forked from Archives/langchain
5f4552391f
# Add SKLearnVectorStore This PR adds SKLearnVectorStore, a simply vector store based on NearestNeighbors implementations in the scikit-learn package. This provides a simple drop-in vector store implementation with minimal dependencies (scikit-learn is typically installed in a data scientist / ml engineer environment). The vector store can be persisted and loaded from json, bson and parquet format. SKLearnVectorStore has soft (dynamic) dependency on the scikit-learn, numpy and pandas packages. Persisting to bson requires the bson package, persisting to parquet requires the pyarrow package. ## Before submitting Integration tests are provided under `tests/integration_tests/vectorstores/test_sklearn.py` Sample usage notebook is provided under `docs/modules/indexes/vectorstores/examples/sklear.ipynb` Co-authored-by: Dev 2049 <dev.dev2049@gmail.com> |
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| _static | ||
| additional_resources | ||
| ecosystem | ||
| getting_started | ||
| integrations | ||
| modules | ||
| reference | ||
| tracing | ||
| use_cases | ||
| conf.py | ||
| dependents.md | ||
| index.rst | ||
| integrations.rst | ||
| make.bat | ||
| Makefile | ||
| reference.rst | ||
| requirements.txt | ||