Added **kwargs for embedding funcs #7664
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🤖:improvement
| @@ -461,7 +463,7 @@ async def _aembedding_func(self, text: str, *, engine: str) -> List[float]: | |||
| )["data"][0]["embedding"] | |||
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| def embed_documents( | |||
| self, texts: List[str], chunk_size: Optional[int] = 0 | |||
| self, texts: List[str], chunk_size: Optional[int] = 0, **kwargs | |||
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this signature is defined on base embeddings class, probably don't want to break the interface just here and im not sure we should add it to the base class.
what if added something like this instead? https://github.com/hwchase17/langchain/blob/c7b687e944883df972cabdf00064112587306daf/langchain/llms/openai.py#L137
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The issue is that I need to also pass a parameter model. If I place stuff in model_kwargs (in other places where I can)
llm = AzureOpenAI(deployment_name="text-davinci-003",model_name="text-davinci-003", model_kwargs={ "user" : "JL", "model" : "text-davinci-003" })
__root__
Parameters {'model'} should be specified explicitly. Instead they were passed in as part of `model_kwargs` parameter. (type=value_error)
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for embeddings you can already pass model in directly, no?
OpenAIEmbeddings(model=...)There was a problem hiding this comment.
yes but I need to place it also on the request body because that is parsed by our custom proxy 😢
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@FrancescoSaverioZuppichini Hi , could you, please, resolve the merging issues and address the last comments (if needed)? After that, ping me and I push this PR for the review. Thanks! |
sorry, no time |
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@baskaryan I'm closing it. |
Hi There,
This is a simple PR, adding **kwargs to
.embed_querysimilar to the other OpenAI functions. This is handy because I can add to the request whatever I want, in my case I am running OpenAI behind a custom proxy and I need a couple of more things to the requests@baskaryan
Thanks
Cheers,
Fra