# Streamlit Annotator
<table>
<tr>
<td>
**Download the package from PyPI:**
[](https://badge.fury.io/py/st-annotator)
</td>
<td>
**Try the demo on Streamlit Cloud:**
[](https://st-annotator.streamlit.app)
</td>
</tr>
</table>
# Install with pip
```
pip install st-annotator
```
st-annotator is a Streamlit component usefull to annotate text, expecially for NLP and Argument Mining purposes.
Based on the original project [Streamlit Annotation Tools](https://github.com/streamlit/annotation-tools) of [rmarquet21](https://github.com/rmarquet21).
### Features:
- 📍 Smart positioning that stays within screen bounds
- 📊 Shows text content, label category, position, and all custom metadata
- 🎨 Matches your custom color scheme
- ⚡ Instant display on hover, disappears on mouse leave
- 🔧 Supports strings, numbers, booleans, lists, and objects
### New Features
- Key parameter to text_annotator function
- A special button to show all the annotations together
- **🆕 Hover Popup with Metadata**: Hover over annotations to see detailed information including custom metadata
### Metadata Support
You can now add custom metadata to each annotation that will appear in a hover popup:
```python
labels = {
"Sentiment": [
{
"start": 0,
"end": 20,
"label": "This is amazing!",
"metadata": {
"confidence": 0.95,
"emotion": "Joy",
"intensity": "High",
"source": "Customer feedback"
}
}
]
}
```
# Quick Start
Run the example.py file:
```
streamlit run examples/example.py
```
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