Update app.py

app.py

@@ -1,16 +1,31 @@
-import numpy as np
+#from transformers import pipeline
+
 import gradio as gr
 
-def sepia(input_img):
-    sepia_filter = np.array([
-        [0.393, 0.769, 0.189], 
-        [0.349, 0.686, 0.168], 
-        [0.272, 0.534, 0.131]
-    ])
-    sepia_img = input_img.dot(sepia_filter.T)
-    sepia_img /= sepia_img.max()
-    
-    return 'conversion complete'
-
-demo = gr.Interface(sepia, gr.Image(), "text")
+#asr = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
+#classifier = pipeline("text-classification")
+
+
+def speech_to_text():
+    text = 'running speech to text'
+    return text
+
+
+def text_to_sentiment():
+    return 'running text to sentiment'
+
+
+demo = gr.Blocks()
+
+with demo:
+    audio_file = gr.File()
+    text = gr.Textbox()
+    label = gr.Label()
+
+    b1 = gr.Button("Recognize Speech")
+    b2 = gr.Button("Classify Sentiment")
+
+    b1.click(speech_to_text, inputs=audio_file, outputs=text)
+    b2.click(text_to_sentiment, inputs=text, outputs=label)
+
 demo.launch()