Update agents/chat.py

agents/chat.py

@@ -1,68 +1,68 @@
-import pandas as pd
-import google.generativeai as genai
-import os
-from data import eligibility_df
-
-#function for the chatbot functionality
-eligibility_lookup = {}
-for _, row in eligibility_df.iterrows():
-    card_name = row["Name"].strip()
-    eligibility_info = f"""
-        - Bank: {row['Bank']}
-        - Age: {row['Minimum Age']} to {row['Maximum Age']}
-        - Minimum Income: {row['Minimum Income (LPA)']} LPA
-        - Minimum Credit Score: {row['Minimum Credit Score']}
-        - Joining Fee: ₹{row['Joining fee']}
-        - Annual Fee: ₹{row['Annual fee']}
-    """
-    eligibility_lookup[card_name] = eligibility_info.strip()
-    
-# Function to handle chat interaction with Gemini
-def chat_with_gemini(user_query, user_message, chat_history, card_lookup): 
-    genai.configure(api_key=os.environ.get("api_key_4"))  
-    model4 = genai.GenerativeModel('gemini-1.5-flash-latest')
-    context = ""
-    for name, desc in list(card_lookup.items())[:5]:
-        eligibility_info = eligibility_lookup.get(name, "No eligibility or fee information available.")
-        full_desc = f"{desc}\n\nEligibility & Fees:\n{eligibility_info}"
-        context += f"{name}:\n{full_desc}\n\n"
-    recent_user_messages = [
-        msg["content"] for msg in chat_history if msg["role"] == "user"
-    ][-5:]
-
-    conversation = f"""
-        You are a helpful financial assistant. A user has already shared their overall credit card preferences.
-        
-        ### User’s Requirements:
-        {user_query}
-        
-        ### Credit Card Options:
-        {context}
-        
-        ### User's Follow-up Question:
-        {user_message}
-        
-        ### Recent User Messages:
-        {recent_user_messages}
-        
-        ### Instructions:
-        1. Answer the user's current question clearly and concisely.
-        2. Always consider the user's overall requirements above.
-        3. Use only the card descriptions provided. Do not assume or invent any card benefits.
-        4. If the user asks which card is best or suitable for their needs, use the user’s requirements above to select and explain.
-        5. Don't ask the user to restate their requirements — they're already provided above.
-    """
-    # print(conversation)
-    try:
-        response = model4.generate_content(conversation)
-        gemini_response = response.text
-
-        chat_history.append({"role": "user", "content": user_message})
-        chat_history.append({"role": "assistant", "content": gemini_response})
-
-    except Exception as e:
-        error_msg = "Error: Unable to retrieve response from Gemini. Please try again later."
-        chat_history.append({"role": "user", "content": user_message})
-        chat_history.append({"role": "assistant", "content": error_msg})
-
+import pandas as pd
+import google.generativeai as genai
+import os
+from data import eligibility_df
+
+#function for the chatbot functionality
+eligibility_lookup = {}
+for _, row in eligibility_df.iterrows():
+    card_name = row["Name"].strip()
+    eligibility_info = f"""
+        - Bank: {row['Bank']}
+        - Age: {row['Minimum Age']} to {row['Maximum Age']}
+        - Minimum Income: {row['Minimum Income (LPA)']} LPA
+        - Minimum Credit Score: {row['Minimum Credit Score']}
+        - Joining Fee: ₹{row['Joining fee']}
+        - Annual Fee: ₹{row['Annual fee']}
+    """
+    eligibility_lookup[card_name] = eligibility_info.strip()
+    
+# Function to handle chat interaction with Gemini
+def chat_with_gemini(user_query, user_message, chat_history, card_lookup): 
+    genai.configure(api_key=os.environ.get("api_key_4"))  
+    model4 = genai.GenerativeModel('gemini-2.0-flash')
+    context = ""
+    for name, desc in list(card_lookup.items())[:5]:
+        eligibility_info = eligibility_lookup.get(name, "No eligibility or fee information available.")
+        full_desc = f"{desc}\n\nEligibility & Fees:\n{eligibility_info}"
+        context += f"{name}:\n{full_desc}\n\n"
+    recent_user_messages = [
+        msg["content"] for msg in chat_history if msg["role"] == "user"
+    ][-5:]
+
+    conversation = f"""
+        You are a helpful financial assistant. A user has already shared their overall credit card preferences.
+        
+        ### User’s Requirements:
+        {user_query}
+        
+        ### Credit Card Options:
+        {context}
+        
+        ### User's Follow-up Question:
+        {user_message}
+        
+        ### Recent User Messages:
+        {recent_user_messages}
+        
+        ### Instructions:
+        1. Answer the user's current question clearly and concisely.
+        2. Always consider the user's overall requirements above.
+        3. Use only the card descriptions provided. Do not assume or invent any card benefits.
+        4. If the user asks which card is best or suitable for their needs, use the user’s requirements above to select and explain.
+        5. Don't ask the user to restate their requirements — they're already provided above.
+    """
+    # print(conversation)
+    try:
+        response = model4.generate_content(conversation)
+        gemini_response = response.text
+
+        chat_history.append({"role": "user", "content": user_message})
+        chat_history.append({"role": "assistant", "content": gemini_response})
+
+    except Exception as e:
+        error_msg = "Error: Unable to retrieve response from Gemini. Please try again later."
+        chat_history.append({"role": "user", "content": user_message})
+        chat_history.append({"role": "assistant", "content": error_msg})
+
     return chat_history, chat_history