dhSSKrSSKJrJrJrJr SSKJr SSKJ r SSK J r SSK J r JrJr SSKJr SrS r\"S S S S 9"SS\ \ 55rg)N)AnyDictListOptional) deprecated) Embeddings)get_from_dict_or_env) BaseModel ConfigDictmodel_validator)Selfz'sentence-transformers/all-mpnet-base-v2)feature-extractionz0.2.2z1.0z3langchain_huggingface.HuggingFaceEndpointEmbeddings)sinceremovalalternative_importcv\rSrSr%SrSr\\S'Sr\\S'Sr \ \ \S'Sr \ \ \S'Sr \ \ \S 'Sr\ \\S 'Sr\ \ \S '\"S S S9r\"SS9\S\S\4Sj55r\"SS9S\4Sj5rS\\ S\\\4SjrS\\ S\\\4SjrS\ S\\4SjrS\ S\\4SjrS rg)HuggingFaceHubEmbeddingsaCHuggingFaceHub 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", ) Nclient async_clientmodelrepo_idrtask model_kwargshuggingfacehub_api_tokenforbid)extraprotected_namespacesbefore)modevaluesreturnc<[USS5nSSKJnJn UR S5(a USUS'O1UR S5(a USUS'O[ US'[ US'U"USUS9nU"USUS9nXQS'XaS 'U$![ a [ S 5ef=f) z?Validate that api key and python package exists in environment.rHUGGINGFACEHUB_API_TOKENr)AsyncInferenceClientInferenceClientrr)rtokenrrzfCould not import huggingface_hub python package. Please install it with `pip install huggingface_hub`.)r huggingface_hubr&r'get DEFAULT_MODEL ImportError)clsr"rr&r'rrs f/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/embeddings/huggingface_hub.pyvalidate_environment-HuggingFaceHubEmbeddings.validate_environment5s$8 .0J$    Mzz'""$*7Oy!I&&"("3w"/w$1y!$Wo.F 0Wo.L &8 %1> "  H  s A4BBaftercnUR[;a [SURS[S35eU$)z#Post init validation for the class.zGot invalid task z, currently only z are supported)r VALID_TASKS ValueError)selfs r. post_init"HuggingFaceHubEmbeddings.post_init\s@ 99K '#DII;/""-n>  textscUVs/sHo"RSS5PM nnUR=(d 0nURRSU0UEURS9n[ R "UR55$s snf)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.   inputsjsonr)replacerrpostrr?loadsdecoder5r9text _model_kwargs responsess r.embed_documents(HuggingFaceHubEmbeddings.embed_documentsfs|6;;UTdC(U;))/R KK$$E3]3$))% zz)**,-- N)r@rrrArr?rBrCrDs r.aembed_documents)HuggingFaceHubEmbeddings.aembed_documentsxs6;;UTdC(U;))/R ++00!?dii1  zz)**,-- < sBB AB!B".BrEc0URU/5SnU$)zCall out to HuggingFaceHub's embedding endpoint for embedding query text. Args: text: The text to embed. Returns: Embeddings for the text. r)rHr5rEresponses r. embed_query$HuggingFaceHubEmbeddings.embed_querys ''/2r8cL# URU/5IShvN SnU$N 7f)zAsync Call to HuggingFaceHub's embedding endpoint for embedding query text. Args: text: The text to embed. Returns: Embeddings for the text. Nr)rLrOs r. aembed_query%HuggingFaceHubEmbeddings.aembed_querys+//77;8s $" $) __name__ __module__ __qualname____firstlineno____doc__rr__annotations__rrrstrrrrdictrr model_configr classmethodrr/r r6rfloatrHrLrQrT__static_attributes__rr8r.rrs8 $FCL#E8C=!GXc]!C.D(3-.&#'L(4.'1.2hsm2H2FL(##$#3#$#J'"4#.T#Y.4U 3D.$.DI.$tE{:K."  U  s tE{ r8r)r?typingrrrrlangchain_core._apirlangchain_core.embeddingsrlangchain_core.utilsr pydanticr r r typing_extensionsr r+r3rrr8r.rhsX ,,*05;;"9 %   L Ly*L  Lr8