Update app.py

app.py

@@ -84,7 +84,7 @@ def get_transcript_url(url, audio_intelligence_options):
         time.sleep(3)
 
     
-    return transcription_result['text'], transcription_result['summary']
+    return transcription_result['text'], transcription_result['summary'], transcription_result['sentiment_analysis_results']
 
 def get_transcript_file(filename):
 
@@ -170,7 +170,7 @@ with gr.Blocks() as demo:
     with gr.Column(elem_id = "col_container"):
         with gr.Tab("Audio URL file"):
             inputs = gr.Textbox(label = "Enter the url for the audio file")
-            audio_intelligence_options = gr.CheckboxGroup(audio_intelligence_list, label="Audio Intelligence Options")
+            #audio_intelligence_options = gr.CheckboxGroup(audio_intelligence_list, label="Audio Intelligence Options")
             b1 = gr.Button('Transcribe')
         
         with gr.Tab("Upload Audio as File"):
@@ -178,14 +178,15 @@ with gr.Blocks() as demo:
             transcribe_audio_u = gr.Button('Transcribe')
 
         transcript = gr.Textbox(label = "Transcript Result" )
-        summary = gr.Textbox(label = "Summary Result" )
+        summary = gr.Textbox(label = "Summary Result")
+        sentiment_analysis = gr.Textbox(label = "Sentiment Analysis Result" )
         
     
-    inputs.submit(get_transcript_url, [inputs, audio_intelligence_options], [transcript, summary])
-    b1.click(get_transcript_url, [inputs, audio_intelligence_options], [transcript, summary])
+    inputs.submit(get_transcript_url, [inputs], [transcript, summary, sentiment_analysis])
+    b1.click(get_transcript_url, [inputs], [transcript, summary, sentiment_analysis])
     transcribe_audio_u.click(get_transcript_file, [audio_input_u], [transcript])
 
-    #examples = gr.Examples(examples = [['https://bit.ly/3yxKEIY']], inputs = inputs, outputs=transcript, cache_examples = True, fn = get_transcript_url)
+    examples = gr.Examples(examples = [["https://github.com/AssemblyAI-Examples/assemblyai-and-python-in-5-minutes/blob/main/audio.mp3?raw=true"], inputs = inputs, outputs=[transcript, summary, sentiment_analysis], cache_examples = True, fn = get_transcript_url)
                     
     
     demo.queue().launch(debug=True)