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app.py
CHANGED
@@ -636,7 +636,7 @@ def generate_paraphrases(text, setting, output_format):
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temperature=temperature
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)
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paraphrases_texts = [paraphraser_tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True) for output in outputs]
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formatted_output += f"Original sentence {i+1}: {sentence}\n"
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for j, paraphrase in enumerate(paraphrases_texts, 1):
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@@ -692,21 +692,20 @@ def generate_paraphrases(text, setting, output_format):
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else:
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return json.dumps(json_output, indent=2), "\n\n".join([v[0] for v in human_versions])
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def clean_paraphrased_output(text):
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cleaned_text = clean_text(text)
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return cleaned_text
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# Define the Gradio interface
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iface = gr.Interface(
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fn=
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inputs=[
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gr.Textbox(lines=5, label="Input Text")
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],
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outputs=[
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gr.Textbox(lines=20, label="
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],
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title="
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description="Enter a text
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)
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# Launch the interface
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temperature=temperature
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)
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paraphrases_texts = [clean_text(paraphraser_tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)) for output in outputs]
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formatted_output += f"Original sentence {i+1}: {sentence}\n"
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for j, paraphrase in enumerate(paraphrases_texts, 1):
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else:
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return json.dumps(json_output, indent=2), "\n\n".join([v[0] for v in human_versions])
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# Define the Gradio interface
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iface = gr.Interface(
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fn=generate_paraphrases,
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inputs=[
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gr.Textbox(lines=5, label="Input Text"),
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gr.Slider(minimum=1, maximum=5, step=1, label="Readability to Human-like Setting"),
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gr.Radio(["text", "json"], label="Output Format")
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],
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outputs=[
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gr.Textbox(lines=20, label="Detailed Paraphrases and Classifications"),
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gr.Textbox(lines=10, label="Human-like or Less Confident Machine-generated Paraphrases")
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],
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title="Advanced Diverse Paraphraser with Human-like Filter",
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description="Enter a text, select a setting from readable to human-like, and choose the output format to generate diverse paraphrased versions. Combined versions are classified, and those detected as human-produced or less confidently machine-generated are presented in the final output."
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)
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# Launch the interface
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