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构建并部署 AI Agent 服务 / deploy (push) Successful in 5m41s
主要变更: - 简化 agent_service:移除复杂双协程,只用 stream_mode=["updates"] - stream_context:提供更清晰的 API (set_stream_queue/get_stream_queue) - main_graph_builder:简化图结构,移除 tools 节点和条件边 - agent 节点:包含完整 ReAct 循环 + 流式 Tool Calling 拼接 - 前端:适配新的事件格式 - 添加测试文件:test_full_react_streaming.py, test_stream.py
80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
#!/usr/bin/env python3
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"""测试后端流式接口,看看是否真的有流式输出"""
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import asyncio
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import aiohttp
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import json
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BACKEND_URL = "http://localhost:8079/chat/stream"
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async def test_stream():
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print("=" * 60)
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print("🧪 测试后端流式接口")
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print("=" * 60)
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async with aiohttp.ClientSession() as session:
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payload = {
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"message": "你好,请简单介绍一下自己",
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"thread_id": "test-thread-001",
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"model": "zhipu",
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"user_id": "test-user"
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}
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print(f"\n📤 发送请求: {json.dumps(payload, ensure_ascii=False)}")
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try:
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async with session.post(BACKEND_URL, json=payload) as response:
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print(f"\n✅ 响应状态: {response.status}")
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print(f"\n📥 开始接收流式响应...\n")
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event_count = 0
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token_count = 0
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async for line in response.content:
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line = line.decode('utf-8').strip()
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if line:
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if line.startswith("data: "):
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data_str = line[6:]
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if data_str == "[DONE]":
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print("\n🏁 收到 [DONE] 事件")
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break
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try:
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event = json.loads(data_str)
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event_count += 1
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print(f" [{event_count}] {event.get('type')}")
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if event.get('type') == 'llm_token' and 'token' in event:
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token = event['token']
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token_count += 1
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print(f" → token: {repr(token)}")
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if event.get('type') == 'node_start':
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print(f" → node: {event.get('node')}")
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if event.get('type') == 'tool_call_start':
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print(f" → tool: {event.get('tool')}")
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if event.get('type') == 'tool_call_end':
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print(f" → tool: {event.get('tool')}")
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if event.get('type') == 'error':
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print(f" ❌ 错误: {event.get('message')}")
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except Exception as e:
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print(f" ❌ 解析失败: {e}, 原始数据: {repr(data_str)}")
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else:
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print(f" 📝 原始行: {repr(line)}")
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print(f"\n📊 统计: {event_count} 个事件, {token_count} 个 token")
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except Exception as e:
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print(f"\n❌ 请求异常: {e}")
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import traceback
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print(f"📋 堆栈: {traceback.format_exc()}")
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if __name__ == "__main__":
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asyncio.run(test_stream())
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