Update app.py

app.py

@@ -46,14 +46,14 @@ title = "Scream: Fine-Tuned Whisper model for automatic gutural speech recogniti
 classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", top_k=None)
 
 #Functions-----------------------------------------------------------------------------------------------------------------------
-def transcribe(link,download,thumbnail,file,use_timestamps,sentiment_analysis):#file, return_timestamps, *kwargs):
+def transcribe(*args):
     '''inputs: file, return_timestamps'''
-    outputs = pipe(file, batch_size=BATCH_SIZE, generate_kwargs={"task": 'transcribe'}, return_timestamps=True)
+    outputs = pipe(args[3], batch_size=BATCH_SIZE, generate_kwargs={"task": 'transcribe'}, return_timestamps=True)
     text = outputs["text"]
     timestamps = outputs["chunks"]
 
     #If return timestamps is True, return html text with timestamps format
-    if use_timestamps==True:
+    if args[4]==True:
       spider_text = [f"{chunk['text']}" for chunk in timestamps] #Text for spider chart without timestamps
       timestamps = [f"[{format_timestamp(chunk['timestamp'][0])} -> {format_timestamp(chunk['timestamp'][1])}] {chunk['text']}" for chunk in timestamps]
 
@@ -69,7 +69,7 @@ def transcribe(link,download,thumbnail,file,use_timestamps,sentiment_analysis):#
     av_dict = calculate_average(trans_dict)
     fig = spider_chart(av_dict)
     
-    return file, text, fig, av_dict
+    return args[3], text, fig, av_dict
 
 embed_html = '<iframe src="https://www.youtube.com/embed/YOUTUBE_ID'\
               'title="YouTube video player" frameborder="0" allow="accelerometer;'\
@@ -77,39 +77,42 @@ embed_html = '<iframe src="https://www.youtube.com/embed/YOUTUBE_ID'\
               'picture-in-picture" allowfullscreen></iframe>'
 
 def download(link):
+    '''Runs youtubetowav.py
+    inputs: link from textbox'''
     subprocess.run(['python3', 'youtubetowav.py', link])
     return thumbnail.update(value=embed_html.replace("YOUTUBE_ID",get_youtube_video_id(link)))
 
-def hide_sa(value):
+def hide_sentiment(value):
   if value == True:
-    return sa_plot.update(visible=True), sa_frequency.update(visible=True)
+    return sentiment_plot.update(visible=True), sentiment_frequency.update(visible=True)
   else:
-    return sa_plot.update(visible=False), sa_frequency.update(visible=False)
+    return sentiment_plot.update(visible=False), sentiment_frequency.update(visible=False)
 
 #----------------------------------------------------------------------------------------------------------------------------------------------
       
 #Components------------------------------------------------------------------------------------------------------------------------------------      
       
 #Input components        
-yt_link = gr.Textbox(value=None,label="YouTube link", info = "Optional: Copy and paste YouTube URL")
-audio_input = gr.Audio(source="upload", type="filepath", label="Upload audio file for transcription")
-download_button = gr.Button(value="Download")
-thumbnail = gr.HTML(value="", label = "Thumbnail")
-sa_checkbox = gr.Checkbox(value=True, label="Sentiment analysis")
+yt_link = gr.Textbox(value=None,label="YouTube link", info = "Optional: Copy and paste YouTube URL") #0
+download_button = gr.Button(value="Download") #1
+thumbnail = gr.HTML(value="", label = "Thumbnail") #2
+audio_input = gr.Audio(source="upload", type="filepath", label="Upload audio file for transcription") #3
+timestamp_checkbox = gr.Checkbox(value=True, label="Return timestamps") #4
+sentiment_checkbox = gr.Checkbox(value=True, label="Sentiment analysis") #5
 
 inputs = [yt_link, #0
           download_button, #1
           thumbnail, #2
           audio_input, #3
-          gr.Checkbox(value=True, label="Return timestamps"), #4
-          sa_checkbox] #5
+          timestamp_checkbox, #4
+          sentiment_checkbox] #5
 
 #Ouput components
 audio_out = gr.Audio(label="Processed Audio", type="filepath", info = "Vocals only") 
-sa_plot = gr.Plot(label="Sentiment Analysis")
-sa_frequency = gr.Label(label="Frequency")
+sentiment_plot = gr.Plot(label="Sentiment Analysis")
+sentiment_frequency = gr.Label(label="Frequency")
 
-outputs = [audio_out, gr.outputs.HTML("text"), sa_plot, sa_frequency]
+outputs = [audio_out, gr.outputs.HTML("text"), sentiment_plot, sentiment_frequency]
 
 #----------------------------------------------------------------------------------------------------------------------------------------------------
 
@@ -117,12 +120,12 @@ outputs = [audio_out, gr.outputs.HTML("text"), sa_plot, sa_frequency]
 
 with gr.Blocks() as demo:
   download_button.click(download, inputs=[yt_link], outputs=[thumbnail])
-  sa_checkbox.change(hide_sa, inputs=[sa_checkbox], outputs=[sa_plot, sa_frequency])
+  sentiment_checkbox.change(hide_sentiment, inputs=[sentiment_checkbox], outputs=[sentiment_plot, sentiment_frequency])
 
 
   with gr.Column():
       gr.Interface(title = title, fn=transcribe, inputs = inputs, outputs = outputs, 
-                   description=description, allow_flagging="never", article = article,
+                   description=description, cache_examples=True, allow_flagging="never", article = article,
                    examples="examples")