Create app.py

app.py

@@ -0,0 +1,33 @@
+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 audio2text(audio):
+  text = trans(audio)["text"]
+  return text
+
+def text2sentiment(text):
+  return clasificador(text)[0]["label"]
+
+demo=gr.Blocks()
+with demo:
+  gr.Markdown("Gradio + Blocks + TabItem")
+  with gr.Tabs():
+    with gr.TabItem("Transcribe audio en espanol"):
+      with gr.Row():
+        audio=gr.Audio(sources="microphone",type="filepath")
+        transcripcion=gr.Textbox()
+      b1=gr.Button("Transcribe")
+
+    with gr.TabItem("Analisis de sentimiento en espanol"):
+      with gr.Row():
+        text=gr.Textbox()
+        label=gr.Label()
+      b2=gr.Button("Sentimiento")
+
+      b1.click(audio2text,inputs=audio,outputs=transcripcion)
+      b2.click(text2sentiment,inputs=text,outputs=label)
+
+demo.launch()