j NddlmZddlmZmZmZddlmZmZm Z GddeZ y)) annotations)AnyOptionalcast) TextSplitter Tokenizersplit_text_on_tokenscveZdZUdZ d d fd Z d dZd dZddZdZde d<dd Z xZ S)%SentenceTransformersTokenTextSplitterz8Splitting text to tokens using sentence model tokenizer.intc t|di|d|i ddlm}||_||j |_|j j|_|j|y#t$r}d}t ||d}~wwxYw)zCreate a new TextSplitter. chunk_overlapr)SentenceTransformerzCould not import sentence_transformers python package. This is needed in order to for SentenceTransformersTokenTextSplitter. Please install it with `pip install sentence-transformers`.N)tokens_per_chunk) super__init__sentence_transformersr ImportError model_name_model tokenizer_initialize_chunk_configuration) selfrrrkwargsrerrmsg __class__s x/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_text_splitters/sentence_transformers.pyrz.SentenceTransformersTokenTextSplitter.__init__ s ?6?? , A%)$//: .. ,,>N,O ,N  c" +  ,sA(( B1A??Bc |jj|_||j|_n||_|j|jkDr5d|jd|jd|jd}t |y)NzThe token limit of the models 'z' is: z. Argument tokens_per_chunk=z > maximum token limit.)rmax_seq_lengthmaximum_tokens_per_chunkrr ValueError)rrrs rrzESentenceTransformersTokenTextSplitter._initialize_chunk_configuration$s)- (B(B%  #$($A$AD !$4D !  4#@#@ @1$//1BC5567..2.C.C-D)+  S/ ! Acdfd }tjjjj|}t ||S)aSplits the input text into smaller components by splitting text on tokens. This method encodes the input text using a private `_encode` method, then strips the start and stop token IDs from the encoded result. It returns the processed segments as a list of strings. Args: text (str): The input text to be split. Returns: List[str]: A list of string components derived from the input text after encoding and processing. c,j|ddS)N)_encode)textrs r%encode_strip_start_and_stop_token_idsz_SentenceTransformersTokenTextSplitter.split_text..encode_strip_start_and_stop_token_idsFs<<%a+ +r$)rrdecodeencode)r*rr*strreturn list[int])r_chunk_overlaprrr,r )rr*r+rs` r split_textz0SentenceTransformersTokenTextSplitter.split_text7sE ,--!22>>((8  $CCr$c6t|j|S)ayCounts the number of tokens in the given text. This method encodes the input text using a private `_encode` method and calculates the total number of tokens in the encoded result. Args: text (str): The input text for which the token count is calculated. Returns: int: The number of tokens in the encoded text. )lenr))rr*s r count_tokensz2SentenceTransformersTokenTextSplitter.count_tokensRs4<<%&&r$l _max_length_equal_32_bit_integercj|jj||jd}td|S)Ndo_not_truncate) max_length truncationr1)rr-r7r)rr*&token_ids_with_start_and_end_token_idss rr)z-SentenceTransformersTokenTextSplitter._encodebs<151F1F <<(2G2 . K!GHHr$)2z'sentence-transformers/all-mpnet-base-v2N) rr rr/r Optional[int]rrr0None)rr>r0r?)r*r/r0z list[str])r*r/r0r r.) __name__ __module__ __qualname____doc__rrr3r6r7__annotations__r) __classcell__)rs@rr r sB C*. PPP( P  P  P2"#0" "&D6 '-2$c1Ir$r N) __future__rtypingrrrlangchain_text_splitters.baserrr r rr$rrIs$"&&WW`IL`Ir$