app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the pretrained model and tokenizer separately
model = AutoModelForCausalLM.from_pretrained("Adityyaa/Mistral-7b_finetuned_mental_health")
tokenizer = AutoTokenizer.from_pretrained("Adityyaa/Mistral-7b_finetuned_mental_health")

# Define the Streamlit app
def main():
    st.title("Mental Health Chatbot")
    st.write("Enter your message below and the chatbot will respond.")

    user_input = st.text_input("You:", "")

    if st.button("Send"):
        if user_input:
            # Generate response from the chatbot
            input_ids = tokenizer.encode(user_input, return_tensors="pt")
            response = model.generate(input_ids, max_length=50, num_return_sequences=1)
            response_text = tokenizer.decode(response[0], skip_special_tokens=True)
            st.text_area("Chatbot:", response_text)
        else:
            st.warning("Please enter a message.")

if __name__ == "__main__":
    main()