Update app.py

app.py

@@ -2,21 +2,28 @@ import streamlit as st
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-# Load the model
+# Load the model and tokenizer
 model_name = "Tom158/Nutri_Assist"
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
+# Set pad token if not already set
+if model.config.pad_token_id is None:
+    model.config.pad_token_id = model.config.eos_token_id
+
 # Streamlit App Interface
 st.title("Nutrition Chatbot")
 user_input = st.text_input("Ask me about nutrition:")
 
 if user_input:
-    # Process user input
-    inputs = tokenizer.encode(user_input, return_tensors="pt")
-    outputs = model.generate(inputs, max_length=50)
+    # Encode the input with attention mask
+    inputs = tokenizer.encode(user_input, return_tensors="pt", return_attention_mask=True)
+    input_ids = inputs['input_ids']
+    attention_mask = inputs['attention_mask']
+    
+    # Generate output with attention mask and pad token ID
+    outputs = model.generate(input_ids, attention_mask=attention_mask, max_length=50)
     answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
     
     # Display answer
     st.write("Answer:", answer)
-