dh>SrSSKJrJrJr SSKJr "SS\5rg)z+Wrapper around Xinference embedding models.)AnyListOptional) Embeddingsc^\rSrSr%Sr\\S'\\\S'\\\S'S S\\S\\4U4Sjjjr S\ \S\ \ \ 4S jr S \S\ \ 4S jr S rU=r$)XinferenceEmbeddingsaXinference embedding models. To use, you should have the xinference library installed: .. code-block:: bash pip install xinference If you're simply using the services provided by Xinference, you can utilize the xinference_client package: .. code-block:: bash pip install xinference_client Check out: https://github.com/xorbitsai/inference To run, you need to start a Xinference supervisor on one server and Xinference workers on the other servers. Example: To start a local instance of Xinference, run .. code-block:: bash $ xinference You can also deploy Xinference in a distributed cluster. Here are the steps: Starting the supervisor: .. code-block:: bash $ xinference-supervisor If you're simply using the services provided by Xinference, you can utilize the xinference_client package: .. code-block:: bash pip install xinference_client Starting the worker: .. code-block:: bash $ xinference-worker Then, launch a model using command line interface (CLI). Example: .. code-block:: bash $ xinference launch -n orca -s 3 -q q4_0 It will return a model UID. Then you can use Xinference Embedding with LangChain. Example: .. code-block:: python from langchain_community.embeddings import XinferenceEmbeddings xinference = XinferenceEmbeddings( server_url="http://0.0.0.0:9997", model_uid = {model_uid} # replace model_uid with the model UID return from launching the model ) client server_url model_uidc>SSKJn [TU]5 Uc [ S5eUc [ S5eXlX lU"U5Ul g![a( SSKJn NW![an[S5UeSnAff=ff=f)Nr) RESTfulClientzCould not import RESTfulClient from xinference. Please install it with `pip install xinference` or `pip install xinference_client`.zPlease provide server URLzPlease provide the model UID) xinference.clientr ImportErrorxinference_clientsuper__init__ ValueErrorr r r )selfr r re __class__s a/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/embeddings/xinference.pyrXinferenceEmbeddings.__init__Rs  7   89 9  ;< <$"#J/ +  ; !Y  s)A A?A  A;* A66A;;A?textsreturnc URRUR5nUVs/sHo2RU5SSSPM nnUVs/sHn[ [ [ U55PM sn$s snfs snf)zEmbed a list of documents using Xinference. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. datar embeddingr get_modelr create_embeddinglistmapfloat)rrmodeltext embeddingsrs rembed_documents$XinferenceEmbeddings.embed_documentsns %%dnn5NS MRT " "4 ( 0 3K @U  .88ZS]#Z88 9s "A7"A<r&cURRUR5nURU5nUSSSn[ [ [ U55$)zvEmbed a query of documents using Xinference. Args: text: The text to embed. Returns: Embeddings for the text. rrrr)rr&r% embedding_resrs r embed_query XinferenceEmbeddings.embed_query}sR %%dnn5..t4 !&)!,[9 Cy)**)r r r )NN)__name__ __module__ __qualname____firstlineno____doc__r__annotations__rstrrrr$r(r,__static_attributes__ __classcell__)rs@rrrsAF K &}#LP0"3-0;CC=008 9T#Y 94U 3D 9++U ++r.rN)r3typingrrrlangchain_core.embeddingsrrr.rr;s1&&0C+:C+r.