app.py

from transformers import pipeline
import gradio as gr

model_id = "pollner/distilhubert-finetuned-ravdess"
classifier = pipeline("audio-classification", model=model_id)

def classify_audio(audio_file):
    # audio_file is path or file object
    result = classifier(audio_file)
    return result

iface = gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(type="filepath"),  # Removed 'source' parameter
    outputs=gr.JSON(label="Classification result"),
    title="Emotion recognition from speech (RAVDESS)",
    description="Classifies emotion from audio using distilhubert-finetuned-ravdess"
)

iface.launch()