https://github.com/lakeraai/canica

A text embedding viewer for the Jupyter environment
https://github.com/lakeraai/canica

jupyter jupyter-notebook text-embedding text-embeddings visualization

Last synced: about 1 month ago
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A text embedding viewer for the Jupyter environment

• Host: GitHub
• URL: https://github.com/lakeraai/canica
• Owner: lakeraai
• License: mit
• Created: 2023-10-30T09:00:09.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-24T16:50:33.000Z (12 months ago)
• Last Synced: 2024-05-08T00:17:29.190Z (9 months ago)
• Topics: jupyter, jupyter-notebook, text-embedding, text-embeddings, visualization
• Language: TypeScript
• Homepage:
• Size: 1.68 MB
• Stars: 16
• Watchers: 3
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
# canica

**canica** is an interactive tool to visualize embeddings. Its main current goal is to explore text datasets, representing the input embeddings in a 2D tSNE plot.

![canica gif](./docs/static/replot.gif)

## How to install

Just

```sh

pip install canica

```

And start using the `CanicaTSNE` and `CanicaUMAP` class in your notebooks.

## How to use

canica is designed to work mainly as a data exploration tool embedded as a widget inside of a jupyter notebook. These are the instructions to explore a dataset in a notebook ([the tutorial notebook](./tutorial.ipynb) provides more information).

In a notebook, load a pandas DataFrame and make sure that at least one column contains the embeddings you want to plot.

In a cell, run:

```python

from canica.widget import CanicaTSNE

CanicaTSNE(df, embedding_col="embedding_col", text_col="text_col", hue_col="some_score")

```

Where `df` is the pandas DataFrame, `"embedding_col"` is a column in `df` containing embeddings and `hue_var` is another column that will be represented using colours (currently it has to be a numerical column with values between 0 and 1).

You can also use `CanicaUMAP` instead of `CanicaTSNE` to use UMAP.

This will show the canica embedding explorer and will enable interactive exploration of your dataset. Have a look at the [tutorial](./tutorial.ipynb) notebook to see it working.

## How to contribute

We welcome contributions of all kinds. For more information on how to do it, we refer you to the [CONTRIBUTING.md](./CONTRIBUTING.md) file.