昺htddlZddlZddlmZmZmZmZddlmZddl m Z m Z m Z dZ dZGdde eZdS) N)AnyDictListOptional) Embeddings) BaseModelExtraroot_validatorz'sentence-transformers/all-mpnet-base-v2)feature-extractionceZdZUdZeed<eed<dZeeed< dZ eeed< dZ eeed< dZ ee ed < dZ eeed <Gd d Zed edefdZdeedeeefdZdeedeeefdZdedeefdZdedeefdZdS)HuggingFaceHubEmbeddingsawHuggingFaceHub embedding models. To use, you should have the ``huggingface_hub`` python package installed, and the environment variable ``HUGGINGFACEHUB_API_TOKEN`` set with your API token, or pass it as a named parameter to the constructor. Example: .. code-block:: python from langchain_community.embeddings import HuggingFaceHubEmbeddings model = "sentence-transformers/all-mpnet-base-v2" hf = HuggingFaceHubEmbeddings( model=model, task="feature-extraction", huggingfacehub_api_token="my-api-key", ) client async_clientNmodelrepo_idr task model_kwargshuggingfacehub_api_tokenc eZdZdZejZdS)HuggingFaceHubEmbeddings.Configz'Configuration for this pydantic object.N)__name__ __module__ __qualname____doc__r forbidextrav/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/langchain_community/embeddings/huggingface_hub.pyConfigr,s55 rr valuesreturnc|dptjd} ddlm}m}|dr |d|d<n(|dr |d|d<nt |d<t |d<||d|}||d|}|dt vr!td |dd t d ||d <||d <n#t$rtdwxYw|S)z?Validate that api key and python package exists in environment.rHUGGINGFACEHUB_API_TOKENr)AsyncInferenceClientInferenceClientrr)rtokenrzGot invalid task z, currently only z are supportedrrzfCould not import huggingface_hub python package. Please install it with `pip install huggingface_hub`.) osgetenvhuggingface_hubr%r& DEFAULT_MODEL VALID_TASKS ValueError ImportError)clsr!rr%r&rrs rvalidate_environmentz-HuggingFaceHubEmbeddings.validate_environment1sx$**D#E$  &J J  !  M M M M M M M Mg 2$*7Oy!! " 2"("3w"/w$1y!$_Wo.F 0/Wo.L f~[00 BvBB&1BBB &F8 %1F> " "   H    s B$CCtextscd|D}|jpi}|j||d|j}t j|S)zCall out to HuggingFaceHub's embedding endpoint for embedding search docs. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. c:g|]}|ddS  replace.0texts r z.f&;;;TdC((;;;rinputs parametersjsonr)rrpostrrBloadsdecodeselfr1 _model_kwargs responsess rembed_documentsz(HuggingFaceHubEmbeddings.embed_documents\sm<;U;;;)/R K$$!??di%  z)**,,---rcKd|D}|jpi}|j||d|jd{V}t j|S)zAsync Call to HuggingFaceHub's embedding endpoint for embedding search docs. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. c:g|]}|ddSr4r7r9s rr<z=HuggingFaceHubEmbeddings.aembed_documents..wr=rr>rAN)rrrCrrBrDrErFs raembed_documentsz)HuggingFaceHubEmbeddings.aembed_documentsms<;U;;;)/R +00!??di1        z)**,,---rr;c>||gd}|S)zCall out to HuggingFaceHub's embedding endpoint for embedding query text. Args: text: The text to embed. Returns: Embeddings for the text. r)rJrGr;responses r embed_queryz$HuggingFaceHubEmbeddings.embed_query~s#''//2rcNK||gd{Vd}|S)zAsync Call to HuggingFaceHub's embedding endpoint for embedding query text. Args: text: The text to embed. Returns: Embeddings for the text. Nr)rMrOs r aembed_queryz%HuggingFaceHubEmbeddings.aembed_querys9//77777777;r)rrrrr__annotations__rrstrrrrdictrr r rr0rfloatrJrMrQrSrrrr r s$ KKKE8C=!GXc]!!!C.D(3-...&#'L(4.'''1.2hsm222 ^($(4((((T.T#Y.4U 3D....".DI.$tE{:K...."  U     s tE{      rr )rBr(typingrrrrlangchain_core.embeddingsrlangchain_core.pydantic_v1rr r r+r,r rrrr[s ,,,,,,,,,,,,000000GGGGGGGGGG9 % HHHHHy*HHHHHr