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import gradio as gr |
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import os |
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os.system('python -m spacy download ko_core_news_sm') |
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import spacy |
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from spacy import displacy |
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nlp = spacy.load("ko_core_news_sm") |
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def text_analysis(text): |
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doc = nlp(text) |
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html = displacy.render(doc, style="dep", page=True) |
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html = ( |
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"" |
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+ html |
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+ "" |
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) |
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pos_count = { |
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"char_count": len(text), |
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"token_count": 0, |
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} |
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pos_tokens = [] |
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for token in doc: |
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pos_tokens.extend([(token.text, token.pos_), (" ", None)]) |
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return pos_tokens, pos_count, html |
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demo = gr.Interface( |
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text_analysis, |
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gr.Textbox(placeholder="Enter sentence here..."), |
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["highlight", "json", "html"], |
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examples=[ |
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["๋ ์์ด ๋ณด๋ ์ฒซ ๋ด์ด, ์ฌ๋ฆ์ด"], |
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["์ถ์ตํ ๊ทธ ๋ฐค ์์ ๊ฐํผ๋ฅผ ๊ฝ๊ณ ์ "], |
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], |
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) |
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demo.launch() |
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