Update app.py

app.py

@@ -1,15 +1,22 @@
+import streamlit as st
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
+# Load the model
 model_name = "Tom158/Nutri_Assist"
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-def chat(question):
-    inputs = tokenizer.encode(question, return_tensors="pt")
+# 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)
     answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return answer
+    
+    # Display answer
+    st.write("Answer:", answer)
 
-iface = gr.Interface(fn=chat, inputs="text", outputs="text")
-iface.launch()