U h @sbdZddlZddlmZmZddlZddlmZddlm Z m Z dZ dZ dZ Gd d d e eZdS) z+Wrapper around Bookend AI embedding models.N)AnyList) Embeddings) BaseModelFieldzhttps://api.bookend.ai/Z embeddingsz/models/predictcseZdZUdZeed<eed<eed<eedZeed<e dfdd Z e ee e e d d d Z ee e d ddZZS)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)kwargsc s$tjf|dd|ji|_dS)N AuthorizationzBasic {})super__init__formatr r )selfr  __class__J/tmp/pip-unpacked-wheel-9gdii04g/langchain_community/embeddings/bookend.pyr-szBookendEmbeddings.__init__)textsreturncCstg}|j}d|d<|jtd}|D]L}t|dddd}tjdt|jt |||d}| |dd q"|S) zEmbed documents using a Bookend deployed embeddings model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. zapplication/json; charset=utf-8z Content-Type)r ZtaskN)textZquestioncontextZ instructionPOST)headersparamsdatarr) r r DEFAULT_TASKjsondumpsrequestsrequestAPI_URLrPATHappend)rrresultrrrrrrrrembed_documents1s&   z!BookendEmbeddings.embed_documents)rrcCs||gdS)zEmbed a query using a Bookend deployed embeddings model. Args: text: The text to embed. Returns: Embeddings for the text. r)r))rrrrr embed_queryQs zBookendEmbeddings.embed_query)__name__ __module__ __qualname____doc__str__annotations__rdictr rrrfloatr)r* __classcell__rrrrrs  r)r.r typingrrr"Zlangchain_core.embeddingsrZlangchain_core.pydantic_v1rrr$rr%rrrrrs