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Updated LocalAIEmbeddings
docstring to better explain why openai
(#10946)
Fixes my misgivings in https://github.com/langchain-ai/langchain/issues/10912
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@ -120,16 +120,19 @@ async def async_embed_with_retry(embeddings: LocalAIEmbeddings, **kwargs: Any) -
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class LocalAIEmbeddings(BaseModel, Embeddings):
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"""LocalAI embedding models.
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To use, you should have the ``openai`` python package installed, and the
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environment variable ``OPENAI_API_KEY`` set to a random string. You need to
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specify ``OPENAI_API_BASE`` to point to your LocalAI service endpoint.
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Since LocalAI and OpenAI have 1:1 compatibility between APIs, this class
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uses the ``openai`` Python package's ``openai.Embedding`` as its client.
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Thus, you should have the ``openai`` python package installed, and defeat
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the environment variable ``OPENAI_API_KEY`` by setting to a random string.
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You also need to specify ``OPENAI_API_BASE`` to point to your LocalAI
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service endpoint.
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Example:
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.. code-block:: python
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from langchain.embeddings import LocalAIEmbeddings
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openai = LocalAIEmbeddings(
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openai_api_key="random-key",
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openai_api_key="random-string",
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openai_api_base="http://localhost:8080"
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)
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