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Author:
Piyush Kumar Mondal
Summary:
The embedding lifecycle, end to end — recommend, generate, store, search, cache, track, model, inspect, and visualize embeddings behind one consistent surface.
Latest version:
0.1.0.dev0
Required dependencies:
kaleido
|
numpy
|
plotly
|
qdrant-client
|
redis
|
scikit-learn
|
scipy
|
sqlite-vec
|
umap-learn
Optional dependencies:
hypothesis
|
mypy
|
pillow
|
pytest
|
ruff
|
sentence-transformers
|
soundfile
|
torch
|
transformers
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