"""
检查课程知识库的录入情况
"""

import asyncio
import sys
from pathlib import Path

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

from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
from sqlalchemy.orm import sessionmaker
from app.core.config import get_settings
from app.core.qdrant_client import QdrantClient
from app.models.entities import Document


async def check_course_kb_status():
    """检查课程知识库的录入情况"""
    settings = get_settings()
    
    engine = create_async_engine(settings.database_url)
    async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
    
    tenant_id = "szmp@ash@2026"
    kb_id = "75c465fe-277d-455d-a30b-4b168adcc03b"
    
    print(f"\n{'='*80}")
    print(f"检查课程知识库的录入情况")
    print(f"{'='*80}")
    print(f"租户 ID: {tenant_id}")
    print(f"知识库 ID: {kb_id}")
    
    async with async_session() as session:
        stmt = select(Document).where(
            Document.tenant_id == tenant_id,
            Document.kb_id == kb_id,
        )
        result = await session.execute(stmt)
        documents = result.scalars().all()
        
        print(f"\n数据库中的文档记录: {len(documents)} 个")
        if documents:
            for doc in documents[:5]:
                print(f"  - {doc.file_name} (status: {doc.status})")
            if len(documents) > 5:
                print(f"  ... 还有 {len(documents) - 5} 个文档")
    
    client = QdrantClient()
    qdrant = await client.get_client()
    
    collection_name = client.get_kb_collection_name(tenant_id, kb_id)
    print(f"\nQdrant Collection 名称: {collection_name}")
    
    exists = await qdrant.collection_exists(collection_name)
    if exists:
        points_result = await qdrant.scroll(
            collection_name=collection_name,
            limit=5,
            with_vectors=False,
        )
        points = points_result[0] if isinstance(points_result, tuple) else points_result
        print(f"Qdrant Collection 存在，有 {len(points)} 条数据")
        for i, point in enumerate(points, 1):
            if hasattr(point, 'payload'):
                payload = point.payload
                point_id = point.id
            else:
                payload = point.get('payload', {})
                point_id = point.get('id', 'unknown')
            print(f"  [{i}] id: {point_id}")
            if 'text' in payload:
                text = payload['text'][:50] + '...' if len(payload['text']) > 50 else payload['text']
                print(f"      text: {text}")
    else:
        print(f"Qdrant Collection 不存在!")
    
    print(f"\n{'='*80}")
    print(f"结论:")
    if len(documents) > 0 and not exists:
        print("  数据库有文档记录，但 Qdrant Collection 不存在")
        print("  需要等待文档向量化任务完成")
    elif len(documents) == 0 and exists:
        print("  数据库没有文档记录，但 Qdrant Collection 存在")
        print("  可能是旧数据")
    elif len(documents) > 0 and exists:
        print(f"  数据库有 {len(documents)} 个文档记录")
        print(f"  Qdrant Collection 存在")
        print("  ✅ 知识库已录入完成")
    else:
        print("  数据库没有文档记录")
        print("  Qdrant Collection 不存在")
        print("  ❌ 知识库未录入")


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