app.py

import gradio as gr
import requests
import os

ACCESS_TOKEN = os.getenv("HF_TOKEN")

API_URL = "https://api-inference.huggingface.co/v1/chat/completions"
HEADERS = {"Authorization": f"Bearer {ACCESS_TOKEN}"}

def respond(
    message,
    history,
    system_message,
    max_tokens,
    temperature,
    top_p,
    frequency_penalty,
    seed,
    custom_model
):
    if seed == -1:
        seed = None
    
    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})
    
    model_to_use = custom_model.strip() if custom_model.strip() else "meta-llama/Llama-3.2-3B-Instruct"
    
    payload = {
        "model": model_to_use,
        "messages": messages,
        "max_tokens": max_tokens,
        "temperature": temperature,
        "top_p": top_p,
        "frequency_penalty": frequency_penalty,
        "seed": seed,
    }
    
    response = requests.post(API_URL, headers=HEADERS, json=payload)
    
    if response.status_code == 200:
        return response.json()["choices"][0]["message"]["content"]
    else:
        return "Error: " + response.text

chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="ChatGPT is initializing...", likeable=True, layout="panel")

system_message_box = gr.Textbox(value="System message here", label="System Message")
max_tokens_slider = gr.Slider(1024, 2048, value=1024, step=100, label="Max Tokens")
temperature_slider = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Temperature")
top_p_slider = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-P")
frequency_penalty_slider = gr.Slider(-2.0, 2.0, value=0.0, step=0.1, label="Frequency Penalty")
seed_slider = gr.Slider(-1, 65535, value=-1, step=1, label="Seed (-1 for random)")
custom_model_box = gr.Textbox(value="meta-llama/Llama-3.2-3B-Instruct", label="Custom Model")

voice_input = gr.Microphone(label="Speak your message")

with gr.Blocks() as demo:
    gr.Markdown("# AI Chatbot with Voice Input")
    chatbot.render()
    
    with gr.Row():
        system_message_box.render()
        max_tokens_slider.render()
        temperature_slider.render()
        top_p_slider.render()
    
    with gr.Row():
        frequency_penalty_slider.render()
        seed_slider.render()
        custom_model_box.render()
    
    voice_input.render()
    
    voice_input.change(respond, inputs=[voice_input, chatbot, system_message_box, max_tokens_slider, temperature_slider, top_p_slider, frequency_penalty_slider, seed_slider, custom_model_box], outputs=chatbot)

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