mirror of
https://github.com/deepset-ai/haystack.git
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a44b6c18c0
* Refactored code to unify vector_dim and embedding_dim parameter in DocumentStores * Unit test cases updated to use `embedding_dim` instead of `vector_dim` * Unit test case update to use embedding_dim instead of vector_dim * Add latest docstring and tutorial changes * Put usage of `vector_dim` param in same if-block as corresponding warning Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: bogdankostic <bogdankostic@web.de>
12 lines
727 B
INI
12 lines
727 B
INI
[pytest]
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addopts = --strict-markers
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markers =
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slow: marks tests as slow (deselect with '-m "not slow"')
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tika: marks tests which require tika container (deselect with '-m "not tika"')
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elasticsearch: marks tests which require elasticsearch container (deselect with '-m "not elasticsearch"')
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graphdb: marks tests which require graphdb container (deselect with '-m "not graphdb"')
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generator: marks generator tests (deselect with '-m "not generator"')
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pipeline: marks tests with pipeline
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summarizer: marks summarizer tests
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weaviate: marks tests that require weaviate container
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embedding_dim: marks usage of document store with non-default embedding dimension (e.g @pytest.mark.embedding_dim(128)) |