abhicodes commited on
Commit
41df8e3
1 Parent(s): 20a0847

Updated app.py for latest Gradio version 4.0

Browse files

1. Changed the gr.Box() with gr.Column().
2. Removed few unsupported attributes in gr.TextBox() and gr.Radio().

Files changed (1) hide show
  1. app.py +3 -10
app.py CHANGED
@@ -84,18 +84,13 @@ description = """
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  <br>
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  🎯 The sentiment analysis results are provided as a dictionary with different emotions and their corresponding scores.<br>
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  <br>
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-
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  😃 The sentiment analysis results are displayed with emojis representing the corresponding sentiment.<br>
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  <br>
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-
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  ✅ The higher the score for a specific emotion, the stronger the presence of that emotion in the transcribed text.<br>
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  <br>
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-
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  ❓ Use the microphone for real-time speech recognition.<br>
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  <br>
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-
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  ⚡️ The model will transcribe the audio and perform sentiment analysis on the transcribed text.<br>
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-
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  """
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  custom_css = """
@@ -122,18 +117,16 @@ with block:
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  gr.HTML(description)
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  with gr.Group():
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- with gr.Box():
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  audio = gr.Audio(
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  label="Input Audio",
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  show_label=False,
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- source="microphone",
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  type="filepath"
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  )
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  sentiment_option = gr.Radio(
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  choices=["Sentiment Only", "Sentiment + Score"],
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  label="Select an option",
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- default="Sentiment Only"
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  )
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  btn = gr.Button("Transcribe")
@@ -142,7 +135,7 @@ with block:
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  text = gr.Textbox(label="Transcription")
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- sentiment_output = gr.Textbox(label="Sentiment Analysis Results", output=True)
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  btn.click(inference, inputs=[audio, sentiment_option], outputs=[lang_str, text, sentiment_output])
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@@ -153,4 +146,4 @@ with block:
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  </div>
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  ''')
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- block.launch()
 
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  <br>
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  🎯 The sentiment analysis results are provided as a dictionary with different emotions and their corresponding scores.<br>
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  <br>
 
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  😃 The sentiment analysis results are displayed with emojis representing the corresponding sentiment.<br>
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  <br>
 
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  ✅ The higher the score for a specific emotion, the stronger the presence of that emotion in the transcribed text.<br>
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  <br>
 
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  ❓ Use the microphone for real-time speech recognition.<br>
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  <br>
 
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  ⚡️ The model will transcribe the audio and perform sentiment analysis on the transcribed text.<br>
 
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  """
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  custom_css = """
 
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  gr.HTML(description)
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  with gr.Group():
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+ with gr.Column():
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  audio = gr.Audio(
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  label="Input Audio",
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  show_label=False,
 
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  type="filepath"
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  )
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  sentiment_option = gr.Radio(
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  choices=["Sentiment Only", "Sentiment + Score"],
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  label="Select an option",
 
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  )
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  btn = gr.Button("Transcribe")
 
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  text = gr.Textbox(label="Transcription")
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+ sentiment_output = gr.Textbox(label="Sentiment Analysis Results")
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  btn.click(inference, inputs=[audio, sentiment_option], outputs=[lang_str, text, sentiment_output])
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  </div>
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  ''')
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+ block.launch()