app.py

import gradio as gr
from huggingface_hub import InferenceClient

# Change this to point to your model
client = InferenceClient("Danna8/aya-8b")

def respond(
    message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p,
):
    messages = [{"role": "system", "content": system_message}]
    
    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})
    
    messages.append({"role": "user", "content": message})
    
    try:
        response = ""
        for message in client.text_generation(
            prompt=message,  # Changed to use text_generation instead of chat_completion
            max_new_tokens=max_tokens,
            stream=True,
            temperature=temperature,
            top_p=top_p,
        ):
            response += message
            yield response
    except Exception as e:
        yield f"Error: {str(e)}"

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)",
        ),
    ],
)

if __name__ == "__main__":
    demo.launch()