app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

# Load the model and tokenizer from Hugging Face Hub
model_name = "teckmill/Jaleah-ai"  # Replace with your model repo name if needed
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Initialize the pipeline
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)

def generate_text(prompt):
    # Generate text using the model
    generated = generator(prompt, max_length=50)
    return generated[0]['generated_text']

# Streamlit UI
st.title("Jaleah AI - Text Generation")
st.write("Enter a prompt to generate text:")

# Text input for the user to enter a prompt
prompt = st.text_area("Prompt", "Once upon a time...")

# Button to trigger the model inference
if st.button("Generate Text"):
    if prompt:
        generated_text = generate_text(prompt)
        st.subheader("Generated Text")
        st.write(generated_text)
    else:
        st.warning("Please enter a prompt to generate text.")