tjddlZddlmZmZmZmZddlmZddlm Z ddl m Z ddl m Z mZmZddlmZdZd Zed d d Gdde e ZdS)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_importceZdZUdZdZeed<dZeed<dZe e ed< dZ e e ed< dZ e e ed< dZ e eed < dZe e ed <ed d ZedededefdZeddefdZdee deeefdZdee deeefdZde deefdZde deefdZdS)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", ) Nclient async_clientmodelrepo_idrtask model_kwargshuggingfacehub_api_tokenforbid)extraprotected_namespacesbefore)modevaluesreturnct|dd} ddlm}m}|dr |d|d<n5|dr |d|d<nt |d<t |d<||d|}||d|}||d<||d <n#t $rt d wxYw|S) 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 l/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/embeddings/huggingface_hub.pyvalidate_environmentz-HuggingFaceHubEmbeddings.validate_environment5s,$8 .0J$ $    M M M M M M M Mzz'"" 2$*7Oy!!I&& 2"("3w"/w$1y!$_Wo.F 0/Wo.L &F8 %1F> " "   H    s BB""B<aftercb|jtvr td|jdtd|S)z#Post init validation for the class.zGot invalid task z, currently only z are supported)r VALID_TASKS ValueError)selfs r- post_initz"HuggingFaceHubEmbeddings.post_init\sO 9K ' '>DI>>"->>>  textscd|D}|jpi}|jd|i||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.p&;;;TdC((;;;r5inputsjsonr)rrpostrrEloadsdecoder3r6 _model_kwargs responsess r-embed_documentsz(HuggingFaceHubEmbeddings.embed_documentsfso<;U;;;)/R K$$E3]3$)%  z)**,,---r5cKd|D}|jpi}|j||d|jd{V}t j|S)zAsync Call to HuggingFaceHub's embedding endpoint for embedding search docs. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. c:g|]}|ddSr9r<r>s r-rAz=HuggingFaceHubEmbeddings.aembed_documents..rBr5)rC parametersrDN)rrrFrrErGrHrIs r-aembed_documentsz)HuggingFaceHubEmbeddings.aembed_documentsxs<;U;;;)/R +00!??di1        z)**,,---r5r@c>||gd}|S)zCall out to HuggingFaceHub's embedding endpoint for embedding query text. Args: text: The text to embed. Returns: Embeddings for the text. r)rLr3r@responses r- embed_queryz$HuggingFaceHubEmbeddings.embed_querys#''//2r5cNK||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)rPrRs r- aembed_queryz%HuggingFaceHubEmbeddings.aembed_querys9//77777777;r5)__name__ __module__ __qualname____doc__rr__annotations__rrrstrrrrdictrr model_configr classmethodrr.r r4rfloatrLrPrTrVrr5r-rrs $FCL#E8C=!GXc]!!!C.D(3-...&#'L(4.'''1.2hsm222:H2FFFL_(####$#3###[$##J_'"""4#".T#Y.4U 3D....$.DI.$tE{:K...."  U     s tE{      r5r)rEtypingrrrrlangchain_core._apirlangchain_core.embeddingsrlangchain_core.utilsr pydanticr r r typing_extensionsr r*r1rrr5r-rgs  ,,,,,,,,,,,,******000000555555;;;;;;;;;;""""""9 %    L LLLLLy*LL  LLLr5