主要修复： 1. 修复 RAG 推理无限循环问题（大小写不匹配 + 缺少已检索结果检查） 2. 修复 intent_classifier.py 的绝对导入错误 3. 删除旧的 start.sh 脚本，添加新的启动脚本 4. 优化路由逻辑和状态管理
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97
tools/test/test_fast_rag_fix.py
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97
tools/test/test_fast_rag_fix.py
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#!/usr/bin/env python3
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"""
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快速测试 - 测试 fast_rag 路径修复
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"""
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import sys
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import asyncio
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from pathlib import Path
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from dotenv import load_dotenv
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# 路径设置
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project_root = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(project_root))
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sys.path.insert(0, str(project_root / "backend"))
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load_dotenv(project_root / ".env")
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from app.main_graph.state import MainGraphState, CurrentAction
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from app.main_graph.utils.main_graph_builder import build_react_main_graph
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from app.model_services.chat_services import get_all_chat_services
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from app.main_graph.tools.graph_tools import AVAILABLE_TOOLS
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async def test_fast_rag_path():
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"""测试 fast_rag 路径"""
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print("=" * 60)
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print("测试 fast_rag 路径修复")
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print("=" * 60)
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# 1. 获取 LLM
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chat_services = get_all_chat_services()
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if not chat_services:
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print("✗ 没有可用的 LLM 服务")
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return
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llm = list(chat_services.values())[0]
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print(f"✓ 使用 LLM: {list(chat_services.keys())[0]}")
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# 2. 构建图
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graph = build_react_main_graph(
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llm=llm,
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tools=AVAILABLE_TOOLS,
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use_hybrid_router=True
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).compile()
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print(f"✓ 图构建完成")
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# 3. 测试问题
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test_query = "吕布和张飞谁厉害？"
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print(f"\n测试问题: {test_query}")
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# 4. 创建状态
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input_state = {
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"user_query": test_query,
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"messages": [{"role": "user", "content": test_query}],
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"user_id": "test_user",
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"current_action": CurrentAction.NONE
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}
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# 5. 执行
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print("开始执行...")
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try:
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result = await graph.ainvoke(
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input_state,
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config={"configurable": {"thread_id": "test_fast_rag"}}
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)
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print(f"\n✓ 执行成功！")
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print(f"最终回答: {result.get('final_result', '')[:300]}")
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# 调试信息
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debug_info = result.get("debug_info", {})
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print(f"\n调试信息:")
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if "fast_path_failed" in debug_info:
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print(f" - fast_path_failed: {debug_info['fast_path_failed']}")
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if "fast_path_fail_reason" in debug_info:
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print(f" - fast_path_fail_reason: {debug_info['fast_path_fail_reason']}")
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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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print(traceback.format_exc())
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return False
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return True
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async def main():
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success = await test_fast_rag_path()
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if success:
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print("\n🎉 测试通过！")
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else:
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print("\n⚠️ 测试失败")
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if __name__ == "__main__":
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try:
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asyncio.run(main())
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except KeyboardInterrupt:
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print("\n测试被中断")
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221
tools/test/test_graph_branches.py
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tools/test/test_graph_branches.py
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#!/usr/bin/env python3
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"""
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主图完整测试 - 覆盖各个分支
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"""
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import sys
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import asyncio
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from pathlib import Path
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from dotenv import load_dotenv
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# 路径设置
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project_root = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(project_root))
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sys.path.insert(0, str(project_root / "backend"))
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load_dotenv(project_root / ".env")
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from app.main_graph.state import MainGraphState, CurrentAction
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from app.main_graph.utils.main_graph_builder import build_react_main_graph
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from app.model_services.chat_services import get_all_chat_services
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from app.main_graph.tools.graph_tools import AVAILABLE_TOOLS
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from app.main_graph.utils.rag_initializer import init_rag_tool
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# ========== 测试用例配置 ==========
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TEST_CASES = [
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# 测试1: 简单闲聊 - 应该走 fast_chitchat
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{
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"name": "闲聊测试",
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"query": "你好！",
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"description": "测试快速闲聊分支"
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},
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# 测试2: 知识查询 - 应该走 fast_rag，然后可能升级到 react
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{
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"name": "知识查询测试",
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"query": "什么是机器学习？",
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"description": "测试快速 RAG 分支"
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},
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# 测试3: 需要推理的复杂问题 - 应该直接到 React 循环
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{
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"name": "复杂推理测试",
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"query": "请帮我分析：如果我有10万元，想要在一年内获得15%的收益，有哪些低风险的投资方案？",
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"description": "测试 React 循环推理分支"
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},
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# 测试4: 需要工具调用的问题
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{
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"name": "工具调用测试",
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"query": "搜索一下今天的天气怎么样",
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"description": "测试工具调用分支"
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},
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# 测试5: 带记忆的对话
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{
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"name": "记忆测试",
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"query": "你刚才回答了我什么问题？",
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"description": "测试记忆检索分支",
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"thread_id": "test_memory_thread"
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}
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]
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async def setup_test_environment():
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"""设置测试环境"""
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print("=" * 60)
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print("设置测试环境...")
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print("=" * 60)
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# 获取 LLM 服务
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chat_services = get_all_chat_services()
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if not chat_services:
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raise RuntimeError("没有可用的 LLM 服务")
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llm = list(chat_services.values())[0]
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print(f"✓ 使用 LLM: {list(chat_services.keys())[0]}")
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# 初始化 RAG 工具
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def create_local_llm():
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return llm
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rag_tool = await init_rag_tool(create_local_llm)
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tools = AVAILABLE_TOOLS.copy()
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if rag_tool:
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tools.append(rag_tool)
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print(f"✓ RAG 工具初始化成功")
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# 构建图
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graph = build_react_main_graph(
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llm=llm,
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tools=tools,
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use_hybrid_router=True
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).compile()
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print(f"✓ 图构建完成")
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print()
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return graph
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def create_test_state(query: str, thread_id: str = None) -> dict:
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"""创建测试状态"""
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return {
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"user_query": query,
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"messages": [{"role": "user", "content": query}],
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"user_id": "test_user",
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"current_action": CurrentAction.NONE
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}
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async def run_single_test(graph, test_case: dict) -> dict:
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"""运行单个测试"""
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name = test_case["name"]
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query = test_case["query"]
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description = test_case["description"]
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thread_id = test_case.get("thread_id", "test_thread")
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print(f"\n{'=' * 60}")
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print(f"测试: {name}")
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print(f"描述: {description}")
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print(f"查询: {query}")
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print(f"{'=' * 60}")
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try:
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# 创建初始状态
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input_state = create_test_state(query, thread_id)
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# 配置
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config = {
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"configurable": {"thread_id": thread_id}
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}
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# 执行图
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print("开始执行图...")
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result = await graph.ainvoke(input_state, config=config)
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# 检查结果
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success = result.get("success", False)
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final_result = result.get("final_result", "")
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print(f"\n结果:")
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print(f" 成功: {'✓' if success else '✗'}")
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print(f" 最终回答: {final_result[:200]}{'...' if len(final_result) > 200 else ''}")
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# 调试信息
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if "debug_info" in result:
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debug_info = result["debug_info"]
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print(f" 调试信息:")
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if "fast_path_failed" in debug_info:
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print(f" - 快速路径失败: {debug_info['fast_path_failed']}")
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if "fast_path_fail_reason" in debug_info:
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print(f" - 失败原因: {debug_info['fast_path_fail_reason']}")
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if "hybrid_decision" in debug_info:
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decision = debug_info["hybrid_decision"]
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print(f" - 路由决策: {decision.path if hasattr(decision, 'path') else 'unknown'}")
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return {
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"name": name,
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"success": success,
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"result": result
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}
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except Exception as e:
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print(f"\n✗ 测试失败: {e}")
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import traceback
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print(f"堆栈: {traceback.format_exc()}")
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return {
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"name": name,
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"success": False,
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"error": str(e)
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}
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async def main():
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"""主函数"""
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print("\n" + "=" * 60)
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print("主图完整测试套件")
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print("=" * 60)
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# 设置环境
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graph = await setup_test_environment()
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# 运行所有测试
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results = []
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for test_case in TEST_CASES:
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result = await run_single_test(graph, test_case)
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results.append(result)
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# 稍微间隔一下
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await asyncio.sleep(1)
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# 总结
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print("\n" + "=" * 60)
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print("测试总结")
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print("=" * 60)
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total = len(results)
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passed = sum(1 for r in results if r["success"])
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failed = total - passed
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print(f"\n总测试数: {total}")
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print(f"通过: {passed}")
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print(f"失败: {failed}")
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print("\n详细结果:")
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for result in results:
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status = "✓ 通过" if result["success"] else "✗ 失败"
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print(f" {result['name']}: {status}")
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print("\n" + "=" * 60)
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if failed == 0:
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print("🎉 所有测试通过！")
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else:
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print(f"⚠️ 有 {failed} 个测试失败")
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print("=" * 60)
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if __name__ == "__main__":
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try:
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asyncio.run(main())
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except KeyboardInterrupt:
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print("\n\n测试被用户中断")
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except Exception as e:
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print(f"\n\n测试运行失败: {e}")
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import traceback
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print(traceback.format_exc())
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@@ -22,7 +22,7 @@ async def test_rag_pipeline_direct():
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rerank_top_n=5
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)
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query = "黄双银的经历"
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query = "吕布的经历"
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print(f"\n用户查询: {query}")
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print("-" * 80)
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@@ -64,7 +64,7 @@ async def test_rag_tool():
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rerank_top_n=5
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)
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query = "黄双银的经历"
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query = "吕布的经历"
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print(f"\n用户查询: {query}")
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print("-" * 80)
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@@ -91,7 +91,7 @@ async def test_custom_pipeline():
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rerank_top_n=3 # 只返回前 3 个最相关文档
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)
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query = "黄双银的经历"
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query = "吕布的经历"
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print(f"\n用户查询: {query}")
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print(f"配置: num_queries=2, rerank_top_n=3")
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@@ -124,7 +124,7 @@ async def main():
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"""主测试函数"""
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print("\n" + "="*80)
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print("完整 RAG Pipeline 测试")
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print("查询: '黄双银的经历'")
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print("查询: '吕布的经历'")
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print("="*80)
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# 测试 1: 直接使用 pipeline
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Reference in New Issue
Block a user