"""
测试 kb_search_dynamic 工具 - 课程咨询场景
"""

import asyncio
import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).parent.parent))

from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
from sqlalchemy.orm import sessionmaker
from app.services.mid.kb_search_dynamic_tool import (
    KbSearchDynamicTool,
    KbSearchDynamicConfig,
    StepKbConfig,
)
from app.core.config import get_settings


async def test_kb_search():
    """测试知识库搜索 - 课程咨询场景"""
    settings = get_settings()
    
    engine = create_async_engine(settings.database_url)
    async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
    
    async with async_session() as session:
        config = KbSearchDynamicConfig(
            enabled=True,
            top_k=10,
            timeout_ms=15000,
            min_score_threshold=0.3,
        )
        
        tool = KbSearchDynamicTool(session=session, config=config)
        
        course_kb_id = "75c465fe-277d-455d-a30b-4b168adcc03b"
        
        step_kb_config = StepKbConfig(
            allowed_kb_ids=[course_kb_id],
            preferred_kb_ids=[course_kb_id],
            step_id="test_course_query",
        )
        
        test_params = {
            "query": "课程介绍",
            "tenant_id": "szmp@ash@2026",
            "top_k": 10,
            "context": {
                "grade": "五年级",
            },
            "step_kb_config": step_kb_config,
        }
        
        print(f"\n{'='*80}")
        print(f"测试: kb_search_dynamic - 课程知识库")
        print(f"{'='*80}")
        print(f"参数: query={test_params['query']}")
        print(f"      tenant_id={test_params['tenant_id']}")
        print(f"      context={test_params['context']}")
        print(f"      step_kb_config.allowed_kb_ids={step_kb_config.allowed_kb_ids}")
        print(f"超时设置: {config.timeout_ms}ms")
        print(f"最低分数阈值: {config.min_score_threshold}")
        
        try:
            result = await tool.execute(**test_params)
            
            print(f"\n结果:")
            print(f"  success: {result.success}")
            print(f"  hits count: {len(result.hits)}")
            print(f"  applied_filter: {result.applied_filter}")
            print(f"  fallback_reason_code: {result.fallback_reason_code}")
            print(f"  duration_ms: {result.duration_ms}")
            
            if result.filter_debug:
                print(f"  filter_debug: {result.filter_debug}")
            
            if result.step_kb_binding:
                print(f"  step_kb_binding: {result.step_kb_binding}")
            
            if result.tool_trace:
                print(f"\n  Tool Trace:")
                print(f"    tool_name: {result.tool_trace.tool_name}")
                print(f"    status: {result.tool_trace.status}")
                print(f"    duration_ms: {result.tool_trace.duration_ms}")
                print(f"    args_digest: {result.tool_trace.args_digest}")
                print(f"    result_digest: {result.tool_trace.result_digest}")
                if hasattr(result.tool_trace, 'arguments') and result.tool_trace.arguments:
                    print(f"    arguments: {result.tool_trace.arguments}")
            
            if result.hits:
                print(f"\n  检索结果 (共 {len(result.hits)} 条):")
                for i, hit in enumerate(result.hits, 1):
                    text = hit.get('text', '')
                    text_preview = text[:200] + '...' if len(text) > 200 else text
                    score = hit.get('score', 0)
                    metadata = hit.get('metadata', {})
                    collection = hit.get('collection', 'unknown')
                    kb_id = hit.get('kb_id', 'unknown')
                    print(f"\n    [{i}] score={score:.4f}")
                    print(f"        collection: {collection}")
                    print(f"        kb_id: {kb_id}")
                    print(f"        metadata: {metadata}")
                    print(f"        text: {text_preview}")
            else:
                print(f"\n  ⚠️  没有命中任何结果")
                print(f"  请检查:")
                print(f"    1. 知识库是否有数据")
                print(f"    2. 向量是否正确生成")
                print(f"    3. 过滤条件是否过于严格")
                
        except Exception as e:
            print(f"\n  ❌ 错误: {e}")
            import traceback
            traceback.print_exc()


if __name__ == "__main__":
    asyncio.run(test_kb_search())