Use orchestration lib #22
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libs/elasticsearch/tests/integration_tests/test_vectorstores.py
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Update documentation with the [new names for retrieval strategies](langchain-ai/langchain-elastic#22) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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Update documentation with the [new names for retrieval strategies](langchain-ai/langchain-elastic#22) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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Update documentation with the [new names for retrieval strategies](langchain-ai/langchain-elastic#22) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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We moved much of the VectorStore logic to the Elasticsearch client library (elastic/elasticsearch-py#2528, see module) in order to centralize the development, ensure all GenAI library integrations work the same and offer users direct access to this abstraction in the future.
This PR integrates the new module into LangChain and converts most tests to unit tests that just check if the backend vector store is called correctly (the integration tests now live in elasticsearch-py).
The LangChain classes keep their existing interfaces.