import gradio as gr
from huggingface_hub import InferenceClient

client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")

def format_alpaca_prompt(user_input, system_prompt):
    """Formats input in Alpaca/LLaMA style"""
    prompt = f"""{system_prompt}

### Instruction:
{user_input}

### Response:
"""
    return prompt

def respond(message, history, system_message, max_tokens, temperature, top_p):
    formatted_prompt = format_alpaca_prompt(message, system_message)

    response = client.text_generation(
        formatted_prompt,  # ✅ Pass as a single string
        max_new_tokens=max_tokens,  # ✅ Use max_new_tokens, not max_tokens
        temperature=temperature,
        top_p=top_p,
    )

    yield response  # ✅ Output the generated response

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=250, value=128, step=1, label="Max new tokens"),  # ✅ Keep ≤250
        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()