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[ElasticsearchStore] Improve migration text to ElasticsearchStore #11158

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merged 2 commits into from
Sep 28, 2023
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[ElasticsearchStore] Improve migration text to ElasticsearchStore #11158

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2556ab3
un-deprecate the elastic vector store
joemcelroy Sep 28, 2023
5fec163
fix lint
joemcelroy Sep 28, 2023
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22 changes: 19 additions & 3 deletions libs/langchain/langchain/vectorstores/elastic_vector_search.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
"""[DEPRECATED] Please use ElasticsearchStore instead."""
from __future__ import annotations

import uuid
Expand Down Expand Up @@ -51,9 +50,19 @@ def _default_script_query(query_vector: List[float], filter: Optional[dict]) ->
}


@deprecated("0.0.265", alternative="ElasticsearchStore class.", pending=True)
class ElasticVectorSearch(VectorStore):
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Should we keep the deprecation notice? It sends a warning to users letting them know that there's a better implementation. It doesn't necessarily mean that this implementation will be removed soon.

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Hey @eyurtsev thanks for review. Will the notice "deprecated" be still mentioned in the docs if it continues to be there? Ideally we dont want this message there as gives the wrong signal. Thanks!

"""[DEPRECATED] `Elasticsearch` vector store.
"""

ElasticVectorSearch uses the brute force method of searching on vectors.

Recommended to use ElasticsearchStore instead, which gives you the option
to uses the approx HNSW algorithm which performs better on large datasets.

ElasticsearchStore also supports metadata filtering, customising the
query retriever and much more!

You can read more on ElasticsearchStore:
https://python.langchain.com/docs/integrations/vectorstores/elasticsearch

To connect to an `Elasticsearch` instance that does not require
login credentials, pass the Elasticsearch URL and index name along with the
Expand Down Expand Up @@ -339,10 +348,17 @@ def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> None:
self.client.delete(index=self.index_name, id=id)


@deprecated("0.0.265", alternative="ElasticsearchStore class.", pending=True)
class ElasticKnnSearch(VectorStore):
"""[DEPRECATED] `Elasticsearch` with k-nearest neighbor search
(`k-NN`) vector store.

Recommended to use ElasticsearchStore instead, which supports
metadata filtering, customising the query retriever and much more!

You can read more on ElasticsearchStore:
https://python.langchain.com/docs/integrations/vectorstores/elasticsearch

It creates an Elasticsearch index of text data that
can be searched using k-NN search. The text data is transformed into
vector embeddings using a provided embedding model, and these embeddings
Expand Down