redeploy for prod

app.py

@@ -97,9 +97,10 @@ async def search_documents(
 
         # Encode the query using the custom embedding function
         query_embedding = embed_text(body.query)
-
+        print(body.query)
         collection_name = "embed"  # Use the collection name where the embeddings are stored    
 
+        logging.info("Performing search using the precomputed embeddings")
         # Perform search using the precomputed embeddings
         hits, error = searcher.search_documents(collection_name, query_embedding, user_id, body.limit)
         
@@ -130,7 +131,7 @@ async def generate_rag_response_api(
 
         # Encode the query using the custom embedding function
         query_embedding = embed_text(body.search_query)
-
+        print(body.query)
         collection_name = "embed"  # Use the collection name where the embeddings are stored   
         # Perform search using the precomputed embeddings
         hits, error = searcher.search_documents(collection_name, query_embedding, user_id)

services/qdrant_searcher.py

@@ -55,4 +55,5 @@ class QdrantSearcher:
             hits_list.append(hit_info)
 
         logging.info(f"Document search completed with {len(hits_list)} hits")
+        logging.info(f"Hits: {hits_list}")
         return hits_list, None