gingnxz/NER

1import gradio as gr2import os3os.system('python -m spacy download en_core_web_sm')4import spacy5from spacy import displacy6 7nlp = spacy.load("en_core_web_sm")8 9def text_analysis(text):10    doc = nlp(text)11    html = displacy.render(doc, style="dep", page=True)12    html = (13        ""14        + html15        + ""16    )17    pos_count = {18        "char_count": len(text),19        "token_count": 0,20    }21    pos_tokens = []22 23    for token in doc:24        pos_tokens.extend([(token.text, token.pos_), (" ", None)])25 26    return pos_tokens, pos_count, html27 28demo = gr.Interface(29    text_analysis,30    gr.Textbox(placeholder="Enter sentence here..."),31    ["highlight", "json", "html"],32    examples=[33        ["What a beautiful morning for a walk!"],34        ["It was the best of times, it was the worst of times."],35    ],36)37 38demo.launch()39