#!/usr/bin/env python3
"""
检查 Qdrant 集合里的数据结构
"""

import asyncio
import os
import sys

from backend.rag_core import QdrantVectorStore
from backend.app.model_services import get_embedding_service


def check_qdrant_data():
    """检查 Qdrant 中的数据结构"""
    print("="*70)
    print("检查 Qdrant 中的数据结构...")
    print("="*70)
    
    embeddings = get_embedding_service()
    vs = QdrantVectorStore(collection_name="rag_documents", embeddings=embeddings)
    client = vs.get_qdrant_client()
    
    # 先获取几个点看看 payload 结构
    print("\n获取 5 个随机文档:")
    results = client.scroll(
        collection_name="rag_documents",
        limit=5,
        with_payload=True,
        with_vectors=True
    )
    
    for i, point in enumerate(results[0], 1):
        print(f"\n{i}. ID: {point.id}")
        print(f"   Payload: {point.payload}")
        print(f"   Payload 键: {list(point.payload.keys())}")
        if "text" in point.payload:
            text = point.payload["text"]
            print(f"   Text 长度: {len(text)}")
            print(f"   Text 预览: {text[:150]}...")
        if "page_content" in point.payload:
            print(f"   page_content: {point.payload['page_content'][:150]}...")
        
        # 看看向量
        if point.vector:
            print(f"   向量存在: {type(point.vector)}")
            if isinstance(point.vector, dict):
                print(f"   向量键: {list(point.vector.keys())}")


def check_sparse_embedder():
    """检查稀疏嵌入器"""
    from backend.rag_core import get_sparse_embedder
    
    print("\n" + "="*70)
    print("检查稀疏嵌入器...")
    print("="*70)
    
    sparse_embedder = get_sparse_embedder()
    
    print(f"\n稀疏嵌入器: {sparse_embedder}")
    print(f"Vocabulary 大小: {len(sparse_embedder.model.vocab)}")
    print(f"示例查询: '冬天 食物'")
    
    # 用中文试试
    sparse_vec = sparse_embedder.embed_query("冬天 食物")
    print(f"\n生成的稀疏向量:")
    print(f"  索引数量: {len(sparse_vec['indices'])}")
    print(f"  索引: {sparse_vec['indices'][:10]}")
    print(f"  值: {sparse_vec['values'][:10]}")


if __name__ == "__main__":
    check_qdrant_data()
    check_sparse_embedder()