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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
<div id="content_align">Convert any text to a specified reading level while retaining the core text meaning</div>'''
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() |