Update custom_utils.py

custom_utils.py

@@ -26,7 +26,7 @@ def rag_ingestion(collection):
     listings = process_records(dataset_df)
     collection.delete_many({})
     collection.insert_many(listings)
-    # Manually create a vector search index (in free tier, this feature is not available via SDK)
+    return "Manually create a vector search index (in free tier, this feature is not available via SDK)"
 
 def rag_retrieval(openai_api_key, prompt, db, collection, stages=[], vector_index="vector_index"):
     # Assuming vector_search returns a list of dictionaries with keys 'title' and 'plot'
@@ -45,6 +45,10 @@ def rag_retrieval(openai_api_key, prompt, db, collection, stages=[], vector_inde
     # Convert search results into a DataFrame for better rendering in Jupyter
     search_results_df = pd.DataFrame([item.dict() for item in search_results_models])
 
+    print("###")
+    print(search_results_df)
+    print("###")
+    
     return search_results_df
 
 def rag_inference(openai_api_key, prompt, search_results_df):
@@ -69,9 +73,9 @@ def rag_inference(openai_api_key, prompt, search_results_df):
     result = completion.choices[0].message.content
 
     print("###")
-    print(f"- User Content:\n{content}\n")
+    print(content)
     print("###")
-    print(f"- Prompt Completion:\n{result}\n")
+    print(result)
     print("###")
 
     return result