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import gradio as gr |
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from transformers import pipeline |
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summarizer = pipeline("summarization", model="facebook/bart-large-cnn") |
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def summarize_text(text): |
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word_count = len(text.split()) |
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if word_count < 10: |
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return "Error: The text should have at least 10 words." |
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elif word_count > 100: |
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return "Error: The text should have no more than 100 words." |
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summary = summarizer(text, min_length=10, max_length=100) |
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return summary[0]['summary_text'] |
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interface = gr.Interface( |
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fn=summarize_text, |
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inputs=gr.Textbox(label="Enter Text", lines=10, placeholder="Paste your long text here..."), |
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outputs=gr.Textbox(label="Summarized Text"), |
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title="Text Summarizer", |
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description="This app uses the BART model to summarize your text. The input text must be between 10 and 100 words." |
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) |
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interface.launch() |
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