Update app.py

app.py

@@ -1,34 +1,21 @@
 import gradio as gr
 from transformers import pipeline
 
-#trans = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-spanish")
 classifier = pipeline("text-classification", model="pysentimiento/robertuito-sentiment-analysis")
 
-def audio_to_text(audio):
-  text = trans(audio)["text"]
-  return text
-
 def text_to_sentiment(text):
-  return classifier(text)[0]#["label"]
+  return {classifier(text)[0]["label"]: classifier(text)[0]["score"]}
 
 demo = gr.Blocks()
 
 with demo:
-  gr.Markdown("Demostración de análisis de sentimientos de textos")
   with gr.Tabs():
-    #with gr.TabItem("Transcribe audio in Spanish"):
-    #  with gr.Row():
-    #    audio = gr.Audio(source="microphone", type="filepath")
-    #    transcription = gr.Textbox()
-    #  b1 = gr.Button("Transcribe")
-    
     with gr.TabItem("Análisis de sentimientos de textos en español"):
       with gr.Row():
         texto = gr.Textbox()
         label = gr.Label(num_top_classes=1)
-      b2 = gr.Button("Sentimiento")
+      b1 = gr.Button("Analizar")
 
-    #b1.click(audio_to_text, inputs=audio, outputs=transcription)
-    b2.click(text_to_sentiment, inputs=texto, outputs=label)
+    b1.click(text_to_sentiment, inputs=texto, outputs=label)
 
 demo.launch()