Feature: Manual Annotation and Tagging

Hi,

Embedding Atlas is a very powerful tool for visualizing embeddings. However, more often than not, we want to do more than just observe the embeddings produced by our models, we want to actively make adjustments to the generated cluster labels. As of now, there is a significant lack of tools in the ecosystem that seamlessly bridge the gap between visualization and manual annotation.

It would be highly beneficial to have the ability to create, delete, or merge categories using the existing selection mechanisms. Adding this feature (and ideally a way to export the updated labels, or store them in a database) would allow ML developers and researchers to immediately act on the insights they discover in their data.

Best regards,
Arthur

Start by reviewing the existing selection mechanisms and the parts of Embedding Atlas that manage cluster labels. The issue does not name files, tests, or entry points, and leaves category creation, deletion, merging, and label export or database storage open for design. Done would require an agreed scope and an implementation that supports the selected annotation workflow.

Written by the indexing model from the issue text.