mirror of
https://github.com/hwchase17/langchain
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7773943a51
- **Description:** - support custom kwargs in object initialization. For instantance, QPS differs from multiple object(chat/completion/embedding with diverse models), for which global env is not a good choice for configuration. - **Issue:** no - **Dependencies:** no - **Twitter handle:** no @baskaryan PTAL
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""Test Baidu Qianfan Embedding Endpoint."""
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from langchain_community.embeddings.baidu_qianfan_endpoint import (
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QianfanEmbeddingsEndpoint,
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)
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def test_embedding_multiple_documents() -> None:
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documents = ["foo", "bar"]
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embedding = QianfanEmbeddingsEndpoint()
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output = embedding.embed_documents(documents)
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assert len(output) == 2
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assert len(output[0]) == 384
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assert len(output[1]) == 384
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def test_embedding_query() -> None:
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query = "foo"
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embedding = QianfanEmbeddingsEndpoint()
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output = embedding.embed_query(query)
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assert len(output) == 384
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def test_model() -> None:
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documents = ["hi", "qianfan"]
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embedding = QianfanEmbeddingsEndpoint(model="Embedding-V1")
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output = embedding.embed_documents(documents)
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assert len(output) == 2
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def test_rate_limit() -> None:
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llm = QianfanEmbeddingsEndpoint(
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model="Embedding-V1", init_kwargs={"query_per_second": 2}
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)
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assert llm.client._client._rate_limiter._sync_limiter._query_per_second == 2
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documents = ["foo", "bar"]
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output = llm.embed_documents(documents)
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assert len(output) == 2
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assert len(output[0]) == 384
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assert len(output[1]) == 384
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