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import lancedb | |
from langchain.vectorstores import LanceDB | |
from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings | |
def test_lancedb() -> None: | |
embeddings = FakeEmbeddings() | |
db = lancedb.connect("/tmp/lancedb") | |
texts = ["text 1", "text 2", "item 3"] | |
vectors = embeddings.embed_documents(texts) | |
table = db.create_table( | |
"my_table", | |
data=[ | |
{"vector": vectors[idx], "id": text, "text": text} | |
for idx, text in enumerate(texts) | |
], | |
mode="overwrite", | |
) | |
store = LanceDB(table, embeddings) | |
result = store.similarity_search("text 1") | |
result_texts = [doc.page_content for doc in result] | |
assert "text 1" in result_texts | |
def test_lancedb_add_texts() -> None: | |
embeddings = FakeEmbeddings() | |
db = lancedb.connect("/tmp/lancedb") | |
texts = ["text 1"] | |
vectors = embeddings.embed_documents(texts) | |
table = db.create_table( | |
"my_table", | |
data=[ | |
{"vector": vectors[idx], "id": text, "text": text} | |
for idx, text in enumerate(texts) | |
], | |
mode="overwrite", | |
) | |
store = LanceDB(table, embeddings) | |
store.add_texts(["text 2"]) | |
result = store.similarity_search("text 2") | |
result_texts = [doc.page_content for doc in result] | |
assert "text 2" in result_texts | |