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

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"""Test dashscope embeddings."""
import numpy as np
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
2023-12-11 21:53:30 +00:00
from langchain_community.embeddings.dashscope import DashScopeEmbeddings
def test_dashscope_embedding_documents() -> None:
"""Test dashscope embeddings."""
documents = ["foo bar"]
embedding = DashScopeEmbeddings(model="text-embedding-v1")
output = embedding.embed_documents(documents)
assert len(output) == 1
assert len(output[0]) == 1536
def test_dashscope_embedding_documents_multiple() -> None:
"""Test dashscope embeddings."""
Fixing the Issue with DashScopeEmbeddings Handling More than 25 Rows of Data (#14662) <!-- 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>
2024-01-02 00:50:13 +00:00
documents = [
"foo bar",
"bar foo",
"foo",
"foo0",
"foo1",
"foo2",
"foo3",
"foo4",
"foo5",
"foo6",
"foo7",
"foo8",
"foo9",
"foo10",
"foo11",
"foo12",
"foo13",
"foo14",
"foo15",
"foo16",
"foo17",
"foo18",
"foo19",
"foo20",
"foo21",
"foo22",
"foo23",
"foo24",
]
embedding = DashScopeEmbeddings(model="text-embedding-v1")
output = embedding.embed_documents(documents)
Fixing the Issue with DashScopeEmbeddings Handling More than 25 Rows of Data (#14662) <!-- 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>
2024-01-02 00:50:13 +00:00
assert len(output) == 28
assert len(output[0]) == 1536
assert len(output[1]) == 1536
assert len(output[2]) == 1536
def test_dashscope_embedding_query() -> None:
"""Test dashscope embeddings."""
document = "foo bar"
embedding = DashScopeEmbeddings(model="text-embedding-v1")
output = embedding.embed_query(document)
assert len(output) == 1536
def test_dashscope_embedding_with_empty_string() -> None:
"""Test dashscope embeddings with empty string."""
import dashscope
document = ["", "abc"]
embedding = DashScopeEmbeddings(model="text-embedding-v1")
output = embedding.embed_documents(document)
assert len(output) == 2
assert len(output[0]) == 1536
expected_output = dashscope.TextEmbedding.call(
input="", model="text-embedding-v1", text_type="document"
).output["embeddings"][0]["embedding"]
assert np.allclose(output[0], expected_output)
assert len(output[1]) == 1536
if __name__ == "__main__":
test_dashscope_embedding_documents()
test_dashscope_embedding_documents_multiple()
test_dashscope_embedding_query()
test_dashscope_embedding_with_empty_string()