This is a small project for visualizing embeddings.
See the screenshot above or the interactive demo output here.
The overall flow is:
- One or more text sequences is split into sentences or paragraphs.
- Each resulting text fragment is embedded using the requested embedding model.
- The embeddings are reduced to two or three dimensions (as requested) via UMAP.
- The low dimensionality embeddings are optionally clustered with hdbscan. A single set of embeddings can be clustered at multiple granularities.
- Clusters are optionally summarized using the requested language model.
The resulting points and cluster info are plotted in an interactive 3D scatter plot.
- Plotly provides a number of default handlers for interaction.
- Left and right arrow keys step through text fragments in original text order (i.e. you could, in theory, read a book by stepping through its fragments and simultaneously see how the fragments relate to each other in embedding space).
- Up and down arrow keys step through clustering granularities. (i.e. you can see a very high-level "table" of contents and then "zoom in" to more and more granular "tables" of contents)
There's also some support and integration with a few existing text sources. A small web interface (python -m hammock.gunicorn) is provided for:
- Visualizing arbitrary text submitted in a textarea
- Fetching one or more books from Project Gutenberg by title and visualizing them
- Fetching one or more articles from Wikipedia by title and visualizing them
Modules can be accessed from the command line to:
- Batch process epubs from Calibre (
python -m hammock.calibre.core) - Fetch cards from an Anki database and visualize them (
python -m hammock.anki -d <path-to-DB> -p <path-to-excluded-substrings-file>)
If you have nix, you can simply do nix run from the project directory to set up the project launch the web server on localhost. nix develop will dump you into a shell with all the dependencies set up.