app.py

import spacy
from spacy import displacy

import gradio as gr

# nlp = spacy.load("en_core_web_sm")
nlp =spacy.load("en_pipeline")


def text_analysis(text):
    doc = nlp(text)
    html = displacy.render(doc, style="ent", 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  html


demo = gr.Interface(
    text_analysis,
    gr.Textbox(placeholder="Enter sentence here..."),
    ["html"],
    examples=[
        ["There is a challenge of food in Uganda. Gloria goes to Kyambogo University."],
        [" She knows programming in HTML and CSS. Prof. Twinomujuni sent the team in Isingiro some 100 USD."],
         ["Students will bbe leaving the University on Friday September 20.They will graduate in 2023." ],
       ["Uganda has many parts that is the north, east, west and south."]
    ],
)

demo.launch()