j: ldZddlZddlmZmZddlZddlmZddlm Z m Z m Z dZ dZ dZGd d e eZy) z+Wrapper around Bookend AI embedding models.N)AnyList) Embeddings) BaseModel ConfigDictFieldzhttps://api.bookend.ai/ embeddingsz/models/predictceZdZUdZeed< eed< eed< eeZeed<e dZ d e ffd Z d e ed e e efd Zded e efdZxZS)BookendEmbeddingsaBookend AI sentence_transformers embedding models. Example: .. code-block:: python from langchain_community.embeddings import BookendEmbeddings bookend = BookendEmbeddings( domain={domain} api_token={api_token} model_id={model_id} ) bookend.embed_documents([ "Please put on these earmuffs because I can't you hear.", "Baby wipes are made of chocolate stardust.", ]) bookend.embed_query( "She only paints with bold colors; she does not like pastels." ) domain api_tokenmodel_id)default_factory auth_header)protected_namespaceskwargsc ht|di|ddj|ji|_y)N AuthorizationzBasic {}r)super__init__formatr r)selfr __class__s p/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/embeddings/bookend.pyrzBookendEmbeddings.__init__/s/ "6"+Z->->t~~-NOtextsreturncBg}|j}d|d<|jtd}|D]s}tj|dddd}t j dt|jztz|||}|j|jdd u|S) zEmbed documents using a Bookend deployed embeddings model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. zapplication/json; charset=utf-8z Content-Type)rtaskN)textquestioncontext instructionPOST)headersparamsdatarr() rr DEFAULT_TASKjsondumpsrequestsrequestAPI_URLr PATHappend)rrresultr&r'r!r(rs rembed_documentsz!BookendEmbeddings.embed_documents3s"""C    D:: $##' D  $++%, A MM!&&(1+f- .!$ rr!c,|j|gdS)zEmbed a query using a Bookend deployed embeddings model. Args: text: The text to embed. Returns: Embeddings for the text. r)r3)rr!s r embed_queryzBookendEmbeddings.embed_queryXs##TF+A..r)__name__ __module__ __qualname____doc__str__annotations__rdictrr model_configrrrfloatr3r5 __classcell__)rs@rr r s* KTNXM%d3K326LPP#T#Y#4U 3D#J / /U /rr )r9r*typingrrr,langchain_core.embeddingsrpydanticrrrr.r)r/r rrrrCs91 011 # R/ :R/r