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import gradio as gr | |
import websockets | |
import asyncio | |
import json | |
async def process_audio_stream(audio_path, max_tokens): | |
""" | |
Process audio with streaming response via WebSocket | |
""" | |
if not audio_path: | |
return "Please upload or record an audio file first." | |
try: | |
# Read audio file | |
with open(audio_path, 'rb') as f: | |
audio_data = f.read() | |
# Connect to WebSocket | |
async with websockets.connect('ws://localhost:8330/ws/process-audio/') as websocket: | |
# Send audio data | |
await websocket.send(audio_data) | |
# Send parameters | |
await websocket.send(json.dumps({ | |
"prompt": "", | |
"max_tokens": max_tokens | |
})) | |
# Initialize response | |
response = "" | |
# Receive streaming tokens | |
async for message in websocket: | |
if message == "[DONE]": | |
break | |
response += message | |
yield response | |
except Exception as e: | |
yield f"Error processing audio: {str(e)}" | |
# Create Gradio interface | |
demo = gr.Interface( | |
fn=process_audio_stream, | |
inputs=[ | |
gr.Audio( | |
type="filepath", | |
label="Upload or Record Audio", | |
sources=["upload", "microphone"] | |
), | |
gr.Slider( | |
minimum=50, | |
maximum=200, | |
value=50, | |
step=1, | |
label="Max Tokens" | |
) | |
], | |
outputs=gr.Textbox(label="Response", interactive=False), | |
title="Nexa Omni", | |
description="Upload an audio file and optionally provide a prompt to analyze the audio content.", | |
examples=[ | |
["example_audios/example_1.wav", 200], | |
] | |
) | |
def clear_output(audio, max_tokens): | |
return "" | |
demo.load_examples = clear_output | |
if __name__ == "__main__": | |
demo.queue().launch() | |