Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import pandas as pd
 from transformers import pipeline
+import spaces
 
 # Load CSV data
 data = pd.read_csv('documents.csv')
@@ -10,6 +11,7 @@ data = pd.read_csv('documents.csv')
 qa_model = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
 
 # Function to retrieve the relevant document and generate a response
+@spaces.GPU(duration=120)
 def retrieve_and_generate(question):
     # Combine all abstracts into a single string (you can improve this by better retrieval methods)
     abstracts = " ".join(data['Abstract'].fillna("").tolist())