Create restaurant_feedback_analysis.py
Browse files
restaurant_feedback_analysis.py
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from transformers import pipeline
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import gradio as gr
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# Hugging Face's sentiment analysis pipeline
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sentiment_analysis = pipeline('sentiment-analysis')
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# Function to analyze customer feedback
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def analyze_feedback(feedback):
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result = sentiment_analysis(feedback)
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return f"Sentiment: {result[0]['label']} (Confidence: {result[0]['score']:.2f})"
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# Gradio interface for feedback analysis
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with gr.Blocks() as feedback_app:
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feedback = gr.Textbox(label="Customer Feedback")
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analyze_button = gr.Button("Analyze Feedback")
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sentiment_output = gr.Textbox(label="Sentiment Analysis")
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analyze_button.click(fn=analyze_feedback, inputs=feedback, outputs=sentiment_output)
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feedback_app.launch()
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