MedResearcher/example/subagent-example/basic_example.py

#!/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()