Update app.py

app.py

@@ -52,7 +52,6 @@ And ARKA? He is simply the reminder.
 That even in the dark, we are made to glow.
 """
 
-# Hardcoded FAQs (remains the same)
 # Hardcoded FAQs
 FAQ_ANSWERS = {
     "What is SAB-EK?": {
@@ -478,8 +477,8 @@ That is the moment it becomes real."""
 
 FAQ_QUESTIONS = list(FAQ_ANSWERS.keys())
 
-# Base URL for the Gemini API
-API_BASE_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent"
+# --- FIX: Corrected the Gemini API model name in the URL ---
+API_BASE_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent"
 
 # --- NEW: FAQ Matcher Class using Sentence Transformers ---
 class FAQMatcher:
@@ -533,7 +532,6 @@ faq_matcher = FAQMatcher(FAQ_QUESTIONS)
 def query_gemini_api(contents_payload, api_key):
     """
     Sends a structured contents payload to the Gemini API and returns the generated text.
-    (This function remains largely the same)
     """
     if not api_key:
         return "Error: GEMINI_API_KEY is not set. Please set it in your environment."
@@ -602,9 +600,6 @@ def respond_as_arka(message, chat_history):
         
         # Prepare conversation history
         gemini_chat_contents = [
-            # Note: The new Gemini API prefers the system instruction outside the 'contents' list.
-            # However, for compatibility with the older model/API structure, we keep it here.
-            # A more modern approach would use a 'system_instruction' key at the top level of the payload.
             {"role": "user", "parts": [{"text": system_instruction}]},
             {"role": "model", "parts": [{"text": "I understand. I am ARKA. I await the seeker's question."}]}
         ]