"""
Phase 1 基础设施测试

测试项：
1. 依赖包导入
2. API密钥配置
3. LLM连接
4. 批量搜索工具
"""

import sys
import os

# 添加src目录到Python路径
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))


def test_imports():
    """测试所有必要的包是否能正确导入"""
    print("=" * 60)
    print("测试 1: 检查依赖包导入")
    print("=" * 60)

    try:
        import deepagents
        print("✓ deepagents 导入成功")
    except ImportError as e:
        print(f"✗ deepagents 导入失败: {e}")
        return False

    try:
        import langchain
        print("✓ langchain 导入成功")
    except ImportError as e:
        print(f"✗ langchain 导入失败: {e}")
        return False

    try:
        import tavily
        print("✓ tavily 导入成功")
    except ImportError as e:
        print(f"✗ tavily 导入失败: {e}")
        return False

    try:
        from dotenv import load_dotenv
        print("✓ python-dotenv 导入成功")
    except ImportError as e:
        print(f"✗ python-dotenv 导入失败: {e}")
        return False

    try:
        import click
        print("✓ click 导入成功")
    except ImportError as e:
        print(f"✗ click 导入失败: {e}")
        return False

    try:
        from rich import print as rprint
        print("✓ rich 导入成功")
    except ImportError as e:
        print(f"✗ rich 导入失败: {e}")
        return False

    print("\n所有依赖包导入成功！\n")
    return True


def test_config():
    """测试配置是否正确"""
    print("=" * 60)
    print("测试 2: 检查配置")
    print("=" * 60)

    try:
        from src.config import Config

        print(f"LLM模型: {Config.LLM_MODEL}")
        print(f"LLM温度: {Config.LLM_TEMPERATURE}")
        print(f"最大Tokens: {Config.LLM_MAX_TOKENS}")
        print(f"默认深度模式: {Config.DEFAULT_DEPTH}")
        print(f"最大并行搜索数: {Config.MAX_PARALLEL_SEARCHES}")
        print(f"搜索超时: {Config.SEARCH_TIMEOUT}秒")

        # 检查API密钥
        if Config.DASHSCOPE_API_KEY and Config.DASHSCOPE_API_KEY != "your_dashscope_api_key_here":
            print("✓ DASHSCOPE_API_KEY 已配置")
        else:
            print("✗ DASHSCOPE_API_KEY 未配置或使用默认值")
            print("  请在.env文件中设置真实的API密钥")
            return False

        if Config.TAVILY_API_KEY and Config.TAVILY_API_KEY != "your_tavily_api_key_here":
            print("✓ TAVILY_API_KEY 已配置")
        else:
            print("✗ TAVILY_API_KEY 未配置或使用默认值")
            print("  请在.env文件中设置真实的API密钥")
            return False

        print("\n配置检查通过！\n")
        return True

    except Exception as e:
        print(f"✗ 配置检查失败: {e}\n")
        return False


def test_llm_connection():
    """测试LLM连接"""
    print("=" * 60)
    print("测试 3: 检查LLM连接")
    print("=" * 60)

    try:
        from src.config import Config

        llm = Config.get_llm()
        print(f"LLM实例创建成功: {llm.model_name}")

        # 发送一个简单的测试消息
        print("发送测试消息...")
        response = llm.invoke("你好，请用一句话介绍你自己。")
        print(f"LLM响应: {response.content[:100]}...")

        print("\n✓ LLM连接测试成功！\n")
        return True

    except Exception as e:
        print(f"✗ LLM连接测试失败: {e}\n")
        return False


def test_search_tools():
    """测试批量搜索工具"""
    print("=" * 60)
    print("测试 4: 检查批量搜索工具")
    print("=" * 60)

    try:
        from src.tools.search_tools import batch_internet_search

        # 测试并行搜索
        test_queries = [
            "Python programming",
            "Machine learning basics",
            "Web development tutorial"
        ]

        print(f"执行 {len(test_queries)} 个并行搜索...")
        print(f"查询: {test_queries}")

        result = batch_internet_search.invoke({
            "queries": test_queries,
            "max_results_per_query": 3
        })

        print(f"\n搜索结果统计:")
        print(f"  总查询数: {result['total_queries']}")
        print(f"  成功查询: {result['successful_queries']}")
        print(f"  失败查询: {result['failed_queries']}")
        print(f"  总结果数: {result['total_results']}")
        print(f"  去重后结果数: {result['unique_results']}")

        if result['errors']:
            print(f"\n错误信息:")
            for error in result['errors']:
                print(f"  - {error}")

        if result['success'] and result['unique_results'] > 0:
            print(f"\n前3个搜索结果:")
            for i, res in enumerate(result['results'][:3], 1):
                print(f"  {i}. {res.get('title', 'N/A')}")
                print(f"     URL: {res.get('url', 'N/A')}")
                print(f"     得分: {res.get('score', 'N/A')}")

            print("\n✓ 批量搜索工具测试成功！\n")
            return True
        else:
            print("\n✗ 批量搜索工具测试失败：未返回有效结果\n")
            return False

    except Exception as e:
        print(f"✗ 批量搜索工具测试失败: {e}\n")
        import traceback
        traceback.print_exc()
        return False


def main():
    """运行所有测试"""
    print("\n")
    print("=" * 60)
    print("Phase 1 基础设施测试")
    print("=" * 60)
    print("\n")

    results = []

    # 测试1: 导入检查
    results.append(("依赖包导入", test_imports()))

    # 测试2: 配置检查
    results.append(("配置检查", test_config()))

    # 测试3: LLM连接（如果配置通过）
    if results[-1][1]:
        results.append(("LLM连接", test_llm_connection()))

    # 测试4: 搜索工具（如果配置通过）
    if results[1][1]:
        results.append(("批量搜索工具", test_search_tools()))

    # 总结
    print("=" * 60)
    print("测试总结")
    print("=" * 60)

    for test_name, passed in results:
        status = "✓ 通过" if passed else "✗ 失败"
        print(f"{test_name}: {status}")

    all_passed = all(result[1] for result in results)

    print("\n" + "=" * 60)
    if all_passed:
        print("✓ 所有测试通过！Phase 1 基础设施搭建完成。")
    else:
        print("✗ 部分测试失败，请检查配置和依赖。")
    print("=" * 60 + "\n")

    return all_passed


if __name__ == "__main__":
    success = main()
    sys.exit(0 if success else 1)