import requests
import gradio as gr
import os

API_URL = "https://api-inference.huggingface.co/models/MIT/ast-finetuned-audioset-10-10-0.4593"
headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN')}"}

def classify_audio(audio_file):
    """
    Classify the uploaded audio file using Hugging Face AST model
    """
    if audio_file is None:
        return "Please upload an audio file."
    
    with open(audio_file.name, "rb") as f:
        data = f.read()
    response = requests.post(API_URL, headers=headers, data=data)
    try:
        results = response.json()
        return results
    except Exception as e:
        return f"Error processing audio: {str(e)}"

# Create Gradio interface
iface = gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(type="filepath", label="Upload Audio File"),
    outputs=gr.JSON(label="Classification Results"),
    title="Audio Classification using AST Model",
    description="Upload an audio file to get its classification results using the Audio Spectrogram Transformer model.",
    examples=[],
)

# Launch the interface
iface.launch()