dhxSSKrSSKJrJr SSKrSSKJr SSKJr \R"\ 5r "SS\\5r g)N)ListOptional) Embeddings) BaseModelc\rSrSr%SrSr\\S'Sr\ \ \S'S\S\ \ 4S jr S \ \S\ \ \ 4S jrS\S\ \ 4S jrS rg)LlamafileEmbeddings aLlamafile lets you distribute and run large language models with a single file. To get started, see: https://github.com/Mozilla-Ocho/llamafile To use this class, you will need to first: 1. Download a llamafile. 2. Make the downloaded file executable: `chmod +x path/to/model.llamafile` 3. Start the llamafile in server mode with embeddings enabled: `./path/to/model.llamafile --server --nobrowser --embedding` Example: .. code-block:: python from langchain_community.embeddings import LlamafileEmbeddings embedder = LlamafileEmbeddings() doc_embeddings = embedder.embed_documents( [ "Alpha is the first letter of the Greek alphabet", "Beta is the second letter of the Greek alphabet", ] ) query_embedding = embedder.embed_query( "What is the second letter of the Greek alphabet" ) zhttp://localhost:8080base_urlNrequest_timeouttextreturnc[R"URS3SS0SU0URS9nUR 5 UR5nSU;a [S 5eUSn[U5S :Xa [S 5eU$![RR a. [RR SURS35ef=f) Nz /embeddingz Content-Typezapplication/jsoncontent)urlheadersjsontimeoutzTCould not connect to Llamafile server. Please make sure that a server is running at . embeddingzPUnexpected output from /embedding endpoint, output dict missing 'embedding' key.gz^Embedding sums to 0, did you start the llamafile server with the `--embedding` option enabled?) requestspostr r exceptionsConnectionErrorraise_for_statusrKeyErrorsum ValueError)selfr responsecontentsrs `/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/embeddings/llamafile.py_embedLlamafileEmbeddings._embed0s }}}}oZ0"$6t,, H" !!#==? h &+  [)  y>S 4  =""22 %%55//3}}oQ@  s 2BA Ctextsc\/nUH#nURURU55 M% U$)zEmbed documents using a llamafile server running at `self.base_url`. llamafile server should be started in a separate process before invoking this method. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. )appendr")rr$doc_embeddingsr s r!embed_documents#LlamafileEmbeddings.embed_documents\s0D  ! !$++d"3 4c$URU5$)zEmbed a query using a llamafile server running at `self.base_url`. llamafile server should be started in a separate process before invoking this method. Args: text: The text to embed. Returns: Embeddings for the text. )r")rr s r! embed_queryLlamafileEmbeddings.embed_queryls{{4  r*)__name__ __module__ __qualname____firstlineno____doc__r str__annotations__r rintrfloatr"r(r,__static_attributes__r.r*r!rr sv<,Hc+;%)OXc])%*3*4;*XT#Y4U 3D ! !U !r*r) loggingtypingrrrlangchain_core.embeddingsrpydanticr getLoggerr/loggerrr.r*r!r?s4!0   8 $l!)Zl!r*