mirror of
https://github.com/hwchase17/langchain
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b99274c9d8
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.
68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
"""Test Vertex AI API wrapper.
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In order to run this test, you need to install VertexAI SDK
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pip install google-cloud-aiplatform>=1.35.0
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Your end-user credentials would be used to make the calls (make sure you've run
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`gcloud auth login` first).
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"""
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import pytest
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from langchain_community.embeddings import VertexAIEmbeddings
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def test_embedding_documents() -> None:
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documents = ["foo bar"]
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model = VertexAIEmbeddings()
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output = model.embed_documents(documents)
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assert len(output) == 1
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assert len(output[0]) == 768
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assert model.model_name == model.client._model_id
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assert model.model_name == "textembedding-gecko@001"
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def test_embedding_query() -> None:
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document = "foo bar"
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model = VertexAIEmbeddings()
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output = model.embed_query(document)
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assert len(output) == 768
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def test_large_batches() -> None:
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documents = ["foo bar" for _ in range(0, 251)]
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model_uscentral1 = VertexAIEmbeddings(location="us-central1")
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model_asianortheast1 = VertexAIEmbeddings(location="asia-northeast1")
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model_uscentral1.embed_documents(documents)
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model_asianortheast1.embed_documents(documents)
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assert model_uscentral1.instance["batch_size"] >= 250
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assert model_asianortheast1.instance["batch_size"] < 50
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def test_paginated_texts() -> None:
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documents = [
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"foo bar",
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"foo baz",
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"bar foo",
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"baz foo",
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"bar bar",
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"foo foo",
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"baz baz",
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"baz bar",
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]
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model = VertexAIEmbeddings()
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output = model.embed_documents(documents)
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assert len(output) == 8
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assert len(output[0]) == 768
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assert model.model_name == model.client._model_id
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def test_warning(caplog: pytest.LogCaptureFixture) -> None:
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_ = VertexAIEmbeddings()
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assert len(caplog.records) == 1
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record = caplog.records[0]
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assert record.levelname == "WARNING"
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expected_message = (
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"Model_name will become a required arg for VertexAIEmbeddings starting from "
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"Feb-01-2024. Currently the default is set to textembedding-gecko@001"
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)
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assert record.message == expected_message
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