#!/usr/bin/env python3
"""
测试修复后的查询解析功能
验证翻译和向量生成是否正常工作
"""

import sys
import os

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

def test_fixed_query_parsing():
    """测试修复后的查询解析"""
    print("🧪 测试修复后的查询解析功能")
    print("=" * 60)

    try:
        from context.request_context import create_request_context
        from query.query_parser import QueryParser
        from config import CustomerConfig
        from config.config_loader import ConfigLoader

        # 加载配置
        print("📝 加载配置...")
        loader = ConfigLoader()
        config = loader.load_customer_config("customer1")
        print(f"✅ 配置加载成功: {config.customer_id}")
        print(f"  - 翻译功能: {'启用' if config.query_config.enable_translation else '禁用'}")
        print(f"  - 向量功能: {'启用' if config.query_config.enable_text_embedding else '禁用'}")

        # 创建解析器和上下文
        parser = QueryParser(config)
        context = create_request_context("test_fixed", "test_user")

        # 测试查询
        test_query = "推车"
        print(f"\n🔍 测试查询: '{test_query}'")

        # 执行解析
        result = parser.parse(
            test_query,
            context=context,
            generate_vector=config.query_config.enable_text_embedding
        )

        # 显示结果
        print(f"\n📊 查询解析结果:")
        print(f"  原查询: {result.original_query}")
        print(f"  标准化: {result.normalized_query}")
        print(f"  重写后: {result.rewritten_query}")
        print(f"  检测语言: {result.detected_language}")
        print(f"  域: {result.domain}")
        print(f"  翻译结果: {result.translations}")

        if result.query_vector is not None:
            print(f"  向量: ✅ 已生成 (形状: {result.query_vector.shape})")
            print(f"  向量类型: {type(result.query_vector)}")
            print(f"  向量前5个值: {result.query_vector[:5]}")
        else:
            print(f"  向量: ❌ 未生成")

        # 检查翻译质量
        if result.translations:
            print(f"\n🌍 翻译质量检查:")
            for lang, translation in result.translations.items():
                if translation:
                    print(f"  {lang}: '{translation}' ✅")
                else:
                    print(f"  {lang}: 翻译失败 ❌")
        else:
            print(f"\n🌍 翻译: 无翻译结果")

        # 测试上下文存储
        print(f"\n💾 上下文存储检查:")
        stored_query = context.get_intermediate_result('normalized_query')
        stored_lang = context.get_intermediate_result('detected_language')
        stored_translations = context.get_intermediate_result('translations')

        print(f"  存储的查询: {stored_query}")
        print(f"  存储的语言: {stored_lang}")
        print(f"  存储的翻译: {stored_translations}")

        # 性能摘要
        summary = context.get_summary()
        print(f"\n📈 性能摘要:")
        print(f"  请求ID: {summary['request_info']['reqid']}")
        print(f"  用户ID: {summary['request_info']['uid']}")
        print(f"  有错误: {summary['request_info']['has_error']}")
        print(f"  警告数量: {summary['request_info']['warnings_count']}")
        print(f"  查询有向量: {summary['query_analysis']['has_vector']}")

        # 判断修复是否成功
        print(f"\n🎯 修复结果评估:")

        translation_success = (
            result.translations and
            any(translation is not None and translation != result.original_query
                for translation in result.translations.values())
        )

        vector_success = result.query_vector is not None

        print(f"  翻译功能: {'✅ 修复成功' if translation_success else '❌ 仍有问题'}")
        print(f"  向量功能: {'✅ 修复成功' if vector_success else '❌ 仍有问题'}")

        if translation_success and vector_success:
            print(f"\n🎉 所有功能修复成功！")
            return True
        else:
            print(f"\n⚠️  还有功能需要修复")
            return False

    except Exception as e:
        print(f"❌ 测试失败: {e}")
        import traceback
        traceback.print_exc()
        return False

if __name__ == "__main__":
    success = test_fixed_query_parsing()

    if success:
        print(f"\n✨ 修复验证完成 - 系统正常运行！")
    else:
        print(f"\n💥 修复验证失败 - 需要进一步检查")

    sys.exit(0 if success else 1)