Update recommender/retrieval_ranking.py

recommender/retrieval_ranking.py

@@ -11,7 +11,7 @@ from data import df
 # Function to generate direct query using Gemini
 def convert_to_direct_query_gradio(user_query,preferences,all_card_names, feature_list):
     genai.configure(api_key=os.environ.get("api_key_2"))  
-    model2 = genai.GenerativeModel('gemini-1.5-flash-latest')
+    model2 = genai.GenerativeModel('gemini-2.0-flash')
     
     preferences_text = ""
     if preferences:
@@ -100,7 +100,7 @@ def convert_to_direct_query_gradio(user_query,preferences,all_card_names, featur
 # Function to generate multiple focused subqueries from a user query
 def generate_multi_queries(direct_query, n=3):
     genai.configure(api_key=os.environ.get("api_key_2"))  
-    model2 = genai.GenerativeModel('gemini-1.5-flash-latest')
+    model2 = genai.GenerativeModel('gemini-2.0-flash')
     prompt = f"""
     The following is a detailed credit card search query:
     "{direct_query}"
@@ -208,7 +208,7 @@ def retrieve_and_rank_cards(faiss_index,filtered_mapping,direct_query, queries,
 
 def generate_credit_card_recommendation_gemini(indirect_query,user_query,retrieved_cards, max_new_tokens=500):
     genai.configure(api_key=os.environ.get("api_key_3"))  
-    model3 = genai.GenerativeModel('gemini-1.5-flash-latest')
+    model3 = genai.GenerativeModel('gemini-2.0-flash')
     print("using gemini")
     if not retrieved_cards:
         return "Unfortunately, no credit cards match your eligibility criteria."