168 lines
5.3 KiB
Python
168 lines
5.3 KiB
Python
"""
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示例使用脚本
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演示如何使用多智能体系统生成代码和文档
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"""
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import asyncio
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import json
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from pathlib import Path
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from datetime import datetime
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from crew_factory import CrewFactory, run_multi_agent_task
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from stream_manager import stream_manager
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async def save_generated_content(task_id: str, output_dir: str = "generated_output"):
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"""
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订阅 SSE 流并保存生成的内容到文件
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Args:
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task_id: 任务 ID
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output_dir: 输出目录
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"""
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output_path = Path(output_dir)
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output_path.mkdir(exist_ok=True)
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# 创建时间戳目录
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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task_output_dir = output_path / f"task_{timestamp}"
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task_output_dir.mkdir()
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print(f"📁 生成内容将保存到：{task_output_dir}")
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# 保存的文件
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prd_file = task_output_dir / "PRD_产品需求文档.md"
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qa_file = task_output_dir / "QA_测试计划.md"
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dev_file = task_output_dir / "Dev_技术方案.md"
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final_file = task_output_dir / "Final_交付报告.md"
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content_buffer = {
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"ProductManager": [],
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"QAEngineer": [],
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"SoftwareDeveloper": [],
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"Coordinator": []
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}
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print(f"\n🚀 开始订阅任务流：{task_id}\n")
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# 获取流
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stream = await stream_manager.get_stream(task_id)
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if not stream:
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print("❌ 未找到流")
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return
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try:
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while not stream.is_closed or not stream.queue.empty():
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try:
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event = await asyncio.wait_for(stream.get(), timeout=5.0)
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if not event:
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break
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# 打印事件
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agent = event.agent
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content = event.content
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event_type = event.event_type
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print(f"[{agent}] {event_type}: {content[:100]}...")
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# 累积内容（简单示例，实际应该解析完整内容）
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if event_type == "output" and agent in content_buffer:
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content_buffer[agent].append(content)
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# 检测任务完成
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if event_type == "end":
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print("\n✅ 任务完成！正在保存文件...\n")
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# 保存各角色的输出
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for role, contents in content_buffer.items():
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if contents:
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filename = None
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if role == "ProductManager":
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filename = prd_file
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elif role == "QAEngineer":
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filename = qa_file
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elif role == "SoftwareDeveloper":
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filename = dev_file
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elif role == "Coordinator":
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filename = final_file
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if filename:
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with open(filename, 'w', encoding='utf-8') as f:
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f.write(f"# {role} 输出\n\n")
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f.write(f"生成时间：{datetime.now().isoformat()}\n\n")
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f.write('\n'.join(contents))
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print(f"✓ 已保存：{filename}")
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# 保存完整的事件日志
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log_file = task_output_dir / "events_log.json"
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print(f"✓ 已保存完整日志：{log_file}")
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break
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except asyncio.TimeoutError:
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if stream.is_closed:
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break
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continue
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except Exception as e:
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print(f"❌ 错误：{e}")
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import traceback
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traceback.print_exc()
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async def main():
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"""主函数"""
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print("=" * 60)
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print("多智能体系统 - 代码和文档生成示例")
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print("=" * 60)
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# 用户需求
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user_requirement = """
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开发一个简单的在线待办事项应用（Todo App），包含以下功能：
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1. 用户可以注册和登录
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2. 创建、编辑、删除待办事项
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3. 标记事项为完成/未完成
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4. 按优先级和截止日期排序
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5. 基本的搜索和过滤功能
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技术栈要求：
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- 后端：Python FastAPI
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- 数据库：SQLite
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- 前端：简单的 HTML/CSS/JavaScript
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"""
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print(f"\n📝 用户需求：{user_requirement[:200]}...\n")
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print("⏳ 启动多智能体系统，请稍候...\n")
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try:
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# 启动任务
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task_id = await run_multi_agent_task(
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user_requirement=user_requirement,
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skip_confirmation=True
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)
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print(f"✅ 任务已启动，Task ID: {task_id}\n")
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# 订阅并保存生成的内容
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await save_generated_content(task_id)
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print("\n" + "=" * 60)
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print("✨ 生成完成！请查看 generated_output/ 目录")
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print("=" * 60)
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except Exception as e:
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print(f"\n❌ 执行失败：{e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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# 加载环境变量
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except ImportError:
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pass
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asyncio.run(main())
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