#!/usr/bin/env python3 """ Vertex AI Memory Bank 测试脚本 验证稷下学宫记忆银行功能 """ import asyncio import sys import os # 添加项目根目录到路径 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from src.jixia.memory.vertex_memory_bank import VertexMemoryBank, initialize_baxian_memory_banks from src.jixia.agents.memory_enhanced_agent import MemoryEnhancedAgent, create_memory_enhanced_council from config.doppler_config import get_google_genai_config, validate_config async def test_memory_bank_basic(): """测试Memory Bank基础功能""" print("🧪 测试 Memory Bank 基础功能...") try: # 验证配置 if not validate_config("google_adk"): print("❌ Google ADK 配置验证失败") return False config = get_google_genai_config() if not config.get('project_id'): print("❌ Google Cloud Project ID 未配置") print("请设置环境变量: GOOGLE_CLOUD_PROJECT_ID") return False # 创建Memory Bank实例 memory_bank = VertexMemoryBank.from_config() print(f"✅ Memory Bank 实例创建成功") print(f" 项目ID: {config['project_id']}") print(f" 区域: {config['location']}") # 测试创建记忆银行 bank_id = await memory_bank.create_memory_bank( agent_name="tieguaili", display_name="铁拐李测试记忆银行" ) print(f"✅ 创建记忆银行成功: {bank_id}") # 测试添加记忆 memory_id = await memory_bank.add_memory( agent_name="tieguaili", content="测试记忆：在分析NVIDIA时，我倾向于关注潜在的市场风险和估值泡沫。", memory_type="preference", debate_topic="NVIDIA投资分析", metadata={"test": True, "priority": "high"} ) print(f"✅ 添加记忆成功: {memory_id}") # 测试搜索记忆 results = await memory_bank.search_memories( agent_name="tieguaili", query="NVIDIA 风险", limit=5 ) print(f"✅ 搜索记忆成功，找到 {len(results)} 条结果") for i, result in enumerate(results, 1): print(f" {i}. {result['content'][:50]}... (相关度: {result.get('relevance_score', 'N/A')})") # 测试获取上下文 context = await memory_bank.get_agent_context("tieguaili", "NVIDIA投资分析") print(f"✅ 获取上下文成功，长度: {len(context)} 字符") return True except Exception as e: print(f"❌ Memory Bank 基础测试失败: {e}") return False async def test_memory_enhanced_agent(): """测试记忆增强智能体""" print("\n🧪 测试记忆增强智能体...") try: # 创建记忆银行 memory_bank = VertexMemoryBank.from_config() # 创建记忆增强智能体 agent = MemoryEnhancedAgent("tieguaili", memory_bank) print(f"✅ 创建记忆增强智能体: {agent.personality.chinese_name}") # 测试基于记忆的响应 response = await agent.respond_with_memory( message="你对NVIDIA的最新财报有什么看法？", topic="NVIDIA投资分析" ) print(f"✅ 智能体响应成功") print(f" 响应长度: {len(response)} 字符") print(f" 响应预览: {response[:100]}...") # 测试学习偏好 await agent.learn_preference( preference="用户偏好保守的投资策略，关注风险控制", topic="投资偏好" ) print("✅ 学习用户偏好成功") # 测试保存策略洞察 await agent.save_strategy_insight( insight="在高估值环境下，应该更加关注基本面分析和风险管理", topic="投资策略" ) print("✅ 保存策略洞察成功") return True except Exception as e: print(f"❌ 记忆增强智能体测试失败: {e}") return False async def test_baxian_memory_council(): """测试八仙记忆议会""" print("\n🧪 测试八仙记忆议会...") try: # 创建记忆增强议会 council = await create_memory_enhanced_council() print(f"✅ 创建八仙记忆议会成功，智能体数量: {len(council.agents)}") # 列出所有智能体 for agent_name, agent in council.agents.items(): print(f" - {agent.personality.chinese_name} ({agent_name})") # 进行简短的记忆辩论测试 print("\n🏛️ 开始记忆增强辩论测试...") result = await council.conduct_memory_debate( topic="比特币投资价值分析", participants=["tieguaili", "lvdongbin"], # 只选择两个智能体进行快速测试 rounds=1 ) print(f"✅ 辩论完成") print(f" 主题: {result['topic']}") print(f" 参与者: {len(result['participants'])} 位") print(f" 发言次数: {result['total_exchanges']}") # 显示辩论内容 for exchange in result['conversation_history']: print(f" {exchange['chinese_name']}: {exchange['content'][:80]}...") # 获取集体记忆摘要 summary = await council.get_collective_memory_summary("比特币投资价值分析") print(f"\n📚 集体记忆摘要长度: {len(summary)} 字符") return True except Exception as e: print(f"❌ 八仙记忆议会测试失败: {e}") return False async def test_memory_bank_initialization(): """测试Memory Bank初始化""" print("\n🧪 测试 Memory Bank 初始化...") try: config = get_google_genai_config() project_id = config.get('project_id') location = config.get('location', 'us-central1') if not project_id: print("❌ 项目ID未配置，跳过初始化测试") return False # 初始化所有八仙记忆银行 memory_bank = await initialize_baxian_memory_banks(project_id, location) print(f"✅ 八仙记忆银行初始化成功") print(f" 记忆银行数量: {len(memory_bank.memory_banks)}") for agent_name, bank_name in memory_bank.memory_banks.items(): chinese_name = memory_bank.baxian_agents.get(agent_name, agent_name) print(f" - {chinese_name}: {bank_name}") return True except Exception as e: print(f"❌ Memory Bank 初始化测试失败: {e}") return False async def main(): """主测试函数""" print("🏛️ 稷下学宫 Vertex AI Memory Bank 测试") print("=" * 50) # 检查配置 print("🔧 检查配置...") config = get_google_genai_config() print(f"Google API Key: {'已配置' if config.get('api_key') else '未配置'}") print(f"Project ID: {config.get('project_id', '未配置')}") print(f"Location: {config.get('location', 'us-central1')}") print(f"Memory Bank: {'启用' if config.get('memory_bank_enabled', 'TRUE') == 'TRUE' else '禁用'}") if not config.get('project_id'): print("\n❌ 测试需要 Google Cloud Project ID") print("请设置环境变量: GOOGLE_CLOUD_PROJECT_ID=your-project-id") return # 运行测试 tests = [ ("Memory Bank 基础功能", test_memory_bank_basic), ("记忆增强智能体", test_memory_enhanced_agent), ("八仙记忆议会", test_baxian_memory_council), ("Memory Bank 初始化", test_memory_bank_initialization) ] results = [] for test_name, test_func in tests: print(f"\n{'='*20}") print(f"测试: {test_name}") print(f"{'='*20}") try: result = await test_func() results.append((test_name, result)) except Exception as e: print(f"❌ 测试 {test_name} 出现异常: {e}") results.append((test_name, False)) # 显示测试结果摘要 print(f"\n{'='*50}") print("🏛️ 测试结果摘要") print(f"{'='*50}") passed = 0 total = len(results) for test_name, result in results: status = "✅ 通过" if result else "❌ 失败" print(f"{status} {test_name}") if result: passed += 1 print(f"\n📊 总体结果: {passed}/{total} 测试通过") if passed == total: print("🎉 所有测试通过！Vertex AI Memory Bank 集成成功！") else: print("⚠️ 部分测试失败，请检查配置和网络连接") if __name__ == "__main__": # 运行测试 asyncio.run(main())