Aoun-Ai / verify_rag.py
MuhammadMahmoud's picture
enhance rag
468ea61
import os
import sys
# Add current dir to path to allow absolute imports
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__))))
import asyncio
from app.core.config import settings
from app.services.rag.embedder import embedder
from app.services.rag.vector_store import vector_store
from app.services.rag.rag_engine import rag_engine
async def main():
print("Initializing embedder...")
embedder.initialize()
print(f"Embedder mode: {embedder.is_ready}, dimension: {embedder.dimension}")
vec = embedder.embed_text("مرحبا بك في منصة عون")
if vec:
print(f"Embedding successful: Length {len(vec)}, first elements: {vec[:3]}")
else:
print("Embedding failed!")
print("\nConnecting to Qdrant (Make sure Docker is running!)...")
# This might fail if Docker Qdrant is not up, but it shouldn't crash the app.
success = vector_store.connect()
print(f"Qdrant connection: {success}")
if success:
print(vector_store.get_collection_info())
print("\nInitializing RAG Engine...")
rag_engine.initialize()
print(f"TF-IDF Matrix Shape: {rag_engine.tfidf_matrix.shape if rag_engine.tfidf_matrix is not None else 'None'}")
print("\nTesting Hybrid Search:")
res = rag_engine.search("كيف يتم دعم الأسر؟")
for r in res:
print(f"- [Score: {r['score']:.4f}]: {r['title']}")
if __name__ == "__main__":
asyncio.run(main())