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23f701b08e
This is a follow-on PR to go with the identical changes that were made in parters/openai. Previous PR: https://github.com/langchain-ai/langchain/pull/30757 When calling embed_documents and providing a chunk_size argument, that argument is ignored when OpenAIEmbeddings is instantiated with its default configuration (where check_embedding_ctx_length=True). _get_len_safe_embeddings specifies a chunk_size parameter but it's not being passed through in embed_documents, which is its only caller. This appears to be an oversight, especially given that the _get_len_safe_embeddings docstring states it should respect "the set embedding context length and chunk size." Developers typically expect method parameters to take effect (also, take precedence) when explicitly provided, especially when instantiating using defaults. I was confused as to why my API calls were being rejected regardless of the chunk size I provided.
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
import os
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from unittest.mock import patch
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import pytest
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from langchain_community.embeddings.openai import OpenAIEmbeddings
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os.environ["OPENAI_API_KEY"] = "foo"
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@pytest.mark.requires("openai")
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def test_openai_invalid_model_kwargs() -> None:
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with pytest.raises(ValueError):
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OpenAIEmbeddings(model_kwargs={"model": "foo"})
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@pytest.mark.requires("openai")
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def test_openai_incorrect_field() -> None:
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with pytest.warns(match="not default parameter"):
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llm = OpenAIEmbeddings(foo="bar", openai_api_key="foo") # type: ignore[call-arg]
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assert llm.model_kwargs == {"foo": "bar"}
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@pytest.mark.requires("openai")
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def test_embed_documents_with_custom_chunk_size() -> None:
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embeddings = OpenAIEmbeddings(chunk_size=2)
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texts = ["text1", "text2", "text3", "text4"]
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custom_chunk_size = 3
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with patch.object(embeddings.client, "create") as mock_create:
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mock_create.side_effect = [
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{"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
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{"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
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]
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embeddings.embed_documents(texts, chunk_size=custom_chunk_size)
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mock_create.assert_any_call(input=[[1342, 19]], **embeddings._invocation_params)
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mock_create.assert_any_call(input=[[1342, 19]], **embeddings._invocation_params)
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