app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer

def main():
    st.title("Chatbot with Hugging Face Model")

    model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
    tokenizer = AutoTokenizer.from_pretrained(model_id)
    model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

    user_input = st.text_input("User Input:", "What is your favourite condiment?")

    if st.button("Generate Response"):
        messages = [
            {"role": "user", "content": user_input},
            {"role": "assistant", "content": "Placeholder assistant message"}  # You can modify this as needed
        ]

        inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")

        outputs = model.generate(inputs, max_new_tokens=20)
        response = tokenizer.decode(outputs[0], skip_special_tokens=True)

        st.text_area("Assistant's Response:", response)

if __name__ == "__main__":
    main()