Update rag.py

rag.py

@@ -23,8 +23,8 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 # Greeting list
 GREETINGS = [
     "hi", "hello", "hey", "good morning", "good afternoon", "good evening",
-    "assalam o alaikum", "salam", "namaste", "hola", "bonjour", "hi there",
-    "hey there", "greetings", "howdy"
+    "assalam o alaikum", "salam", "aoa", "hi there",
+    "hey there", "greetings"
 ]
 
 # Load local dataset
@@ -110,21 +110,35 @@ def get_best_answer(user_input):
 
     if best_score >= 0.65:
         original_answer = dataset_answers[best_match_idx]
-        prompt = f"""As an official assistant for University of Education Lahore, provide a clear response:
-        Question: {user_input}
-        Original Answer: {original_answer}
-        Improved Answer:"""
+        prompt = f"""You are an official assistant for the University of Education Lahore.
+
+Rephrase the following official answer clearly and professionally. 
+Use structured formatting (like headings, bullet points, or numbered lists) where appropriate.
+DO NOT add any new or extra information. ONLY rephrase and improve the clarity and formatting of the original answer.
+
+### Question:
+{user_input}
+
+### Original Answer:
+{original_answer}
+
+### Rephrased Answer:
+"""
     else:
         prompt = f"""As an official assistant for University of Education Lahore, provide a helpful response:
-        Include relevant details about university policies.
-        If unsure, direct to official channels.
-        Question: {user_input}
-        Official Answer:"""
+Include relevant details about university policies.
+If unsure, direct to official channels.
+
+### Question:
+{user_input}
+
+### Official Answer:
+"""
 
     llm_response = query_groq_llm(prompt)
 
     if llm_response:
-        for marker in ["Improved Answer:", "Official Answer:"]:
+        for marker in ["Improved Answer:", "Official Answer:", "Rephrased Answer:"]:
             if marker in llm_response:
                 return llm_response.split(marker)[-1].strip()
         return llm_response