Update app.py

app.py

@@ -76,17 +76,19 @@ def retrieve_and_generate(question):
         # Embed the question
         question_embedding = embed_question(question, model, tokenizer)
 
+        # Ensure the embedding is in the correct format for FAISS search
+        question_embedding = question_embedding.astype(np.float32)
+
         # Search in FAISS index
         try:
-            if question_embedding.ndim == 2 and question_embedding.shape[0] == 1:
-                logging.debug("Correct question embedding shape for FAISS search.")
-            else:
-                logging.error(f"Incorrect question embedding shape: {question_embedding.shape}")
             _, indices = gpu_index.search(question_embedding, k=1)
+            if indices.size == 0:
+                logging.error("No results found in FAISS search.")
+                return "No relevant document found."
             logging.debug(f"Indices found: {indices}")
         except Exception as e:
             logging.error(f"Error during FAISS search: {e}")
-            return "An error occurred during search. Please try again."
+            return f"An error occurred during search: {e}"
 
         # Retrieve the most relevant document
         try: