Update rag.py

rag.py

@@ -24,13 +24,6 @@ similarity_model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
 HF_DATASET_REPO = "midrees2806/unmatched_queries"
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-# Greeting list
-GREETINGS = [
-    "hi", "hello", "hey", "good morning", "good afternoon", "good evening",
-    "assalam o alaikum", "salam", "aoa", "hi there",
-    "hey there", "greetings"
-]
-
 # Load dataset (automatically using the path)
 with open('dataset.json', 'r') as f:
     dataset = json.load(f)
@@ -79,13 +72,6 @@ def get_best_answer(user_input):
         return "Please enter a valid question."
     user_input_lower = user_input.lower().strip()
 
-    if any(greet in user_input_lower for greet in GREETINGS):
-        greeting_response = query_groq_llm(
-            f"You are an official assistant for University of Education Lahore. "
-            f"Respond to this greeting in a friendly and professional manner: {user_input}"
-        )
-        return greeting_response if greeting_response else "Hello! How can I assist you today?"
-
     # 👉 Check if question is about fee
     if any(keyword in user_input_lower for keyword in ["fee structure", "fees structure"]):
         return (