Update app.py

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
 
 # Load the model and tokenizer
 model_name = "GRMenon/mental-health-mistral-7b-instructv0.2-finetuned-V2"
@@ -11,7 +12,10 @@ def get_bot_response(user_input):
     inputs = tokenizer.encode(user_input, return_tensors="pt")
 
     # Generate response
-    bot_response = model.generate(inputs, max_length=100, num_return_sequences=1)
+    try:
+        bot_response = model.generate(inputs, max_length=100, num_return_sequences=1)
+    except Exception as e:
+        return f"Sorry, an error occurred while generating a response: {e}"
 
     # Decode and return response
     return tokenizer.decode(bot_response[0], skip_special_tokens=True)