Streamlit component for text highlighting
Project description
Text Highlighter
A Streamlit component for annotating text using text highlighting. Useful for NLP tasks.
Installation
You can install the Text Highlighter package using the following command:
pip install --upgrade text-highlighter
Usage
The package can be used as follows:
from text_highlighter import text_highlighter
import streamlit as st
# Basic usage
result = text_highlighter(
text="John Doe is the founder of MyComp Inc. and lives in New York with his wife Jane Doe.",
labels=[("PERSON", "red"), ("ORG", "#0000FF")],
# Optionally you can specify pre-existing annotations:
annotations=[
{"start": 0, "end": 8, "tag": "PERSON"},
{"start": 27, "end": 38, "tag": "ORG"},
{"start": 75, "end": 83, "tag": "PERSON"},
],
)
# Show the results (in XML format)
st.code(result.to_xml())
# Show the results (as a list)
st.write(result)
In the example.py
script you can find the above example. You can run the example as follows:
streamlit run example.py
The output will look like this:
Contribute
Feel free to add a pull request or open an issue if you have any questions or suggestions.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
text_highlighter-0.0.13.tar.gz
(473.0 kB
view hashes)
Built Distribution
Close
Hashes for text_highlighter-0.0.13-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3504954e72327fc1b9e26961703a10e20fd843ee05c7e8205e29c6861a9a1d6f |
|
MD5 | f5b68e40cebe5ae0b2b6bd7376849133 |
|
BLAKE2b-256 | b0098d8fa5bdc2008ed086d1da2e8911268aff43e2329248c007daf8a6238720 |