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Update app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Load the sentiment analysis pipeline
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sentiment_pipeline = pipeline("sentiment-analysis")
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def sentiment_analysis(message, history):
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# Perform sentiment analysis on the user's message
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result = sentiment_pipeline(message)[0]
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label = result["label"]
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score = result["score"]
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#
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import gradio as gr
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from transformers import pipeline
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# Load the sentiment analysis pipeline
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sentiment_pipeline = pipeline("sentiment-analysis")
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# Function to analyze sentiment
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def sentiment_analysis(message, history):
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result = sentiment_pipeline(message)[0]
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label = result["label"]
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score = result["score"]
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response = f"Sentiment: {label}, Confidence: {score:.2f}"
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return response
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# Function to record feedback
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feedback_store = [] # A list to store feedback
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def record_feedback(response, feedback):
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feedback_store.append({"response": response, "feedback": feedback})
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return f"Thank you for your feedback! ({len(feedback_store)} recorded)"
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# Gradio Interface
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with gr.Blocks() as demo:
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chat = gr.ChatInterface(fn=sentiment_analysis, type="messages")
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# Additional components for feedback
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with gr.Row():
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feedback_input = gr.Textbox(placeholder="Enter your feedback here", label="Feedback")
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record_button = gr.Button("Submit Feedback")
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# Feedback submission functionality
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feedback_status = gr.Textbox(interactive=False, label="Feedback Status")
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record_button.click(
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fn=record_feedback,
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inputs=[chat.output_component, feedback_input],
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outputs=feedback_status,
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)
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demo.launch()
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