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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 | ||
| chat_models | ||
| client | ||
| data | ||
| docstore | ||
| document_loaders | ||
| evaluation | ||
| examples | ||
| llms | ||
| memory | ||
| output_parsers | ||
| prompts | ||
| retrievers | ||
| tools | ||
| utilities | ||
| vectorstores | ||
| __init__.py | ||
| conftest.py | ||
| test_bash.py | ||
| test_depedencies.py | ||
| test_document_transformers.py | ||
| test_formatting.py | ||
| test_math_utils.py | ||
| test_pytest_config.py | ||
| test_python.py | ||
| test_schema.py | ||
| test_sql_database_schema.py | ||
| test_sql_database.py | ||
| test_text_splitter.py | ||