   │   ├── store/            # Zustand 状态管理\n│   │   └── lib/              # API 客户端\n│   └── package.json\n│\n├── ⚙️ 后端 API (FastAPI)\n│   ├── main.py               # API 服务入口\n│   ├── routes/               # 路由模块\n│   │   ├── chat.py          # 流式对话 (SSE)\n│   │   ├── sessions.py      # 会话管理\n│   │   ├── agents.py        # Agent 配置\n│   │   ├── skills.py        # 技能管理\n│   │   ├── models.py        # 模型配置\n│   │   ├── files.py         # 文件处理\n│   │   └── stats.py         # 用量统计\n│   └── schemas.py           # Pydantic 模型\n│\n├── 🧠 核心引擎\n│   ├── chat_engine.py       # 主对话引擎\n│   ├── worker_executor.py   # Worker 执行器\n│   ├── fc_dispatcher.py     # Function Calling 调度器\n│   ├── skill_executor.py    # 技能执行器\n│   ├── memory.py            # 内存管理 + Token 裁剪\n│   ├── security.py          # 安全加密模块\n│   ├── llm_factory.py       # LLM 工厂\n│   └── model_router.py      # 模型路由\n│\n├── 🛠️ 技能库 (15+ 内置技能)\n│   ├── search_report.py      # 智能搜索报告\n│   ├── image_generate.py    # AI 图像生成\n│   ├── code_execute.py      # 代码执行\n│   ├── doc_summary.py       # 文档摘要\n│   ├── doc_generator.py     # 文档生成\n│   ├── data_analysis.py     # 数据分析\n│   ├── translate.py         # 翻译\n│   ├── tts.py               # 文本转语音\n│   ├── web_scrape.py        # 网页抓取\n│   ├── email_send.py        # 邮件发送\n│   ├── reminder.py          # 提醒任务\n│   ├── knowledge_base.py    # 知识库\n│   ├── media_understand.py  # 媒体理解\n│   ├── prompt_optimizer.py  # 提示词优化\n│   └── task_manager.py      # 任务管理\n│\n├── 🔌 插件扩展\n│   ├── browser/             # 浏览器自动化\n│   ├── code_executor/       # 代码执行器\n│   └── bot/                 # 机器人扩展\n│\n├── ⚙️ 配置与部署\n│   ├── config.yaml "},{"language":"bash","snippet":"git clone https://github.com/zbin0929/my_ai_agent.git\ncd my_ai_agent"},{"language":"bash","snippet":"# 创建虚拟环境\npython -m venv venv\nsource venv/bin/activate  # Linux/Mac\n# 或: venv\\Scripts\\activate  # Windows\n\n# 安装 Python 依赖\npip install -r requirements.txt\n\n# 安装前端依赖（可选）\ncd frontend && npm install && cd .."},{"language":"bash","snippet":"cp .env.example .env\n# 编辑 .env 填入你的 API Keys"},{"language":"bash","snippet":"# 方式一：一键启动所有服务（推荐）\n./start.sh\n\n# 方式二：单独启动\n# 启动 API 服务\nuvicorn api.main:app --host 0.0.0.0 --port 8000\n\n# 启动前端（新终端）\ncd frontend && npm run dev"},{"language":"bash","snippet":"# 基础用法\npython main.py\n\n# 指定研究主题\npython main.py --topic \"量子计算最新进展\"\n\n# 自定义参数\npython main.py \\\n  --topic \"AI智能体技术\" \\\n  --num-points 5 \\\n  --word-count 500 \\\n  --output-file \"report.txt\"\n\n# 仅验证配置\npython main.py --validate\n\n# 启用详细日志\npython main.py --verbose\n\n# 指定执行模式\npython main.py --mode hierarchical"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["python"],"docsSourceLabel":"GITHUB REPOS","editorialOverview":"基于 CrewAI 的模块化多 Agent 智能协作系统 <div align=\"center\"> 🤖 My AI Agent **基于 CrewAI 的模块化多 Agent 智能协作系统** $1 $1 $1 $1 $1 $1 | 中文 </div> 📖 简介 My AI Agent 是一个**企业级多 Agent 智能协作平台**，通过配置化方式定义智能体角色、目标和工作流程。系统提供三种交互模式（命令行、REST API、Web 界面），支持多种主流 LLM，内置丰富的技能工具，帮助团队高效完成复杂任务。 ✨ 核心亮点 - 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