mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-30 03:28:40 +00:00
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> |
||
|---|---|---|
| .. | ||
| analyticdb.ipynb | ||
| annoy.ipynb | ||
| atlas.ipynb | ||
| chroma.ipynb | ||
| deeplake.ipynb | ||
| docarray_hnsw.ipynb | ||
| docarray_in_memory.ipynb | ||
| elasticsearch.ipynb | ||
| faiss.ipynb | ||
| lanecdb.ipynb | ||
| milvus.ipynb | ||
| myscale.ipynb | ||
| opensearch.ipynb | ||
| pgvector.ipynb | ||
| pinecone.ipynb | ||
| qdrant.ipynb | ||
| redis.ipynb | ||
| sklearn.ipynb | ||
| supabase.ipynb | ||
| tair.ipynb | ||
| typesense.ipynb | ||
| vectara.ipynb | ||
| weaviate.ipynb | ||
| zilliz.ipynb | ||