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dd1d818a82
<!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> This change addresses the issue where DashScopeEmbeddingAPI limits requests to 25 lines of data, and DashScopeEmbeddings did not handle cases with more than 25 lines, leading to errors. I have implemented a fix to manage data exceeding this limit efficiently. --------- Co-authored-by: xuxiang <xuxiang@aliyun.com>
85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
"""Test dashscope embeddings."""
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import numpy as np
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from langchain_community.embeddings.dashscope import DashScopeEmbeddings
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def test_dashscope_embedding_documents() -> None:
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"""Test dashscope embeddings."""
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documents = ["foo bar"]
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embedding = DashScopeEmbeddings(model="text-embedding-v1")
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output = embedding.embed_documents(documents)
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assert len(output) == 1
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assert len(output[0]) == 1536
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def test_dashscope_embedding_documents_multiple() -> None:
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"""Test dashscope embeddings."""
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documents = [
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"foo bar",
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"bar foo",
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"foo",
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"foo0",
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"foo1",
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"foo2",
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"foo3",
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"foo4",
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"foo5",
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"foo6",
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"foo7",
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"foo8",
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"foo9",
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"foo10",
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"foo11",
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"foo12",
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"foo13",
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"foo14",
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"foo15",
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"foo16",
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"foo17",
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"foo18",
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"foo19",
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"foo20",
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"foo21",
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"foo22",
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"foo23",
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"foo24",
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]
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embedding = DashScopeEmbeddings(model="text-embedding-v1")
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output = embedding.embed_documents(documents)
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assert len(output) == 28
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assert len(output[0]) == 1536
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assert len(output[1]) == 1536
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assert len(output[2]) == 1536
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def test_dashscope_embedding_query() -> None:
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"""Test dashscope embeddings."""
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document = "foo bar"
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embedding = DashScopeEmbeddings(model="text-embedding-v1")
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output = embedding.embed_query(document)
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assert len(output) == 1536
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def test_dashscope_embedding_with_empty_string() -> None:
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"""Test dashscope embeddings with empty string."""
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import dashscope
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document = ["", "abc"]
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embedding = DashScopeEmbeddings(model="text-embedding-v1")
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output = embedding.embed_documents(document)
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assert len(output) == 2
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assert len(output[0]) == 1536
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expected_output = dashscope.TextEmbedding.call(
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input="", model="text-embedding-v1", text_type="document"
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).output["embeddings"][0]["embedding"]
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assert np.allclose(output[0], expected_output)
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assert len(output[1]) == 1536
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if __name__ == "__main__":
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test_dashscope_embedding_documents()
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test_dashscope_embedding_documents_multiple()
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test_dashscope_embedding_query()
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test_dashscope_embedding_with_empty_string()
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