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import gradio as gr
import requests
import os
# FastAPI endpoint
API_URL = "https://nexa-omni.nexa4ai.com/process-audio/"
# Add this global variable to track the last valid audio file
last_valid_audio = None
def process_audio(audio_path, max_tokens):
"""
Send audio file to FastAPI backend for processing
"""
global last_valid_audio
# Check audio file availability
if audio_path and os.path.exists(audio_path):
# New audio uploaded/recorded
last_valid_audio = audio_path
elif not audio_path and not last_valid_audio:
# No audio provided and no previous valid audio
return "Please upload or record an audio file first."
# Use the appropriate audio path
current_audio = last_valid_audio if last_valid_audio else audio_path
try:
# Only proceed if we have a valid audio file
if current_audio and os.path.exists(current_audio):
files = {
'file': ('audio.wav', open(current_audio, 'rb'), 'audio/wav')
}
data = {'max_tokens': max_tokens}
response = requests.post(API_URL, files=files, data=data)
response.raise_for_status()
return response.json()['response']
else:
return "No valid audio file available."
except Exception as e:
return f"Error processing audio: {str(e)}"
# Create Gradio interface
demo = gr.Interface(
fn=process_audio,
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"),
title="Nexa Omni",
description="Upload an audio file and optionally provide a prompt to analyze the audio content.",
examples=[
["example_audios/example_1.wav", 50],
]
)
def clear_output(audio, max_tokens):
return ""
demo.load_examples = clear_output
if __name__ == "__main__":
demo.launch()
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