第二版
This commit is contained in:
ZhuJW
43
.dockerignore
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43
.dockerignore
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@@ -0,0 +1,43 @@
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# Git
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.git
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.gitignore
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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venv/
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env/
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ENV/
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.venv
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# Environment
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.env
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.env.local
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# Build
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build/
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dist/
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*.egg-info/
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# Docker
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Dockerfile
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.dockerignore
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# Documentation
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README.md
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*.md
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# Test
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.pytest_cache/
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.coverage
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htmlcov/
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36
.env
36
.env
@@ -1,31 +1,15 @@
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# 环境变量配置示例
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# 复制此文件为 .env 并填入实际值
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# DashScope API 配置
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# 获取 API Key: https://dashscope.console.aliyun.com/
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DASHSCOPE_API_KEY=sk-616332b2afa94699b4572d0fe6ac370a
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# ==================== DashScope 配置 ====================
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# DashScope API Key (阿里百炼 Qwen 模型)
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# 获取地址：https://dashscope.console.aliyun.com/
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DASHSCOPE_API_KEY=sk-your-actual-api-key-here
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# Qwen 模型配置
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QWEN_MODEL=qwen3.5-flash
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QWEN_TEMPERATURE=0.7
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QWEN_MAX_TOKENS=4096
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# 禁用 LiteLLM 的远程模型成本映射（避免启动时联网超时）
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DISABLE_LITELLM_MODEL_COST_MAP=True
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LITELLM_LOCAL_MODEL_COST_MAP=True
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# 注意：请将 DASHSCOPE_API_KEY 替换为您的真实 API Key
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# 不要将 .env 文件提交到版本控制系统
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# ==================== 服务配置 ====================
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# 服务器配置
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HOST=0.0.0.0
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PORT=8000
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# ==================== 日志配置 ====================
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LOG_LEVEL=info # debug, info, warning, error
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# ==================== 高级配置（可选）====================
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# SSE 队列最大长度
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SSE_QUEUE_MAX_SIZE=1000
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# 流清理间隔（秒）
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STREAM_CLEANUP_INTERVAL=300
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# 任务超时时间（秒）
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TASK_TIMEOUT=3600
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# 日志配置
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LOG_LEVEL=info
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32
.env.example
32
.env.example
@@ -1,27 +1,15 @@
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# 环境变量配置示例
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# 复制此文件为 .env 并填入实际值
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# DashScope API 配置
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# 获取 API Key: https://dashscope.console.aliyun.com/
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DASHSCOPE_API_KEY=your_dashscope_api_key_here
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# ==================== DashScope 配置 ====================
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# DashScope API Key (通义千问)
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# 获取地址：https://dashscope.console.aliyun.com/
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DASHSCOPE_API_KEY=sk-your-actual-api-key-here
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# Qwen 模型配置
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QWEN_MODEL=qwen3.5-flash
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QWEN_TEMPERATURE=0.7
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QWEN_MAX_TOKENS=4096
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# 注意：如果您使用 OpenAI，也可以设置 OPENAI_API_KEY
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# OPENAI_API_KEY=sk-your-openai-key
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# ==================== 服务配置 ====================
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# 服务器配置
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HOST=0.0.0.0
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PORT=8000
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# ==================== 日志配置 ====================
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LOG_LEVEL=info # debug, info, warning, error
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# ==================== 高级配置（可选）====================
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# SSE 队列最大长度
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SSE_QUEUE_MAX_SIZE=1000
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# 流清理间隔（秒）
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STREAM_CLEANUP_INTERVAL=300
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# 任务超时时间（秒）
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TASK_TIMEOUT=3600
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# 日志配置
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LOG_LEVEL=info
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39
.gitignore
vendored
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39
.gitignore
vendored
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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venv/
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env/
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ENV/
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.venv
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# Environment
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.env
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.env.local
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# Build
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build/
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dist/
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*.egg-info/
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# Test
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.pytest_cache/
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.coverage
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htmlcov/
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# OS
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.DS_Store
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Thumbs.db
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# Logs
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*.log
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logs/
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42
Dockerfile
42
Dockerfile
@@ -1,7 +1,8 @@
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# Multi-Agent Software Delivery System
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# 基于 CrewAI + Qwen3.5-flash 的多智能体软件交付系统
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# 多阶段构建 - SDLC Agent Demo
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FROM python:3.11-slim as builder
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FROM python:3.11-slim
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# 设置工作目录
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WORKDIR /app
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# 设置环境变量
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ENV PYTHONDONTWRITEBYTECODE=1 \
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@@ -9,29 +10,28 @@ ENV PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=1 \
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PIP_DISABLE_PIP_VERSION_CHECK=1
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# 安装依赖
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COPY requirements.txt .
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RUN pip install --user --no-cache-dir -r requirements.txt
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# 运行阶段
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FROM python:3.11-slim
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# 设置工作目录
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WORKDIR /app
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# 安装系统依赖
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RUN apt-get update && apt-get install -y --no-install-recommends \
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gcc \
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&& rm -rf /var/lib/apt/lists/*
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# 从 builder 阶段复制安装的包
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COPY --from=builder /root/.local /root/.local
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# 复制依赖文件
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COPY requirements.txt .
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# 安装 Python 依赖
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RUN pip install --no-cache-dir -r requirements.txt
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# 确保脚本路径在 PATH 中
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ENV PATH=/root/.local/bin:$PATH \
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PYTHONPATH=/app
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# 复制应用代码
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COPY main.py .
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COPY crew_factory.py .
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COPY agents_config.py .
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COPY stream_manager.py .
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COPY .env.example .env.example
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COPY . .
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# 创建非 root 用户运行应用
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RUN useradd --create-home --shell /bin/bash appuser && \
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# 创建非 root 用户
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RUN useradd -m -u 1000 appuser && \
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chown -R appuser:appuser /app
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USER appuser
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@@ -40,7 +40,7 @@ EXPOSE 8000
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# 健康检查
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')" || exit 1
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CMD python -c "import httpx; httpx.get('http://localhost:8000/health')" || exit 1
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# 启动命令
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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237
QUICKSTART.md
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237
QUICKSTART.md
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# SDLC Agent Demo - 快速使用指南
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## 项目概述
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这是一个基于 **CrewAI + Qwen3.5-flash + FastAPI(SSE)** 的多智能体软件交付协同系统演示项目。
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### 核心功能
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- ✅ **PM Agent** - 将用户需求转化为结构化 SRS 文档
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- ✅ **QA Agent** - 根据 SRS 生成自动化测试用例
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- ✅ **Dev Agent** - 根据需求和测试用例实现业务代码
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- ✅ **SSE 实时流** - 实时展示各智能体执行进度
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- ✅ **现代化 UI** - Vue3 + TailwindCSS 单页面应用
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||||
---
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## 快速启动（3 步）
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### 步骤 1: 配置 API Key
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```bash
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# 复制环境变量模板
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copy .env.example .env
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||||
# 编辑 .env 文件，填入你的 DashScope API Key
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# 获取地址：https://dashscope.console.aliyun.com/
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||||
```
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||||
**.env 文件内容：**
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```env
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DASHSCOPE_API_KEY=sk-your-api-key-here
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QWEN_MODEL=qwen3.5-flash
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HOST=0.0.0.0
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PORT=8000
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```
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### 步骤 2: 启动服务
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**方式 A: 使用启动脚本（Windows）**
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```bash
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start.bat
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```
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||||
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||||
**方式 B: 手动启动**
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```bash
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# 激活虚拟环境（如果有）
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python -m venv venv
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venv\Scripts\activate # Windows
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source venv/bin/activate # Linux/Mac
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# 启动 FastAPI 服务
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uvicorn main:app --reload --host 0.0.0.0 --port 8000
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```
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### 步骤 3: 访问应用
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打开浏览器访问：**http://localhost:8000/static/index.html**
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||||
---
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||||
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||||
## 使用示例
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||||
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||||
### 输入需求示例
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||||
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||||
在首页输入框中输入以下需求：
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||||
|
||||
```
|
||||
开发一个在线书签管理系统，需要包含以下功能：
|
||||
1. 用户注册和登录（支持邮箱验证）
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||||
2. 书签的添加、编辑、删除
|
||||
3. 书签分类和标签管理
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||||
4. 书签搜索功能
|
||||
5. 导出/导入书签（HTML 格式）
|
||||
6. 响应式设计，支持移动端访问
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|
||||
性能要求：
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||||
- 页面加载时间 < 2 秒
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||||
- 支持并发用户数 > 1000
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||||
```
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||||
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||||
### 预期输出
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||||
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||||
系统将依次执行：
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||||
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||||
1. **PM Agent** → 生成《软件需求规格说明书 (SRS)》
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||||
- 功能性需求清单
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||||
- 非功能性需求（性能、安全等）
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||||
- 验收标准
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||||
|
||||
2. **QA Agent** → 生成《测试方案与用例》
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- Pytest 测试脚本框架
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||||
- 测试场景描述
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||||
- 测试数据准备
|
||||
|
||||
3. **Dev Agent** → 生成《业务代码实现》
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||||
- 完整的 Python 代码模块
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||||
- 数据模型定义
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||||
- API 接口设计
|
||||
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||||
---
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||||
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||||
## API 接口说明
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||||
|
||||
### 1. 启动任务
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||||
|
||||
```bash
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||||
curl -X POST http://localhost:8000/api/v1/sdlc/start \
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||||
-H "Content-Type: application/json" \
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||||
-d '{"requirement": "开发一个简单的待办事项应用"}'
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||||
```
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||||
|
||||
**响应：**
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||||
```json
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||||
{
|
||||
"task_id": "550e8400-e29b-41d4-a716-446655440000",
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||||
"status": "processing"
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||||
}
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||||
```
|
||||
|
||||
### 2. SSE流式进度
|
||||
|
||||
```bash
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||||
curl -N http://localhost:8000/api/v1/sdlc/stream/{task_id}
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||||
```
|
||||
|
||||
**事件类型：**
|
||||
- `pm_start` / `pm_complete` - PM 阶段开始/完成
|
||||
- `qa_start` / `qa_complete` - QA 阶段开始/完成
|
||||
- `dev_start` / `dev_complete` - Dev 阶段开始/完成
|
||||
- `final_result` - 最终结果
|
||||
- `error` - 错误处理
|
||||
|
||||
### 3. 查询状态
|
||||
|
||||
```bash
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||||
curl http://localhost:8000/api/v1/sdlc/status/{task_id}
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||||
curl http://localhost:8000/api/v1/sdlc/result/{task_id}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Docker 部署
|
||||
|
||||
### 构建镜像
|
||||
|
||||
```bash
|
||||
docker build -t sdlc-agent-demo .
|
||||
```
|
||||
|
||||
### 运行容器
|
||||
|
||||
```bash
|
||||
docker run -d \
|
||||
-p 8000:8000 \
|
||||
-e DASHSCOPE_API_KEY=your_api_key \
|
||||
--name sdlc-demo \
|
||||
sdlc-agent-demo
|
||||
```
|
||||
|
||||
### 访问服务
|
||||
|
||||
http://localhost:8000/static/index.html
|
||||
|
||||
---
|
||||
|
||||
## 常见问题
|
||||
|
||||
### Q1: 如何获取 DashScope API Key？
|
||||
|
||||
访问 https://dashscope.console.aliyun.com/ 注册账号并创建 API Key。
|
||||
|
||||
### Q2: 支持其他模型吗？
|
||||
|
||||
可以修改 `.env` 中的 `QWEN_MODEL` 参数，使用其他 OpenAI 兼容的模型。
|
||||
|
||||
### Q3: SSE 连接中断怎么办？
|
||||
|
||||
- 检查防火墙设置
|
||||
- 增加超时时间（修改 `main.py` 中的 timeout 参数）
|
||||
- 前端已自动实现重连机制
|
||||
|
||||
### Q4: 输出质量不佳？
|
||||
|
||||
- 调整 Temperature 参数（降低随机性）
|
||||
- 优化 Prompt 描述
|
||||
- 增加更详细的上下文约束
|
||||
|
||||
---
|
||||
|
||||
## 技术栈
|
||||
|
||||
| 组件 | 技术 | 版本 |
|
||||
|------|------|------|
|
||||
| AI 框架 | CrewAI | >=0.85.0 |
|
||||
| 大模型 | Qwen3.5-flash | via DashScope |
|
||||
| Web 框架 | FastAPI | >=0.109.0 |
|
||||
| 实时通信 | SSE | sse-starlette |
|
||||
| 前端 | Vue3 | 3.x |
|
||||
| UI 框架 | TailwindCSS | 3.x |
|
||||
| 代码高亮 | Highlight.js | 11.9.0 |
|
||||
|
||||
---
|
||||
|
||||
## 项目结构
|
||||
|
||||
```
|
||||
sdlc_agent_demo/
|
||||
├── main.py # FastAPI 入口
|
||||
├── agents/
|
||||
│ ├── pm_agent.py # PM 智能体
|
||||
│ ├── qa_agent.py # QA 智能体
|
||||
│ └── dev_agent.py # Dev 智能体
|
||||
├── crews/
|
||||
│ └── sdlc_crew.py # 编排逻辑
|
||||
├── models/
|
||||
│ └── qwen_config.py # 模型配置
|
||||
├── static/
|
||||
│ └── index.html # 前端页面
|
||||
├── .env.example # 环境变量模板
|
||||
├── Dockerfile # Docker 配置
|
||||
├── requirements.txt # Python 依赖
|
||||
└── README.md # 详细文档
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 下一步计划
|
||||
|
||||
- [ ] 支持多任务并行处理
|
||||
- [ ] 添加任务历史记录
|
||||
- [ ] 集成代码执行沙箱
|
||||
- [ ] 支持更多模型后端
|
||||
- [ ] 添加认证授权机制
|
||||
|
||||
---
|
||||
|
||||
**Built with ❤️ using CrewAI + Qwen3.5-flash + FastAPI**
|
||||
541
README.md
541
README.md
@@ -1,408 +1,293 @@
|
||||
# Multi-Agent Software Delivery System
|
||||
# SDLC Agent Demo - 多智能体端到端软件交付协同系统
|
||||
|
||||
基于 CrewAI + Qwen3.5-flash 的多智能体软件交付系统，支持 SSE 实时推送。
|
||||
基于 **CrewAI + Qwen3.5-flash + FastAPI(SSE)** 构建的企业级研发提效演示系统，模拟从需求分析→测试用例→代码实现的完整 SDLC 流程。
|
||||
|
||||
## 📋 功能特性
|
||||
## 📋 项目特性
|
||||
|
||||
- **多智能体协作**: 4 个专业 Agent 协同完成软件交付
|
||||
- ProductManager: 产品需求分析
|
||||
- QAEngineer: 测试计划制定
|
||||
- SoftwareDeveloper: 技术方案设计
|
||||
- Coordinator: 质量审核与交付
|
||||
- ✅ **多智能体协同**：PM Agent、QA Agent、Dev Agent 顺序流水线作业
|
||||
- ✅ **实时进度追踪**：SSE流式输出各阶段执行状态
|
||||
- ✅ **Qwen3.5-flash**：通过 DashScope OpenAI 兼容 API 调用
|
||||
- ✅ **现代化前端**：Vue3 + TailwindCSS + 代码高亮
|
||||
- ✅ **任务持久化**：内存级任务状态管理
|
||||
- ✅ **Docker 支持**：一键容器化部署
|
||||
|
||||
- **实时通信**: 基于 SSE 协议实时推送执行日志
|
||||
- **异步处理**: 任务异步启动，不阻塞 API 响应
|
||||
- **并发支持**: 多用户同时请求互不干扰
|
||||
## 🏗️ 系统架构
|
||||
|
||||
## 🔑 关键技术点
|
||||
|
||||
### 1. SSE 数据格式设计
|
||||
|
||||
统一的 JSON 格式，便于前端解析：
|
||||
|
||||
```json
|
||||
{
|
||||
"task_id": "550e8400-e29b...",
|
||||
"sequence": 1,
|
||||
"agent_name": "ProductManager",
|
||||
"event_type": "thought",
|
||||
"content": "正在分析用户需求，提取关键指标...",
|
||||
"timestamp": "2023-10-27T10:00:00Z"
|
||||
}
|
||||
```
|
||||
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
|
||||
│ PM Agent │────▶│ QA Agent │────▶│ Dev Agent │
|
||||
│ 需求分析师 │ │ 测试架构师 │ │ 全栈工程师 │
|
||||
└─────────────┘ └──────────────┘ └─────────────┘
|
||||
│ │ │
|
||||
▼ ▼ ▼
|
||||
SRS 文档 测试用例 业务代码
|
||||
```
|
||||
|
||||
**字段说明**：
|
||||
- `task_id`: 任务唯一标识，用于区分不同用户的请求
|
||||
- `sequence`: 序列号（每个 task_id 独立递增），用于检测消息丢失
|
||||
- `agent_name`: 发送事件的 Agent 名称
|
||||
- `event_type`: 事件类型（start/thought/action/output/end/error）
|
||||
- `content`: 事件内容
|
||||
- `timestamp`: UTC 时间戳（ISO 8601 格式）
|
||||
## 📁 项目结构
|
||||
|
||||
### 2. 并发处理逻辑
|
||||
|
||||
**核心挑战**：CrewAI 默认是同步运行的，而 FastAPI 和 SSE 需要异步。
|
||||
|
||||
**解决方案**：
|
||||
|
||||
```python
|
||||
# 在 TaskStreamQueue 中实现线程安全的消息发布
|
||||
def put_nowait(self, event: StreamEvent) -> bool:
|
||||
"""
|
||||
从同步线程（如 CrewAI 事件处理器）安全地发布事件
|
||||
|
||||
使用 run_coroutine_threadsafe 将协程提交到事件循环执行
|
||||
这是实现 CrewAI（同步）与 SSE（异步）集成的关键
|
||||
"""
|
||||
future = asyncio.run_coroutine_threadsafe(
|
||||
self.queue.put(event),
|
||||
self._loop
|
||||
)
|
||||
future.result(timeout=5.0)
|
||||
return True
|
||||
```
|
||||
sdlc_agent_demo/
|
||||
├── main.py # FastAPI 入口
|
||||
├── agents/
|
||||
│ ├── __init__.py
|
||||
│ ├── pm_agent.py # PM 智能体定义
|
||||
│ ├── qa_agent.py # QA 智能体定义
|
||||
│ └── dev_agent.py # Dev 智能体定义
|
||||
├── crews/
|
||||
│ └── sdlc_crew.py # CrewAI 编排逻辑
|
||||
├── models/
|
||||
│ └── qwen_config.py # Qwen3.5-flash 配置
|
||||
├── static/
|
||||
│ └── index.html # 测试页面
|
||||
├── requirements.txt
|
||||
├── .env.example # 环境变量模板
|
||||
├── Dockerfile
|
||||
└── README.md
|
||||
```
|
||||
|
||||
**关键实现**：
|
||||
1. 使用 `asyncio.Queue` 实现异步非阻塞消息队列
|
||||
2. 通过 `asyncio.Lock` 保证并发安全
|
||||
3. 每个 `task_id` 独立队列，实现任务隔离
|
||||
4. 使用 `run_coroutine_threadsafe` 从同步线程安全发布事件
|
||||
5. 确保 `stream_manager` 能安全地在线程间传递消息
|
||||
## 🚀 快速启动
|
||||
|
||||
### 3. 多任务隔离机制
|
||||
### 方法一：本地运行
|
||||
|
||||
```python
|
||||
class StreamManager:
|
||||
"""全局流管理器 - 管理所有任务的 SSE 流"""
|
||||
#### 1. 创建虚拟环境
|
||||
|
||||
def __init__(self):
|
||||
# task_id -> TaskStreamQueue 映射
|
||||
self.streams: Dict[str, TaskStreamQueue] = {}
|
||||
self._lock = asyncio.Lock() # 并发控制
|
||||
```bash
|
||||
# Windows
|
||||
python -m venv venv
|
||||
venv\Scripts\activate
|
||||
|
||||
# Linux/Mac
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
```
|
||||
|
||||
- 每个 `task_id` 对应独立的 `TaskStreamQueue`
|
||||
- 使用 `asyncio.Lock` 保护字典操作
|
||||
- 定期清理已完成的流（默认每小时）
|
||||
- 序列号计数器按 `task_id` 独立维护
|
||||
|
||||
## 🚀 快速开始
|
||||
|
||||
### 1. 安装依赖
|
||||
#### 2. 安装依赖
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
### 2. 测试模块
|
||||
|
||||
运行测试脚本验证所有模块正常：
|
||||
|
||||
```bash
|
||||
python test_import.py
|
||||
```
|
||||
|
||||
预期输出：
|
||||
```
|
||||
[OK] Module Imports
|
||||
[OK] Agent Creation
|
||||
[OK] Stream Manager
|
||||
[OK] API Endpoints
|
||||
|
||||
[SUCCESS] All tests passed! System is ready.
|
||||
```
|
||||
|
||||
### 3. 配置环境变量
|
||||
|
||||
复制 `.env.example` 为 `.env` 并填入 DashScope API Key：
|
||||
#### 3. 配置环境变量
|
||||
|
||||
```bash
|
||||
# 复制模板
|
||||
cp .env.example .env
|
||||
|
||||
# 编辑 .env 文件，填入你的 DashScope API Key
|
||||
# 获取 API Key: https://dashscope.console.aliyun.com/
|
||||
```
|
||||
|
||||
编辑 `.env` 文件：
|
||||
```
|
||||
DASHSCOPE_API_KEY=sk-your-actual-api-key
|
||||
**.env 文件内容：**
|
||||
```env
|
||||
DASHSCOPE_API_KEY=your_dashscope_api_key_here
|
||||
QWEN_MODEL=qwen3.5-flash
|
||||
HOST=0.0.0.0
|
||||
PORT=8000
|
||||
```
|
||||
|
||||
获取 API Key: https://dashscope.console.aliyun.com/
|
||||
|
||||
### 4. 启动服务
|
||||
#### 4. 启动服务
|
||||
|
||||
```bash
|
||||
python main.py
|
||||
uvicorn main:app --reload --host 0.0.0.0 --port 8000
|
||||
```
|
||||
|
||||
或使用 uvicorn：
|
||||
#### 5. 访问测试页面
|
||||
|
||||
打开浏览器访问：http://localhost:8000/static/index.html
|
||||
|
||||
### 方法二：Docker 运行
|
||||
|
||||
#### 1. 构建镜像
|
||||
|
||||
```bash
|
||||
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
|
||||
docker build -t sdlc-agent-demo .
|
||||
```
|
||||
|
||||
### 4. 访问服务
|
||||
#### 2. 运行容器
|
||||
|
||||
- **API 文档**: http://localhost:8000/docs
|
||||
- **测试 UI**: http://localhost:8000/test-ui
|
||||
```bash
|
||||
docker run -d \
|
||||
-p 8000:8000 \
|
||||
-e DASHSCOPE_API_KEY=your_api_key \
|
||||
--name sdlc-demo \
|
||||
sdlc-agent-demo
|
||||
```
|
||||
|
||||
#### 3. 访问服务
|
||||
|
||||
http://localhost:8000/static/index.html
|
||||
|
||||
## 📡 API 接口
|
||||
|
||||
### POST /api/run_task
|
||||
### 1. 启动 SDLC 流程
|
||||
|
||||
启动多智能体任务
|
||||
**请求：**
|
||||
```http
|
||||
POST /api/v1/sdlc/start
|
||||
Content-Type: application/json
|
||||
|
||||
**请求体**:
|
||||
```json
|
||||
{
|
||||
"user_requirement": "开发一个在线商城系统...",
|
||||
"skip_confirmation": true
|
||||
"requirement": "开发一个用户管理系统，支持增删改查功能"
|
||||
}
|
||||
```
|
||||
|
||||
**响应**:
|
||||
**响应：**
|
||||
```json
|
||||
{
|
||||
"task_id": "550e8400-e29b-41d4-a716-446655440000",
|
||||
"status": "started",
|
||||
"message": "任务已启动..."
|
||||
"status": "processing"
|
||||
}
|
||||
```
|
||||
|
||||
### GET /api/stream/{task_id}
|
||||
### 2. SSE流式进度
|
||||
|
||||
SSE 端点，订阅任务执行日志
|
||||
|
||||
**事件格式**:
|
||||
```json
|
||||
{
|
||||
"agent": "ProductManager",
|
||||
"type": "thought",
|
||||
"content": "正在分析用户需求...",
|
||||
"timestamp": "2024-01-01T12:00:00",
|
||||
"task_id": "uuid"
|
||||
}
|
||||
**请求：**
|
||||
```http
|
||||
GET /api/v1/sdlc/stream/{task_id}
|
||||
Accept: text/event-stream
|
||||
```
|
||||
|
||||
**事件类型**:
|
||||
- `start`: 任务开始
|
||||
- `agent_start`: Agent 开始执行
|
||||
- `thought`: Agent 思考过程
|
||||
- `action`: Agent 执行动作
|
||||
- `output`: Agent 输出结果
|
||||
- `step_end`: 步骤完成
|
||||
- `end`: 任务结束
|
||||
- `error`: 发生错误
|
||||
**SSE事件格式：**
|
||||
```javascript
|
||||
event: pm_start
|
||||
data: {"stage": "需求分析", "status": "started", "timestamp": "2026-01-15T10:30:00Z"}
|
||||
|
||||
### GET /api/task/{task_id}/status
|
||||
event: pm_complete
|
||||
data: {"stage": "需求分析", "content": "SRS 文档...", "status": "completed", "timestamp": "2026-01-15T10:35:00Z"}
|
||||
|
||||
查询任务状态
|
||||
event: final_result
|
||||
data: {"stage": "交付完成", "status": "success", ...}
|
||||
```
|
||||
|
||||
### GET /api/streams
|
||||
### 3. 查询任务状态
|
||||
|
||||
列出所有活跃的 SSE 流
|
||||
```http
|
||||
GET /api/v1/sdlc/status/{task_id}
|
||||
```
|
||||
|
||||
## 🧪 使用示例
|
||||
### 4. 获取任务结果
|
||||
|
||||
### 使用 curl 测试
|
||||
```http
|
||||
GET /api/v1/sdlc/result/{task_id}
|
||||
```
|
||||
|
||||
## 🤖 智能体角色
|
||||
|
||||
### PM Agent（产品经理）
|
||||
- **角色**：资深产品需求分析师
|
||||
- **职责**：将用户需求转化为结构化 SRS 文档
|
||||
- **输出**：功能性需求、非功能性需求、验收标准
|
||||
|
||||
### QA Agent（测试工程师）
|
||||
- **角色**：高级测试架构师
|
||||
- **职责**：根据 SRS 生成自动化测试用例
|
||||
- **输出**：Pytest 测试脚本、测试场景
|
||||
|
||||
### Dev Agent（开发工程师）
|
||||
- **角色**：全栈软件工程师
|
||||
- **职责**：根据 SRS 和测试用例实现业务代码
|
||||
- **输出**：可运行的 Python 代码模块
|
||||
|
||||
## 💡 使用示例
|
||||
|
||||
### 示例需求输入
|
||||
|
||||
```
|
||||
开发一个在线书签管理系统，需要包含以下功能：
|
||||
1. 用户注册和登录（支持邮箱验证）
|
||||
2. 书签的添加、编辑、删除
|
||||
3. 书签分类和标签管理
|
||||
4. 书签搜索功能
|
||||
5. 导出/导入书签（HTML 格式）
|
||||
6. 响应式设计，支持移动端访问
|
||||
|
||||
性能要求：
|
||||
- 页面加载时间 < 2 秒
|
||||
- 支持并发用户数 > 1000
|
||||
```
|
||||
|
||||
### 预期输出
|
||||
|
||||
1. **PM Agent** → 软件需求规格说明书（包含功能列表、验收标准）
|
||||
2. **QA Agent** → Pytest 测试用例（覆盖所有核心功能）
|
||||
3. **Dev Agent** → 完整的 Python 实现代码（FastAPI + SQLite）
|
||||
|
||||
## 🔧 配置说明
|
||||
|
||||
### 模型配置
|
||||
|
||||
| 参数 | 默认值 | 说明 |
|
||||
|------|--------|------|
|
||||
| `QWEN_MODEL` | `qwen3.5-flash` | 模型名称 |
|
||||
| `QWEN_TEMPERATURE` | `0.7` | 温度参数 (0-1) |
|
||||
| `QWEN_MAX_TOKENS` | `4096` | 最大生成长度 |
|
||||
|
||||
### 服务器配置
|
||||
|
||||
| 参数 | 默认值 | 说明 |
|
||||
|------|--------|------|
|
||||
| `HOST` | `0.0.0.0` | 监听地址 |
|
||||
| `PORT` | `8000` | 监听端口 |
|
||||
| `LOG_LEVEL` | `info` | 日志级别 |
|
||||
|
||||
## 🧪 测试与验证
|
||||
|
||||
### API 测试（使用 curl）
|
||||
|
||||
```bash
|
||||
# 1. 启动任务
|
||||
curl -X POST http://localhost:8000/api/run_task \
|
||||
curl -X POST http://localhost:8000/api/v1/sdlc/start \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"user_requirement": "开发一个简单的待办事项应用",
|
||||
"skip_confirmation": true
|
||||
}'
|
||||
-d '{"requirement": "开发一个简单的待办事项应用"}'
|
||||
|
||||
# 2. 订阅 SSE 流 (使用返回的 task_id)
|
||||
curl -N http://localhost:8000/api/stream/{task_id}
|
||||
# 2. 查看 SSE流（新终端）
|
||||
curl -N http://localhost:8000/api/v1/sdlc/stream/{task_id}
|
||||
|
||||
# 3. 健康检查
|
||||
curl http://localhost:8000/health
|
||||
```
|
||||
|
||||
### Python 客户端示例
|
||||
## ⚠️ 注意事项
|
||||
|
||||
```python
|
||||
import requests
|
||||
import json
|
||||
1. **API Key 安全**：不要将 `.env` 文件提交到版本控制系统
|
||||
2. **网络要求**：需要访问 DashScope API 服务
|
||||
3. **资源消耗**：每个任务约消耗 10,000-50,000 tokens
|
||||
4. **超时设置**：SSE 连接默认超时 120 秒，可根据需要调整
|
||||
|
||||
# 启动任务
|
||||
response = requests.post(
|
||||
'http://localhost:8000/api/run_task',
|
||||
json={
|
||||
'user_requirement': '开发一个博客系统',
|
||||
'skip_confirmation': True
|
||||
}
|
||||
)
|
||||
task_data = response.json()
|
||||
task_id = task_data['task_id']
|
||||
## 🛠️ 故障排查
|
||||
|
||||
# 订阅 SSE 流
|
||||
import eventstream
|
||||
### 问题 1：无法连接到 DashScope API
|
||||
|
||||
with requests.get(
|
||||
f'http://localhost:8000/api/stream/{task_id}',
|
||||
stream=True
|
||||
) as r:
|
||||
for line in r.iter_lines():
|
||||
if line:
|
||||
data = line.decode('utf-8').replace('data: ', '')
|
||||
event = json.loads(data)
|
||||
print(f"[{event['agent']}] {event['type']}: {event['content']}")
|
||||
```
|
||||
**解决方案：**
|
||||
- 检查 API Key 是否正确
|
||||
- 确认网络连接正常
|
||||
- 验证账户余额充足
|
||||
|
||||
## 🏗️ 项目结构
|
||||
### 问题 2：SSE 连接中断
|
||||
|
||||
```
|
||||
.
|
||||
├── main.py # FastAPI 入口和路由
|
||||
├── crew_factory.py # CrewAI 工厂和事件处理器
|
||||
├── agents_config.py # Agent 配置和 Prompt 模板
|
||||
├── stream_manager.py # SSE 流管理和消息队列
|
||||
├── requirements.txt # Python 依赖
|
||||
├── test_import.py # 模块测试脚本
|
||||
├── Dockerfile # Docker 镜像构建文件
|
||||
├── docker-compose.yml # Docker Compose 配置
|
||||
├── nginx.conf # Nginx 反向代理配置
|
||||
├── .env.example # 环境变量示例
|
||||
└── README.md # 本文档
|
||||
```
|
||||
**解决方案：**
|
||||
- 检查防火墙设置
|
||||
- 增加超时时间
|
||||
- 启用前端自动重连机制
|
||||
|
||||
## ⚙️ 配置说明
|
||||
### 问题 3：智能体输出质量不佳
|
||||
|
||||
### LLM 配置
|
||||
**解决方案：**
|
||||
- 调整 Temperature 参数（降低随机性）
|
||||
- 优化 Prompt 描述
|
||||
- 增加上下文约束
|
||||
|
||||
在 `agents_config.py` 中配置：
|
||||
## 📝 许可证
|
||||
|
||||
```python
|
||||
QWEN_MODEL_CONFIG = {
|
||||
"model": "qwen-plus", # Qwen3.5-flash
|
||||
"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
"api_key_env": "DASHSCOPE_API_KEY",
|
||||
}
|
||||
```
|
||||
本项目仅供学习和演示用途。
|
||||
|
||||
### Agent 角色定制
|
||||
## 🔗 相关链接
|
||||
|
||||
在 `agents_config.py` 中修改各 Agent 的：
|
||||
- `role`: 角色名称
|
||||
- `goal`: 目标
|
||||
- `backstory`: 背景描述
|
||||
- `TASK_TEMPLATES`: 任务 Prompt 模板
|
||||
- [CrewAI 官方文档](https://docs.crewai.com/)
|
||||
- [DashScope 控制台](https://dashscope.console.aliyun.com/)
|
||||
- [FastAPI 文档](https://fastapi.tiangolo.com/)
|
||||
- [Vue3 文档](https://vuejs.org/)
|
||||
|
||||
## 🔧 高级用法
|
||||
---
|
||||
|
||||
### 自定义事件处理器
|
||||
|
||||
继承 `CrewEventsHandler` 类并重写回调方法：
|
||||
|
||||
```python
|
||||
class MyCustomHandler(CrewEventsHandler):
|
||||
def on_agent_output(self, agent, output):
|
||||
# 自定义处理逻辑
|
||||
pass
|
||||
```
|
||||
|
||||
### 调整并发策略
|
||||
|
||||
在 `stream_manager.py` 中调整队列大小和清理策略：
|
||||
|
||||
```python
|
||||
TaskStreamQueue(task_id, max_size=1000) # 默认 1000
|
||||
```
|
||||
|
||||
## 🐛 故障排查
|
||||
|
||||
### 问题：SSE 连接立即断开
|
||||
|
||||
**解决**: 确保 Nginx 配置中禁用了缓冲：
|
||||
```nginx
|
||||
proxy_buffering off;
|
||||
proxy_cache off;
|
||||
proxy_request_buffering off;
|
||||
```
|
||||
|
||||
### 问题：LLM 调用失败
|
||||
|
||||
**检查**:
|
||||
1. DASHSCOPE_API_KEY 是否正确配置
|
||||
2. 网络连接是否正常
|
||||
3. API Key 是否有足够额度
|
||||
|
||||
### 问题：内存占用过高
|
||||
|
||||
**解决**: 调整 `cleanup_old_streams` 的调用频率和保留时间
|
||||
|
||||
## 🏗️ Docker 部署
|
||||
|
||||
### 使用 Docker Compose（推荐）
|
||||
|
||||
```bash
|
||||
# 1. 设置环境变量
|
||||
export DASHSCOPE_API_KEY=sk-your-api-key
|
||||
|
||||
# 2. 启动服务
|
||||
docker-compose up -d
|
||||
|
||||
# 3. 查看日志
|
||||
docker-compose logs -f multi-agent-system
|
||||
|
||||
# 4. 停止服务
|
||||
docker-compose down
|
||||
```
|
||||
|
||||
### 生产环境部署（带 Nginx）
|
||||
|
||||
```bash
|
||||
# 使用 production profile 启动（包含 Nginx）
|
||||
docker-compose --profile production up -d
|
||||
```
|
||||
|
||||
**目录结构**：
|
||||
```
|
||||
.
|
||||
├── docker-compose.yml # Docker Compose 配置
|
||||
├── Dockerfile # 应用镜像构建文件
|
||||
├── nginx.conf # Nginx 配置（反向代理 + SSE 支持）
|
||||
├── .env # 环境变量文件
|
||||
└── ...
|
||||
```
|
||||
|
||||
### Nginx 关键配置
|
||||
|
||||
对于 SSE 流端点，Nginx 必须禁用缓冲：
|
||||
|
||||
```nginx
|
||||
location /api/stream/ {
|
||||
proxy_pass http://multi-agent-system:8000;
|
||||
|
||||
# HTTP/1.1 支持（SSE 必需）
|
||||
proxy_http_version 1.1;
|
||||
proxy_set_header Connection "";
|
||||
|
||||
# 禁用缓冲（关键）
|
||||
proxy_buffering off;
|
||||
proxy_cache off;
|
||||
proxy_request_buffering off;
|
||||
|
||||
# 长连接超时
|
||||
proxy_read_timeout 300s;
|
||||
}
|
||||
```
|
||||
|
||||
## 📝 注意事项
|
||||
|
||||
1. **生产环境部署**:
|
||||
- 限制 CORS 允许的来源域名
|
||||
- 添加 API 认证机制
|
||||
- 使用 Redis 等持久化队列替代内存队列
|
||||
|
||||
2. **性能优化**:
|
||||
- 调整 SSE 队列大小避免内存溢出
|
||||
- 限制单个任务的超时时间
|
||||
- 实现任务优先级队列
|
||||
|
||||
3. **安全考虑**:
|
||||
- 验证用户输入防止注入攻击
|
||||
- 限制请求频率防止滥用
|
||||
- 记录审计日志
|
||||
|
||||
## 📄 License
|
||||
|
||||
MIT License
|
||||
**Built with ❤️ using CrewAI + Qwen3.5-flash + FastAPI**
|
||||
|
||||
243
USAGE_GUIDE.md
243
USAGE_GUIDE.md
@@ -1,243 +0,0 @@
|
||||
# 多智能体系统使用指南
|
||||
|
||||
## 📋 目录结构
|
||||
|
||||
```
|
||||
AI_CrewAI/
|
||||
├── generated_output/ # 生成的代码和文档输出目录
|
||||
│ └── task_YYYYMMDD_HHMMSS/ # 每次任务的时间戳目录
|
||||
│ ├── PRD_产品需求文档.md # 产品需求文档
|
||||
│ ├── QA_测试计划.md # 测试计划文档
|
||||
│ ├── Dev_技术方案.md # 技术方案文档
|
||||
│ ├── Final_交付报告.md # 最终交付报告
|
||||
│ └── events_log.json # 完整事件日志
|
||||
├── code_docs/ # 文档目录
|
||||
├── example_usage.py # 使用示例脚本
|
||||
├── main.py # FastAPI服务入口
|
||||
└── USAGE_GUIDE.md # 本文件
|
||||
```
|
||||
|
||||
## 🚀 快速开始
|
||||
|
||||
### 1. 配置 API Key
|
||||
|
||||
编辑 `.env` 文件，设置您的阿里百炼 API Key：
|
||||
|
||||
```bash
|
||||
DASHSCOPE_API_KEY=sk-your-actual-api-key-here
|
||||
```
|
||||
|
||||
获取 API Key: https://dashscope.console.aliyun.com/
|
||||
|
||||
### 2. 安装依赖
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
### 3. 启动服务
|
||||
|
||||
**方式一：直接运行 Python**
|
||||
```bash
|
||||
python main.py
|
||||
```
|
||||
|
||||
**方式二：使用 uvicorn**
|
||||
```bash
|
||||
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
|
||||
```
|
||||
|
||||
### 4. 访问服务
|
||||
|
||||
- **API 文档**: http://localhost:8000/docs
|
||||
- **测试 UI**: http://localhost:8000/test-ui
|
||||
|
||||
## 📝 使用方法
|
||||
|
||||
### 方法一：通过 Web UI（推荐）
|
||||
|
||||
1. 访问 http://localhost:8000/test-ui
|
||||
2. 在输入框中输入您的需求，例如：
|
||||
```
|
||||
开发一个简单的在线待办事项应用（Todo App），包含以下功能：
|
||||
1. 用户可以注册和登录
|
||||
2. 创建、编辑、删除待办事项
|
||||
3. 标记事项为完成/未完成
|
||||
4. 按优先级和截止日期排序
|
||||
5. 基本的搜索和过滤功能
|
||||
|
||||
技术栈要求：
|
||||
- 后端：Python FastAPI
|
||||
- 数据库：SQLite
|
||||
- 前端：简单的 HTML/CSS/JavaScript
|
||||
```
|
||||
3. 点击"启动任务"按钮
|
||||
4. 实时查看各 Agent 的执行过程
|
||||
5. 完成后查看生成的文档
|
||||
|
||||
### 方法二：通过 API 调用
|
||||
|
||||
使用 curl 或任何 HTTP 客户端：
|
||||
|
||||
```bash
|
||||
# 启动任务
|
||||
curl -X POST http://localhost:8000/api/run_task \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"user_requirement": "开发一个博客系统",
|
||||
"skip_confirmation": true
|
||||
}'
|
||||
|
||||
# 返回示例：
|
||||
# {"task_id":"uuid","status":"started","message":"..."}
|
||||
```
|
||||
|
||||
然后订阅 SSE 流：
|
||||
|
||||
```bash
|
||||
curl -N http://localhost:8000/api/stream/{task_id}
|
||||
```
|
||||
|
||||
### 方法三：使用示例脚本
|
||||
|
||||
运行提供的示例脚本：
|
||||
|
||||
```bash
|
||||
python example_usage.py
|
||||
```
|
||||
|
||||
这会自动保存生成的内容到 `generated_output/` 目录。
|
||||
|
||||
## 📊 生成的内容
|
||||
|
||||
每个任务会生成以下文档：
|
||||
|
||||
### 1. PRD_产品需求文档.md
|
||||
- 项目概述
|
||||
- 功能需求列表（按优先级）
|
||||
- 用户故事和用例
|
||||
- 验收标准
|
||||
- 风险评估
|
||||
|
||||
### 2. QA_测试计划.md
|
||||
- 测试策略
|
||||
- 测试用例（正常场景 + 异常场景）
|
||||
- 性能测试方案
|
||||
- 自动化测试建议
|
||||
|
||||
### 3. Dev_技术方案.md
|
||||
- 系统架构设计
|
||||
- 技术栈选择
|
||||
- 数据库 Schema
|
||||
- API 接口设计
|
||||
- 核心代码实现
|
||||
- 部署方案
|
||||
|
||||
### 4. Final_交付报告.md
|
||||
- 交付摘要
|
||||
- 一致性检查
|
||||
- 质量评估
|
||||
- 风险提示
|
||||
- 后续行动建议
|
||||
|
||||
## 🔍 查看生成的文件
|
||||
|
||||
生成的文件保存在 `generated_output/task_YYYYMMDD_HHMMSS/` 目录下。
|
||||
|
||||
**Windows 用户**：
|
||||
```powershell
|
||||
# 打开最新生成的目录
|
||||
explorer (Get-ChildItem generated_output -Directory | Sort-Object LastWriteTime -Descending | Select-Object -First 1).FullName
|
||||
```
|
||||
|
||||
**Linux/Mac 用户**：
|
||||
```bash
|
||||
# 打开最新生成的目录
|
||||
xdg-open $(ls -td generated_output/task_* | head -n1) # Linux
|
||||
open $(ls -td generated_output/task_* | head -n1) # Mac
|
||||
```
|
||||
|
||||
或者直接在文件管理器中浏览 `generated_output/` 目录。
|
||||
|
||||
## 💡 实用技巧
|
||||
|
||||
### 1. 实时监控任务进度
|
||||
|
||||
在另一个终端窗口查看日志：
|
||||
|
||||
```bash
|
||||
# Docker Compose 方式
|
||||
docker-compose logs -f multi-agent-system
|
||||
|
||||
# 直接运行
|
||||
# 日志会自动输出到控制台
|
||||
```
|
||||
|
||||
### 2. 自定义输出目录
|
||||
|
||||
修改 `example_usage.py` 中的 `output_dir` 参数：
|
||||
|
||||
```python
|
||||
await save_generated_content(task_id, output_dir="my_custom_output")
|
||||
```
|
||||
|
||||
### 3. 批量处理多个需求
|
||||
|
||||
创建批处理脚本：
|
||||
|
||||
```python
|
||||
requirements = [
|
||||
"需求 1...",
|
||||
"需求 2...",
|
||||
"需求 3..."
|
||||
]
|
||||
|
||||
for req in requirements:
|
||||
task_id = await run_multi_agent_task(user_requirement=req)
|
||||
await save_generated_content(task_id)
|
||||
```
|
||||
|
||||
## ⚠️ 常见问题
|
||||
|
||||
### Q: 为什么没有生成文件？
|
||||
|
||||
**A**: 确保：
|
||||
1. API Key 已正确配置
|
||||
2. 网络连接正常
|
||||
3. 任务执行完成（看到"任务执行完成"事件）
|
||||
|
||||
### Q: 生成的内容在哪里？
|
||||
|
||||
**A**:
|
||||
- 默认在 `generated_output/task_时间戳/` 目录
|
||||
- 可以通过 Web UI 直接查看
|
||||
- 或在控制台查找保存路径
|
||||
|
||||
### Q: 如何重新查看生成的内容？
|
||||
|
||||
**A**:
|
||||
1. 找到对应的任务时间戳目录
|
||||
2. 打开相应的 .md 文件
|
||||
3. 使用 Markdown 阅读器或 VS Code 查看
|
||||
|
||||
### Q: 可以修改生成的文档吗？
|
||||
|
||||
**A**: 当然可以！生成的文档是 Markdown 格式，可以使用任何文本编辑器修改。
|
||||
|
||||
## 🎯 最佳实践
|
||||
|
||||
1. **明确需求描述**：需求越详细，生成的文档越准确
|
||||
2. **指定技术栈**：明确说明使用的技术和框架
|
||||
3. **设定约束条件**：如性能要求、安全要求等
|
||||
4. **迭代优化**：根据生成结果调整需求描述
|
||||
|
||||
## 📞 技术支持
|
||||
|
||||
如有问题，请查看：
|
||||
- API 文档：http://localhost:8000/docs
|
||||
- 项目 README：README.md
|
||||
- 日志输出：控制台或 Docker 日志
|
||||
|
||||
---
|
||||
|
||||
**祝您使用愉快！** 🎉
|
||||
19
agents/__init__.py
Normal file
19
agents/__init__.py
Normal file
@@ -0,0 +1,19 @@
|
||||
"""
|
||||
Agents 包初始化
|
||||
"""
|
||||
|
||||
from .pm_agent import create_pm_agent, create_pm_task, execute_pm_stage
|
||||
from .qa_agent import create_qa_agent, create_qa_task, execute_qa_stage
|
||||
from .dev_agent import create_dev_agent, create_dev_task, execute_dev_stage
|
||||
|
||||
__all__ = [
|
||||
"create_pm_agent",
|
||||
"create_pm_task",
|
||||
"execute_pm_stage",
|
||||
"create_qa_agent",
|
||||
"create_qa_task",
|
||||
"execute_qa_stage",
|
||||
"create_dev_agent",
|
||||
"create_dev_task",
|
||||
"execute_dev_stage"
|
||||
]
|
||||
145
agents/dev_agent.py
Normal file
145
agents/dev_agent.py
Normal file
@@ -0,0 +1,145 @@
|
||||
"""
|
||||
Dev Agent - 开发工程师智能体
|
||||
负责根据 SRS 和测试用例编写业务代码
|
||||
"""
|
||||
|
||||
from typing import Dict, Any
|
||||
from crewai import Agent, Task
|
||||
from models.qwen_config import get_llm
|
||||
|
||||
|
||||
def create_dev_agent() -> Agent:
|
||||
"""
|
||||
创建开发工程师智能体
|
||||
|
||||
Returns:
|
||||
Agent: Dev 智能体实例
|
||||
"""
|
||||
return Agent(
|
||||
role="全栈软件工程师",
|
||||
goal="根据软件需求规格说明书 (SRS) 和测试用例实现高质量的业务代码",
|
||||
backstory="""你是一位拥有 10 年经验的全栈软件工程师，擅长：
|
||||
1. 快速理解需求并设计合理的系统架构
|
||||
2. 编写清晰、可维护、高性能的代码
|
||||
3. 遵循 TDD（测试驱动开发）实践
|
||||
4. 遵循博世研发规范中的编码标准
|
||||
|
||||
你的代码实现必须通过所有测试用例，并满足性能和安全要求。""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=get_llm()
|
||||
)
|
||||
|
||||
|
||||
def create_dev_task(srs_document: str, test_plan: str) -> Task:
|
||||
"""
|
||||
创建代码实现任务
|
||||
|
||||
Args:
|
||||
srs_document: 软件需求规格说明书
|
||||
test_plan: 测试方案和测试用例
|
||||
|
||||
Returns:
|
||||
Task: Dev 任务实例
|
||||
"""
|
||||
return Task(
|
||||
description=f"""
|
||||
请根据以下 SRS 文档和测试方案，实现完整的业务代码：
|
||||
|
||||
【SRS 文档】
|
||||
{srs_document}
|
||||
|
||||
【测试方案】
|
||||
{test_plan}
|
||||
|
||||
【输出要求】
|
||||
请按照以下结构输出代码实现：
|
||||
|
||||
## 1. 项目结构设计
|
||||
- 1.1 目录结构
|
||||
- 1.2 模块划分
|
||||
- 1.3 依赖关系
|
||||
|
||||
## 2. 核心业务代码
|
||||
实现所有功能性需求，包含：
|
||||
```python
|
||||
# 示例：主业务逻辑
|
||||
class <ServiceName>:
|
||||
\"\"\"<服务>业务逻辑类\"\"\"
|
||||
|
||||
def __init__(self):
|
||||
# 初始化
|
||||
|
||||
def <method_name>(self, params) -> ReturnType:
|
||||
\"\"\"
|
||||
方法描述
|
||||
|
||||
Args:
|
||||
params: 参数说明
|
||||
|
||||
Returns:
|
||||
返回值说明
|
||||
\"\"\"
|
||||
# 实现逻辑
|
||||
pass
|
||||
```
|
||||
|
||||
## 3. 数据模型定义
|
||||
- 3.1 Pydantic 模型
|
||||
- 3.2 数据库模型（如需要）
|
||||
- 3.3 DTO/VO 对象
|
||||
|
||||
## 4. API 接口定义（如适用）
|
||||
- 4.1 RESTful 端点
|
||||
- 4.2 请求/响应格式
|
||||
- 4.3 错误处理
|
||||
|
||||
## 5. 配置文件
|
||||
- 5.1 环境变量配置
|
||||
- 5.2 日志配置
|
||||
- 5.3 其他配置项
|
||||
|
||||
## 6. 使用说明
|
||||
- 6.1 安装步骤
|
||||
- 6.2 运行命令
|
||||
- 6.3 配置说明
|
||||
|
||||
【注意事项】
|
||||
- 遵循 PEP 8 编码规范
|
||||
- 使用类型提示 (Type Hints)
|
||||
- 包含必要的文档字符串
|
||||
- 实现适当的错误处理
|
||||
- 确保代码可通过所有测试用例
|
||||
""",
|
||||
expected_output="完整的业务代码实现和使用说明",
|
||||
agent=create_dev_agent()
|
||||
)
|
||||
|
||||
|
||||
def execute_dev_stage(srs_document: str, test_plan: str) -> Dict[str, Any]:
|
||||
"""
|
||||
执行 Dev 阶段任务
|
||||
|
||||
Args:
|
||||
srs_document: 软件需求规格说明书
|
||||
test_plan: 测试方案和测试用例
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: 包含代码实现和执行结果
|
||||
"""
|
||||
dev_agent = create_dev_agent()
|
||||
dev_task = create_dev_task(srs_document, test_plan)
|
||||
|
||||
crew = Crew(
|
||||
agents=[dev_agent],
|
||||
tasks=[dev_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
result = crew.kickoff()
|
||||
|
||||
return {
|
||||
"stage": "代码实现",
|
||||
"implementation": result.raw,
|
||||
"status": "completed"
|
||||
}
|
||||
115
agents/pm_agent.py
Normal file
115
agents/pm_agent.py
Normal file
@@ -0,0 +1,115 @@
|
||||
"""
|
||||
PM Agent - 产品经理智能体
|
||||
负责将用户输入的非结构化需求转化为结构化软件需求规格说明书 (SRS)
|
||||
"""
|
||||
|
||||
from typing import Dict, Any
|
||||
from crewai import Agent, Task, Crew
|
||||
from models.qwen_config import get_llm
|
||||
|
||||
|
||||
def create_pm_agent() -> Agent:
|
||||
"""
|
||||
创建产品经理智能体
|
||||
|
||||
Returns:
|
||||
Agent: PM 智能体实例
|
||||
"""
|
||||
return Agent(
|
||||
role="资深产品需求分析师",
|
||||
goal="将模糊的用户需求转化为清晰、完整、可执行的软件需求规格说明书 (SRS)",
|
||||
backstory="""你是一位拥有 10 年经验的资深产品需求分析师，擅长：
|
||||
1. 快速理解用户业务场景和核心痛点
|
||||
2. 识别功能性需求和非功能性需求
|
||||
3. 定义清晰的验收标准 (Acceptance Criteria)
|
||||
4. 遵循博世研发规范，确保需求的可追溯性和可验证性
|
||||
|
||||
你的输出将作为测试和开发团队的输入，务必保证准确性和完整性。""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=get_llm()
|
||||
)
|
||||
|
||||
|
||||
def create_pm_task(requirement: str) -> Task:
|
||||
"""
|
||||
创建需求分析任务
|
||||
|
||||
Args:
|
||||
requirement: 用户需求描述
|
||||
|
||||
Returns:
|
||||
Task: PM 任务实例
|
||||
"""
|
||||
return Task(
|
||||
description=f"""
|
||||
请分析以下用户需求，生成结构化的软件需求规格说明书 (SRS)：
|
||||
|
||||
【用户需求】
|
||||
{requirement}
|
||||
|
||||
【输出要求】
|
||||
请按照以下结构输出 SRS 文档：
|
||||
|
||||
## 1. 项目概述
|
||||
- 1.1 项目背景
|
||||
- 1.2 项目目标
|
||||
- 1.3 适用范围
|
||||
|
||||
## 2. 功能性需求
|
||||
- 2.1 功能列表（使用 MoSCoW 优先级标注）
|
||||
- 2.2 功能详细描述（包含输入、处理、输出）
|
||||
- 2.3 业务流程图描述
|
||||
|
||||
## 3. 非功能性需求
|
||||
- 3.1 性能要求（响应时间、并发量等）
|
||||
- 3.2 安全要求（认证、授权、数据保护）
|
||||
- 3.3 可用性要求（易用性、可访问性）
|
||||
- 3.4 可维护性要求（日志、监控、可扩展性）
|
||||
|
||||
## 4. 验收标准 (Acceptance Criteria)
|
||||
- 4.1 功能验收标准（每个功能的通过标准）
|
||||
- 4.2 性能验收标准（量化指标）
|
||||
- 4.3 用户体验验收标准
|
||||
|
||||
## 5. 约束条件
|
||||
- 5.1 技术约束
|
||||
- 5.2 业务约束
|
||||
- 5.3 合规约束（博世研发规范）
|
||||
|
||||
【注意事项】
|
||||
- 使用清晰、无歧义的语言
|
||||
- 需求必须是可测试、可验证的
|
||||
- 优先保证核心功能的完整性
|
||||
""",
|
||||
expected_output="完整的软件需求规格说明书 (SRS)，包含功能性需求、非功能性需求和验收标准",
|
||||
agent=create_pm_agent()
|
||||
)
|
||||
|
||||
|
||||
def execute_pm_stage(requirement: str) -> Dict[str, Any]:
|
||||
"""
|
||||
执行 PM 阶段任务
|
||||
|
||||
Args:
|
||||
requirement: 用户需求描述
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: 包含 SRS 文档和执行结果
|
||||
"""
|
||||
pm_agent = create_pm_agent()
|
||||
pm_task = create_pm_task(requirement)
|
||||
|
||||
crew = Crew(
|
||||
agents=[pm_agent],
|
||||
tasks=[pm_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
result = crew.kickoff()
|
||||
|
||||
return {
|
||||
"stage": "需求分析",
|
||||
"srs_document": result.raw,
|
||||
"status": "completed"
|
||||
}
|
||||
128
agents/qa_agent.py
Normal file
128
agents/qa_agent.py
Normal file
@@ -0,0 +1,128 @@
|
||||
"""
|
||||
QA Agent - 测试工程师智能体
|
||||
负责根据 SRS 生成自动化测试用例（Pytest 格式）
|
||||
"""
|
||||
|
||||
from typing import Dict, Any
|
||||
from crewai import Agent, Task
|
||||
from models.qwen_config import get_llm
|
||||
|
||||
|
||||
def create_qa_agent() -> Agent:
|
||||
"""
|
||||
创建测试工程师智能体
|
||||
|
||||
Returns:
|
||||
Agent: QA 智能体实例
|
||||
"""
|
||||
return Agent(
|
||||
role="高级测试架构师",
|
||||
goal="根据软件需求规格说明书 (SRS) 设计并生成完整的自动化测试用例",
|
||||
backstory="""你是一位拥有 8 年经验的高级测试架构师，擅长：
|
||||
1. 基于需求文档设计全面的测试策略
|
||||
2. 编写高质量的 Pytest 自动化测试脚本
|
||||
3. 覆盖单元测试、集成测试、端到端测试
|
||||
4. 遵循博世研发规范中的测试要求
|
||||
|
||||
你的测试用例将作为开发实现的验证标准，务必保证覆盖率和可执行性。""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=get_llm()
|
||||
)
|
||||
|
||||
|
||||
def create_qa_task(srs_document: str) -> Task:
|
||||
"""
|
||||
创建测试用例生成任务
|
||||
|
||||
Args:
|
||||
srs_document: 软件需求规格说明书
|
||||
|
||||
Returns:
|
||||
Task: QA 任务实例
|
||||
"""
|
||||
return Task(
|
||||
description=f"""
|
||||
请根据以下 SRS 文档，生成完整的自动化测试用例：
|
||||
|
||||
【SRS 文档】
|
||||
{srs_document}
|
||||
|
||||
【输出要求】
|
||||
请按照以下结构输出测试方案：
|
||||
|
||||
## 1. 测试策略概述
|
||||
- 1.1 测试范围
|
||||
- 1.2 测试方法（单元测试/集成测试/E2E 测试）
|
||||
- 1.3 测试工具和技术栈
|
||||
|
||||
## 2. 测试场景列表
|
||||
- 2.1 功能测试场景（对应每个功能性需求）
|
||||
- 2.2 边界值测试场景
|
||||
- 2.3 异常场景测试
|
||||
- 2.4 性能测试场景
|
||||
|
||||
## 3. Pytest 测试代码
|
||||
为每个核心功能生成 Pytest 测试脚本，包含：
|
||||
```python
|
||||
# 测试文件：test_<feature>.py
|
||||
import pytest
|
||||
|
||||
class Test<Feature>:
|
||||
\"\"\"<功能>测试类\"\"\"
|
||||
|
||||
def test_<scenario>_(self):
|
||||
\"\"\"测试场景描述\"\"\"
|
||||
# Arrange - 准备测试数据
|
||||
# Act - 执行操作
|
||||
# Assert - 验证结果
|
||||
pass
|
||||
```
|
||||
|
||||
## 4. 测试数据准备
|
||||
- 4.1 测试 fixtures
|
||||
- 4.2 Mock 数据
|
||||
- 4.3 测试数据库种子
|
||||
|
||||
## 5. 测试执行说明
|
||||
- 5.1 运行命令
|
||||
- 5.2 环境要求
|
||||
- 5.3 预期通过率
|
||||
|
||||
【注意事项】
|
||||
- 遵循 AAA(Arrange-Act-Assert)测试模式
|
||||
- 使用描述性的测试函数命名
|
||||
- 包含充足的断言验证
|
||||
- 考虑边界条件和异常情况
|
||||
""",
|
||||
expected_output="完整的测试方案和 Pytest 测试代码",
|
||||
agent=create_qa_agent()
|
||||
)
|
||||
|
||||
|
||||
def execute_qa_stage(srs_document: str) -> Dict[str, Any]:
|
||||
"""
|
||||
执行 QA 阶段任务
|
||||
|
||||
Args:
|
||||
srs_document: 软件需求规格说明书
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: 包含测试方案和执行结果
|
||||
"""
|
||||
qa_agent = create_qa_agent()
|
||||
qa_task = create_qa_task(srs_document)
|
||||
|
||||
crew = Crew(
|
||||
agents=[qa_agent],
|
||||
tasks=[qa_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
result = crew.kickoff()
|
||||
|
||||
return {
|
||||
"stage": "测试用例设计",
|
||||
"test_plan": result.raw,
|
||||
"status": "completed"
|
||||
}
|
||||
302
agents_config.py
302
agents_config.py
@@ -1,302 +0,0 @@
|
||||
"""
|
||||
Agent 配置文件
|
||||
定义所有 Agent 的角色、目标、背景描述和任务模板
|
||||
"""
|
||||
|
||||
from typing import Dict, Any
|
||||
from crewai import Agent
|
||||
|
||||
|
||||
# Qwen3.5-flash 模型配置（阿里百炼 - DashScope）
|
||||
QWEN_MODEL_CONFIG = {
|
||||
"model": "qwen3.5-flash", # 阿里百炼 Qwen3.5-flash 对应 qwen-plus
|
||||
"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
"api_key_env": "DASHSCOPE_API_KEY",
|
||||
}
|
||||
|
||||
|
||||
def get_product_manager_agent() -> Agent:
|
||||
"""创建产品经理 Agent"""
|
||||
from crewai.llm import LLM
|
||||
|
||||
# 创建一个基础的 LLM 占位符（会在 configure_llm 中被替换）
|
||||
llm_placeholder = LLM(
|
||||
model="qwen-plus",
|
||||
api_key="placeholder", # 会被 configure_llm 替换
|
||||
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
)
|
||||
|
||||
return Agent(
|
||||
role="ProductManager",
|
||||
goal="将用户需求转化为清晰的产品需求文档 (PRD)",
|
||||
backstory="""你是一位经验丰富的产品经理，擅长理解用户需求并转化为可执行的产品规格。
|
||||
你的职责包括：
|
||||
1. 分析用户需求的核心痛点和业务价值
|
||||
2. 定义功能列表和优先级
|
||||
3. 编写详细的功能描述和验收标准
|
||||
4. 识别潜在的技术风险和业务风险""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=llm_placeholder,
|
||||
)
|
||||
|
||||
|
||||
def get_qa_engineer_agent() -> Agent:
|
||||
"""创建 QA 工程师 Agent"""
|
||||
from crewai.llm import LLM
|
||||
|
||||
# 创建一个基础的 LLM 占位符（会在 configure_llm 中被替换）
|
||||
llm_placeholder = LLM(
|
||||
model="qwen-plus",
|
||||
api_key="placeholder", # 会被 configure_llm 替换
|
||||
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
)
|
||||
|
||||
return Agent(
|
||||
role="QAEngineer",
|
||||
goal="根据产品需求制定测试计划和测试用例",
|
||||
backstory="""你是一位资深 QA 工程师，专注于软件质量保障。
|
||||
你的职责包括：
|
||||
1. 分析 PRD 文档，识别测试范围
|
||||
2. 设计测试策略（单元测试、集成测试、端到端测试）
|
||||
3. 编写详细的测试用例，包括正常场景和异常场景
|
||||
4. 定义验收标准和性能指标""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=llm_placeholder,
|
||||
)
|
||||
|
||||
|
||||
def get_software_developer_agent() -> Agent:
|
||||
"""创建软件开发工程师 Agent"""
|
||||
from crewai.llm import LLM
|
||||
|
||||
# 创建一个基础的 LLM 占位符（会在 configure_llm 中被替换）
|
||||
llm_placeholder = LLM(
|
||||
model="qwen-plus",
|
||||
api_key="placeholder", # 会被 configure_llm 替换
|
||||
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
)
|
||||
|
||||
return Agent(
|
||||
role="SoftwareDeveloper",
|
||||
goal="根据需求和测试用例设计技术方案并生成代码框架",
|
||||
backstory="""你是一位全栈软件架构师，拥有深厚的技术功底。
|
||||
你的职责包括：
|
||||
1. 根据 PRD 和测试用例设计系统架构
|
||||
2. 选择合适的技术栈和框架
|
||||
3. 设计数据库 schema 和 API 接口
|
||||
4. 生成核心模块的代码框架和关键算法实现
|
||||
5. 编写技术文档和部署指南""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=llm_placeholder,
|
||||
)
|
||||
|
||||
|
||||
def get_coordinator_agent() -> Agent:
|
||||
"""创建协调员 Agent - 负责最终审核和交付"""
|
||||
from crewai.llm import LLM
|
||||
|
||||
# 创建一个基础的 LLM 占位符（会在 configure_llm 中被替换）
|
||||
llm_placeholder = LLM(
|
||||
model="qwen-plus",
|
||||
api_key="placeholder", # 会被 configure_llm 替换
|
||||
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
)
|
||||
|
||||
return Agent(
|
||||
role="Coordinator",
|
||||
goal="审核所有产出物，确保质量并生成最终交付报告",
|
||||
backstory="""你是一位项目协调员，负责把控整体交付质量。
|
||||
你的职责包括：
|
||||
1. 审核 PRD、测试计划和技术方案的完整性
|
||||
2. 识别各文档之间的一致性和潜在冲突
|
||||
3. 汇总所有产出物，生成结构化交付报告
|
||||
4. 评估项目风险和后续建议
|
||||
5. 在需要时请求人工确认（通过 API 控制）""",
|
||||
verbose=True,
|
||||
allow_delegation=False,
|
||||
llm=llm_placeholder,
|
||||
)
|
||||
|
||||
|
||||
# 任务模板配置
|
||||
TASK_TEMPLATES = {
|
||||
"product_manager": """
|
||||
## 任务：产品需求分析
|
||||
|
||||
### 用户需求输入：
|
||||
{user_requirement}
|
||||
|
||||
### 输出要求：
|
||||
请按照以下结构输出产品需求文档 (PRD)：
|
||||
|
||||
1. **项目概述**
|
||||
- 项目背景
|
||||
- 目标用户群体
|
||||
- 核心价值主张
|
||||
|
||||
2. **功能需求列表**
|
||||
- 按优先级排序（P0/P1/P2）
|
||||
- 每个功能的详细描述
|
||||
- 用户故事格式（作为...我希望...以便...）
|
||||
|
||||
3. **非功能需求**
|
||||
- 性能要求
|
||||
- 安全性要求
|
||||
- 可用性要求
|
||||
|
||||
4. **验收标准**
|
||||
- 每个功能的验收条件
|
||||
- 关键业务指标 (KPI)
|
||||
|
||||
5. **风险评估**
|
||||
- 技术风险
|
||||
- 业务风险
|
||||
- 缓解措施
|
||||
|
||||
请使用 Markdown 格式输出，确保结构清晰、内容完整.
|
||||
""",
|
||||
|
||||
"qa_engineer": """
|
||||
## 任务：制定测试计划
|
||||
|
||||
### 输入信息：
|
||||
- 产品需求文档 (来自 ProductManager):
|
||||
{prd_content}
|
||||
|
||||
### 输出要求：
|
||||
请按照以下结构输出测试计划文档：
|
||||
|
||||
1. **测试策略**
|
||||
- 测试范围界定
|
||||
- 测试类型（单元/集成/E2E/性能/安全）
|
||||
- 测试环境规划
|
||||
|
||||
2. **测试用例设计**
|
||||
- 针对每个 P0/P1 功能设计测试用例
|
||||
- 包含：测试目的、前置条件、测试步骤、预期结果
|
||||
- 覆盖正常流程和异常流程
|
||||
|
||||
3. **自动化测试建议**
|
||||
- 推荐使用的测试框架
|
||||
- 需要自动化的测试场景列表
|
||||
- CI/CD 集成建议
|
||||
|
||||
4. **性能测试方案**
|
||||
- 压测场景设计
|
||||
- 性能基准指标
|
||||
- 监控指标
|
||||
|
||||
5. **验收检查清单**
|
||||
- 上线前必须通过的检查项
|
||||
|
||||
请使用 Markdown 格式，测试用例使用表格形式展示。
|
||||
""",
|
||||
|
||||
"software_developer": """
|
||||
## 任务：技术方案设计与代码实现
|
||||
|
||||
### 输入信息：
|
||||
- 产品需求文档：
|
||||
{prd_content}
|
||||
|
||||
- 测试计划：
|
||||
{qa_plan}
|
||||
|
||||
### 输出要求：
|
||||
请按照以下结构输出技术方案文档：
|
||||
|
||||
1. **系统架构设计**
|
||||
- 架构图（使用文字描述或 ASCII art）
|
||||
- 技术选型及理由
|
||||
- 系统组件划分
|
||||
|
||||
2. **API 接口设计**
|
||||
- RESTful API 列表（方法、路径、请求/响应格式）
|
||||
- 接口鉴权方案
|
||||
- 错误码规范
|
||||
|
||||
3. **数据模型设计**
|
||||
- 数据库表结构（表名、字段、类型、索引）
|
||||
- ER 关系描述
|
||||
- 数据迁移策略
|
||||
|
||||
4. **核心代码实现**
|
||||
- 关键模块的代码框架（Python/TypeScript 等）
|
||||
- 核心算法伪代码或实现
|
||||
- 重要设计模式的应用
|
||||
|
||||
5. **部署方案**
|
||||
- 基础设施需求
|
||||
- Docker 容器化配置示例
|
||||
- CI/CD 流水线配置建议
|
||||
|
||||
6. **开发注意事项**
|
||||
- 代码规范
|
||||
- 日志和监控
|
||||
- 安全最佳实践
|
||||
|
||||
请确保代码片段语法正确，注释清晰。
|
||||
""",
|
||||
|
||||
"coordinator": """
|
||||
## 任务：最终审核与交付报告
|
||||
|
||||
### 输入信息：
|
||||
- 产品需求文档：
|
||||
{prd_content}
|
||||
|
||||
- 测试计划：
|
||||
{qa_plan}
|
||||
|
||||
- 技术方案：
|
||||
{dev_plan}
|
||||
|
||||
### 输出要求：
|
||||
请按照以下结构输出最终交付报告：
|
||||
|
||||
1. **交付摘要**
|
||||
- 项目基本信息
|
||||
- 交付物清单
|
||||
- 整体质量评估
|
||||
|
||||
2. **一致性检查**
|
||||
- PRD 与测试计划的匹配度
|
||||
- 技术方案对需求的覆盖度
|
||||
- 发现的遗漏或不一致点
|
||||
|
||||
3. **质量评估**
|
||||
- 文档完整性评分（1-10 分）
|
||||
- 技术可行性评估
|
||||
- 测试覆盖度评估
|
||||
|
||||
4. **风险提示**
|
||||
- 高风险项列表
|
||||
- 中低风险项列表
|
||||
- 风险缓解建议
|
||||
|
||||
5. **后续行动建议**
|
||||
- 短期行动计划（1-2 周）
|
||||
- 中期目标（1-3 月）
|
||||
- 长期演进方向
|
||||
|
||||
6. **交付确认**
|
||||
- 是否满足交付标准
|
||||
- 需要人工复核的点
|
||||
- 最终结论（通过/有条件通过/不通过）
|
||||
|
||||
请使用专业、客观的语气，给出具体、可执行的建议。
|
||||
""",
|
||||
}
|
||||
|
||||
|
||||
def create_agents() -> Dict[str, Agent]:
|
||||
"""创建所有 Agent 实例"""
|
||||
return {
|
||||
"product_manager": get_product_manager_agent(),
|
||||
"qa_engineer": get_qa_engineer_agent(),
|
||||
"software_developer": get_software_developer_agent(),
|
||||
"coordinator": get_coordinator_agent(),
|
||||
}
|
||||
133
check_config.py
Normal file
133
check_config.py
Normal file
@@ -0,0 +1,133 @@
|
||||
"""
|
||||
Configuration Check Script
|
||||
Verify project configuration is correct
|
||||
"""
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def check_python_version():
|
||||
"""Check Python version"""
|
||||
print("Checking Python version...")
|
||||
if sys.version_info < (3, 10):
|
||||
print(f"[ERROR] Python version too low: {sys.version}")
|
||||
print(" Required: Python 3.10+")
|
||||
return False
|
||||
print(f"[OK] Python version: {sys.version.split()[0]}")
|
||||
return True
|
||||
|
||||
|
||||
def check_dependencies():
|
||||
"""Check required packages"""
|
||||
print("\nChecking dependencies...")
|
||||
|
||||
required_packages = {
|
||||
'crewai': 'CrewAI',
|
||||
'fastapi': 'FastAPI',
|
||||
'uvicorn': 'Uvicorn',
|
||||
'pydantic': 'Pydantic',
|
||||
'pydantic_settings': 'Pydantic Settings',
|
||||
'dotenv': 'python-dotenv'
|
||||
}
|
||||
|
||||
all_ok = True
|
||||
for package, name in required_packages.items():
|
||||
try:
|
||||
__import__(package)
|
||||
print(f"[OK] {name}: Installed")
|
||||
except ImportError:
|
||||
print(f"[ERROR] {name}: Not installed")
|
||||
all_ok = False
|
||||
|
||||
return all_ok
|
||||
|
||||
|
||||
def check_env_file():
|
||||
"""Check environment file"""
|
||||
print("\nChecking environment configuration...")
|
||||
|
||||
env_file = Path('.env')
|
||||
env_example = Path('.env.example')
|
||||
|
||||
if not env_example.exists():
|
||||
print("[ERROR] .env.example file not found")
|
||||
return False
|
||||
|
||||
print("[OK] .env.example exists")
|
||||
|
||||
if not env_file.exists():
|
||||
print("[WARNING] .env file not found. Please copy from .env.example and configure")
|
||||
print(" Command: cp .env.example .env")
|
||||
return False
|
||||
|
||||
print("[OK] .env file exists")
|
||||
|
||||
# Check API Key
|
||||
with open(env_file, 'r', encoding='utf-8') as f:
|
||||
content = f.read()
|
||||
if 'DASHSCOPE_API_KEY=your_dashscope_api_key_here' in content:
|
||||
print("[WARNING] Please configure valid DashScope API Key in .env file")
|
||||
return False
|
||||
elif 'DASHSCOPE_API_KEY=' in content:
|
||||
print("[OK] DashScope API Key configured")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
def check_project_structure():
|
||||
"""Check project structure"""
|
||||
print("\nChecking project structure...")
|
||||
|
||||
required_files = [
|
||||
'main.py',
|
||||
'agents/__init__.py',
|
||||
'agents/pm_agent.py',
|
||||
'agents/qa_agent.py',
|
||||
'agents/dev_agent.py',
|
||||
'crews/__init__.py',
|
||||
'crews/sdlc_crew.py',
|
||||
'models/__init__.py',
|
||||
'models/qwen_config.py',
|
||||
'static/index.html',
|
||||
'requirements.txt'
|
||||
]
|
||||
|
||||
all_ok = True
|
||||
for file_path in required_files:
|
||||
if Path(file_path).exists():
|
||||
print(f"[OK] {file_path}")
|
||||
else:
|
||||
print(f"[ERROR] {file_path} not found")
|
||||
all_ok = False
|
||||
|
||||
return all_ok
|
||||
|
||||
|
||||
def main():
|
||||
"""Main function"""
|
||||
print("=" * 60)
|
||||
print("SDLC Agent Demo - Configuration Check")
|
||||
print("=" * 60)
|
||||
|
||||
checks = [
|
||||
check_python_version(),
|
||||
check_dependencies(),
|
||||
check_env_file(),
|
||||
check_project_structure()
|
||||
]
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
if all(checks):
|
||||
print("All checks passed! Ready to start the service.")
|
||||
print("\nStart command:")
|
||||
print(" uvicorn main:app --reload --host 0.0.0.0 --port 8000")
|
||||
print("\nAccess URL:")
|
||||
print(" http://localhost:8000/static/index.html")
|
||||
else:
|
||||
print("Some checks failed. Please fix the issues first.")
|
||||
print("=" * 60)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
22
check_error.py
Normal file
22
check_error.py
Normal file
@@ -0,0 +1,22 @@
|
||||
import requests
|
||||
import time
|
||||
|
||||
# Start a task
|
||||
print("Starting task...")
|
||||
response = requests.post('http://localhost:8000/api/v1/sdlc/start', json={'requirement': 'test'})
|
||||
task_id = response.json()['task_id']
|
||||
print(f"Task ID: {task_id}")
|
||||
|
||||
# Wait 2 seconds
|
||||
time.sleep(2)
|
||||
|
||||
# Get status
|
||||
status = requests.get(f'http://localhost:8000/api/v1/sdlc/status/{task_id}')
|
||||
print(f"\nStatus: {status.json()}")
|
||||
|
||||
# Get events via SSE stream
|
||||
print("\nGetting events...")
|
||||
stream = requests.get(f'http://localhost:8000/api/v1/sdlc/stream/{task_id}', timeout=5)
|
||||
for line in stream.iter_lines():
|
||||
if line:
|
||||
print(line.decode('utf-8'))
|
||||
@@ -1,481 +0,0 @@
|
||||
"""
|
||||
示例代码 - 待办事项应用后端实现
|
||||
这是多智能体系统生成的代码示例
|
||||
"""
|
||||
|
||||
from fastapi import FastAPI, HTTPException, Depends, status
|
||||
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
|
||||
from pydantic import BaseModel, EmailStr, Field
|
||||
from typing import Optional, List
|
||||
from datetime import datetime, timedelta
|
||||
import uvicorn
|
||||
import sqlite3
|
||||
import hashlib
|
||||
import jwt
|
||||
|
||||
# ==================== 配置 ====================
|
||||
|
||||
SECRET_KEY = "your-secret-key-change-in-production"
|
||||
ALGORITHM = "HS256"
|
||||
DATABASE = "todo_app.db"
|
||||
|
||||
# ==================== 数据模型 ====================
|
||||
|
||||
class UserCreate(BaseModel):
|
||||
"""用户注册请求"""
|
||||
username: str = Field(..., min_length=3, max_length=50)
|
||||
email: EmailStr
|
||||
password: str = Field(..., min_length=6)
|
||||
|
||||
|
||||
class UserLogin(BaseModel):
|
||||
"""用户登录请求"""
|
||||
username: str
|
||||
password: str
|
||||
|
||||
|
||||
class TodoItemCreate(BaseModel):
|
||||
"""创建待办事项"""
|
||||
title: str = Field(..., min_length=1, max_length=200)
|
||||
description: Optional[str] = None
|
||||
priority: int = Field(default=1, ge=1, le=5) # 1-5, 5 最高
|
||||
due_date: Optional[datetime] = None
|
||||
|
||||
|
||||
class TodoItemUpdate(BaseModel):
|
||||
"""更新待办事项"""
|
||||
title: Optional[str] = Field(None, min_length=1, max_length=200)
|
||||
description: Optional[str] = None
|
||||
priority: Optional[int] = Field(None, ge=1, le=5)
|
||||
due_date: Optional[datetime] = None
|
||||
completed: Optional[bool] = None
|
||||
|
||||
|
||||
class TodoItemResponse(BaseModel):
|
||||
"""待办事项响应"""
|
||||
id: int
|
||||
user_id: int
|
||||
title: str
|
||||
description: Optional[str]
|
||||
priority: int
|
||||
completed: bool
|
||||
due_date: Optional[datetime]
|
||||
created_at: datetime
|
||||
updated_at: datetime
|
||||
|
||||
class Config:
|
||||
from_attributes = True
|
||||
|
||||
|
||||
# ==================== 数据库操作 ====================
|
||||
|
||||
def get_db_connection():
|
||||
"""获取数据库连接"""
|
||||
conn = sqlite3.connect(DATABASE)
|
||||
conn.row_factory = sqlite3.Row
|
||||
return conn
|
||||
|
||||
|
||||
def init_db():
|
||||
"""初始化数据库"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 创建用户表
|
||||
cursor.execute('''
|
||||
CREATE TABLE IF NOT EXISTS users (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
username VARCHAR(50) UNIQUE NOT NULL,
|
||||
email VARCHAR(100) UNIQUE NOT NULL,
|
||||
password_hash VARCHAR(255) NOT NULL,
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
)
|
||||
''')
|
||||
|
||||
# 创建待办事项表
|
||||
cursor.execute('''
|
||||
CREATE TABLE IF NOT EXISTS todo_items (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
user_id INTEGER NOT NULL,
|
||||
title VARCHAR(200) NOT NULL,
|
||||
description TEXT,
|
||||
priority INTEGER DEFAULT 1,
|
||||
completed BOOLEAN DEFAULT 0,
|
||||
due_date TIMESTAMP,
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
|
||||
)
|
||||
''')
|
||||
|
||||
# 创建索引
|
||||
cursor.execute('CREATE INDEX IF NOT EXISTS idx_todo_user ON todo_items(user_id)')
|
||||
cursor.execute('CREATE INDEX IF NOT EXISTS idx_todo_completed ON todo_items(completed)')
|
||||
cursor.execute('CREATE INDEX IF NOT EXISTS idx_todo_priority ON todo_items(priority DESC)')
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print("✓ 数据库初始化完成")
|
||||
|
||||
|
||||
# ==================== 认证工具 ====================
|
||||
|
||||
security = HTTPBearer()
|
||||
|
||||
|
||||
def hash_password(password: str) -> str:
|
||||
"""密码哈希"""
|
||||
return hashlib.sha256(password.encode()).hexdigest()
|
||||
|
||||
|
||||
def verify_password(password: str, password_hash: str) -> bool:
|
||||
"""验证密码"""
|
||||
return hash_password(password) == password_hash
|
||||
|
||||
|
||||
def create_access_token(data: dict, expires_delta: timedelta = timedelta(days=7)) -> str:
|
||||
"""创建 JWT Token"""
|
||||
to_encode = data.copy()
|
||||
expire = datetime.utcnow() + expires_delta
|
||||
to_encode.update({"exp": expire})
|
||||
return jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
|
||||
|
||||
|
||||
def get_current_user(
|
||||
credentials: HTTPAuthorizationCredentials = Depends(security)
|
||||
) -> dict:
|
||||
"""获取当前用户（从 JWT Token）"""
|
||||
try:
|
||||
token = credentials.credentials
|
||||
payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
|
||||
user_id = payload.get("sub")
|
||||
if user_id is None:
|
||||
raise HTTPException(status_code=401, detail="Invalid token")
|
||||
return {"user_id": int(user_id), "username": payload.get("username")}
|
||||
except jwt.PyJWTError:
|
||||
raise HTTPException(status_code=401, detail="Token validation failed")
|
||||
|
||||
|
||||
# ==================== FastAPI 应用 ====================
|
||||
|
||||
app = FastAPI(
|
||||
title="Todo App API",
|
||||
description="在线待办事项应用 - 由多智能体系统生成",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""应用启动时初始化"""
|
||||
init_db()
|
||||
|
||||
|
||||
# ==================== 用户接口 ====================
|
||||
|
||||
@app.post("/api/users/register", tags=["用户管理"])
|
||||
async def register(user_data: UserCreate):
|
||||
"""用户注册"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 检查用户名是否已存在
|
||||
cursor.execute('SELECT id FROM users WHERE username = ?', (user_data.username,))
|
||||
if cursor.fetchone():
|
||||
conn.close()
|
||||
raise HTTPException(status_code=400, detail="Username already exists")
|
||||
|
||||
# 检查邮箱是否已存在
|
||||
cursor.execute('SELECT id FROM users WHERE email = ?', (user_data.email,))
|
||||
if cursor.fetchone():
|
||||
conn.close()
|
||||
raise HTTPException(status_code=400, detail="Email already registered")
|
||||
|
||||
# 创建用户
|
||||
password_hash = hash_password(user_data.password)
|
||||
cursor.execute(
|
||||
'INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)',
|
||||
(user_data.username, user_data.email, password_hash)
|
||||
)
|
||||
conn.commit()
|
||||
user_id = cursor.lastrowid
|
||||
conn.close()
|
||||
|
||||
return {
|
||||
"message": "注册成功",
|
||||
"user_id": user_id,
|
||||
"username": user_data.username
|
||||
}
|
||||
|
||||
|
||||
@app.post("/api/users/login", tags=["用户管理"])
|
||||
async def login(credentials: UserLogin):
|
||||
"""用户登录"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 查找用户
|
||||
cursor.execute(
|
||||
'SELECT id, username, password_hash FROM users WHERE username = ?',
|
||||
(credentials.username,)
|
||||
)
|
||||
user = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
if not user or not verify_password(credentials.password, user['password_hash']):
|
||||
raise HTTPException(status_code=401, detail="Invalid username or password")
|
||||
|
||||
# 生成 Token
|
||||
access_token = create_access_token(
|
||||
data={"sub": str(user['id']), "username": user['username']}
|
||||
)
|
||||
|
||||
return {
|
||||
"message": "登录成功",
|
||||
"access_token": access_token,
|
||||
"token_type": "bearer",
|
||||
"user_id": user['id'],
|
||||
"username": user['username']
|
||||
}
|
||||
|
||||
|
||||
# ==================== 待办事项接口 ====================
|
||||
|
||||
@app.post("/api/todos", tags=["待办事项"], response_model=TodoItemResponse)
|
||||
async def create_todo(
|
||||
todo_data: TodoItemCreate,
|
||||
current_user: dict = Depends(get_current_user)
|
||||
):
|
||||
"""创建待办事项"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute('''
|
||||
INSERT INTO todo_items (user_id, title, description, priority, due_date)
|
||||
VALUES (?, ?, ?, ?, ?)
|
||||
''', (
|
||||
current_user["user_id"],
|
||||
todo_data.title,
|
||||
todo_data.description,
|
||||
todo_data.priority,
|
||||
todo_data.due_date
|
||||
))
|
||||
|
||||
conn.commit()
|
||||
todo_id = cursor.lastrowid
|
||||
|
||||
# 查询刚创建的记录
|
||||
cursor.execute('SELECT * FROM todo_items WHERE id = ?', (todo_id,))
|
||||
todo_row = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
return dict(todo_row)
|
||||
|
||||
|
||||
@app.get("/api/todos", tags=["待办事项"], response_model=List[TodoItemResponse])
|
||||
async def list_todos(
|
||||
skip: int = 0,
|
||||
limit: int = 50,
|
||||
completed: Optional[bool] = None,
|
||||
priority: Optional[int] = None,
|
||||
search: Optional[str] = None,
|
||||
sort_by: str = "priority", # priority, due_date, created_at
|
||||
current_user: dict = Depends(get_current_user)
|
||||
):
|
||||
"""获取待办事项列表（支持过滤和排序）"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 构建查询
|
||||
query = 'SELECT * FROM todo_items WHERE user_id = ?'
|
||||
params = [current_user["user_id"]]
|
||||
|
||||
# 添加过滤条件
|
||||
if completed is not None:
|
||||
query += ' AND completed = ?'
|
||||
params.append(completed)
|
||||
|
||||
if priority is not None:
|
||||
query += ' AND priority = ?'
|
||||
params.append(priority)
|
||||
|
||||
if search:
|
||||
query += ' AND (title LIKE ? OR description LIKE ?)'
|
||||
search_term = f'%{search}%'
|
||||
params.extend([search_term, search_term])
|
||||
|
||||
# 添加排序
|
||||
order_map = {
|
||||
'priority': 'priority DESC',
|
||||
'due_date': 'due_date ASC',
|
||||
'created_at': 'created_at DESC'
|
||||
}
|
||||
order_clause = order_map.get(sort_by, 'priority DESC')
|
||||
query += f' ORDER BY {order_clause}'
|
||||
|
||||
# 添加分页
|
||||
query += ' LIMIT ? OFFSET ?'
|
||||
params.extend([limit, skip])
|
||||
|
||||
cursor.execute(query, params)
|
||||
todos = cursor.fetchall()
|
||||
conn.close()
|
||||
|
||||
return [dict(todo) for todo in todos]
|
||||
|
||||
|
||||
@app.get("/api/todos/{todo_id}", tags=["待办事项"], response_model=TodoItemResponse)
|
||||
async def get_todo(
|
||||
todo_id: int,
|
||||
current_user: dict = Depends(get_current_user)
|
||||
):
|
||||
"""获取单个待办事项详情"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute(
|
||||
'SELECT * FROM todo_items WHERE id = ? AND user_id = ?',
|
||||
(todo_id, current_user["user_id"])
|
||||
)
|
||||
todo = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
if not todo:
|
||||
raise HTTPException(status_code=404, detail="Todo item not found")
|
||||
|
||||
return dict(todo)
|
||||
|
||||
|
||||
@app.put("/api/todos/{todo_id}", tags=["待办事项"], response_model=TodoItemResponse)
|
||||
async def update_todo(
|
||||
todo_id: int,
|
||||
todo_data: TodoItemUpdate,
|
||||
current_user: dict = Depends(get_current_user)
|
||||
):
|
||||
"""更新待办事项"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 检查是否存在
|
||||
cursor.execute(
|
||||
'SELECT id FROM todo_items WHERE id = ? AND user_id = ?',
|
||||
(todo_id, current_user["user_id"])
|
||||
)
|
||||
if not cursor.fetchone():
|
||||
conn.close()
|
||||
raise HTTPException(status_code=404, detail="Todo item not found")
|
||||
|
||||
# 构建更新字段
|
||||
updates = []
|
||||
params = []
|
||||
|
||||
if todo_data.title is not None:
|
||||
updates.append('title = ?')
|
||||
params.append(todo_data.title)
|
||||
|
||||
if todo_data.description is not None:
|
||||
updates.append('description = ?')
|
||||
params.append(todo_data.description)
|
||||
|
||||
if todo_data.priority is not None:
|
||||
updates.append('priority = ?')
|
||||
params.append(todo_data.priority)
|
||||
|
||||
if todo_data.completed is not None:
|
||||
updates.append('completed = ?')
|
||||
params.append(todo_data.completed)
|
||||
|
||||
if todo_data.due_date is not None:
|
||||
updates.append('due_date = ?')
|
||||
params.append(todo_data.due_date)
|
||||
|
||||
# 添加更新时间
|
||||
updates.append('updated_at = CURRENT_TIMESTAMP')
|
||||
|
||||
# 执行更新
|
||||
params.append(todo_id)
|
||||
query = f'UPDATE todo_items SET {", ".join(updates)} WHERE id = ?'
|
||||
cursor.execute(query, params)
|
||||
conn.commit()
|
||||
|
||||
# 查询更新后的记录
|
||||
cursor.execute('SELECT * FROM todo_items WHERE id = ?', (todo_id,))
|
||||
todo = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
return dict(todo)
|
||||
|
||||
|
||||
@app.delete("/api/todos/{todo_id}", tags=["待办事项"])
|
||||
async def delete_todo(
|
||||
todo_id: int,
|
||||
current_user: dict = Depends(get_current_user)
|
||||
):
|
||||
"""删除待办事项"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 检查是否存在
|
||||
cursor.execute(
|
||||
'SELECT id FROM todo_items WHERE id = ? AND user_id = ?',
|
||||
(todo_id, current_user["user_id"])
|
||||
)
|
||||
if not cursor.fetchone():
|
||||
conn.close()
|
||||
raise HTTPException(status_code=404, detail="Todo item not found")
|
||||
|
||||
# 执行删除
|
||||
cursor.execute('DELETE FROM todo_items WHERE id = ?', (todo_id,))
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
return {"message": "删除成功"}
|
||||
|
||||
|
||||
@app.get("/api/todos/stats", tags=["待办事项"])
|
||||
async def get_stats(current_user: dict = Depends(get_current_user)):
|
||||
"""获取统计信息"""
|
||||
conn = get_db_connection()
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 总数
|
||||
cursor.execute(
|
||||
'SELECT COUNT(*) as total FROM todo_items WHERE user_id = ?',
|
||||
(current_user["user_id"],)
|
||||
)
|
||||
total = cursor.fetchone()['total']
|
||||
|
||||
# 已完成
|
||||
cursor.execute(
|
||||
'SELECT COUNT(*) as completed FROM todo_items WHERE user_id = ? AND completed = 1',
|
||||
(current_user["user_id"],)
|
||||
)
|
||||
completed = cursor.fetchone()['completed']
|
||||
|
||||
# 未完成
|
||||
pending = total - completed
|
||||
|
||||
conn.close()
|
||||
|
||||
return {
|
||||
"total": total,
|
||||
"completed": completed,
|
||||
"pending": pending
|
||||
}
|
||||
|
||||
|
||||
# ==================== 主程序入口 ====================
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("=" * 60)
|
||||
print("🚀 Todo App API服务启动中...")
|
||||
print("=" * 60)
|
||||
print("\n📖 API 文档：http://localhost:8000/docs")
|
||||
print("📊 健康检查：http://localhost:8000/health\n")
|
||||
|
||||
uvicorn.run(
|
||||
"example_code:app",
|
||||
host="0.0.0.0",
|
||||
port=8000,
|
||||
reload=True
|
||||
)
|
||||
523
crew_factory.py
523
crew_factory.py
@@ -1,523 +0,0 @@
|
||||
"""
|
||||
CrewAI 工厂模块
|
||||
负责根据输入动态创建 Crew 实例，并集成 SSE 事件推送
|
||||
|
||||
技术方案说明：
|
||||
由于 CrewAI 库的事件 API 可能随版本变化，我们采用更稳定的方案：
|
||||
1. 使用自定义的 Logger 拦截 Agent 输出
|
||||
2. 在任务执行前后手动发送 SSE 事件
|
||||
3. 通过 run_in_executor 实现同步转异步
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from typing import Dict, Any, Optional, List, Callable
|
||||
from datetime import datetime
|
||||
import uuid
|
||||
import io
|
||||
import sys
|
||||
from contextlib import contextmanager
|
||||
|
||||
from crewai import Agent, Task, Crew, Process
|
||||
|
||||
from agents_config import (
|
||||
create_agents,
|
||||
TASK_TEMPLATES,
|
||||
QWEN_MODEL_CONFIG,
|
||||
)
|
||||
from stream_manager import stream_manager, StreamEvent
|
||||
|
||||
|
||||
class CrewExecutionLogger:
|
||||
"""
|
||||
CrewAI 执行日志拦截器
|
||||
|
||||
通过捕获 stdout/stderr 来实时获取 CrewAI 的执行日志，
|
||||
并将其转发到 SSE 流。这是一种稳定且非侵入式的方法。
|
||||
"""
|
||||
|
||||
def __init__(self, task_id: str, callback: Optional[Callable] = None):
|
||||
self.task_id = task_id
|
||||
self.callback = callback
|
||||
self._old_stdout = None
|
||||
self._old_stderr = None
|
||||
self._buffer = io.StringIO()
|
||||
|
||||
def _write(self, text: str):
|
||||
"""写入时触发回调"""
|
||||
self._buffer.write(text)
|
||||
|
||||
# 按行处理（遇到换行符时发送）
|
||||
if '\n' in text:
|
||||
lines = self._buffer.getvalue().split('\n')
|
||||
for line in lines[:-1]: # 除了最后一行
|
||||
if line.strip():
|
||||
self._send_line(line)
|
||||
self._buffer = io.StringIO()
|
||||
self._buffer.write(lines[-1]) # 保留未完成的行
|
||||
|
||||
def _send_line(self, line: str):
|
||||
"""发送单行日志到 SSE 流"""
|
||||
if self.callback:
|
||||
self.callback("log", "System", line.strip())
|
||||
|
||||
def start_capture(self):
|
||||
"""开始捕获输出"""
|
||||
self._old_stdout = sys.stdout
|
||||
self._old_stderr = sys.stderr
|
||||
|
||||
# 创建代理对象
|
||||
class OutputProxy:
|
||||
def __init__(self, logger, original):
|
||||
self.logger = logger
|
||||
self.original = original
|
||||
|
||||
def write(self, text):
|
||||
self.logger._write(text)
|
||||
if self.original:
|
||||
self.original.write(text)
|
||||
|
||||
def flush(self):
|
||||
if self.original:
|
||||
self.original.flush()
|
||||
|
||||
sys.stdout = OutputProxy(self, self._old_stdout)
|
||||
sys.stderr = OutputProxy(self, self._old_stderr)
|
||||
|
||||
def stop_capture(self):
|
||||
"""停止捕获输出"""
|
||||
if self._old_stdout:
|
||||
sys.stdout = self._old_stdout
|
||||
if self._old_stderr:
|
||||
sys.stderr = self._old_stderr
|
||||
|
||||
# 发送剩余内容
|
||||
remaining = self._buffer.getvalue()
|
||||
if remaining.strip():
|
||||
self._send_line(remaining)
|
||||
|
||||
|
||||
class SSECrewExecutor:
|
||||
"""
|
||||
SSE Crew 执行器
|
||||
|
||||
封装 CrewAI 的执行过程，在关键节点发送 SSE 事件。
|
||||
这是与 CrewAI 版本无关的稳定方案。
|
||||
"""
|
||||
|
||||
def __init__(self, task_id: str):
|
||||
self.task_id = task_id
|
||||
self.logger = None
|
||||
|
||||
def _send_event(self, event_type: str, agent_name: str, content: str, metadata: Optional[Dict] = None):
|
||||
"""发送 SSE 事件（同步方法，使用线程安全的方式）"""
|
||||
try:
|
||||
loop = asyncio.get_event_loop()
|
||||
|
||||
async def send_async():
|
||||
stream = await stream_manager.get_stream(self.task_id)
|
||||
if stream is None:
|
||||
return False
|
||||
|
||||
event = StreamEvent(
|
||||
event_type=event_type,
|
||||
agent=agent_name,
|
||||
content=content,
|
||||
task_id=self.task_id,
|
||||
metadata=metadata or {}
|
||||
)
|
||||
return stream.put_nowait(event)
|
||||
|
||||
future = asyncio.run_coroutine_threadsafe(send_async(), loop)
|
||||
future.result(timeout=5.0)
|
||||
except Exception as e:
|
||||
# 静默失败，不影响主流程
|
||||
pass
|
||||
|
||||
def execute(self, crew: 'Crew', inputs: Dict[str, Any]) -> Any:
|
||||
"""
|
||||
执行 Crew 任务，并在过程中发送 SSE 事件
|
||||
|
||||
Args:
|
||||
crew: CrewAI Crew 实例
|
||||
inputs: 任务输入参数
|
||||
|
||||
Returns:
|
||||
Crew 执行结果
|
||||
"""
|
||||
# 1. 发送开始事件
|
||||
self._send_event(
|
||||
event_type="start",
|
||||
agent_name="System",
|
||||
content=f"Crew 任务开始执行，共 {len(crew.agents)} 个 Agent，{len(crew.tasks)} 个任务",
|
||||
metadata={
|
||||
"agent_count": len(crew.agents),
|
||||
"task_count": len(crew.tasks)
|
||||
}
|
||||
)
|
||||
|
||||
# 2. 设置日志拦截
|
||||
def log_callback(event_type: str, agent_name: str, content: str):
|
||||
self._send_event(event_type, agent_name, content)
|
||||
|
||||
self.logger = CrewExecutionLogger(self.task_id, log_callback)
|
||||
self.logger.start_capture()
|
||||
|
||||
try:
|
||||
# 3. 遍历执行任务（手动控制以便发送事件）
|
||||
context = inputs.copy()
|
||||
last_output = None
|
||||
|
||||
for i, task in enumerate(crew.tasks):
|
||||
# 将 context 字典转换为 JSON 字符串（CrewAI 要求）
|
||||
import json
|
||||
context_str = json.dumps(context, ensure_ascii=False)
|
||||
task_result = self._execute_task(task, context_str, context, i)
|
||||
|
||||
# 更新上下文（简单的字符串替换）
|
||||
if task_result:
|
||||
context[f"task_{i}_output"] = str(task_result)
|
||||
last_output = task_result
|
||||
|
||||
# 4. 发送结束事件
|
||||
self._send_event(
|
||||
event_type="end",
|
||||
agent_name="System",
|
||||
content="Crew 任务执行完成",
|
||||
metadata={"success": True}
|
||||
)
|
||||
|
||||
return last_output
|
||||
|
||||
except Exception as e:
|
||||
# 5. 发送错误事件
|
||||
self._send_event(
|
||||
event_type="error",
|
||||
agent_name="System",
|
||||
content=str(e),
|
||||
metadata={"error_type": type(e).__name__}
|
||||
)
|
||||
raise
|
||||
|
||||
finally:
|
||||
# 6. 恢复原始输出
|
||||
self.logger.stop_capture()
|
||||
|
||||
def _execute_task(self, task: 'Task', context_str: str, context_dict: Dict[str, Any], index: int) -> Optional[Any]:
|
||||
"""
|
||||
执行单个任务
|
||||
|
||||
Args:
|
||||
task: Task 实例
|
||||
context_str: 上下文信息（JSON 字符串格式，用于传递给 CrewAI）
|
||||
context_dict: 上下文信息（字典格式，用于变量替换）
|
||||
index: 任务索引
|
||||
|
||||
Returns:
|
||||
任务执行结果
|
||||
"""
|
||||
# 获取负责此任务的 agent
|
||||
agent_name = task.agent.role if task.agent else "Unknown"
|
||||
|
||||
# 1. 发送任务开始事件
|
||||
self._send_event(
|
||||
event_type="agent_start",
|
||||
agent_name=agent_name,
|
||||
content=f"[任务 {index + 1}] {agent_name} 开始执行任务",
|
||||
metadata={
|
||||
"task_index": index,
|
||||
"task_description": task.description[:200] if task.description else ""
|
||||
}
|
||||
)
|
||||
|
||||
# 2. 准备任务描述（替换上下文变量）
|
||||
description = self._prepare_task_description(task.description, context_dict)
|
||||
|
||||
# 3. 执行任务
|
||||
try:
|
||||
# 使用 CrewAI 的原生执行方式
|
||||
result = task.execute_sync(context=context_str)
|
||||
|
||||
# 4. 发送任务完成事件
|
||||
output_str = str(result)[:500] if result else "No output"
|
||||
self._send_event(
|
||||
event_type="output",
|
||||
agent_name=agent_name,
|
||||
content=f"任务完成，输出摘要：{output_str}",
|
||||
metadata={
|
||||
"output_length": len(str(result)) if result else 0
|
||||
}
|
||||
)
|
||||
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
# 5. 发送错误事件
|
||||
self._send_event(
|
||||
event_type="error",
|
||||
agent_name=agent_name,
|
||||
content=f"任务执行失败：{str(e)}",
|
||||
metadata={"error_type": type(e).__name__}
|
||||
)
|
||||
raise
|
||||
|
||||
def _prepare_task_description(self, description: str, context: Dict[str, Any]) -> str:
|
||||
"""
|
||||
准备任务描述，替换上下文变量
|
||||
|
||||
支持以下占位符格式：
|
||||
- {prd_output}: 产品需求文档输出
|
||||
- {qa_output}: QA 测试计划输出
|
||||
- {dev_output}: 技术方案输出
|
||||
"""
|
||||
if not description:
|
||||
return ""
|
||||
|
||||
result = description
|
||||
|
||||
# 尝试从上下文中获取输出
|
||||
prd_output = context.get('prd_content', context.get('task_0_output', ''))
|
||||
qa_output = context.get('qa_plan', context.get('task_1_output', ''))
|
||||
dev_output = context.get('dev_plan', context.get('task_2_output', ''))
|
||||
|
||||
# 替换占位符
|
||||
result = result.replace('{prd_output}', str(prd_output)[:3000])
|
||||
result = result.replace('{qa_plan}', str(qa_output)[:3000])
|
||||
result = result.replace('{qa_output}', str(qa_output)[:3000])
|
||||
result = result.replace('{dev_plan}', str(dev_output)[:3000])
|
||||
result = result.replace('{dev_output}', str(dev_output)[:3000])
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def configure_llm():
|
||||
"""配置 LLM 使用 Qwen3.5-flash (DashScope/阿里百炼)"""
|
||||
import os
|
||||
|
||||
# 检查 API Key 是否配置
|
||||
dashscope_api_key = os.getenv("DASHSCOPE_API_KEY")
|
||||
if not dashscope_api_key:
|
||||
raise ValueError(
|
||||
"DASHSCOPE_API_KEY 未配置，请设置环境变量或在 .env 文件中配置"
|
||||
)
|
||||
|
||||
# 使用 CrewAI 原生的 LLM 类（通过 OpenAI 兼容接口连接 DashScope）
|
||||
from crewai.llm import LLM
|
||||
|
||||
llm = LLM(
|
||||
model=QWEN_MODEL_CONFIG["model"], # qwen-plus (Qwen3.5-flash)
|
||||
api_key=dashscope_api_key,
|
||||
base_url=QWEN_MODEL_CONFIG["base_url"], # https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
temperature=0.7,
|
||||
max_tokens=4096,
|
||||
)
|
||||
|
||||
return llm
|
||||
|
||||
|
||||
class CrewFactory:
|
||||
"""Crew 工厂类 - 负责创建和执行业务流程"""
|
||||
|
||||
@staticmethod
|
||||
def create_crew(
|
||||
task_id: str,
|
||||
user_requirement: str,
|
||||
skip_confirmation: bool = True
|
||||
) -> tuple[Crew, Dict[str, Any]]:
|
||||
"""
|
||||
创建 Crew 实例
|
||||
|
||||
Args:
|
||||
task_id: 任务 ID
|
||||
user_requirement: 用户需求描述
|
||||
skip_confirmation: 是否跳过 Coordinator 的人工确认环节
|
||||
|
||||
Returns:
|
||||
(Crew 实例，上下文信息)
|
||||
"""
|
||||
# 创建 Agents
|
||||
agents = create_agents()
|
||||
pm_agent = agents["product_manager"]
|
||||
qa_agent = agents["qa_engineer"]
|
||||
dev_agent = agents["software_developer"]
|
||||
coord_agent = agents["coordinator"]
|
||||
|
||||
# 配置 LLM
|
||||
try:
|
||||
llm = configure_llm()
|
||||
# 为每个 agent 分配 LLM
|
||||
for agent in agents.values():
|
||||
agent.llm = llm
|
||||
except ValueError as e:
|
||||
# 如果 LLM 配置失败，使用默认配置（会在运行时失败）
|
||||
print(f"警告：LLM 配置失败 - {e}")
|
||||
|
||||
# 创建任务
|
||||
# Task 1: ProductManager 分析需求
|
||||
pm_task = Task(
|
||||
description=TASK_TEMPLATES["product_manager"].format(
|
||||
user_requirement=user_requirement
|
||||
),
|
||||
expected_output="完整的产品需求文档 (PRD)，包含功能列表、验收标准和风险评估",
|
||||
agent=pm_agent,
|
||||
)
|
||||
|
||||
# Task 2: QAEngineer 制定测试计划
|
||||
qa_task = Task(
|
||||
description=TASK_TEMPLATES["qa_engineer"].format(
|
||||
prd_content="{prd_output}"
|
||||
),
|
||||
expected_output="详细的测试计划文档，包含测试策略、测试用例和性能测试方案",
|
||||
agent=qa_agent,
|
||||
context=[pm_task],
|
||||
)
|
||||
|
||||
# Task 3: SoftwareDeveloper 设计技术方案
|
||||
dev_task = Task(
|
||||
description=TASK_TEMPLATES["software_developer"].format(
|
||||
prd_content="{prd_output}",
|
||||
qa_plan="{qa_output}"
|
||||
),
|
||||
expected_output="完整的技术方案文档，包含架构设计、API 接口、数据模型和核心代码实现",
|
||||
agent=dev_agent,
|
||||
context=[pm_task, qa_task],
|
||||
)
|
||||
|
||||
# Task 4: Coordinator 最终审核
|
||||
coord_task = Task(
|
||||
description=TASK_TEMPLATES["coordinator"].format(
|
||||
prd_content="{prd_output}",
|
||||
qa_plan="{qa_output}",
|
||||
dev_plan="{dev_output}"
|
||||
),
|
||||
expected_output="最终交付报告，包含质量评估、风险提示和交付结论",
|
||||
agent=coord_agent,
|
||||
context=[pm_task, qa_task, dev_task],
|
||||
)
|
||||
|
||||
# 创建 Crew
|
||||
crew = Crew(
|
||||
agents=list(agents.values()),
|
||||
tasks=[pm_task, qa_task, dev_task, coord_task],
|
||||
process=Process.sequential,
|
||||
verbose=True,
|
||||
)
|
||||
|
||||
# 上下文信息
|
||||
context = {
|
||||
"user_requirement": user_requirement,
|
||||
"skip_confirmation": skip_confirmation,
|
||||
"created_at": datetime.now().isoformat(),
|
||||
}
|
||||
|
||||
return crew, context
|
||||
|
||||
@staticmethod
|
||||
async def execute_crew_async(
|
||||
task_id: str,
|
||||
user_requirement: str,
|
||||
skip_confirmation: bool = True
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
异步执行 Crew 任务
|
||||
|
||||
Args:
|
||||
task_id: 任务 ID
|
||||
user_requirement: 用户需求描述
|
||||
skip_confirmation: 是否跳过人工确认
|
||||
|
||||
Returns:
|
||||
执行结果摘要
|
||||
"""
|
||||
# 创建流队列
|
||||
await stream_manager.create_stream(task_id)
|
||||
|
||||
# 发送开始事件
|
||||
await stream_manager.publish_event(
|
||||
task_id=task_id,
|
||||
event_type="start",
|
||||
agent="System",
|
||||
content="任务已启动，开始处理用户需求...",
|
||||
metadata={"user_requirement": user_requirement[:200]}
|
||||
)
|
||||
|
||||
try:
|
||||
# 创建 Crew
|
||||
crew, context = CrewFactory.create_crew(
|
||||
task_id=task_id,
|
||||
user_requirement=user_requirement,
|
||||
skip_confirmation=skip_confirmation
|
||||
)
|
||||
|
||||
# 创建 SSE 执行器
|
||||
executor = SSECrewExecutor(task_id)
|
||||
|
||||
# 在线程池中执行（避免阻塞事件循环）
|
||||
loop = asyncio.get_event_loop()
|
||||
result = await loop.run_in_executor(
|
||||
None,
|
||||
lambda: executor.execute(crew, context)
|
||||
)
|
||||
|
||||
# 发送完成事件
|
||||
await stream_manager.publish_event(
|
||||
task_id=task_id,
|
||||
event_type="end",
|
||||
agent="System",
|
||||
content="任务执行完成",
|
||||
metadata={"success": True}
|
||||
)
|
||||
|
||||
return {
|
||||
"task_id": task_id,
|
||||
"status": "completed",
|
||||
"result": str(result)[:5000] if result else None,
|
||||
"context": context,
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
# 发送错误事件
|
||||
await stream_manager.publish_event(
|
||||
task_id=task_id,
|
||||
event_type="error",
|
||||
agent="System",
|
||||
content=str(e),
|
||||
metadata={"error_type": type(e).__name__}
|
||||
)
|
||||
|
||||
await stream_manager.close_stream(task_id)
|
||||
|
||||
return {
|
||||
"task_id": task_id,
|
||||
"status": "failed",
|
||||
"error": str(e),
|
||||
"error_type": type(e).__name__,
|
||||
}
|
||||
|
||||
|
||||
# 便捷函数
|
||||
async def run_multi_agent_task(
|
||||
user_requirement: str,
|
||||
skip_confirmation: bool = True
|
||||
) -> str:
|
||||
"""
|
||||
运行多智能体任务的便捷函数
|
||||
|
||||
Args:
|
||||
user_requirement: 用户需求描述
|
||||
skip_confirmation: 是否跳过人工确认
|
||||
|
||||
Returns:
|
||||
task_id: 任务 ID（用于后续 SSE 流订阅）
|
||||
"""
|
||||
task_id = str(uuid.uuid4())
|
||||
|
||||
# 异步启动任务
|
||||
asyncio.create_task(
|
||||
CrewFactory.execute_crew_async(
|
||||
task_id=task_id,
|
||||
user_requirement=user_requirement,
|
||||
skip_confirmation=skip_confirmation
|
||||
)
|
||||
)
|
||||
|
||||
return task_id
|
||||
7
crews/__init__.py
Normal file
7
crews/__init__.py
Normal file
@@ -0,0 +1,7 @@
|
||||
"""
|
||||
Crews 包初始化
|
||||
"""
|
||||
|
||||
from .sdlc_crew import SDLCCrew
|
||||
|
||||
__all__ = ["SDLCCrew"]
|
||||
176
crews/sdlc_crew.py
Normal file
176
crews/sdlc_crew.py
Normal file
@@ -0,0 +1,176 @@
|
||||
"""
|
||||
SDLC Crew - CrewAI 编排逻辑 (纯同步版本)
|
||||
负责协调 PM、QA、Dev 三个智能体按顺序执行
|
||||
"""
|
||||
|
||||
from typing import Dict, Any, Optional, Generator
|
||||
from datetime import datetime
|
||||
from crewai import Crew
|
||||
from agents.pm_agent import create_pm_agent, create_pm_task
|
||||
from agents.qa_agent import create_qa_agent, create_qa_task
|
||||
from agents.dev_agent import create_dev_agent, create_dev_task
|
||||
|
||||
|
||||
class SDLCCrew:
|
||||
"""
|
||||
SDLC 多智能体协同编排类
|
||||
实现从需求分析→测试用例→代码实现的完整流程
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""初始化 SDLC Crew"""
|
||||
self.pm_agent = create_pm_agent()
|
||||
self.qa_agent = create_qa_agent()
|
||||
self.dev_agent = create_dev_agent()
|
||||
|
||||
# 存储各阶段结果
|
||||
self.srs_document: Optional[str] = None
|
||||
self.test_plan: Optional[str] = None
|
||||
self.implementation: Optional[str] = None
|
||||
|
||||
def execute(self, requirement: str) -> Generator[Dict[str, Any], None, None]:
|
||||
"""
|
||||
执行完整的 SDLC 流程（纯同步生成器）
|
||||
|
||||
Args:
|
||||
requirement: 用户需求描述
|
||||
|
||||
Yields:
|
||||
Dict[str, Any]: 各阶段的 SSE事件
|
||||
"""
|
||||
try:
|
||||
# ========== 阶段 1: PM Agent - 需求分析 ==========
|
||||
pm_task = create_pm_task(requirement)
|
||||
pm_crew = Crew(
|
||||
agents=[self.pm_agent],
|
||||
tasks=[pm_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
# 发送开始事件
|
||||
yield {
|
||||
"event": "pm_start",
|
||||
"data": {
|
||||
"stage": "需求分析",
|
||||
"status": "started",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
|
||||
# 执行 Crew 任务
|
||||
result = pm_crew.kickoff()
|
||||
content = result.raw if hasattr(result, 'raw') else str(result)
|
||||
|
||||
# 发送完成事件
|
||||
yield {
|
||||
"event": "pm_complete",
|
||||
"data": {
|
||||
"stage": "需求分析",
|
||||
"content": content,
|
||||
"status": "completed",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
self.srs_document = content
|
||||
|
||||
# ========== 阶段 2: QA Agent - 测试用例设计 ==========
|
||||
qa_task = create_qa_task(self.srs_document)
|
||||
qa_crew = Crew(
|
||||
agents=[self.qa_agent],
|
||||
tasks=[qa_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
# 发送开始事件
|
||||
yield {
|
||||
"event": "qa_start",
|
||||
"data": {
|
||||
"stage": "测试用例设计",
|
||||
"status": "started",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
|
||||
# 执行 Crew 任务
|
||||
result = qa_crew.kickoff()
|
||||
content = result.raw if hasattr(result, 'raw') else str(result)
|
||||
|
||||
# 发送完成事件
|
||||
yield {
|
||||
"event": "qa_complete",
|
||||
"data": {
|
||||
"stage": "测试用例设计",
|
||||
"content": content,
|
||||
"status": "completed",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
self.test_plan = content
|
||||
|
||||
# ========== 阶段 3: Dev Agent - 代码实现 ==========
|
||||
dev_task = create_dev_task(self.srs_document, self.test_plan)
|
||||
dev_crew = Crew(
|
||||
agents=[self.dev_agent],
|
||||
tasks=[dev_task],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
# 发送开始事件
|
||||
yield {
|
||||
"event": "dev_start",
|
||||
"data": {
|
||||
"stage": "代码实现",
|
||||
"status": "started",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
|
||||
# 执行 Crew 任务
|
||||
result = dev_crew.kickoff()
|
||||
content = result.raw if hasattr(result, 'raw') else str(result)
|
||||
|
||||
# 发送完成事件
|
||||
yield {
|
||||
"event": "dev_complete",
|
||||
"data": {
|
||||
"stage": "代码实现",
|
||||
"content": content,
|
||||
"status": "completed",
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
self.implementation = content
|
||||
|
||||
# ========== 最终结果汇总 ==========
|
||||
yield {
|
||||
"event": "final_result",
|
||||
"data": {
|
||||
"stage": "交付完成",
|
||||
"status": "success",
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"summary": {
|
||||
"srs_length": len(self.srs_document) if self.srs_document else 0,
|
||||
"test_plan_length": len(self.test_plan) if self.test_plan else 0,
|
||||
"implementation_length": len(self.implementation) if self.implementation else 0
|
||||
},
|
||||
"deliverables": {
|
||||
"srs_document": self.srs_document,
|
||||
"test_plan": self.test_plan,
|
||||
"implementation": self.implementation
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
# 错误处理
|
||||
yield {
|
||||
"event": "error",
|
||||
"data": {
|
||||
"stage": "系统错误",
|
||||
"error": str(e),
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
}
|
||||
|
||||
# 别名，方便调用
|
||||
execute_sync = execute
|
||||
@@ -1,50 +0,0 @@
|
||||
version: '3.8'
|
||||
|
||||
services:
|
||||
multi-agent-system:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: multi-agent-delivery-system
|
||||
restart: unless-stopped
|
||||
ports:
|
||||
- "8000:8000"
|
||||
environment:
|
||||
# DashScope API Key（必需）
|
||||
- DASHSCOPE_API_KEY=${DASHSCOPE_API_KEY:sk-616332b2afa94699b4572d0fe6ac370a}
|
||||
# 可选配置
|
||||
- HOST=0.0.0.0
|
||||
- PORT=8000
|
||||
# 日志级别
|
||||
- LOG_LEVEL=info
|
||||
volumes:
|
||||
# 挂载日志目录
|
||||
- ./logs:/app/logs
|
||||
# 如果需要持久化 .env 文件
|
||||
- ./.env:/app/.env:ro
|
||||
networks:
|
||||
- agent-network
|
||||
# 资源限制
|
||||
deploy:
|
||||
resources:
|
||||
limits:
|
||||
cpus: '2.0'
|
||||
memory: 4G
|
||||
reservations:
|
||||
cpus: '0.5'
|
||||
memory: 1G
|
||||
# 健康检查
|
||||
healthcheck:
|
||||
test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
|
||||
interval: 30s
|
||||
timeout: 10s
|
||||
retries: 3
|
||||
start_period: 10s
|
||||
|
||||
networks:
|
||||
agent-network:
|
||||
driver: bridge
|
||||
|
||||
# 使用示例：
|
||||
# 开发环境：docker-compose up -d
|
||||
# 生产环境：docker-compose --profile production up -d
|
||||
947
main.py
947
main.py
@@ -1,705 +1,344 @@
|
||||
"""
|
||||
FastAPI 主入口
|
||||
提供 RESTful API 和 SSE 流式接口
|
||||
SDLC Agent Demo - FastAPI 主服务 (纯同步版本)
|
||||
多智能体端到端软件交付协同系统
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import uuid
|
||||
import threading
|
||||
from typing import Dict, Optional, Generator
|
||||
from datetime import datetime
|
||||
from typing import Dict, Any, Optional
|
||||
from contextlib import asynccontextmanager
|
||||
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from fastapi.responses import StreamingResponse, JSONResponse, HTMLResponse
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import StreamingResponse, RedirectResponse, JSONResponse
|
||||
from pydantic import BaseModel, Field
|
||||
import uvicorn
|
||||
import time
|
||||
|
||||
from crew_factory import CrewFactory, run_multi_agent_task
|
||||
from stream_manager import stream_manager, create_sse_generator
|
||||
|
||||
|
||||
# ==================== 数据模型 ====================
|
||||
|
||||
class RunTaskRequest(BaseModel):
|
||||
"""运行任务请求体"""
|
||||
user_requirement: str = Field(
|
||||
...,
|
||||
description="用户需求描述",
|
||||
example="开发一个在线商城系统，支持用户注册、商品浏览、购物车和支付功能"
|
||||
)
|
||||
skip_confirmation: bool = Field(
|
||||
default=True,
|
||||
description="是否跳过 Coordinator 的人工确认环节"
|
||||
)
|
||||
|
||||
|
||||
class RunTaskResponse(BaseModel):
|
||||
"""运行任务响应体"""
|
||||
task_id: str
|
||||
status: str
|
||||
message: Optional[str] = None
|
||||
|
||||
|
||||
class SSEEvent(BaseModel):
|
||||
"""SSE 事件数据结构"""
|
||||
agent: str
|
||||
type: str
|
||||
content: str
|
||||
timestamp: str
|
||||
task_id: str
|
||||
|
||||
|
||||
# ==================== 生命周期管理 ====================
|
||||
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
"""应用生命周期管理"""
|
||||
# 启动时执行
|
||||
print("🚀 Multi-Agent System 启动中...")
|
||||
print("📡 SSE 流服务已就绪")
|
||||
|
||||
# 启动后台任务：定期清理旧流
|
||||
asyncio.create_task(cleanup_streams_periodically())
|
||||
|
||||
yield
|
||||
|
||||
# 关闭时清理
|
||||
print("👋 正在关闭所有 SSE 流...")
|
||||
# 可以在这里添加清理逻辑
|
||||
|
||||
|
||||
# ==================== FastAPI 应用 ====================
|
||||
from crews.sdlc_crew import SDLCCrew
|
||||
from models.qwen_config import get_qwen_config
|
||||
|
||||
# ========== FastAPI 应用初始化 ==========
|
||||
app = FastAPI(
|
||||
title="Multi-Agent Software Delivery System",
|
||||
description="""
|
||||
基于 CrewAI + Qwen3.5-flash 的多智能体软件交付系统
|
||||
|
||||
## 核心功能
|
||||
- **产品需求分析**: ProductManager Agent 分析用户需求，生成 PRD
|
||||
- **测试计划制定**: QAEngineer Agent 设计测试策略和用例
|
||||
- **技术方案设计**: SoftwareDeveloper Agent 输出架构设计和代码框架
|
||||
- **质量审核**: Coordinator Agent 审核所有产出物并生成交付报告
|
||||
|
||||
## 实时通信
|
||||
支持 SSE (Server-Sent Events) 协议，实时推送每个 Agent 的思考过程和任务状态
|
||||
|
||||
## API 端点
|
||||
- `POST /api/run_task` - 启动新任务
|
||||
- `GET /api/stream/{task_id}` - 订阅任务执行日志（SSE）
|
||||
- `GET /api/task/{task_id}/status` - 查询任务状态
|
||||
- `GET /test-ui` - 测试页面
|
||||
""",
|
||||
version="1.0.0",
|
||||
lifespan=lifespan,
|
||||
title="SDLC Agent Demo",
|
||||
description="多智能体端到端软件交付协同系统 - 基于 CrewAI + Qwen3.5-flash",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
# CORS 中间件（允许跨域）
|
||||
# 启用 CORS
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"], # 生产环境应限制具体域名
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
|
||||
# ==================== 后台任务 ====================
|
||||
|
||||
async def cleanup_streams_periodically(interval: int = 300):
|
||||
"""定期清理旧的流（每 5 分钟）"""
|
||||
while True:
|
||||
await asyncio.sleep(interval)
|
||||
try:
|
||||
await stream_manager.cleanup_old_streams(max_age_seconds=3600)
|
||||
except Exception as e:
|
||||
print(f"清理流失败：{e}")
|
||||
# 挂载静态文件目录
|
||||
app.mount("/static", StaticFiles(directory="static"), name="static")
|
||||
|
||||
|
||||
# ==================== API 路由 ====================
|
||||
|
||||
@app.post(
|
||||
"/api/run_task",
|
||||
response_model=RunTaskResponse,
|
||||
summary="启动多智能体任务",
|
||||
description="接收用户需求，启动 CrewAI 流程，异步执行并立即返回 task_id"
|
||||
)
|
||||
async def run_task(request: RunTaskRequest):
|
||||
"""
|
||||
启动新的多智能体任务
|
||||
|
||||
- **user_requirement**: 用户需求描述
|
||||
- **skip_confirmation**: 是否跳过人工确认（默认 True）
|
||||
|
||||
返回 task_id 用于后续 SSE 流订阅
|
||||
"""
|
||||
try:
|
||||
# 生成 task_id 并启动任务
|
||||
task_id = await run_multi_agent_task(
|
||||
user_requirement=request.user_requirement,
|
||||
skip_confirmation=request.skip_confirmation
|
||||
)
|
||||
|
||||
return RunTaskResponse(
|
||||
task_id=task_id,
|
||||
status="started",
|
||||
message="任务已启动，请通过 /api/stream/{task_id} 订阅执行日志"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail=f"启动任务失败：{str(e)}"
|
||||
)
|
||||
# ========== 数据模型 ==========
|
||||
class StartRequest(BaseModel):
|
||||
"""启动请求模型"""
|
||||
requirement: str = Field(..., description="用户需求描述", min_length=10)
|
||||
|
||||
|
||||
@app.get(
|
||||
"/api/stream/{task_id}",
|
||||
summary="订阅任务执行日志 (SSE)",
|
||||
description="建立 SSE 连接，实时接收任务执行过程中的所有事件"
|
||||
)
|
||||
async def stream_task_logs(task_id: str):
|
||||
"""
|
||||
SSE 端点 - 实时推送任务执行日志
|
||||
# ========== 任务管理（内存存储） ==========
|
||||
class TaskManager:
|
||||
"""任务管理器 - 负责任务状态持久化"""
|
||||
|
||||
事件类型包括:
|
||||
- **start**: 任务开始
|
||||
- **agent_start**: Agent 开始执行
|
||||
- **thought**: Agent 思考过程
|
||||
- **action**: Agent 执行动作
|
||||
- **output**: Agent 输出结果
|
||||
- **step_end**: 步骤完成
|
||||
- **end**: 任务结束
|
||||
- **error**: 发生错误
|
||||
def __init__(self):
|
||||
self.tasks: Dict[str, Dict] = {}
|
||||
self._lock = threading.Lock()
|
||||
|
||||
数据格式:
|
||||
```json
|
||||
{
|
||||
"agent": "ProductManager",
|
||||
"type": "thought",
|
||||
"content": "正在分析用户需求...",
|
||||
"timestamp": "2024-01-01T12:00:00",
|
||||
"task_id": "uuid"
|
||||
def create_task(self, requirement: str) -> str:
|
||||
"""创建新任务"""
|
||||
task_id = str(uuid.uuid4())
|
||||
with self._lock:
|
||||
self.tasks[task_id] = {
|
||||
"task_id": task_id,
|
||||
"requirement": requirement,
|
||||
"status": "pending",
|
||||
"created_at": datetime.now().isoformat(),
|
||||
"updated_at": datetime.now().isoformat(),
|
||||
"events": []
|
||||
}
|
||||
```
|
||||
"""
|
||||
# 检查任务是否存在
|
||||
stream = await stream_manager.get_stream(task_id)
|
||||
if stream is None:
|
||||
# 任务不存在，返回错误
|
||||
return StreamingResponse(
|
||||
iter([f"data: {json.dumps({'error': 'Task not found', 'task_id': task_id})}\n\n"]),
|
||||
media_type="text/event-stream"
|
||||
)
|
||||
return task_id
|
||||
|
||||
def update_task_status(self, task_id: str, status: str):
|
||||
"""更新任务状态"""
|
||||
with self._lock:
|
||||
if task_id in self.tasks:
|
||||
self.tasks[task_id]["status"] = status
|
||||
self.tasks[task_id]["updated_at"] = datetime.now().isoformat()
|
||||
|
||||
def add_event(self, task_id: str, event: dict):
|
||||
"""添加事件"""
|
||||
with self._lock:
|
||||
if task_id in self.tasks:
|
||||
self.tasks[task_id]["events"].append(event)
|
||||
self.tasks[task_id]["updated_at"] = datetime.now().isoformat()
|
||||
|
||||
def get_task(self, task_id: str) -> Optional[Dict]:
|
||||
"""获取任务信息"""
|
||||
with self._lock:
|
||||
return self.tasks.get(task_id).copy() if task_id in self.tasks else None
|
||||
|
||||
def get_events_after(self, task_id: str, last_index: int):
|
||||
"""获取指定索引之后的事件"""
|
||||
with self._lock:
|
||||
if task_id not in self.tasks:
|
||||
return []
|
||||
events = self.tasks[task_id]["events"]
|
||||
return [e.copy() for e in events[last_index:]]
|
||||
|
||||
|
||||
# 全局任务管理器
|
||||
task_manager = TaskManager()
|
||||
|
||||
|
||||
# ========== API 端点 ==========
|
||||
@app.post("/api/v1/sdlc/start", response_model=Dict[str, str])
|
||||
async def start_sdlc_process(request: StartRequest):
|
||||
"""
|
||||
启动 SDLC 流程（后台线程执行）
|
||||
"""
|
||||
# 验证配置
|
||||
try:
|
||||
get_qwen_config()
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
# 创建任务
|
||||
task_id = task_manager.create_task(request.requirement)
|
||||
|
||||
# 在后台线程中执行 SDLC 流程
|
||||
thread = threading.Thread(
|
||||
target=execute_sdlc_flow,
|
||||
args=(task_id, request.requirement),
|
||||
daemon=True
|
||||
)
|
||||
thread.start()
|
||||
|
||||
return {
|
||||
"task_id": task_id,
|
||||
"status": "processing"
|
||||
}
|
||||
|
||||
|
||||
def execute_sdlc_flow(task_id: str, requirement: str):
|
||||
"""
|
||||
同步执行 SDLC 流程（在后台线程中运行）
|
||||
"""
|
||||
task_manager.update_task_status(task_id, "processing")
|
||||
|
||||
try:
|
||||
crew = SDLCCrew()
|
||||
|
||||
# 同步执行并收集所有事件
|
||||
for event in crew.execute_sync(requirement):
|
||||
task_manager.add_event(task_id, event)
|
||||
|
||||
# 标记完成
|
||||
task_manager.update_task_status(task_id, "completed")
|
||||
|
||||
except Exception as e:
|
||||
task_manager.update_task_status(task_id, "failed")
|
||||
task_manager.add_event(task_id, {
|
||||
"event": "error",
|
||||
"data": {
|
||||
"error": str(e),
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
})
|
||||
|
||||
|
||||
@app.get("/api/v1/sdlc/stream/{task_id}")
|
||||
def stream_task_progress(task_id: str):
|
||||
"""
|
||||
SSE流式输出任务进度（同步生成器）
|
||||
"""
|
||||
# 验证任务存在
|
||||
task = task_manager.get_task(task_id)
|
||||
if not task:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
def event_generator():
|
||||
"""生成 SSE事件（同步）"""
|
||||
last_event_index = 0
|
||||
max_wait_time = 300 # 最多等待 5 分钟
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
while True:
|
||||
# 检查超时
|
||||
if time.time() - start_time > max_wait_time:
|
||||
break
|
||||
|
||||
# 获取新事件
|
||||
events = task_manager.get_events_after(task_id, last_event_index)
|
||||
|
||||
for event in events:
|
||||
event_type = event.get("event", "message")
|
||||
event_data = event.get("data", {})
|
||||
|
||||
yield f"event: {event_type}\ndata: {json.dumps(event_data, ensure_ascii=False)}\n\n"
|
||||
last_event_index += 1
|
||||
|
||||
# 如果是结束事件，断开连接
|
||||
if event_type in ["final_result", "error"]:
|
||||
return
|
||||
|
||||
# 检查任务状态
|
||||
task_data = task_manager.get_task(task_id)
|
||||
if task_data and task_data["status"] in ["completed", "failed"]:
|
||||
break
|
||||
|
||||
# 等待一下再检查
|
||||
time.sleep(0.5)
|
||||
|
||||
# 创建 SSE 流
|
||||
return StreamingResponse(
|
||||
create_sse_generator(task_id),
|
||||
event_generator(),
|
||||
media_type="text/event-stream",
|
||||
headers={
|
||||
"Cache-Control": "no-cache",
|
||||
"Connection": "keep-alive",
|
||||
"X-Accel-Buffering": "no", # Nginx 禁用缓冲
|
||||
"X-Accel-Buffering": "no"
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@app.get(
|
||||
"/api/task/{task_id}/status",
|
||||
summary="查询任务状态",
|
||||
description="获取任务的当前状态和基本信息"
|
||||
)
|
||||
async def get_task_status(task_id: str):
|
||||
"""查询任务状态"""
|
||||
stream = await stream_manager.get_stream(task_id)
|
||||
|
||||
if stream is None:
|
||||
return {"task_id": task_id, "status": "not_found"}
|
||||
@app.get("/api/v1/sdlc/status/{task_id}")
|
||||
def get_task_status(task_id: str):
|
||||
"""
|
||||
获取任务状态（非流式）
|
||||
"""
|
||||
task = task_manager.get_task(task_id)
|
||||
if not task:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
return {
|
||||
"task_id": task_id,
|
||||
"status": "closed" if stream.is_closed else "running",
|
||||
"queue_size": stream.queue.qsize() if hasattr(stream, 'queue') else 0,
|
||||
"task_id": task["task_id"],
|
||||
"status": task["status"],
|
||||
"created_at": task["created_at"],
|
||||
"updated_at": task["updated_at"],
|
||||
"events_count": len(task["events"])
|
||||
}
|
||||
|
||||
|
||||
@app.get(
|
||||
"/api/streams",
|
||||
summary="列出所有活跃流",
|
||||
description="查看当前所有正在执行的任务"
|
||||
)
|
||||
async def list_active_streams():
|
||||
"""列出所有活跃的 SSE 流"""
|
||||
streams = stream_manager.list_active_streams()
|
||||
return {
|
||||
"total": len(streams),
|
||||
"streams": streams
|
||||
@app.get("/api/v1/sdlc/result/{task_id}")
|
||||
def get_task_result(task_id: str):
|
||||
"""
|
||||
获取任务完整结果
|
||||
"""
|
||||
task = task_manager.get_task(task_id)
|
||||
if not task:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
if task["status"] != "completed":
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"Task not completed yet. Status: {task['status']}"
|
||||
)
|
||||
|
||||
return task
|
||||
|
||||
|
||||
@app.get("/api/v1/sdlc/download/{task_id}")
|
||||
def download_result(task_id: str):
|
||||
"""
|
||||
打包下载任务结果（ZIP 文件）
|
||||
"""
|
||||
import zipfile
|
||||
import io
|
||||
from fastapi.responses import StreamingResponse
|
||||
|
||||
task = task_manager.get_task(task_id)
|
||||
if not task:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
if task["status"] != "completed":
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"Task not completed yet. Status: {task['status']}"
|
||||
)
|
||||
|
||||
# 创建 ZIP 文件
|
||||
zip_buffer = io.BytesIO()
|
||||
|
||||
with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zip_file:
|
||||
# 1. SRS 文档
|
||||
srs_content = ""
|
||||
for event in task["events"]:
|
||||
if event["event"] == "pm_complete":
|
||||
srs_content = event["data"].get("content", "")
|
||||
break
|
||||
zip_file.writestr("01_SRS_需求规格说明书.md", srs_content)
|
||||
|
||||
# 2. 测试用例
|
||||
test_content = ""
|
||||
for event in task["events"]:
|
||||
if event["event"] == "qa_complete":
|
||||
test_content = event["data"].get("content", "")
|
||||
break
|
||||
zip_file.writestr("02_Test_测试用例.md", test_content)
|
||||
|
||||
# 3. 代码实现
|
||||
code_content = ""
|
||||
for event in task["events"]:
|
||||
if event["event"] == "dev_complete":
|
||||
code_content = event["data"].get("content", "")
|
||||
break
|
||||
zip_file.writestr("03_Code_代码实现.md", code_content)
|
||||
|
||||
# 4. 项目摘要
|
||||
summary = f"""# SDLC 项目交付摘要
|
||||
|
||||
## 项目信息
|
||||
- 任务 ID: {task['task_id']}
|
||||
- 创建时间：{task['created_at']}
|
||||
- 完成时间：{task['updated_at']}
|
||||
- 原始需求：{task['requirement']}
|
||||
|
||||
## 交付物清单
|
||||
1. 01_SRS_需求规格说明书.md - 软件需求规格说明书
|
||||
2. 02_Test_测试用例.md - 测试方案与用例
|
||||
3. 03_Code_代码实现.md - 业务代码实现
|
||||
|
||||
## 生成说明
|
||||
本项目由 SDLC Agent Demo 自动生成
|
||||
基于 CrewAI + Qwen3.5-flash + FastAPI
|
||||
"""
|
||||
zip_file.writestr("README_项目摘要.md", summary)
|
||||
|
||||
# 准备下载
|
||||
zip_buffer.seek(0)
|
||||
|
||||
return StreamingResponse(
|
||||
zip_buffer,
|
||||
media_type="application/zip",
|
||||
headers={
|
||||
"Content-Disposition": f"attachment; filename=SDLC_Result_{task_id[:8]}.zip"
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@app.get(
|
||||
"/health",
|
||||
summary="健康检查",
|
||||
description="检查服务是否正常运行"
|
||||
)
|
||||
async def health_check():
|
||||
@app.get("/")
|
||||
def root():
|
||||
"""根路径重定向到测试页面"""
|
||||
return RedirectResponse(url="/static/index.html")
|
||||
|
||||
|
||||
@app.get("/health")
|
||||
def health_check():
|
||||
"""健康检查端点"""
|
||||
return {
|
||||
"status": "healthy",
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"service": "Multi-Agent Software Delivery System"
|
||||
}
|
||||
return {"status": "healthy", "version": "1.0.0"}
|
||||
|
||||
|
||||
# ==================== 测试页面 ====================
|
||||
|
||||
@app.get(
|
||||
"/test-ui",
|
||||
response_class=HTMLResponse,
|
||||
summary="测试 UI 页面",
|
||||
description="一个简单的 HTML 页面，用于测试 SSE 流功能"
|
||||
)
|
||||
async def test_ui():
|
||||
"""返回测试页面"""
|
||||
return HTMLResponse(content=get_test_page_html())
|
||||
|
||||
|
||||
def get_test_page_html() -> str:
|
||||
"""生成测试页面 HTML"""
|
||||
return """<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>多智能体系统 - 测试 UI</title>
|
||||
<style>
|
||||
* {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
body {
|
||||
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
min-height: 100vh;
|
||||
padding: 20px;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 1200px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
h1 {
|
||||
color: white;
|
||||
text-align: center;
|
||||
margin-bottom: 30px;
|
||||
font-size: 2.5em;
|
||||
text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
|
||||
}
|
||||
|
||||
.card {
|
||||
background: white;
|
||||
border-radius: 10px;
|
||||
padding: 25px;
|
||||
margin-bottom: 20px;
|
||||
box-shadow: 0 10px 40px rgba(0,0,0,0.2);
|
||||
}
|
||||
|
||||
.input-group {
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
label {
|
||||
display: block;
|
||||
margin-bottom: 8px;
|
||||
font-weight: 600;
|
||||
color: #333;
|
||||
}
|
||||
|
||||
textarea {
|
||||
width: 100%;
|
||||
min-height: 120px;
|
||||
padding: 12px;
|
||||
border: 2px solid #e0e0e0;
|
||||
border-radius: 6px;
|
||||
font-size: 14px;
|
||||
resize: vertical;
|
||||
transition: border-color 0.3s;
|
||||
}
|
||||
|
||||
textarea:focus {
|
||||
outline: none;
|
||||
border-color: #667eea;
|
||||
}
|
||||
|
||||
.checkbox-group {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
}
|
||||
|
||||
button {
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: white;
|
||||
border: none;
|
||||
padding: 12px 30px;
|
||||
border-radius: 6px;
|
||||
font-size: 16px;
|
||||
font-weight: 600;
|
||||
cursor: pointer;
|
||||
transition: transform 0.2s, box-shadow 0.2s;
|
||||
}
|
||||
|
||||
button:hover {
|
||||
transform: translateY(-2px);
|
||||
box-shadow: 0 5px 20px rgba(102, 126, 234, 0.4);
|
||||
}
|
||||
|
||||
button:disabled {
|
||||
opacity: 0.6;
|
||||
cursor: not-allowed;
|
||||
transform: none;
|
||||
}
|
||||
|
||||
.status-bar {
|
||||
background: #f5f5f5;
|
||||
padding: 15px;
|
||||
border-radius: 6px;
|
||||
margin-bottom: 20px;
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
}
|
||||
|
||||
.status-indicator {
|
||||
display: inline-block;
|
||||
width: 12px;
|
||||
height: 12px;
|
||||
border-radius: 50%;
|
||||
margin-right: 8px;
|
||||
}
|
||||
|
||||
.status-idle { background: #ccc; }
|
||||
.status-running { background: #4caf50; animation: pulse 1s infinite; }
|
||||
.status-error { background: #f44336; }
|
||||
|
||||
@keyframes pulse {
|
||||
0%, 100% { opacity: 1; }
|
||||
50% { opacity: 0.5; }
|
||||
}
|
||||
|
||||
.event-log {
|
||||
background: #1e1e1e;
|
||||
color: #d4d4d4;
|
||||
border-radius: 6px;
|
||||
padding: 15px;
|
||||
max-height: 600px;
|
||||
overflow-y: auto;
|
||||
font-family: 'Consolas', 'Monaco', monospace;
|
||||
font-size: 13px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
|
||||
.event-item {
|
||||
padding: 8px 12px;
|
||||
margin-bottom: 8px;
|
||||
border-left: 3px solid;
|
||||
background: rgba(255,255,255,0.05);
|
||||
border-radius: 0 4px 4px 0;
|
||||
}
|
||||
|
||||
.event-start { border-color: #2196f3; }
|
||||
.event-thought { border-color: #ff9800; }
|
||||
.event-output { border-color: #4caf50; }
|
||||
.event-end { border-color: #9c27b0; }
|
||||
.event-error { border-color: #f44336; background: rgba(244, 67, 54, 0.1); }
|
||||
|
||||
.event-header {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
margin-bottom: 5px;
|
||||
font-size: 12px;
|
||||
color: #aaa;
|
||||
}
|
||||
|
||||
.event-agent {
|
||||
font-weight: 600;
|
||||
color: #667eea;
|
||||
}
|
||||
|
||||
.event-type {
|
||||
padding: 2px 8px;
|
||||
border-radius: 3px;
|
||||
background: rgba(102, 126, 234, 0.2);
|
||||
color: #667eea;
|
||||
}
|
||||
|
||||
.event-content {
|
||||
color: #d4d4d4;
|
||||
white-space: pre-wrap;
|
||||
word-break: break-word;
|
||||
}
|
||||
|
||||
.clear-btn {
|
||||
background: #f44336;
|
||||
padding: 8px 16px;
|
||||
font-size: 14px;
|
||||
}
|
||||
|
||||
.example-requirements {
|
||||
margin-top: 15px;
|
||||
}
|
||||
|
||||
.example-btn {
|
||||
background: #f5f5f5;
|
||||
color: #333;
|
||||
padding: 8px 16px;
|
||||
font-size: 13px;
|
||||
margin-right: 10px;
|
||||
margin-bottom: 10px;
|
||||
border: 1px solid #ddd;
|
||||
}
|
||||
|
||||
.example-btn:hover {
|
||||
background: #e0e0e0;
|
||||
transform: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<h1>🤖 多智能体软件交付系统</h1>
|
||||
|
||||
<!-- 控制面板 -->
|
||||
<div class="card">
|
||||
<div class="input-group">
|
||||
<label for="requirement">用户需求描述：</label>
|
||||
<textarea
|
||||
id="requirement"
|
||||
placeholder="请输入您的需求，例如：开发一个在线商城系统，支持用户注册、商品浏览、购物车和支付功能..."
|
||||
></textarea>
|
||||
|
||||
<div class="example-requirements">
|
||||
<strong>示例需求：</strong><br>
|
||||
<button class="example-btn" onclick="useExample('mall')">在线商城</button>
|
||||
<button class="example-btn" onclick="useExample('blog')">博客系统</button>
|
||||
<button class="example-btn" onclick="useExample('task')">任务管理</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="input-group">
|
||||
<div class="checkbox-group">
|
||||
<input type="checkbox" id="skipConfirmation" checked>
|
||||
<label for="skipConfirmation" style="margin: 0;">跳过人工确认环节</label>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<button id="startBtn" onclick="startTask()">🚀 启动任务</button>
|
||||
</div>
|
||||
|
||||
<!-- 状态栏 -->
|
||||
<div class="card">
|
||||
<div class="status-bar">
|
||||
<div>
|
||||
<span class="status-indicator status-idle" id="statusIndicator"></span>
|
||||
<span id="statusText">等待中...</span>
|
||||
</div>
|
||||
<div>
|
||||
<strong>Task ID:</strong> <span id="taskIdDisplay">-</span>
|
||||
</div>
|
||||
<button class="clear-btn" onclick="clearLog()">清空日志</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 事件日志 -->
|
||||
<div class="card">
|
||||
<h2 style="margin-bottom: 15px;">📊 实时事件日志</h2>
|
||||
<div class="event-log" id="eventLog">
|
||||
<div style="color: #666; text-align: center; padding: 40px;">
|
||||
暂无事件，点击上方"启动任务"按钮开始
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
let currentTaskId = null;
|
||||
let eventSource = null;
|
||||
|
||||
// 示例需求
|
||||
const examples = {
|
||||
mall: '开发一个在线商城系统，支持用户注册登录、商品分类浏览、搜索功能、购物车管理、订单创建和支付宝/微信支付集成。需要包含后台管理系统用于商品上架和订单处理。',
|
||||
blog: '构建一个个人博客系统，支持 Markdown 编辑器、文章分类和标签、评论功能、SEO 优化。还需要有访客统计、文章阅读量统计，以及响应式设计适配移动端。',
|
||||
task: '创建一个团队协作任务管理工具，类似简化版 Jira。支持创建项目、分解任务、分配负责人、设置优先级和截止日期、进度跟踪。需要有看板视图和甘特图展示。'
|
||||
};
|
||||
|
||||
function useExample(type) {
|
||||
document.getElementById('requirement').value = examples[type];
|
||||
}
|
||||
|
||||
function updateStatus(status, text) {
|
||||
const indicator = document.getElementById('statusIndicator');
|
||||
indicator.className = `status-indicator status-${status}`;
|
||||
document.getElementById('statusText').textContent = text;
|
||||
}
|
||||
|
||||
function addEventToLog(event) {
|
||||
const log = document.getElementById('eventLog');
|
||||
|
||||
// 清除初始提示
|
||||
if (log.querySelector('[style*="text-align: center"]')) {
|
||||
log.innerHTML = '';
|
||||
}
|
||||
|
||||
const eventDiv = document.createElement('div');
|
||||
eventDiv.className = `event-item event-${event.type}`;
|
||||
|
||||
const time = new Date(event.timestamp).toLocaleTimeString();
|
||||
|
||||
eventDiv.innerHTML = `
|
||||
<div class="event-header">
|
||||
<span class="event-agent">${escapeHtml(event.agent)}</span>
|
||||
<span>
|
||||
<span class="event-type">${event.type}</span>
|
||||
<span style="margin-left: 10px;">${time}</span>
|
||||
</span>
|
||||
</div>
|
||||
<div class="event-content">${escapeHtml(event.content)}</div>
|
||||
`;
|
||||
|
||||
log.appendChild(eventDiv);
|
||||
log.scrollTop = log.scrollHeight;
|
||||
}
|
||||
|
||||
function escapeHtml(text) {
|
||||
const div = document.createElement('div');
|
||||
div.textContent = text;
|
||||
return div.innerHTML;
|
||||
}
|
||||
|
||||
async function startTask() {
|
||||
const requirement = document.getElementById('requirement').value.trim();
|
||||
if (!requirement) {
|
||||
alert('请输入用户需求描述');
|
||||
return;
|
||||
}
|
||||
|
||||
const skipConfirmation = document.getElementById('skipConfirmation').checked;
|
||||
|
||||
try {
|
||||
updateStatus('running', '任务启动中...');
|
||||
document.getElementById('startBtn').disabled = true;
|
||||
|
||||
const response = await fetch('/api/run_task', {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
user_requirement: requirement,
|
||||
skip_confirmation: skipConfirmation
|
||||
})
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP ${response.status}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
currentTaskId = data.task_id;
|
||||
document.getElementById('taskIdDisplay').textContent = currentTaskId;
|
||||
|
||||
// 连接 SSE
|
||||
connectSSE(currentTaskId);
|
||||
|
||||
} catch (error) {
|
||||
console.error('启动任务失败:', error);
|
||||
updateStatus('error', '启动失败：' + error.message);
|
||||
document.getElementById('startBtn').disabled = false;
|
||||
}
|
||||
}
|
||||
|
||||
function connectSSE(taskId) {
|
||||
// 关闭旧的连接
|
||||
if (eventSource) {
|
||||
eventSource.close();
|
||||
}
|
||||
|
||||
const eventSourceUrl = `/api/stream/${taskId}`;
|
||||
eventSource = new EventSource(eventSourceUrl);
|
||||
|
||||
eventSource.onopen = () => {
|
||||
console.log('SSE 连接已建立');
|
||||
updateStatus('running', '任务执行中...');
|
||||
};
|
||||
|
||||
eventSource.onmessage = (event) => {
|
||||
try {
|
||||
const data = JSON.parse(event.data);
|
||||
|
||||
// 忽略连接结束事件
|
||||
if (data.type === 'connection_end') {
|
||||
return;
|
||||
}
|
||||
|
||||
addEventToLog(data);
|
||||
|
||||
// 如果是结束或错误事件，更新状态
|
||||
if (data.type === 'end') {
|
||||
updateStatus('idle', '任务已完成');
|
||||
document.getElementById('startBtn').disabled = false;
|
||||
eventSource.close();
|
||||
} else if (data.type === 'error') {
|
||||
updateStatus('error', '发生错误');
|
||||
document.getElementById('startBtn').disabled = false;
|
||||
}
|
||||
|
||||
} catch (e) {
|
||||
console.error('解析事件数据失败:', e);
|
||||
}
|
||||
};
|
||||
|
||||
eventSource.onerror = (error) => {
|
||||
console.error('SSE 错误:', error);
|
||||
// 不立即显示错误，等待服务端发送的 error 事件
|
||||
};
|
||||
}
|
||||
|
||||
function clearLog() {
|
||||
document.getElementById('eventLog').innerHTML = `
|
||||
<div style="color: #666; text-align: center; padding: 40px;">
|
||||
暂无事件，点击上方"启动任务"按钮开始
|
||||
</div>
|
||||
`;
|
||||
currentTaskId = null;
|
||||
document.getElementById('taskIdDisplay').textContent = '-';
|
||||
if (eventSource) {
|
||||
eventSource.close();
|
||||
eventSource = null;
|
||||
}
|
||||
updateStatus('idle', '等待中...');
|
||||
document.getElementById('startBtn').disabled = false;
|
||||
}
|
||||
</script>
|
||||
</body>
|
||||
</html>"""
|
||||
|
||||
|
||||
# ==================== 主程序入口 ====================
|
||||
|
||||
# ========== 主程序入口 ==========
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
|
||||
# 加载环境变量
|
||||
try:
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv()
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
uvicorn.run(
|
||||
"main:app",
|
||||
host="0.0.0.0",
|
||||
|
||||
7
models/__init__.py
Normal file
7
models/__init__.py
Normal file
@@ -0,0 +1,7 @@
|
||||
"""
|
||||
Models 包初始化
|
||||
"""
|
||||
|
||||
from .qwen_config import QwenConfig, get_qwen_config, get_llm
|
||||
|
||||
__all__ = ["QwenConfig", "get_qwen_config", "get_llm"]
|
||||
83
models/qwen_config.py
Normal file
83
models/qwen_config.py
Normal file
@@ -0,0 +1,83 @@
|
||||
"""
|
||||
Qwen3.5-flash 模型配置模块
|
||||
通过 DashScope OpenAI 兼容 API 调用通义千问模型
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import Optional
|
||||
from crewai import LLM
|
||||
from pydantic_settings import BaseSettings
|
||||
|
||||
|
||||
class QwenConfig(BaseSettings):
|
||||
"""Qwen 模型配置类"""
|
||||
|
||||
api_key: str = "sk-616332b2afa94699b4572d0fe6ac370a"
|
||||
base_url: str = "https://dashscope.aliyuncs.com/compatible-mode/v1"
|
||||
model_name: str = "qwen3.5-flash"
|
||||
temperature: float = 0.7
|
||||
max_tokens: int = 4096
|
||||
|
||||
class Config:
|
||||
env_file = ".env"
|
||||
extra = "ignore"
|
||||
|
||||
def get_llm(self) -> LLM:
|
||||
"""
|
||||
获取 CrewAI LLM 实例
|
||||
|
||||
Returns:
|
||||
LLM: CrewAI LLM 对象
|
||||
"""
|
||||
return LLM(
|
||||
model=self.model_name,
|
||||
base_url=self.base_url,
|
||||
api_key=self.api_key,
|
||||
temperature=self.temperature,
|
||||
max_tokens=self.max_tokens
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def load_from_env(cls) -> "QwenConfig":
|
||||
"""
|
||||
从环境变量加载配置
|
||||
|
||||
Returns:
|
||||
QwenConfig: 配置实例
|
||||
"""
|
||||
config = cls()
|
||||
if not config.api_key:
|
||||
raise ValueError(
|
||||
"DASHSCOPE_API_KEY 未设置，请在 .env 文件中配置或在 https://dashscope.console.aliyun.com/ 获取 API Key"
|
||||
)
|
||||
return config
|
||||
|
||||
|
||||
# 全局配置实例（延迟初始化）
|
||||
_qwen_config: Optional[QwenConfig] = None
|
||||
|
||||
|
||||
def get_qwen_config() -> QwenConfig:
|
||||
"""
|
||||
获取全局 Qwen 配置实例
|
||||
|
||||
Returns:
|
||||
QwenConfig: 配置实例
|
||||
|
||||
Raises:
|
||||
ValueError: 如果 API Key 未设置
|
||||
"""
|
||||
global _qwen_config
|
||||
if _qwen_config is None:
|
||||
_qwen_config = QwenConfig.load_from_env()
|
||||
return _qwen_config
|
||||
|
||||
|
||||
def get_llm() -> LLM:
|
||||
"""
|
||||
获取全局 LLM 实例
|
||||
|
||||
Returns:
|
||||
LLM: CrewAI LLM 对象
|
||||
"""
|
||||
return get_qwen_config().get_llm()
|
||||
129
nginx.conf
129
nginx.conf
@@ -1,129 +0,0 @@
|
||||
events {
|
||||
worker_connections 1024;
|
||||
}
|
||||
|
||||
http {
|
||||
# 上游服务器配置
|
||||
upstream multi_agent_backend {
|
||||
server multi-agent-system:8000;
|
||||
keepalive 32;
|
||||
}
|
||||
|
||||
# 日志格式
|
||||
log_format main '$remote_addr - $remote_user [$time_local] "$request" '
|
||||
'$status $body_bytes_sent "$http_referer" '
|
||||
'"$http_user_agent" "$http_x_forwarded_for"';
|
||||
|
||||
access_log /var/log/nginx/access.log main;
|
||||
error_log /var/log/nginx/error.log warn;
|
||||
|
||||
# 连接超时设置
|
||||
proxy_connect_timeout 60s;
|
||||
proxy_send_timeout 60s;
|
||||
proxy_read_timeout 60s;
|
||||
|
||||
# SSE 特殊配置：禁用缓冲
|
||||
# 这对于 Server-Sent Events 至关重要
|
||||
map $http_accept $sse_connection {
|
||||
default "keep-alive";
|
||||
"text/event-stream" "keep-alive";
|
||||
}
|
||||
|
||||
server {
|
||||
listen 80;
|
||||
server_name localhost;
|
||||
|
||||
# 客户端请求体大小限制
|
||||
client_max_body_size 10M;
|
||||
|
||||
# API 代理配置
|
||||
location /api/ {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
|
||||
# 必要的代理头
|
||||
proxy_set_header Host $host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
||||
proxy_set_header X-Forwarded-Proto $scheme;
|
||||
|
||||
# HTTP/1.1 支持（SSE 必需）
|
||||
proxy_http_version 1.1;
|
||||
proxy_set_header Connection "";
|
||||
|
||||
# 禁用缓冲（SSE 关键配置）
|
||||
proxy_buffering off;
|
||||
proxy_cache off;
|
||||
proxy_request_buffering off;
|
||||
|
||||
# Chunked 传输编码
|
||||
chunked_transfer_encoding on;
|
||||
}
|
||||
|
||||
# SSE 流端点特殊配置
|
||||
location /api/stream/ {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
|
||||
# 代理头
|
||||
proxy_set_header Host $host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
||||
|
||||
# HTTP/1.1 和 Connection
|
||||
proxy_http_version 1.1;
|
||||
proxy_set_header Connection "";
|
||||
|
||||
# SSE 关键：完全禁用缓冲
|
||||
proxy_buffering off;
|
||||
proxy_cache off;
|
||||
proxy_request_buffering off;
|
||||
|
||||
# Nginx 特殊指令：禁用 FastCGI 缓冲
|
||||
fastcgi_buffering off;
|
||||
|
||||
# 保持长连接
|
||||
proxy_connect_timeout 60s;
|
||||
proxy_send_timeout 300s;
|
||||
proxy_read_timeout 300s;
|
||||
|
||||
# SSE 心跳
|
||||
proxy_ignore_client_abort off;
|
||||
}
|
||||
|
||||
# 测试 UI 页面
|
||||
location /test-ui {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
proxy_set_header Host $host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
}
|
||||
|
||||
# 健康检查端点
|
||||
location /health {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
access_log off;
|
||||
}
|
||||
|
||||
# API 文档
|
||||
location /docs {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
proxy_set_header Host $host;
|
||||
}
|
||||
|
||||
location /openapi.json {
|
||||
proxy_pass http://multi_agent_backend;
|
||||
proxy_set_header Host $host;
|
||||
}
|
||||
}
|
||||
|
||||
# HTTPS 配置（可选，取消注释启用）
|
||||
# server {
|
||||
# listen 443 ssl http2;
|
||||
# server_name your-domain.com;
|
||||
#
|
||||
# ssl_certificate /etc/nginx/ssl/fullchain.pem;
|
||||
# ssl_certificate_key /etc/nginx/ssl/privkey.pem;
|
||||
# ssl_protocols TLSv1.2 TLSv1.3;
|
||||
# ssl_ciphers HIGH:!aNULL:!MD5;
|
||||
#
|
||||
# # 同样的代理配置...
|
||||
# }
|
||||
}
|
||||
@@ -1,10 +1,31 @@
|
||||
fastapi==0.109.0
|
||||
uvicorn[standard]==0.27.0
|
||||
crewai==0.51.0
|
||||
langchain==0.1.0
|
||||
langchain-community==0.0.10
|
||||
dashscope==1.14.1
|
||||
python-dotenv==1.0.0
|
||||
pydantic==2.5.3
|
||||
uuid6==2024.1.12
|
||||
sse-starlette==2.0.0
|
||||
# AI 框架核心
|
||||
crewai>=0.85.0
|
||||
crewai-tools>=0.14.0
|
||||
|
||||
# Web 框架
|
||||
fastapi>=0.109.0
|
||||
uvicorn[standard]>=0.27.0
|
||||
python-multipart>=0.0.6
|
||||
|
||||
# SSE 支持
|
||||
sse-starlette>=2.0.0
|
||||
|
||||
# 异步处理
|
||||
asyncio>=3.4.3
|
||||
aiofiles>=23.2.1
|
||||
|
||||
# 工具库
|
||||
pydantic>=2.5.0
|
||||
pydantic-settings>=2.1.0
|
||||
python-dotenv>=1.0.0
|
||||
|
||||
# HTTP 客户端
|
||||
httpx>=0.26.0
|
||||
requests>=2.31.0
|
||||
|
||||
# 代码高亮和格式化
|
||||
pygments>=2.17.0
|
||||
|
||||
# 测试（可选）
|
||||
pytest>=7.4.0
|
||||
pytest-asyncio>=0.23.0
|
||||
|
||||
25
start.bat
Normal file
25
start.bat
Normal file
@@ -0,0 +1,25 @@
|
||||
@echo off
|
||||
chcp 65001 >nul
|
||||
echo ============================================================
|
||||
echo SDLC Agent Demo - Quick Start Script
|
||||
echo ============================================================
|
||||
echo.
|
||||
|
||||
REM Check if .env file exists
|
||||
if not exist ".env" (
|
||||
echo [WARNING] .env file not found!
|
||||
echo Please copy .env.example to .env and configure your API key:
|
||||
echo copy .env.example .env
|
||||
echo.
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo [INFO] Starting FastAPI server...
|
||||
echo [INFO] Access URL: http://localhost:8000/static/index.html
|
||||
echo [INFO] Press Ctrl+C to stop the server
|
||||
echo.
|
||||
|
||||
python -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
|
||||
|
||||
pause
|
||||
655
static/index.html
Normal file
655
static/index.html
Normal file
@@ -0,0 +1,655 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>SDLC Agent Demo - 多智能体软件交付协同系统</title>
|
||||
|
||||
<!-- TailwindCSS -->
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
|
||||
<!-- Vue 3 -->
|
||||
<script src="https://unpkg.com/vue@3/dist/vue.global.js"></script>
|
||||
|
||||
<!-- Highlight.js 代码高亮 - 使用浅色主题 -->
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/github.min.css">
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js"></script>
|
||||
|
||||
<!-- Marked Markdown 解析 -->
|
||||
<script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
|
||||
|
||||
<style>
|
||||
/* 自定义样式 */
|
||||
.stage-card {
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.stage-card.active {
|
||||
transform: scale(1.02);
|
||||
box-shadow: 0 10px 25px rgba(59, 130, 246, 0.3);
|
||||
}
|
||||
|
||||
.stage-card.completed {
|
||||
border-color: #10B981;
|
||||
background: linear-gradient(135deg, #ECFDF5 0%, #FFFFFF 100%);
|
||||
}
|
||||
|
||||
.stage-card.processing {
|
||||
border-color: #3B82F6;
|
||||
animation: pulse 2s infinite;
|
||||
}
|
||||
|
||||
@keyframes pulse {
|
||||
0%, 100% { box-shadow: 0 0 0 0 rgba(59, 130, 246, 0.4); }
|
||||
50% { box-shadow: 0 0 0 10px rgba(59, 130, 246, 0); }
|
||||
}
|
||||
|
||||
.markdown-body {
|
||||
font-size: 0.875rem;
|
||||
line-height: 1.7;
|
||||
}
|
||||
|
||||
.markdown-body pre {
|
||||
background: #f6f8fa;
|
||||
padding: 1rem;
|
||||
border-radius: 0.5rem;
|
||||
margin: 0.5rem 0;
|
||||
overflow-x: auto;
|
||||
border: 1px solid #e1e4e8;
|
||||
}
|
||||
|
||||
.markdown-body code {
|
||||
font-family: 'Consolas', 'Monaco', monospace;
|
||||
color: #24292e;
|
||||
}
|
||||
|
||||
.markdown-body h1, .markdown-body h2, .markdown-body h3 {
|
||||
margin-top: 1rem;
|
||||
margin-bottom: 0.5rem;
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.markdown-body ul, .markdown-body ol {
|
||||
padding-left: 1.5rem;
|
||||
margin: 0.5rem 0;
|
||||
}
|
||||
|
||||
/* SSE 连接状态指示器 */
|
||||
.connection-status {
|
||||
display: inline-block;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border-radius: 50%;
|
||||
margin-right: 0.5rem;
|
||||
}
|
||||
|
||||
.connection-connected {
|
||||
background-color: #10B981;
|
||||
}
|
||||
|
||||
.connection-disconnected {
|
||||
background-color: #EF4444;
|
||||
}
|
||||
|
||||
.connection-connecting {
|
||||
background-color: #F59E0B;
|
||||
animation: blink 1s infinite;
|
||||
}
|
||||
|
||||
@keyframes blink {
|
||||
0%, 100% { opacity: 1; }
|
||||
50% { opacity: 0.3; }
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body class="bg-gray-50 min-h-screen">
|
||||
<div id="app" class="min-h-screen">
|
||||
<!-- 顶部导航栏 -->
|
||||
<header class="bg-white shadow-sm border-b border-gray-200">
|
||||
<div class="max-w-7xl mx-auto px-4 py-4 sm:px-6 lg:px-8">
|
||||
<div class="flex items-center justify-between">
|
||||
<div class="flex items-center">
|
||||
<div class="flex-shrink-0">
|
||||
<svg class="h-8 w-8 text-blue-600" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9.75 17L9 20l-1 1h8l-1-1-.75-3M3 13h18M5 17h14a2 2 0 002-2V5a2 2 0 00-2-2H5a2 2 0 00-2 2v10a2 2 0 002 2z"/>
|
||||
</svg>
|
||||
</div>
|
||||
<div class="ml-4">
|
||||
<h1 class="text-xl font-bold text-gray-900">SDLC Agent Demo</h1>
|
||||
<p class="text-sm text-gray-500">多智能体端到端软件交付协同系统</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="flex items-center space-x-4">
|
||||
<div class="flex items-center text-sm">
|
||||
<span :class="['connection-status', connectionStatusClass]"></span>
|
||||
<span class="text-gray-600">{{ connectionStatusText }}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<!-- 主内容区 -->
|
||||
<main class="max-w-7xl mx-auto px-4 py-8 sm:px-6 lg:px-8">
|
||||
<!-- 需求输入区 -->
|
||||
<div class="bg-white rounded-lg shadow-md p-6 mb-6">
|
||||
<h2 class="text-lg font-semibold text-gray-900 mb-4">1. 输入软件需求</h2>
|
||||
<div class="space-y-4">
|
||||
<textarea
|
||||
v-model="requirement"
|
||||
rows="5"
|
||||
placeholder="请输入您的软件需求描述，例如： 开发一个用户管理系统，支持用户的增删改查功能，需要包含以下特性： - 用户注册和登录 - 用户信息管理 - 角色权限控制 - 操作日志记录"
|
||||
class="w-full px-4 py-3 border border-gray-300 rounded-lg focus:ring-2 focus:ring-blue-500 focus:border-transparent resize-none"
|
||||
:disabled="isProcessing"
|
||||
></textarea>
|
||||
<div class="flex items-center justify-between">
|
||||
<p class="text-sm text-gray-500">
|
||||
当前任务 ID: {{ taskId || '无' }}
|
||||
</p>
|
||||
<button
|
||||
@click="startSDLCProcess"
|
||||
:disabled="!canStart || isProcessing"
|
||||
:class="[
|
||||
'px-6 py-2.5 rounded-lg font-medium text-white transition-all duration-200',
|
||||
canStart && !isProcessing
|
||||
? 'bg-blue-600 hover:bg-blue-700 shadow-md hover:shadow-lg'
|
||||
: 'bg-gray-400 cursor-not-allowed'
|
||||
]"
|
||||
>
|
||||
{{ isProcessing ? '执行中...' : '开始执行' }}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 进度展示区 -->
|
||||
<div class="mb-6" v-show="stages.length > 0">
|
||||
<h2 class="text-lg font-semibold text-gray-900 mb-4">2. 执行进度</h2>
|
||||
<div class="grid grid-cols-1 md:grid-cols-4 gap-4">
|
||||
<div
|
||||
v-for="(stage, index) in stages"
|
||||
:key="stage.id"
|
||||
:class="[
|
||||
'stage-card rounded-lg border-2 p-4 bg-white',
|
||||
{ 'active': stage.status === 'processing' },
|
||||
{ 'completed': stage.status === 'completed' },
|
||||
{ 'processing': stage.status === 'processing' }
|
||||
]"
|
||||
>
|
||||
<div class="flex items-center mb-2">
|
||||
<div
|
||||
:class="[
|
||||
'w-8 h-8 rounded-full flex items-center justify-center mr-3',
|
||||
getStageIconClass(stage.status)
|
||||
]"
|
||||
>
|
||||
<span class="text-white font-bold text-sm">{{ index + 1 }}</span>
|
||||
</div>
|
||||
<div>
|
||||
<h3 class="font-medium text-gray-900">{{ stage.name }}</h3>
|
||||
<p class="text-xs text-gray-500">{{ stage.agent }}</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="mt-3">
|
||||
<span :class="[
|
||||
'inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium',
|
||||
getStageBadgeClass(stage.status)
|
||||
]">
|
||||
{{ getStageStatusText(stage.status) }}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 实时日志区 -->
|
||||
<div class="bg-white rounded-lg shadow-md p-6 mb-6" v-show="logs.length > 0">
|
||||
<div class="flex items-center justify-between mb-4">
|
||||
<h2 class="text-lg font-semibold text-gray-900">3. 实时日志</h2>
|
||||
<button
|
||||
@click="clearLogs"
|
||||
class="text-sm text-gray-500 hover:text-gray-700"
|
||||
>
|
||||
清空日志
|
||||
</button>
|
||||
</div>
|
||||
<div class="bg-gray-900 rounded-lg p-4 h-64 overflow-y-auto font-mono text-sm">
|
||||
<div v-for="(log, index) in logs" :key="index" class="mb-1">
|
||||
<span class="text-gray-500">{{ log.timestamp }}</span>
|
||||
<span :class="getLogLevelClass(log.event)" class="ml-2">[{{ log.event }}]</span>
|
||||
<span class="text-gray-300 ml-2">{{ log.message }}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 结果展示区 -->
|
||||
<div class="space-y-6" v-show="results.length > 0">
|
||||
<div class="flex items-center justify-between">
|
||||
<h2 class="text-lg font-semibold text-gray-900">4. 输出结果</h2>
|
||||
<button
|
||||
@click="downloadResults"
|
||||
:disabled="!isCompleted"
|
||||
:class="[
|
||||
'px-4 py-2 rounded-lg font-medium text-white transition-all duration-200 flex items-center',
|
||||
isCompleted
|
||||
? 'bg-green-600 hover:bg-green-700 shadow-md'
|
||||
: 'bg-gray-400 cursor-not-allowed'
|
||||
]"
|
||||
>
|
||||
<svg class="w-4 h-4 mr-2" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"/>
|
||||
</svg>
|
||||
{{ isCompleted ? '打包下载结果' : '执行完成后下载' }}
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<div v-for="(result, index) in results" :key="index" class="bg-white rounded-lg shadow-md overflow-hidden">
|
||||
<div
|
||||
@click="result.expanded = !result.expanded"
|
||||
class="px-6 py-4 bg-gray-50 border-b border-gray-200 cursor-pointer hover:bg-gray-100 transition-colors"
|
||||
>
|
||||
<div class="flex items-center justify-between">
|
||||
<div class="flex items-center">
|
||||
<svg
|
||||
:class="['w-5 h-5 mr-2 text-gray-500 transform transition-transform', result.expanded ? 'rotate-90' : '']"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
viewBox="0 0 24 24"
|
||||
>
|
||||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 5l7 7-7 7"/>
|
||||
</svg>
|
||||
<h3 class="font-semibold text-gray-900">{{ result.title }}</h3>
|
||||
</div>
|
||||
<div class="flex items-center space-x-2">
|
||||
<span class="text-xs text-gray-500">{{ formatDate(result.timestamp) }}</span>
|
||||
<button
|
||||
@click.stop="copyToClipboard(result.content)"
|
||||
class="text-sm text-blue-600 hover:text-blue-700"
|
||||
>
|
||||
复制
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div v-show="result.expanded" class="p-6">
|
||||
<div class="markdown-body" v-html="renderMarkdown(result.content)"></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</main>
|
||||
|
||||
<!-- 页脚 -->
|
||||
<footer class="bg-white border-t border-gray-200 mt-12">
|
||||
<div class="max-w-7xl mx-auto px-4 py-6 sm:px-6 lg:px-8">
|
||||
<p class="text-center text-sm text-gray-500">
|
||||
基于 CrewAI + Qwen3.5-flash + FastAPI(SSE) 构建 | Bosch Demo
|
||||
</p>
|
||||
</div>
|
||||
</footer>
|
||||
|
||||
<!-- 复制成功提示 -->
|
||||
<div v-if="showCopyToast" class="fixed bottom-4 right-4 bg-green-600 text-white px-6 py-3 rounded-lg shadow-lg transition-opacity duration-300">
|
||||
✓ 已复制到剪贴板
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
const { createApp } = Vue;
|
||||
|
||||
createApp({
|
||||
data() {
|
||||
return {
|
||||
// 需求输入
|
||||
requirement: '',
|
||||
|
||||
// 任务管理
|
||||
taskId: null,
|
||||
isProcessing: false,
|
||||
|
||||
// SSE 连接
|
||||
eventSource: null,
|
||||
connectionStatus: 'disconnected', // 'connecting', 'connected', 'disconnected'
|
||||
|
||||
// 阶段定义
|
||||
stages: [],
|
||||
|
||||
// 实时日志
|
||||
logs: [],
|
||||
|
||||
// 结果数据
|
||||
results: [],
|
||||
|
||||
// UI 状态
|
||||
showCopyToast: false
|
||||
}
|
||||
},
|
||||
|
||||
computed: {
|
||||
canStart() {
|
||||
return this.requirement.trim().length >= 10 && !this.isProcessing;
|
||||
},
|
||||
|
||||
connectionStatusClass() {
|
||||
const statusMap = {
|
||||
'connecting': 'connection-connecting',
|
||||
'connected': 'connection-connected',
|
||||
'disconnected': 'connection-disconnected'
|
||||
};
|
||||
return statusMap[this.connectionStatus];
|
||||
},
|
||||
|
||||
connectionStatusText() {
|
||||
const textMap = {
|
||||
'connecting': '连接中...',
|
||||
'connected': '已连接',
|
||||
'disconnected': '未连接'
|
||||
};
|
||||
return textMap[this.connectionStatus];
|
||||
},
|
||||
|
||||
isCompleted() {
|
||||
return this.stages.length > 0 &&
|
||||
this.stages.every(s => s.status === 'completed');
|
||||
}
|
||||
},
|
||||
|
||||
methods: {
|
||||
/**
|
||||
* 下载打包结果
|
||||
*/
|
||||
downloadResults() {
|
||||
if (!this.taskId || !this.isCompleted) return;
|
||||
|
||||
const url = `/api/v1/sdlc/download/${this.taskId}`;
|
||||
window.open(url, '_blank');
|
||||
},
|
||||
|
||||
/**
|
||||
* 启动 SDLC 流程
|
||||
*/
|
||||
async startSDLCProcess() {
|
||||
if (!this.canStart) return;
|
||||
|
||||
try {
|
||||
this.isProcessing = true;
|
||||
this.stages = [];
|
||||
this.logs = [];
|
||||
this.results = [];
|
||||
|
||||
// 调用 API 启动任务
|
||||
const response = await fetch('/api/v1/sdlc/start', {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json'
|
||||
},
|
||||
body: JSON.stringify({
|
||||
requirement: this.requirement
|
||||
})
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP ${response.status}: ${response.statusText}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
this.taskId = data.task_id;
|
||||
this.addLog('system', '任务已启动', `Task ID: ${data.task_id}`);
|
||||
|
||||
// 初始化阶段
|
||||
this.initStages();
|
||||
|
||||
// 连接 SSE
|
||||
this.connectSSE(data.task_id);
|
||||
|
||||
} catch (error) {
|
||||
console.error('启动失败:', error);
|
||||
this.addLog('error', '启动失败', error.message);
|
||||
this.isProcessing = false;
|
||||
alert(`启动失败：${error.message}`);
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* 初始化阶段
|
||||
*/
|
||||
initStages() {
|
||||
this.stages = [
|
||||
{ id: 'pm', name: '需求分析', agent: 'PM Agent', status: 'pending' },
|
||||
{ id: 'qa', name: '测试设计', agent: 'QA Agent', status: 'pending' },
|
||||
{ id: 'dev', name: '代码实现', agent: 'Dev Agent', status: 'pending' },
|
||||
{ id: 'final', name: '交付完成', agent: 'Orchestrator', status: 'pending' }
|
||||
];
|
||||
},
|
||||
|
||||
/**
|
||||
* 连接 SSE
|
||||
*/
|
||||
connectSSE(taskId) {
|
||||
const url = `/api/v1/sdlc/stream/${taskId}`;
|
||||
|
||||
this.connectionStatus = 'connecting';
|
||||
this.addLog('system', 'SSE', `连接到：${url}`);
|
||||
|
||||
this.eventSource = new EventSource(url);
|
||||
|
||||
// 连接成功
|
||||
this.eventSource.onopen = () => {
|
||||
this.connectionStatus = 'connected';
|
||||
this.addLog('system', 'SSE', '连接成功');
|
||||
};
|
||||
|
||||
// PM 阶段
|
||||
this.eventSource.addEventListener('pm_start', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('pm', 'processing');
|
||||
this.addLog('pm_start', 'PM Agent', '开始需求分析...');
|
||||
});
|
||||
|
||||
this.eventSource.addEventListener('pm_complete', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('pm', 'completed');
|
||||
this.addLog('pm_complete', 'PM Agent', '需求分析完成');
|
||||
this.addResult('📋 软件需求规格说明书 (SRS)', data.content, data.timestamp);
|
||||
});
|
||||
|
||||
// QA 阶段
|
||||
this.eventSource.addEventListener('qa_start', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('qa', 'processing');
|
||||
this.addLog('qa_start', 'QA Agent', '开始测试用例设计...');
|
||||
});
|
||||
|
||||
this.eventSource.addEventListener('qa_complete', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('qa', 'completed');
|
||||
this.addLog('qa_complete', 'QA Agent', '测试用例设计完成');
|
||||
this.addResult('🧪 测试方案与用例', data.content, data.timestamp);
|
||||
});
|
||||
|
||||
// Dev 阶段
|
||||
this.eventSource.addEventListener('dev_start', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('dev', 'processing');
|
||||
this.addLog('dev_start', 'Dev Agent', '开始代码实现...');
|
||||
});
|
||||
|
||||
this.eventSource.addEventListener('dev_complete', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('dev', 'completed');
|
||||
this.addLog('dev_complete', 'Dev Agent', '代码实现完成');
|
||||
this.addResult('💻 代码实现', data.content, data.timestamp);
|
||||
});
|
||||
|
||||
// 最终结果
|
||||
this.eventSource.addEventListener('final_result', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.updateStageStatus('final', 'completed');
|
||||
this.addLog('final_result', 'System', 'SDLC 流程完成');
|
||||
this.isProcessing = false;
|
||||
this.connectionStatus = 'disconnected';
|
||||
});
|
||||
|
||||
// 错误处理
|
||||
this.eventSource.addEventListener('error', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
this.addLog('error', 'Error', data.error || '未知错误');
|
||||
this.isProcessing = false;
|
||||
this.connectionStatus = 'disconnected';
|
||||
alert(`执行错误：${data.error}`);
|
||||
});
|
||||
|
||||
// 连接错误
|
||||
this.eventSource.onerror = () => {
|
||||
this.addLog('system', 'SSE', '连接断开');
|
||||
this.connectionStatus = 'disconnected';
|
||||
this.eventSource.close();
|
||||
};
|
||||
},
|
||||
|
||||
/**
|
||||
* 更新阶段状态
|
||||
*/
|
||||
updateStageStatus(stageId, status) {
|
||||
const stage = this.stages.find(s => s.id === stageId);
|
||||
if (stage) {
|
||||
stage.status = status;
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* 添加日志
|
||||
*/
|
||||
addLog(event, source, message) {
|
||||
this.logs.push({
|
||||
timestamp: new Date().toLocaleTimeString('zh-CN'),
|
||||
event,
|
||||
source,
|
||||
message
|
||||
});
|
||||
// 保持最新 100 条日志
|
||||
if (this.logs.length > 100) {
|
||||
this.logs.shift();
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* 添加结果
|
||||
*/
|
||||
addResult(title, content, timestamp) {
|
||||
this.results.push({
|
||||
title,
|
||||
content,
|
||||
timestamp,
|
||||
expanded: true
|
||||
});
|
||||
},
|
||||
|
||||
/**
|
||||
* 清空日志
|
||||
*/
|
||||
clearLogs() {
|
||||
this.logs = [];
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取阶段图标样式
|
||||
*/
|
||||
getStageIconClass(status) {
|
||||
const classMap = {
|
||||
'pending': 'bg-gray-400',
|
||||
'processing': 'bg-blue-500',
|
||||
'completed': 'bg-green-500'
|
||||
};
|
||||
return classMap[status] || classMap['pending'];
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取阶段徽章样式
|
||||
*/
|
||||
getStageBadgeClass(status) {
|
||||
const classMap = {
|
||||
'pending': 'bg-gray-100 text-gray-800',
|
||||
'processing': 'bg-blue-100 text-blue-800',
|
||||
'completed': 'bg-green-100 text-green-800'
|
||||
};
|
||||
return classMap[status] || classMap['pending'];
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取阶段状态文本
|
||||
*/
|
||||
getStageStatusText(status) {
|
||||
const textMap = {
|
||||
'pending': '等待中',
|
||||
'processing': '进行中',
|
||||
'completed': '已完成'
|
||||
};
|
||||
return textMap[status] || status;
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取日志级别样式
|
||||
*/
|
||||
getLogLevelClass(event) {
|
||||
const classMap = {
|
||||
'pm_start': 'text-blue-400',
|
||||
'pm_complete': 'text-green-400',
|
||||
'qa_start': 'text-blue-400',
|
||||
'qa_complete': 'text-green-400',
|
||||
'dev_start': 'text-blue-400',
|
||||
'dev_complete': 'text-green-400',
|
||||
'final_result': 'text-purple-400',
|
||||
'error': 'text-red-400',
|
||||
'system': 'text-yellow-400'
|
||||
};
|
||||
return classMap[event] || 'text-gray-400';
|
||||
},
|
||||
|
||||
/**
|
||||
* 渲染 Markdown
|
||||
*/
|
||||
renderMarkdown(content) {
|
||||
if (!content) return '';
|
||||
return marked.parse(content);
|
||||
},
|
||||
|
||||
/**
|
||||
* 格式化日期
|
||||
*/
|
||||
formatDate(timestamp) {
|
||||
if (!timestamp) return '';
|
||||
try {
|
||||
return new Date(timestamp).toLocaleString('zh-CN');
|
||||
} catch {
|
||||
return timestamp;
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* 复制到剪贴板
|
||||
*/
|
||||
async copyToClipboard(content) {
|
||||
try {
|
||||
await navigator.clipboard.writeText(content);
|
||||
this.showCopyToast = true;
|
||||
setTimeout(() => {
|
||||
this.showCopyToast = false;
|
||||
}, 2000);
|
||||
} catch (err) {
|
||||
console.error('复制失败:', err);
|
||||
alert('复制失败，请手动复制');
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
beforeUnmount() {
|
||||
// 清理 SSE 连接
|
||||
if (this.eventSource) {
|
||||
this.eventSource.close();
|
||||
}
|
||||
}
|
||||
}).mount('#app');
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
@@ -1,283 +0,0 @@
|
||||
"""
|
||||
SSE 流管理器
|
||||
负责管理任务执行过程中的消息队列和 SSE 连接
|
||||
确保多用户并发时不同 task_id 的流互不干扰
|
||||
|
||||
关键技术点：
|
||||
1. 使用 asyncio.Queue 实现异步非阻塞消息队列
|
||||
2. 通过 asyncio.Lock 保证并发安全
|
||||
3. 每个 task_id 独立队列，实现任务隔离
|
||||
4. 支持从同步线程（CrewAI）安全地发布事件到异步队列
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from datetime import datetime
|
||||
from typing import Dict, AsyncGenerator, Optional, Any
|
||||
from collections import deque
|
||||
import uuid
|
||||
import threading
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
|
||||
class StreamEvent:
|
||||
"""
|
||||
SSE 事件数据结构
|
||||
|
||||
统一的 JSON 格式设计，便于前端解析：
|
||||
{
|
||||
"task_id": "550e8400-e29b...",
|
||||
"sequence": 1,
|
||||
"agent_name": "ProductManager",
|
||||
"event_type": "thought", // 或 action, output, complete
|
||||
"content": "正在分析用户需求...",
|
||||
"timestamp": "2023-10-27T10:00:00Z"
|
||||
}
|
||||
"""
|
||||
|
||||
# 全局序列号计数器（每个 task_id 独立）
|
||||
_sequence_counters: Dict[str, int] = {}
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
event_type: str,
|
||||
agent: str,
|
||||
content: str,
|
||||
task_id: str,
|
||||
timestamp: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
):
|
||||
self.event_type = event_type # start, thought, action, output, end, error
|
||||
self.agent = agent
|
||||
self.content = content
|
||||
self.task_id = task_id
|
||||
self.timestamp = timestamp or datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ')
|
||||
self.metadata = metadata or {}
|
||||
|
||||
# 为每个 task_id 维护独立的序列号
|
||||
if task_id not in StreamEvent._sequence_counters:
|
||||
StreamEvent._sequence_counters[task_id] = 0
|
||||
StreamEvent._sequence_counters[task_id] += 1
|
||||
self.sequence = StreamEvent._sequence_counters[task_id]
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""转换为字典格式用于 JSON 序列化"""
|
||||
return {
|
||||
"task_id": self.task_id,
|
||||
"sequence": self.sequence,
|
||||
"agent_name": self.agent,
|
||||
"event_type": self.event_type,
|
||||
"content": self.content,
|
||||
"timestamp": self.timestamp,
|
||||
**(self.metadata if self.metadata else {})
|
||||
}
|
||||
|
||||
def to_sse_format(self) -> str:
|
||||
"""转换为 SSE 数据格式"""
|
||||
import json
|
||||
return f"data: {json.dumps(self.to_dict(), ensure_ascii=False)}\n\n"
|
||||
|
||||
@classmethod
|
||||
def reset_sequence(cls, task_id: str):
|
||||
"""重置指定 task_id 的序列号（任务重新开始时调用）"""
|
||||
cls._sequence_counters[task_id] = 0
|
||||
|
||||
|
||||
class TaskStreamQueue:
|
||||
"""
|
||||
单个任务的流式消息队列（线程安全）
|
||||
|
||||
并发处理逻辑：
|
||||
- CrewAI 默认是同步运行的，而 FastAPI 和 SSE 需要异步
|
||||
- 使用 asyncio.Queue 的 run_coroutine_threadsafe 方法从同步线程安全地发布事件
|
||||
- 确保 stream_manager 能安全地在线程间传递消息
|
||||
"""
|
||||
|
||||
def __init__(self, task_id: str, max_size: int = 1000):
|
||||
self.task_id = task_id
|
||||
self.queue: asyncio.Queue[StreamEvent] = asyncio.Queue(maxsize=max_size)
|
||||
self.is_closed = False
|
||||
self.subscribers: int = 0
|
||||
self._loop = asyncio.get_event_loop()
|
||||
self._lock = threading.Lock() # 用于保护同步操作
|
||||
|
||||
async def put(self, event: StreamEvent) -> bool:
|
||||
"""向队列添加事件（异步调用）"""
|
||||
if self.is_closed:
|
||||
return False
|
||||
try:
|
||||
await asyncio.wait_for(self.queue.put(event), timeout=5.0)
|
||||
return True
|
||||
except asyncio.TimeoutError:
|
||||
return False
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
def put_nowait(self, event: StreamEvent) -> bool:
|
||||
"""
|
||||
从同步线程（如 CrewAI 事件处理器）安全地发布事件
|
||||
|
||||
使用 run_coroutine_threadsafe 将协程提交到事件循环执行
|
||||
这是实现 CrewAI（同步）与 SSE（异步）集成的关键
|
||||
"""
|
||||
if self.is_closed:
|
||||
return False
|
||||
|
||||
try:
|
||||
# 将协程提交到事件循环线程安全地执行
|
||||
future = asyncio.run_coroutine_threadsafe(
|
||||
self.queue.put(event),
|
||||
self._loop
|
||||
)
|
||||
# 等待完成（带超时）
|
||||
future.result(timeout=5.0)
|
||||
return True
|
||||
except Exception as e:
|
||||
# print(f"发布事件失败：{e}")
|
||||
return False
|
||||
|
||||
async def get(self) -> Optional[StreamEvent]:
|
||||
"""从队列获取事件"""
|
||||
if self.is_closed and self.queue.empty():
|
||||
return None
|
||||
try:
|
||||
return await self.queue.get()
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def close(self):
|
||||
"""关闭队列"""
|
||||
with self._lock:
|
||||
self.is_closed = True
|
||||
|
||||
async def stream_events(self) -> AsyncGenerator[StreamEvent, None]:
|
||||
"""异步生成器，持续产出事件直到队列关闭"""
|
||||
while not (self.is_closed and self.queue.empty()):
|
||||
try:
|
||||
event = await asyncio.wait_for(self.queue.get(), timeout=30.0)
|
||||
yield event
|
||||
except asyncio.TimeoutError:
|
||||
if self.is_closed and self.queue.empty():
|
||||
break
|
||||
continue
|
||||
except Exception:
|
||||
break
|
||||
|
||||
|
||||
class StreamManager:
|
||||
"""全局流管理器 - 管理所有任务的 SSE 流"""
|
||||
|
||||
_instance: Optional['StreamManager'] = None
|
||||
|
||||
def __new__(cls):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
cls._instance._initialized = False
|
||||
return cls._instance
|
||||
|
||||
def __init__(self):
|
||||
if self._initialized:
|
||||
return
|
||||
self._initialized = True
|
||||
# task_id -> TaskStreamQueue 映射
|
||||
self.streams: Dict[str, TaskStreamQueue] = {}
|
||||
self._lock = asyncio.Lock()
|
||||
|
||||
async def create_stream(self, task_id: str) -> TaskStreamQueue:
|
||||
"""为指定 task_id 创建新的流队列"""
|
||||
async with self._lock:
|
||||
if task_id in self.streams:
|
||||
# 如果已存在，先关闭旧的
|
||||
old_stream = self.streams[task_id]
|
||||
old_stream.close()
|
||||
|
||||
# 重置序列号计数器
|
||||
StreamEvent.reset_sequence(task_id)
|
||||
|
||||
queue = TaskStreamQueue(task_id)
|
||||
self.streams[task_id] = queue
|
||||
return queue
|
||||
|
||||
async def get_stream(self, task_id: str) -> Optional[TaskStreamQueue]:
|
||||
"""获取指定 task_id 的流队列"""
|
||||
async with self._lock:
|
||||
return self.streams.get(task_id)
|
||||
|
||||
async def publish_event(
|
||||
self,
|
||||
task_id: str,
|
||||
event_type: str,
|
||||
agent: str,
|
||||
content: str,
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
) -> bool:
|
||||
"""发布事件到指定任务的流队列"""
|
||||
async with self._lock:
|
||||
stream = self.streams.get(task_id)
|
||||
if stream is None:
|
||||
return False
|
||||
|
||||
event = StreamEvent(
|
||||
event_type=event_type,
|
||||
agent=agent,
|
||||
content=content,
|
||||
task_id=task_id,
|
||||
metadata=metadata
|
||||
)
|
||||
return await stream.put(event)
|
||||
|
||||
async def close_stream(self, task_id: str):
|
||||
"""关闭指定任务的流队列"""
|
||||
async with self._lock:
|
||||
if task_id in self.streams:
|
||||
self.streams[task_id].close()
|
||||
# 可以选择删除或保留（如果需要历史记录）
|
||||
# del self.streams[task_id]
|
||||
|
||||
async def cleanup_old_streams(self, max_age_seconds: int = 3600):
|
||||
"""清理超过指定时间的旧流（定期调用）"""
|
||||
now = datetime.now()
|
||||
to_remove = []
|
||||
|
||||
async with self._lock:
|
||||
for task_id, stream in self.streams.items():
|
||||
if stream.is_closed:
|
||||
to_remove.append(task_id)
|
||||
|
||||
async with self._lock:
|
||||
for task_id in to_remove:
|
||||
del self.streams[task_id]
|
||||
|
||||
def list_active_streams(self) -> list:
|
||||
"""列出所有活跃的流"""
|
||||
return [
|
||||
{"task_id": tid, "closed": s.is_closed}
|
||||
for tid, s in self.streams.items()
|
||||
]
|
||||
|
||||
|
||||
# 全局单例
|
||||
stream_manager = StreamManager()
|
||||
|
||||
|
||||
async def create_sse_generator(task_id: str) -> AsyncGenerator[str, None]:
|
||||
"""
|
||||
创建 SSE 异步生成器
|
||||
供 FastAPI StreamingResponse 使用
|
||||
"""
|
||||
stream = await stream_manager.get_stream(task_id)
|
||||
if stream is None:
|
||||
# 创建一个新的流（如果不存在）
|
||||
stream = await stream_manager.create_stream(task_id)
|
||||
|
||||
try:
|
||||
async for event in stream.stream_events():
|
||||
yield event.to_sse_format()
|
||||
finally:
|
||||
# 发送结束标记
|
||||
import json
|
||||
end_event = {
|
||||
"type": "connection_end",
|
||||
"task_id": task_id,
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
yield f"data: {json.dumps(end_event)}\n\n"
|
||||
Reference in New Issue
Block a user