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langchain/libs/community/tests/integration_tests/embeddings/test_vertexai.py

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
community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
10 months ago
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