Jeff Vestal d1f65d8dc1 Es knn index search 5346 (#5569) ... # Create elastic_vector_search.ElasticKnnSearch class This extends `langchain/vectorstores/elastic_vector_search.py` by adding a new class `ElasticKnnSearch` Features: - Allow creating an index with the `dense_vector` mapping compataible with kNN search - Store embeddings in index for use with kNN search (correct mapping creates HNSW data structure) - Perform approximate kNN search - Perform hybrid BM25 (`query{}`) + kNN (`knn{}`) search - perform knn search by either providing a `query_vector` or passing a hosted `model_id` to use query_vector_builder to automatically generate a query_vector at search time Connection options - Using `cloud_id` from Elastic Cloud - Passing elasticsearch client object search options - query - k - query_vector - model_id - size - source - knn_boost (hybrid search) - query_boost (hybrid search) - fields This also adds examples to `docs/modules/indexes/vectorstores/examples/elasticsearch.ipynb` Fixes # [5346](https://github.com/hwchase17/langchain/issues/5346) cc: @dev2049 --> --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>		2023-06-02 08:40:35 -07:00
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examples	Es knn index search 5346 (#5569)	2023-06-02 08:40:35 -07:00
getting_started.ipynb	docs: improved vectorstore notebooks (#3724)	2023-04-28 19:26:50 -07:00