容器处理
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@@ -2,7 +2,7 @@
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AI Agent 应用模块
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"""
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from ..agent import AIAgentService
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from ..graph.graph_tools import AVAILABLE_TOOLS, TOOLS_BY_NAME
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from .agent.service import AIAgentService
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from .graph.graph_tools import AVAILABLE_TOOLS, TOOLS_BY_NAME
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__all__ = ["AIAgentService", "AVAILABLE_TOOLS", "TOOLS_BY_NAME"]
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@@ -1,304 +0,0 @@
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#!/usr/bin/env python3
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"""
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完整后端测试 - 验证 Agent 所有功能
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包括：短期记忆、长期记忆、工具调用、流式对话、历史查询
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"""
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import asyncio
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import os
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from .config import DB_URI
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import sys
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import uuid
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from dotenv import load_dotenv
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# 添加项目根目录到 Python 路径 (现在文件在 backend/app/ 下，backend 就是根)
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
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load_dotenv()
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from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
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from ..agent import AIAgentService
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from ..agent.history import ThreadHistoryService
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from ..logger import info, warning, error
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# PostgreSQL 连接字符串
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async def print_section(title):
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"""打印测试区块标题"""
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print("\n" + "=" * 70)
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print(f" {title}")
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print("=" * 70)
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async def test_short_term_memory(agent_service):
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"""测试短期记忆（同一 thread_id 继续对话）"""
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await print_section("测试 1: 短期记忆（Short-term Memory）")
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thread_id = str(uuid.uuid4())
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user_id = "test_user_memory"
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print(f"\n使用 thread_id: {thread_id[:8]}...")
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print(f"使用 user_id: {user_id}")
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# 第一轮对话
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print("\n[第一轮] 发送消息: '我叫张三，今年28岁'")
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result1 = await agent_service.process_message(
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"我叫张三，今年28岁", thread_id, "local", user_id
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)
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print(f"回复: {result1['reply'][:100]}...")
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# 第二轮对话 - 测试记忆
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print("\n[第二轮] 发送消息: '我叫什么名字？今年多大？'")
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result2 = await agent_service.process_message(
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"我叫什么名字？今年多大？", thread_id, "local", user_id
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)
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print(f"回复: {result2['reply']}")
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# 验证记忆是否存在
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if "张三" in result2['reply'] or "28" in result2['reply']:
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print("\n✅ 短期记忆测试通过！")
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return True
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else:
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print("\n❌ 短期记忆测试失败！")
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return False
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async def test_tool_calling(agent_service):
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"""测试工具调用（RAG 搜索）"""
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await print_section("测试 2: 工具调用（Tool Calling）")
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thread_id = str(uuid.uuid4())
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user_id = "test_user_tools"
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print(f"\n使用 thread_id: {thread_id[:8]}...")
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print(f"使用 user_id: {user_id}")
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# 发送需要 RAG 搜索的问题
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print("\n发送消息: '请告诉我，打虎英雄是谁？'")
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result = await agent_service.process_message(
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"请告诉我，打虎英雄是谁？", thread_id, "local", user_id
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)
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print(f"回复: {result['reply'][:200]}...")
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# 检查是否调用了 RAG 工具（回复中会有水浒传相关内容）
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if "武松" in result['reply'] or "李忠" in result['reply'] or "水浒传" in result['reply']:
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print("\n✅ 工具调用测试通过！")
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return True
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else:
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print("\n⚠️ 工具调用测试结果不确定，需要手动验证")
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return None
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async def test_streaming(agent_service):
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"""测试流式对话"""
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await print_section("测试 3: 流式对话（Streaming）")
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thread_id = str(uuid.uuid4())
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user_id = "test_user_stream"
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print(f"\n使用 thread_id: {thread_id[:8]}...")
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print(f"使用 user_id: {user_id}")
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print("\n发送消息: '用100字介绍一下AI人工智能' (流式)...")
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print("流式输出: ", end="", flush=True)
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full_reply = ""
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chunk_count = 0
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try:
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async for chunk in agent_service.process_message_stream(
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"用100字介绍一下AI人工智能", thread_id, "local", user_id
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):
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chunk_count += 1
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if chunk.get("type") == "llm_token":
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token = chunk.get("token", "")
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print(token, end="", flush=True)
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full_reply += token
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elif chunk.get("type") == "state_update":
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pass # 状态更新不显示
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print(f"\n\n共收到 {chunk_count} 个 chunk")
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print(f"完整回复长度: {len(full_reply)} 字")
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if chunk_count > 0 and len(full_reply) > 10:
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print("\n✅ 流式对话测试通过！")
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return True
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else:
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print("\n❌ 流式对话测试失败！")
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return False
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except Exception as e:
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print(f"\n❌ 流式对话异常: {e}")
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return False
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async def test_history_service(agent_service, history_service):
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"""测试历史查询服务"""
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await print_section("测试 4: 历史查询服务（History Service）")
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user_id = "test_user_history"
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# 先创建几个对话
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print(f"\n为 user_id={user_id} 创建测试对话...")
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thread_ids = []
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for i in range(3):
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thread_id = str(uuid.uuid4())
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thread_ids.append(thread_id)
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await agent_service.process_message(
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f"这是第 {i+1} 个测试对话", thread_id, "local", user_id
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)
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print(f" 创建线程 {i+1}: {thread_id[:8]}...")
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# 1. 测试获取用户线程列表
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print("\n[4.1] 测试获取用户线程列表...")
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threads = await history_service.get_user_threads(user_id, limit=10)
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print(f" 找到 {len(threads)} 个线程")
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if len(threads) >= 3:
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print(" ✅ 线程列表查询通过")
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else:
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print(" ⚠️ 线程数量少于预期")
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# 2. 测试获取单个线程的消息历史
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if thread_ids:
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test_thread_id = thread_ids[0]
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print(f"\n[4.2] 测试获取线程消息历史 (thread_id={test_thread_id[:8]}...)")
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messages = await history_service.get_thread_messages(test_thread_id)
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print(f" 找到 {len(messages)} 条消息")
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if len(messages) >= 2: # 至少有一问一答
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print(" ✅ 消息历史查询通过")
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else:
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print(" ⚠️ 消息数量少于预期")
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# 3. 测试获取线程摘要
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print(f"\n[4.3] 测试获取线程摘要...")
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summary = await history_service.get_thread_summary(test_thread_id)
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print(f" 摘要: {summary.get('summary', '')[:50]}...")
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print(f" 消息数: {summary.get('message_count', 0)}")
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if summary.get('message_count', 0) > 0:
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print(" ✅ 线程摘要查询通过")
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else:
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print(" ⚠️ 摘要查询结果不确定")
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return len(threads) >= 3
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async def test_long_term_memory(agent_service):
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"""测试长期记忆（mem0）"""
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await print_section("测试 5: 长期记忆（Long-term Memory - mem0）")
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thread_id1 = str(uuid.uuid4())
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thread_id2 = str(uuid.uuid4()) # 不同的线程
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user_id = "test_user_longterm"
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print(f"\n使用 user_id: {user_id}")
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print(f"线程 1: {thread_id1[:8]}...")
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print(f"线程 2: {thread_id2[:8]}...")
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# 在第一个线程中保存信息
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print("\n[线程 1] 发送消息: '记住，我的宠物名字叫小白，是一只猫'")
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result1 = await agent_service.process_message(
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"记住，我的宠物名字叫小白，是一只猫", thread_id1, "local", user_id
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)
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print(f"回复: {result1['reply'][:100]}...")
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# 等待一下，让 mem0 保存
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await asyncio.sleep(1)
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# 在第二个线程中询问（不同的 thread_id）
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print("\n[线程 2] 发送消息: '我的宠物叫什么名字？是什么动物？'")
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result2 = await agent_service.process_message(
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"我的宠物叫什么名字？是什么动物？", thread_id2, "local", user_id
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)
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print(f"回复: {result2['reply']}")
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# 验证长期记忆
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if "小白" in result2['reply'] or "猫" in result2['reply']:
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print("\n✅ 长期记忆测试通过！")
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return True
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else:
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print("\n⚠️ 长期记忆可能未启用，或需要手动验证")
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return None
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async def main():
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"""主测试函数"""
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print("\n" + "=" * 70)
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print(" 后端完整功能测试")
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print("=" * 70)
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results = {}
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try:
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# 创建数据库连接和服务
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print("\n正在初始化数据库连接...")
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async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:
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await checkpointer.setup()
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print("✅ 数据库连接成功")
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# 创建服务实例
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print("\n正在初始化 Agent 服务...")
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agent_service = AIAgentService(checkpointer)
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await agent_service.initialize()
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print("✅ Agent 服务初始化成功")
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history_service = ThreadHistoryService(checkpointer)
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print("✅ 历史服务初始化成功")
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print(f"\n可用模型: {list(agent_service.graphs.keys())}")
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# 运行测试
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results["短期记忆"] = await test_short_term_memory(agent_service)
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await asyncio.sleep(1)
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results["工具调用"] = await test_tool_calling(agent_service)
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await asyncio.sleep(1)
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results["流式对话"] = await test_streaming(agent_service)
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await asyncio.sleep(1)
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results["历史查询"] = await test_history_service(agent_service, history_service)
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await asyncio.sleep(1)
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results["长期记忆"] = await test_long_term_memory(agent_service)
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await asyncio.sleep(1)
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# 打印总结
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await print_section("测试总结")
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print("\n测试结果:")
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print("-" * 40)
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pass_count = 0
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fail_count = 0
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skip_count = 0
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for test_name, result in results.items():
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if result is True:
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status = "✅ 通过"
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pass_count += 1
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elif result is False:
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status = "❌ 失败"
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fail_count += 1
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else:
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status = "⚠️ 待验证"
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skip_count += 1
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print(f" {test_name:12s}: {status}")
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print("-" * 40)
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print(f"总计: {len(results)} 个测试")
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print(f"通过: {pass_count}, 失败: {fail_count}, 待验证: {skip_count}")
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if fail_count == 0:
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print("\n🎉 所有核心测试通过！")
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else:
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print(f"\n⚠️ 有 {fail_count} 个测试失败")
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except Exception as e:
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error(f"\n❌ 测试运行异常: {e}")
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import traceback
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traceback.print_exc()
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return 1
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return 0 if fail_count == 0 else 1
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if __name__ == "__main__":
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exit_code = asyncio.run(main())
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sys.exit(exit_code)
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