app.py

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)

# 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)
    
    # Display answer
    st.write("Answer:", answer)