langchain/libs/community/tests/integration_tests/embeddings/test_vertexai.py
Leonid Kuligin b99274c9d8
community[patch]: changed default for VertexAIEmbeddings (#14614)
Replace this entire comment with:
- **Description:** @kurtisvg has raised a point that it's a good idea to
have a fixed version for embeddings (since otherwise a user might run a
query with one version vs a vectorstore where another version was used).
In order to avoid breaking changes, I'd suggest to give users a warning,
and make a `model_name` a required argument in 1.5 months.
2023-12-21 12:15:19 -05:00

68 lines
2.1 KiB
Python

"""Test Vertex AI API wrapper.
In order to run this test, you need to install VertexAI SDK
pip install google-cloud-aiplatform>=1.35.0
Your end-user credentials would be used to make the calls (make sure you've run
`gcloud auth login` first).
"""
import pytest
from langchain_community.embeddings import VertexAIEmbeddings
def test_embedding_documents() -> None:
documents = ["foo bar"]
model = VertexAIEmbeddings()
output = model.embed_documents(documents)
assert len(output) == 1
assert len(output[0]) == 768
assert model.model_name == model.client._model_id
assert model.model_name == "textembedding-gecko@001"
def test_embedding_query() -> None:
document = "foo bar"
model = VertexAIEmbeddings()
output = model.embed_query(document)
assert len(output) == 768
def test_large_batches() -> None:
documents = ["foo bar" for _ in range(0, 251)]
model_uscentral1 = VertexAIEmbeddings(location="us-central1")
model_asianortheast1 = VertexAIEmbeddings(location="asia-northeast1")
model_uscentral1.embed_documents(documents)
model_asianortheast1.embed_documents(documents)
assert model_uscentral1.instance["batch_size"] >= 250
assert model_asianortheast1.instance["batch_size"] < 50
def test_paginated_texts() -> None:
documents = [
"foo bar",
"foo baz",
"bar foo",
"baz foo",
"bar bar",
"foo foo",
"baz baz",
"baz bar",
]
model = VertexAIEmbeddings()
output = model.embed_documents(documents)
assert len(output) == 8
assert len(output[0]) == 768
assert model.model_name == model.client._model_id
def test_warning(caplog: pytest.LogCaptureFixture) -> None:
_ = VertexAIEmbeddings()
assert len(caplog.records) == 1
record = caplog.records[0]
assert record.levelname == "WARNING"
expected_message = (
"Model_name will become a required arg for VertexAIEmbeddings starting from "
"Feb-01-2024. Currently the default is set to textembedding-gecko@001"
)
assert record.message == expected_message