addition of intro_msg

helpmate_ai.py

@@ -119,7 +119,7 @@ def retreive_results(query):
         # Query the collection against the user query and return the top 10 results
     results = insurance_collection.query(
         query_texts=query,
-        n_results=50
+        n_results=10
     )
 
     # Store the query in cache_collection as document w.r.t to ChromaDB so that it can be embedded and searched against later
@@ -156,7 +156,7 @@ from sentence_transformers import CrossEncoder, util
 cross_encoder = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')
 
 #function to re-rank results using cross-encoder
-def rerank_with_cross_encoder(query, results_df, top_k=10):
+def rerank_with_cross_encoder(query, results_df, top_k=3):
 
     # Input (query, response) pairs for each of the top 10 responses received from the semantic search to the cross encoder
     # Generate the cross_encoder scores for these pairs