import gradio as gr from transformers import pipeline trans = pipeline("automatic-speech-recognition", model = "facebook/wav2vec2-large-xlsr-53-spanish") clasificador = pipeline("text-classification", model = "pysentimiento/robertuito-sentiment-analysis") def audio_a_text(audio): text = trans(audio)["text"] return text def texto_a_sentimiento(text): return clasificador(text)[0]["label"] demo = gr.Blocks() with demo: gr.Markdown("demo de sentimientos leidos") audio = gr.Audio(source="microphone", type="filepath") texto = gr.Textbox() b1 = gr.Button("Dictado") b1.click(audio_a_text, inputs=audio, outputs=texto) label = gr.Label() b2 = gr.Button("¿Gusto?") b2.click(texto_a_sentimiento, inputs=texto, outputs=label) demo.launch(share=True)