import gradio as gr from text_converter import fre_levels, sbert_levels, model_types, generate_similar_sentence, user_input_readability_level APP_DESCRIPTION = '''# Reading Level Converter
Convert any text to a specified reading level while retaining the core text meaning
''' MIN_ENTAILMENT = 0.5 MAX_ITER = 5 SYSTEM_PROMPT = "You are a writing assistant. You help convert complex texts to simpler texts while maintaining the core meaning of the text." def convert_text(input_text, grade_level, input_reading_score, model_type): if model_type == "FRE": reading_levels = fre_levels else: reading_levels = sbert_levels min_level, max_level = reading_levels[grade_level] output_text, similarity, reading_level, message = generate_similar_sentence(input_text, min_level, max_level, MIN_ENTAILMENT, SYSTEM_PROMPT, MAX_ITER, float(input_reading_score), model_type) return output_text, similarity, reading_level, message with gr.Blocks(css='styles.css') as app: gr.Markdown(APP_DESCRIPTION) with gr.Tab("FRE"): with gr.Row(): input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, sclae = 2.5) fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 0.5) output_input_reading_score = gr.Textbox(label="Input Text Reading Score", placeholder="Input Text Reading Score...", lines=1) output_input_reading_level = gr.Textbox(label="Input Text Reading Level", placeholder="Input Text Reading Level...", lines=1) fetch_score_and_lvl_btn.click( fn=user_input_readability_level, inputs=[input_text, model_types[0]], outputs=[output_input_reading_score, output_input_reading_level] ) grade_level = gr.Radio(choices=list(fre_levels.keys()), label="Target Reading Level", value = list(fre_levels.keys())[0], interactive=True) output_reading_level = gr.Textbox(label="Output Reading Level", placeholder="Output Reading Level...", lines=1) output_similarity = gr.Textbox(label="Similarity", placeholder="Similarity Score...", lines=1) output_converted_text = gr.Textbox(label="Converted Text", placeholder="Results will appear here...", lines=4) output_message = gr.Textbox(label="Message", placeholder="System Message...", lines=2) convert_button = gr.Button("Convert Text") convert_button.click( fn=convert_text, inputs=[input_text, grade_level, output_input_reading_score, model_types[0]], outputs=[output_converted_text, output_similarity, output_reading_level, output_message] ) with gr.Tab("SBERT"): with gr.Row(): input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, sclae = 2.5) fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 0.5) output_input_reading_score = gr.Textbox(label="Input Text Reading Score", placeholder="Input Text Reading Score...", lines=1) output_input_reading_level = gr.Textbox(label="Input Text Reading Level", placeholder="Input Text Reading Level...", lines=1) fetch_score_and_lvl_btn.click( fn=user_input_readability_level, inputs=[input_text, model_types[1]], outputs=[output_input_reading_score, output_input_reading_level] ) grade_level = gr.Radio(choices=list(sbert_levels.keys()), label="Target Reading Level", value = list(sbert_levels.keys())[0], interactive=True) output_reading_level = gr.Textbox(label="Output Reading Level", placeholder="Output Reading Level...", lines=1) output_similarity = gr.Textbox(label="Similarity", placeholder="Similarity Score...", lines=1) output_converted_text = gr.Textbox(label="Converted Text", placeholder="Results will appear here...", lines=4) output_message = gr.Textbox(label="Message", placeholder="System Message...", lines=2) convert_button = gr.Button("Convert Text") convert_button.click( fn=convert_text, inputs=[input_text, grade_level, output_input_reading_score, model_types[1]], outputs=[output_converted_text, output_similarity, output_reading_level, output_message] ) if __name__ == '__main__': app.launch()