asfasdf3

app.py

@@ -106,27 +106,11 @@ def rag_answer(question: str, collection) -> str:
     context = retrieve_context(question, collection, top_k=2)
     return generate_agent_answer(context, question)
 
-
-def answer_question(question):
-    """
-    Main function that processes the question and returns the answer
-    """
-    if not question.strip():
-        return "Please enter a question about Inha University."
-    
-    try:
-        answer = rag_answer(question, collection)
-        return answer
-    except Exception as e:
-        return f"Sorry, I encountered an error: {str(e)}"
-
-
-import gradio as gr
-
-import gradio as gr
+# gradio interface code below
 
 def answer_question(user_input, history):
-    answer = "This is the answer about SGCS..."  # Replace with actual LLM output
+    answer = rag_answer(question, collection)
+    
     history.append({"role": "user", "content": user_input})
     history.append({"role": "assistant", "content": answer})
     return "", history