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28 lines
1.0 KiB
Python
28 lines
1.0 KiB
Python
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import numpy as np
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import pytest
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@pytest.mark.parametrize("document_store", ["faiss"], indirect=True)
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def test_faiss_indexing(document_store):
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documents = [
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{"name": "name_1", "text": "text_1", "embedding": np.random.rand(768).astype(np.float32)},
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{"name": "name_2", "text": "text_2", "embedding": np.random.rand(768).astype(np.float32)},
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{"name": "name_3", "text": "text_3", "embedding": np.random.rand(768).astype(np.float32)},
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]
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document_store.write_documents(documents)
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documents_indexed = document_store.get_all_documents()
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# test if correct vector_ids are assigned
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for i, doc in enumerate(documents_indexed):
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assert doc.meta["vector_id"] == str(i)
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# test insertion of documents in an existing index fails
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with pytest.raises(Exception):
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document_store.write_documents(documents)
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# test saving the index
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document_store.save("haystack_test_faiss")
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# test loading the index
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document_store.load(sql_url="sqlite:///haystack_test.db", faiss_file_path="haystack_test_faiss")
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