streamlit-nlp-annotator 1.1.0

A Streamlit component for interactive text annotation.

streamlit-nlp-annotator

streamlit-nlp-annotator is a Streamlit component for interactive text annotation. This is especially useful for Natural Language Processing (NLP) tasks.

This component was inspired by the following works:

• st-annotated-text by @tvst
• streamlit-annotator by @EttoreCaputo
• streamlit-annotation-tools by @rmarquet21

Unlike existing tools, streamlit-nlp-annotator allows a clean inline visualization of annotations.

👀 Features

• Inline annotations with visible labels
• Span selection with mouse
• Label assignment via popup
• Editable and removable annotations
• Deterministic color mapping
• JSON-compatible output format
• Supports controlled label sets
• Optional runtime label creation
• Light/dark theme support

🎬 Demo

Live App

👉 Test it here

Preview

🛠️ Installation

pip install streamlit-nlp-annotator

🚀 Quick Start

import streamlit as st
from streamlit_nlp_annotator import annotate_text

text = "John McCarthy was born on September 4, 1927."

result = annotate_text(
    text=text,
    labels=["Name", "Date"],
    allow_runtime_labels=True,
    key="example",
)

st.write(result)

💾 Output Format

The component returns a dictionary-like structure:

{
    "annotations": [
        {
            "id": "...",
            "start": 0,
            "end": 3,
            "label": "Name",
            "text": "John"
        }
    ],
    "labels": ["Name", "Date"],
    "selection": {
        "start": 26,
        "end": 42,
        "text": "September 4, 1927"
    }
}

The above example shows the output when one part of the text has already been annotated, and another text portion has only been selected. The list of available labels is also provided.

⚙️ API

annotate_text(
    text: str,                              # Source text to annotate
    labels: list[str] | None = None,        # Initial list of labels
    annotations: list[dict] | None = None,  # Initial annotations
    allow_runtime_labels: bool = True,      # Allow users to add/remove labels
    readonly: bool = False,                 # Disable editing
    colorPalette: dict | None = None,       # Optional custom color palette
    key: str | None = None,                 # Streamlit key for persistence
)

✅ Example App

streamlit run example.py

License

MIT License