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updated 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
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"summarization",
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model="Manish014/review-summariser-gpt-config1",
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tokenizer="Manish014/review-summariser-gpt-config1",
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device=0 # Use GPU if available
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)
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if not text.strip():
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return "Please enter a
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text,
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max_length=80,
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min_length=10,
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num_beams=4,
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early_stopping=True,
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length_penalty=1.2
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# Example reviews
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example_reviews = [
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["Worst purchase I've made. Do not recommend at all."]
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]
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# Gradio
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#
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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from transformers import pipeline
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# Load both summarization and sentiment models
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summarizer = pipeline(
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"summarization",
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model="Manish014/review-summariser-gpt-config1",
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tokenizer="Manish014/review-summariser-gpt-config1",
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device=0 # Use GPU if available
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)
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sentiment_analyzer = pipeline("sentiment-analysis")
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# Inference function
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def analyze_review(text):
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if not text.strip():
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return "Please enter a review.", "Sentiment unavailable."
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summary = summarizer(
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text,
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max_length=80,
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min_length=10,
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num_beams=4,
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early_stopping=True,
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length_penalty=1.2
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)[0]["summary_text"]
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sentiment = sentiment_analyzer(text)[0]
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sentiment_output = f"{sentiment['label']} ({round(sentiment['score'] * 100, 2)}%)"
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return summary, sentiment_output
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# Example reviews
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example_reviews = [
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["Worst purchase I've made. Do not recommend at all."]
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]
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# Build Gradio UI
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with gr.Blocks(theme=gr.themes.Base()) as demo:
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gr.Markdown("## π Review Summariser GPT - Config 1")
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gr.Markdown("Enter a long product review below to get a helpful short summary and sentiment prediction.")
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with gr.Row():
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input_box = gr.Textbox(label="π£οΈ Product Review", lines=5, placeholder="Write your detailed review here...")
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with gr.Row():
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summary_output = gr.Textbox(label="βοΈ Summary")
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sentiment_output = gr.Textbox(label="π Sentiment")
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submit_btn = gr.Button("π Analyze Review")
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clear_btn = gr.Button("π§Ή Clear")
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submit_btn.click(analyze_review, inputs=input_box, outputs=[summary_output, sentiment_output])
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clear_btn.click(lambda: ("", "", ""), outputs=[input_box, summary_output, sentiment_output])
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gr.Examples(
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examples=example_reviews,
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inputs=input_box,
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label="π Try an Example"
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)
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# Run the app
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if __name__ == "__main__":
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demo.launch()
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