dhn PSrSSKJrJrJr SSKJr SSKJrJ r "SS\\5r g)z)Wrapper around text2vec embedding models.)AnyListOptional) Embeddings) BaseModel ConfigDictc^\rSrSr%SrSr\\\S'Sr \ \S'Sr \ \S'Sr \\\S 'Sr\ \S '\"S S 9rSSS .S \ S\\S\ 4U4SjjjrS\\S\\\4SjrS\S\\4SjrS rU=r$)Text2vecEmbeddings a^text2vec embedding models. Install text2vec first, run 'pip install -U text2vec'. The github repository for text2vec is : https://github.com/shibing624/text2vec Example: .. code-block:: python from langchain_community.embeddings.text2vec import Text2vecEmbeddings embedding = Text2vecEmbeddings() embedding.embed_documents([ "This is a CoSENT(Cosine Sentence) model.", "It maps sentences to a 768 dimensional dense vector space.", ]) embedding.embed_query( "It can be used for text matching or semantic search." ) Nmodel_name_or_pathMEAN encoder_typemax_seq_lengthdevicemodel)protected_namespacesrr kwargsc >SSKJn 0nUbX&S'U=(d U"S0UDUD6n[TU]"SXS.UD6 g![an[S5UeSnAff=f)Nr) SentenceModelzIUnable to import text2vec, please install with `pip install -U text2vec`.r rr)text2vecr ImportErrorsuper__init__)selfrr rre model_kwargs __class__s _/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/embeddings/text2vec.pyrText2vecEmbeddings.__init__&sv  .  )1C- .@@@@ VuVvV -  s8 A AAtextsreturnc8URRU5$)zEmbed documents using the text2vec embeddings model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. rencode)rr#s r!embed_documents"Text2vecEmbeddings.embed_documents;szz  ''textc8URRU5$)z~Embed a query using the text2vec embeddings model. Args: text: The text to embed. Returns: Embeddings for the text. r&)rr+s r! embed_queryText2vecEmbeddings.embed_queryGszz  &&r*)__name__ __module__ __qualname____firstlineno____doc__r rstr__annotations__rrrintrrr model_configrrfloatr(r-__static_attributes__ __classcell__)r s@r!r r s()- ,L#NC FHSM E326L ,0 WW%SM W  WW* (T#Y (4U 3D ( ' 'U ' 'r*r N) r3typingrrrlangchain_core.embeddingsrpydanticrrr rr*r!r>s$/&&0*H'YH'r*