app.py

import gradio as gr
from smolagents import CodeAgent, HfApiModel
from gradio_client import Client
import tempfile

# Initialize Qwen2.5-Omni-7B via SmolAgents
qwen_agent = CodeAgent(
    tools=[],  # Add multimodal tools as needed
    model=HfApiModel("Qwen/Qwen2.5-Omni-7B"),
    execution_timeout=120
)

def process_video(video_path, prompt, request: gr.Request):
    # Handle ZeroGPU rate limiting
    headers = {"X-IP-Token": request.headers.get('x-ip-token', '')}

    # Process video with Qwen's multimodal capabilities
    response = qwen_agent.run(
        f"Analyze this video: {video_path} and {prompt}",
        headers=headers
    )

    # Generate real-time speech response
    audio_response = qwen_agent.model.generate_speech(response)

    return response, audio_response

with gr.Blocks() as demo:
    gr.Markdown("## Multimodal AI Demo with Qwen2.5-Omni-7B")

    with gr.Row():
        video_input = gr.Video(label="Upload Video", sources=["upload"])
        prompt_input = gr.Textbox(label="Analysis Prompt")

    submit_btn = gr.Button("Analyze")

    with gr.Column():
        text_output = gr.Textbox(label="Analysis Results")
        audio_output = gr.Audio(label="Voice Response", autoplay=True)

    submit_btn.click(
        process_video,
        inputs=[video_input, prompt_input, gr.Request()],
        outputs=[text_output, audio_output]
    )

# ZeroGPU configuration
demo.queue(default_concurrency_limit=5)
demo.launch(server_name="0.0.0.0", server_port=7860)