mirror of
https://github.com/hwchase17/langchain
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3f48eed5bd
Signed-off-by: Filip Haltmayer <filip.haltmayer@zilliz.com> Signed-off-by: Frank Liu <frank.liu@zilliz.com> Co-authored-by: Filip Haltmayer <81822489+filip-halt@users.noreply.github.com> Co-authored-by: Frank Liu <frank@frankzliu.com>
30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
"""Test ElasticSearch functionality."""
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from langchain.docstore.document import Document
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from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch
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from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
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def test_elasticsearch() -> None:
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"""Test end to end construction and search."""
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texts = ["foo", "bar", "baz"]
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docsearch = ElasticVectorSearch.from_texts(
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texts, FakeEmbeddings(), elasticsearch_url="http://localhost:9200"
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)
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output = docsearch.similarity_search("foo", k=1)
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assert output == [Document(page_content="foo")]
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def test_elasticsearch_with_metadatas() -> None:
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"""Test end to end construction and search."""
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texts = ["foo", "bar", "baz"]
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metadatas = [{"page": i} for i in range(len(texts))]
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docsearch = ElasticVectorSearch.from_texts(
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texts,
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FakeEmbeddings(),
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metadatas=metadatas,
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elasticsearch_url="http://localhost:9200",
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)
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output = docsearch.similarity_search("foo", k=1)
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assert output == [Document(page_content="foo", metadata={"page": 0})]
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