import gradio as gr

# Replace with the actual LLaMa3 model ID from Hugging Face Hub when available
model_id = "varox34/Llama-3-Mistral-v0.2-Instruct-slerp"

def inference(prompt):
    # Import necessary libraries (replace with LLaMa3-specific ones)
    from transformers import pipeline

    # Create a pipeline using the LLaMa3 model ID (assuming compatibility)
    pipe = pipeline("text-generation", model=model_id)

    # Generate text based on the prompt
    response = pipe(prompt, max_length=250, num_return_sequences=1)[0]["generated_text"]
    return response

interface = gr.Interface(
    fn=inference,
    inputs="text",
    outputs="text",
    title="LLama3 Inference",
    description="Enter a prompt and get text generated by LLaMa3 (if available).",
)

interface.launch()