Create app.py

app.py

@@ -0,0 +1,32 @@
+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_to_text(audio):
+  text = trans(audio)["text"]
+  return text
+
+def text_to_feel(text):
+  return clasificador(text)[0]["label"]
+
+demo = gr.Blocks()
+with demo:
+  gr.Markdown("Demo de blocks")
+  with gr.Tabs():
+    with gr.TabItem("trans"):
+      with gr.Row():
+        audio = gr.Audio(source="microphone", type="filepath")
+        transcription = gr.Textbox()
+      b1 = gr.Button("Transcribe pf")
+    with gr.TabItem("sent"):
+      with gr.Row():
+        texto = gr.Textbox()
+        label = gr.Label()
+      b2 = gr.Button("Sent porfa")
+
+    b1.click(audio_to_text, inputs=audio, outputs=transcription)
+    b2.click(text_to_feel, inputs=texto, outputs=label)
+
+demo.launch()