import asyncio
import sys
import os
sys.path.insert(0, '.')

async def test_specific_query():
    from app.services.vector_db import VectorDB
    from app.services.vector_operations import VectorOperations
    import numpy as np
    
    vdb = VectorDB()
    loaded = vdb.load(22)
    print(f"Index loaded: {loaded}")
    
    query = "What programs / degrees does Iqra University offer?"
    # The E5 model needs 'query: ' prefix for queries
    query_with_prefix = f"query: {query}"
    
    query_emb = await VectorOperations.get_embedding(query)
    
    print("\n--- Testing with default min_score=0.3 ---")
    results = vdb.search(
        np.array(query_emb, dtype=np.float32),
        22,
        k=8,
        min_score=0.3,
        min_truth_level=None
    )
    
    print(f"Found {len(results)} results with min_score=0.3")
    for meta, score in results:
        print(f"  Score: {score:.4f} | {meta.get('text', '')[:100]}...")

    print("\n--- Testing with min_score=0.0 to see raw scores ---")
    results_raw = vdb.search(
        np.array(query_emb, dtype=np.float32),
        22,
        k=8,
        min_score=0.0,
        min_truth_level=None
    )
    
    print(f"Found {len(results_raw)} results total")
    for meta, score in results_raw:
        print(f"  Score: {score:.4f} | {meta.get('text', '')[:100]}...")

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