#!/usr/bin/env python3 """ SubAgent基础使用示例 展示SubAgent系统的基本功能: 1. 创建简单的对话Agent 2. 使用动态prompt模板 3. 结构化JSON输出 4. 错误处理和调试 """ import sys import os from typing import Optional # 添加项目根路径到Python路径 project_root = os.path.dirname(os.path.dirname(os.path.dirname(__file__))) sys.path.append(project_root) from src.agent_system import SubAgent from example_models import BasicResponse, SentimentAnalysis def create_simple_chat_agent() -> SubAgent: """创建简单的聊天Agent""" print("🤖 创建简单聊天Agent...") try: agent = SubAgent( provider="aliyun", model_name="qwen-turbo", name="simple_chat", description="简单的聊天助手", instructions=[ "你是一个友好的AI助手", "请用简洁明了的语言回答问题", "保持积极正面的态度" ] ) print("✅ 简单聊天Agent创建成功") return agent except Exception as e: print(f"❌ Agent创建失败: {e}") raise def create_structured_output_agent() -> SubAgent: """创建支持结构化输出的Agent""" print("\n🔧 创建结构化输出Agent...") try: agent = SubAgent( provider="aliyun", model_name="qwen-max", name="structured_responder", description="提供结构化响应的智能助手", instructions=[ "你是一个专业的响应助手", "始终提供结构化的JSON格式输出", "确保响应准确和有用" ], response_model=BasicResponse ) print("✅ 结构化输出Agent创建成功") return agent except Exception as e: print(f"❌ 结构化输出Agent创建失败: {e}") raise def create_sentiment_agent() -> SubAgent: """创建情感分析Agent""" print("\n💭 创建情感分析Agent...") instructions = [ "你是专业的文本情感分析专家", "准确识别文本的情感倾向：positive（积极）、negative（消极）、neutral（中性）", "提供0-1范围的置信度评分", "给出详细的分析说明和关键词" ] prompt_template = """ 请对以下文本进行情感分析： 文本内容："{text}" 分析要求： 1. 识别情感倾向（positive/negative/neutral） 2. 评估分析置信度（0-1之间的浮点数） 3. 提供分析说明和依据 4. 提取影响情感判断的关键词 请严格按照指定的JSON格式返回结果。 """ try: agent = SubAgent( provider="aliyun", model_name="qwen-max", name="sentiment_analyzer", description="专业的文本情感分析系统", instructions=instructions, prompt_template=prompt_template, response_model=SentimentAnalysis ) print("✅ 情感分析Agent创建成功") return agent except Exception as e: print(f"❌ 情感分析Agent创建失败: {e}") raise def demo_simple_chat(): """演示简单对话功能""" print("\n" + "="*50) print("🗣️ 简单对话演示") print("="*50) try: agent = create_simple_chat_agent() # 测试问题列表 test_questions = [ "你好！请介绍一下你自己", "什么是人工智能？", "请给我一些学习Python的建议" ] for i, question in enumerate(test_questions, 1): print(f"\n问题 {i}: {question}") try: response = agent.run(prompt=question) print(f"回答: {response}") except Exception as e: print(f"❌ 回答失败: {e}") return True except Exception as e: print(f"❌ 简单对话演示失败: {e}") return False def demo_structured_response(): """演示结构化响应功能""" print("\n" + "="*50) print("📋 结构化响应演示") print("="*50) try: agent = create_structured_output_agent() # 测试请求列表 test_requests = [ "请解释什么是机器学习", "介绍Python编程语言的特点", "如何提高工作效率？" ] for i, request in enumerate(test_requests, 1): print(f"\n请求 {i}: {request}") try: result = agent.run(prompt=request) print(f"✅ 响应成功:") print(f" 消息: {result.message}") print(f" 成功: {result.success}") print(f" 时间: {result.timestamp}") except Exception as e: print(f"❌ 响应失败: {e}") return True except Exception as e: print(f"❌ 结构化响应演示失败: {e}") return False def demo_dynamic_prompt(): """演示动态prompt模板功能""" print("\n" + "="*50) print("🎭 动态Prompt模板演示") print("="*50) try: agent = create_sentiment_agent() # 测试文本列表 test_texts = [ "这个产品质量非常好，我很满意！强烈推荐给大家。", "服务态度差，产品质量也不行，非常失望。", "产品功能还可以，价格也合理，算是中规中矩的选择。", "今天天气不错，适合出去散步。", "这部电影真是太精彩了！演员演技出色，剧情引人入胜。" ] for i, text in enumerate(test_texts, 1): print(f"\n文本 {i}: {text}") try: # 使用动态模板构建prompt result = agent.run(template_vars={"text": text}) print(f"✅ 分析结果:") print(f" 情感: {result.sentiment}") print(f" 置信度: {result.confidence}") print(f" 说明: {result.explanation}") print(f" 关键词: {result.keywords}") except Exception as e: print(f"❌ 分析失败: {e}") return True except Exception as e: print(f"❌ 动态prompt演示失败: {e}") return False def demo_error_handling(): """演示错误处理功能""" print("\n" + "="*50) print("⚠️ 错误处理演示") print("="*50) # 测试各种错误情况 error_tests = [ { "name": "无效的提供商", "params": {"provider": "invalid_provider", "model_name": "test"}, "expected_error": "ValueError" }, { "name": "空的prompt模板变量", "params": {"provider": "aliyun", "model_name": "qwen-turbo"}, "template_vars": {}, "prompt_template": "分析这个文本: {missing_var}", "expected_error": "SubAgentError" } ] for test in error_tests: print(f"\n测试: {test['name']}") try: if 'prompt_template' in test: agent = SubAgent(**test['params']) agent.update_prompt_template(test['prompt_template']) agent.run(template_vars=test.get('template_vars', {})) else: agent = SubAgent(**test['params']) print(f"❌ 预期错误未发生") except Exception as e: print(f"✅ 捕获到预期错误: {type(e).__name__}: {e}") return True def interactive_demo(): """交互式演示""" print("\n" + "="*50) print("💬 交互式演示") print("="*50) print("输入文本进行情感分析，输入'quit'退出") try: agent = create_sentiment_agent() while True: user_input = input("\n请输入要分析的文本: ").strip() if user_input.lower() == 'quit': print("再见!") break if not user_input: continue try: print(f"正在分析: {user_input}") result = agent.run(template_vars={"text": user_input}) print(f"\n📊 分析结果:") print(f"情感倾向: {result.sentiment}") print(f"置信度: {result.confidence:.3f}") print(f"分析说明: {result.explanation}") if result.keywords: print(f"关键词: {', '.join(result.keywords)}") except Exception as e: print(f"❌ 分析失败: {e}") except KeyboardInterrupt: print("\n程序已中断") except Exception as e: print(f"❌ 交互式演示失败: {e}") def show_agent_info(agent: SubAgent): """显示Agent信息""" info = agent.get_model_info() print(f"\n📋 Agent信息:") for key, value in info.items(): print(f" {key}: {value}") def main(): """主函数 - 运行所有演示""" print("🚀 SubAgent基础使用示例") print("=" * 60) # 运行所有演示 demos = [ ("简单对话", demo_simple_chat), ("结构化响应", demo_structured_response), ("动态Prompt", demo_dynamic_prompt), ("错误处理", demo_error_handling), ] results = {} for name, demo_func in demos: print(f"\n开始演示: {name}") try: success = demo_func() results[name] = success print(f"{'✅' if success else '❌'} {name}演示{'成功' if success else '失败'}") except Exception as e: print(f"❌ {name}演示异常: {e}") results[name] = False # 显示总结 print("\n" + "="*60) print("📊 演示总结") print("="*60) total_demos = len(results) successful_demos = sum(results.values()) for name, success in results.items(): status = "✅ 成功" if success else "❌ 失败" print(f" {name}: {status}") print(f"\n🎯 总计: {successful_demos}/{total_demos} 个演示成功") # 询问是否运行交互式演示 print(f"\n是否运行交互式演示？(y/n): ", end="") try: choice = input().strip().lower() if choice in ['y', 'yes', '是']: interactive_demo() except (KeyboardInterrupt, EOFError): print("\n程序结束") return successful_demos == total_demos def test_basic_functionality(): """测试基础功能""" print("正在测试SubAgent基础功能...") try: # 创建基本Agent agent = SubAgent( provider="aliyun", model_name="qwen-turbo", name="test_agent" ) print(f"✅ Agent创建成功: {agent}") # 显示Agent信息 show_agent_info(agent) # 测试简单对话 response = agent.run(prompt="请简单介绍一下你自己") print(f"✅ 对话测试成功，响应长度: {len(str(response))}字符") return True except Exception as e: print(f"❌ 基础功能测试失败: {e}") return False if __name__ == "__main__": # 可以选择运行测试或完整演示 import sys if len(sys.argv) > 1 and sys.argv[1] == "--test": # 仅运行基础测试 success = test_basic_functionality() exit(0 if success else 1) else: # 运行完整演示 main()