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Updated app.py for latest Gradio version 4.0
#2
by
abhicodes
- opened
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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✅ 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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@@ -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.
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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")
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@@ -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"
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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()
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