54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
import gradio as gr
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from transformers import pipeline
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from gradio.themes.utils import sizes
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theme = gr.themes.Default(radius_size=sizes.radius_none).set(
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block_label_text_color = '#4D63FF',
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block_title_text_color = '#4D63FF',
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button_primary_text_color = '#4D63FF',
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button_primary_background_fill='#FFFFFF',
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button_primary_border_color='#4D63FF',
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button_primary_background_fill_hover='#EDEFFF',
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)
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sentimentPipeline = pipeline("zero-shot-classification", model="valhalla/distilbart-mnli-12-1")
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def sentiment_analysis(text, labels):
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candidate_labels = labels.split(',')
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results = sentimentPipeline(text, candidate_labels)
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total_results = ""
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index = 0
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for candidate_label in candidate_labels:
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total_results += f"Sentiment: {results.get('labels')[index]}, Score: {results.get('scores')[index]}"
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total_results += '\r\n'
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index += 1
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return total_results
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with gr.Blocks(theme=theme, css="footer {visibility: hidden}") as demo:
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gr.Markdown("""
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<div align='center' ><font size='60'>文本情感分析</font></div>
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""")
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with gr.Row():
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with gr.Column():
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text = gr.Textbox(label="文本")
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label = gr.Textbox(label="标签")
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with gr.Row():
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button = gr.Button("提交", variant="primary")
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clear = gr.Button("清除", variant="primary")
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box2 = gr.Textbox(label="文本")
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button.click(fn=sentiment_analysis, inputs=[text, label], outputs=box2)
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clear.click(lambda x: gr.update(value=''), [], [text])
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clear.click(lambda x: gr.update(value=''), [], [label])
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examples = gr.Examples(examples=[['I have a problem with my iphone that needs to be resolved asap!!', 'urgent, not urgent, phone, tablet, computer'], ['Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.', 'mobile, website, billing, account access']], inputs=[text, label], label="例子")
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if __name__ == "__main__":
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demo.queue(concurrency_count=3)
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demo.launch(server_name = "0.0.0.0", server_port = 7028)
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