Update app.py

app.py

@@ -1,4 +1,6 @@
 import gradio as gr
+import spaces
+import torch
 from langchain.document_loaders import TextLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.embeddings import HuggingFaceEmbeddings
@@ -39,29 +41,33 @@ qa_chain = RetrievalQA.from_chain_type(
     return_source_documents=False
 )
 
+@spaces.GPU
 def preprocess_query(query):
     if "script" in query or "code" in query.lower():
         return f"Write a CPSL script: {query}"
     return query
 
+@spaces.GPU
 def clean_response(response):
     result = response.get("result", "")
     if "Answer:" in result:
         return result.split("Answer:")[1].strip()
     return result.strip()
 
+@spaces.GPU
 def chatbot_response(user_input):
     processed_query = preprocess_query(user_input)
     raw_response = qa_chain.invoke({"query": processed_query})
     return clean_response(raw_response)
 
-# Gradio interface
+@spaces.GPU
 with gr.Blocks() as demo:
     gr.Markdown("# CPSL Chatbot")
     chat_history = gr.Chatbot()
     user_input = gr.Textbox(label="Your Message:")
     send_button = gr.Button("Send")
 
+    @spaces.GPU
     def interact(user_message, history):
         bot_reply = chatbot_response(user_message)
         history.append((user_message, bot_reply))