app.py

import gradio as gr
from transformers import pipeline



#def classify_sentiment(audio, model):
  #pipe = pipeline("audio-classification", model=model)
  #sentiment_classifier = pipe(audio)
  #return sentiment_classifier

def classify_sentiment(audio, model):
  pipe = pipeline("audio-classification", model=model)
  sentiment_classifier = pipe(audio)
  
  preds_dict={}
  for sentiment_classifier in preds[0]:
      preds_dict[pred['label']] = pred['score']

  return preds_dict

input_audio = [gr.inputs.Audio(source="microphone", type="filepath", label="Record/ Drop audio"), gr.inputs.Dropdown(["DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"], label="Model Name")]
label = gr.outputs.Label(num_top_classes=5)

gr.Interface(
    fn = classify_sentiment,
    inputs = input_audio,
    outputs = label,
    #examples=[["test1.wav", "DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11"], ["test2.wav", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"]],
    theme="grass").launch()