gradio/demo/text_analysis.py
2021-09-16 16:16:49 -07:00

39 lines
894 B
Python

import spacy
from spacy import displacy
import gradio as gr
nlp = spacy.load("en_core_web_sm")
def text_analysis(text):
doc = nlp(text)
html = displacy.render(doc, style="dep", page=True)
html = "<div style='max-width:100%; max-height:360px; overflow:auto'>" + html + "</div>"
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
iface = gr.Interface(
text_analysis,
gr.inputs.Textbox(placeholder="Enter sentence here..."),
[
"highlight", "key_values", "html"
],
examples=[
["What a beautiful morning for a walk!"],
["It was the best of times, it was the worst of times."],
]
)
iface.test_launch()
if __name__ == "__main__":
iface.launch()