import gradio as gr
from main import main
import nltk

def rexplore_summarizer(corpus):
    response = main(corpus)
    return response, response['summary'], response['mindmap']

def clear_everything(text_corpus, raw_data, summary, mindmap):
    return None, None, None, None

theme = gr.themes.Soft(
    primary_hue="purple",
    secondary_hue="cyan",
    neutral_hue="slate",
    font=[
        gr.themes.GoogleFont('Syne'), 
        gr.themes.GoogleFont('Poppins'), 
        gr.themes.GoogleFont('Poppins'), 
        gr.themes.GoogleFont('Poppins')
    ],
)

with gr.Blocks(theme=theme, title="ReXplore Summarizer", fill_height=True) as app:
    gr.HTML(
        value ='''
        <h1 style="text-align: center;">ReXplore Summarizer <p style="text-align: center;">Designed and Developed by <a href='https://raannakasturi.eu.org' target="_blank" rel="nofollow noreferrer external">Nayan Kasturi</a></p> </h1>
        <p style="text-align: center;">This app uses a hybrid approach to summarize PDF documents based on CPU as well as GPU.</p>
        <p style="text-align: center;">The app uses traditional methodologies such as TextRank, LSA, Luhn algorithms as well as large language model (LLM) to generate summaries as well as mindmaps.</p>
        <p style="text-align: center;">The summarization process can take some time depending on the size of the text corpus and the complexity of the content.</p>
        ''')
    with gr.Row():
        with gr.Column():
            text_corpus = gr.TextArea(label="Text Corpus", placeholder="Paste the text corpus here", lines=5)
            with gr.Row():
                clear_btn = gr.Button(value="Clear", variant='stop')
                summarize_btn = gr.Button(value="Summarize", variant='primary')
        raw_data = gr.TextArea(label="Raw Data", placeholder="The generated raw data will be displayed here", lines=7, interactive=False, show_copy_button=True)
    with gr.Row():
        summary = gr.TextArea(label="Summary", placeholder="The generated summary will be displayed here", lines=7, interactive=False, show_copy_button=True)
        mindmap = gr.TextArea(label="Mindmap", placeholder="The generated mindmap will be displayed here", lines=7, interactive=False, show_copy_button=True)

    summarize_btn.click(
        rexplore_summarizer,
        inputs=[text_corpus],
        outputs=[raw_data, summary, mindmap],
        concurrency_limit=1,
        scroll_to_output=True,
        show_api=True,
        api_name="rexplore_summarizer",
        show_progress="full",
    )
    clear_btn.click(clear_everything, inputs=[text_corpus, raw_data, summary, mindmap], outputs=[text_corpus, raw_data, summary, mindmap], show_api=False)

nltk.download('punkt')
nltk.download('punkt_tab')
app.queue(default_concurrency_limit=1).launch(show_api=True)