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import gradio as gr
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import json
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from transformers import pipeline
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generator = pipeline('text-generation', model='gpt2')
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def adjust_tone(text, concise, casual):
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tones = [
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{"tone": "concise", "weight": concise},
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{"tone": "casual", "weight": casual},
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{"tone": "professional", "weight": 1 - casual},
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{"tone": "expanded", "weight": 1 - concise}
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]
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tones = sorted(tones, key=lambda x: x['weight'], reverse=True)[:2]
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tone_prompt = " and ".join([f"{t['tone']} (weight: {t['weight']:.2f})" for t in tones])
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prompt = f"Rewrite the following text to match these tones: {tone_prompt}. Text: {text}"
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result = generator(prompt, max_length=100, num_return_sequences=1)
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return result[0]['generated_text']
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with gr.Blocks() as demo:
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gr.Markdown("# Tone Adjuster")
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input_text = gr.Textbox(label="Input Text")
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with gr.Row():
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concise_slider = gr.Slider(minimum=0, maximum=1, value=0.5, label="Concise vs Expanded")
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casual_slider = gr.Slider(minimum=0, maximum=1, value=0.5, label="Casual vs Professional")
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output_text = gr.Textbox(label="Adjusted Text")
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adjust_btn = gr.Button("Adjust Tone")
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adjust_btn.click(
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adjust_tone,
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inputs=[input_text, concise_slider, casual_slider],
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outputs=output_text
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)
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demo.launch() |
