app.py

import gradio as gr
from transformers import pipeline

chatbot = pipeline("text-generation", model="Qwen/Qwen2.5-0.5B-Instruct", trust_remote_code=True)

def respond(message, history):
    """Simplified response function"""
    prompt = ""
    for msg in history:
        prompt += f"{msg['role'].capitalize()}: {msg['content']}\n"
    
    prompt += f"Human: {message}\nAssistant:"
    
    response = chatbot(prompt, max_new_tokens=100)[0]['generated_text']
    return response.split("Assistant:")[-1].strip()

# Simple interface with voice
with gr.Blocks() as demo:
    gr.Markdown("# 🎤 Voice AI Assistant")
    
    # Chat interface
    chat_interface = gr.ChatInterface(
        fn=respond,
        title="AI Chat",
        description="Type or use voice input"
    )
    
    # Add voice input
    with gr.Row():
        audio = gr.Audio(sources=["microphone"], type="filepath", label="Voice Input")

demo.launch()