app.py

import streamlit as st
from transformers import pipeline

# Load the model pipeline
@st.cache_resource  # Cache the model to avoid reloading
def load_pipeline():
    model_name = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
    return pipeline("text-generation", model=model_name)

pipe = load_pipeline()

# App UI
st.set_page_config(page_title="Hugging Face Chatbot", layout="centered")
st.title("🤖 AI Chatbot")
st.markdown(
    """
    Welcome to the **AI Chatbot** powered by Hugging Face's Llama-3.1-8B-Lexi-Uncensored-V2 model. 
    Enter your message below to get started!
    """
)

# Input Box
user_input = st.text_area(
    "Your Message", 
    placeholder="Type your message here...", 
    height=100
)

# Generate Button
if st.button("Generate Response"):
    if user_input.strip():
        with st.spinner("Generating response..."):
            response = pipe(user_input, max_length=150, num_return_sequences=1)
            st.text_area("Response", value=response[0]['generated_text'], height=200)
    else:
        st.warning("Please enter a message before clicking the button.")