app.py

import streamlit as st
from transformers import pipeline

# Load a Hugging Face chat model
@st.cache_resource
def load_chatbot():
    return pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1", max_new_tokens=200)

chatbot = load_chatbot()

# Streamlit UI
st.title("💬 Chat with Mistral (Open Source ChatGPT)")
st.markdown("Ask me anything!")

if "history" not in st.session_state:
    st.session_state.history = []

user_input = st.text_input("Your message", "")

if user_input:
    st.session_state.history.append({"role": "user", "content": user_input})
    
    # Construct prompt
    full_prompt = "\n".join(
        [f"{m['role'].capitalize()}: {m['content']}" for m in st.session_state.history]
    ) + "\nAssistant:"

    response = chatbot(full_prompt)[0]["generated_text"]
    # Get only the new assistant response
    reply = response[len(full_prompt):].strip()
    st.session_state.history.append({"role": "assistant", "content": reply})

# Display chat history
for message in st.session_state.history:
    st.markdown(f"**{message['role'].capitalize()}:** {message['content']}")