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# 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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| .. | ||
| agents | ||
| callbacks | ||
| chains | ||
| indexes | ||
| memory | ||
| models | ||
| prompts | ||
| utils/examples | ||
| agents.rst | ||
| chains.rst | ||
| indexes.rst | ||
| memory.rst | ||
| models.rst | ||
| paul_graham_essay.txt | ||
| prompts.rst | ||
| state_of_the_union.txt | ||