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import gradio as gr
import os
os.system('python -m spacy download ko_core_news_sm')
import spacy
from spacy import displacy

nlp = spacy.load("ko_core_news_sm")

def text_analysis(text):
    doc = nlp(text)
    html = displacy.render(doc, style="dep", page=True)
    html = (
        ""
        + html
        + ""
    )
    pos_count = {
        "char_count": len(text),
        "token_count": 0,
    }
    pos_tokens = []

    for token in doc:
        pos_tokens.extend([(token.text, token.pos_), (" ", None)])

    return pos_tokens, pos_count, html

demo = gr.Interface(
    text_analysis,
    gr.Textbox(placeholder="Enter sentence here..."),
    ["highlight", "json", "html"],
    examples=[
        ["์•„๋ฆ„๋‹ค์šด ์ถ”์–ต๋“ค์€ ์–ธ์  ๊ฐ„ ์‚ฌ๋ผ์ง€๊ฒ ์ง€๋งŒ"],
        ["์ง€๊ธˆ์ด๋ผ๋„ ๋…ธ๋ž˜๋กœ ๋‚จ๊ธฐ๊ณ  ์‹ถ์–ด"],
    ],
)

demo.launch()