import gradio as gr
from text_converter import fre_levels, sbert_levels, model_types, generate_similar_sentence, user_input_readability_level, set_reading_levels

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():
            readability_model = gr.Radio(choices=model_types, label="Readability Model", value = model_types[0], interactive=True, scale = 2)
            readability_model_btn = gr.Button("Set Readability Model", scale = 1)
        
        readability_model_btn.click(
            fn=set_reading_levels,
            inputs=[readability_model],
            outputs=[]
        )

        with gr.Row():
            input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, scale = 2)
            fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 1)

        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, readability_model],
            outputs=[output_input_reading_score, output_input_reading_level]
        )
        
        if readability_model == model_types[0]:
            grade_level = gr.Radio(choices=list(fre_levels.keys()), label="Target Reading Level", interactive=True)
        else:
            grade_level = gr.Radio(choices=list(sbert_levels.keys()), label="Target Reading Level", interactive=True)
            #grade_level = gr.Radio(choices=list(fre_levels.keys()) if readability_model == model_types[0] else list(sbert_levels.keys()), label="Target Reading Level", 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, readability_model],
            outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
        )

if __name__ == '__main__':
    app.launch()