uPjg dZddlZddlZddlmZddlmZdedeefdZ de defd Z dd ed ee d e d e dee f dZ y)ua Pure Python BM25 (Okapi BM25) relevance scorer. No external dependencies — uses only stdlib. N)Counter)FinaltextreturncJtjd|jS)z4Split text into lowercase tokens on word boundaries.z [a-z0-9_]+)refindalllower)rs e/home/oem/CyberBrain26-unified/.venv/lib/python3.12/site-packages/litellm/compression/scoring/bm25.py _tokenizer s ::mTZZ\ 22messagecp|jdd}t|tr|St|trg}|D]j}t|tr6|jddk(r"|j |jddIt|tsZ|j |ldj |Sy)z)Extract text content from a message dict.contenttyper )get isinstancestrlistdictappendjoin)rrpartsparts r _extract_contentrs[[B/G'3'4  #D$%$((6*:f*D TXXfb12D#& T"  # xx r querymessagesk1bcht|}|sdgt|zSg}|D]%}|jtt|'t|}|dk(rgS|Dcgc] }t|} }|dkDrt | |z nd} i} |D],}t |} | D]} | j | ddz| | <.i}t |D];} | j | d}tj||z dz|dzz dz|| <=dtdtdtfd }g}t|D]\}}|s|jdt|}| |}d}|D]@} | |vr|| |}|dk(r||dzz}||d|z ||z| z zzz}||| |z|z z }B|j||Scc}w) a Score each message's relevance to the query using BM25 (Okapi BM25). Parameters: query: The reference text to score against (typically the last user message). messages: List of message dicts with "content" fields. k1: Term frequency saturation parameter. b: Length normalization parameter. Returns: List of float scores, one per message. Higher = more relevant. grg?g? query_term tf_countsrc|jd}|r|Stdkrytfd|jDS)z=Sum TF across all doc tokens that are prefixed by query_term.rc3XK|]!\}}|k7s |js|#yw)N) startswith).0tokencountr$s r z:bm25_score_messages.._expand_tf..^s+w\UE%:BUZ_ZjZjkuZv5ws ***)rlensumitems)r$r%exacts` r _expand_tfz'bm25_score_messages.._expand_tfWsB }}Z3 L z?Q wY__->wwwr ) r r.rrr/setrmathlogrrint enumerate)rrr r! query_terms doc_tokensmsgndt doc_lengthsavgdldfseentermidfterm_dfr2scoresir%dlscoretf numerator denominators r bm25_score_messagesrK"s($#5)K us8}$$*,J<)$4S$9:;<:AAv -77b#b'7K7+,q53{#a'cE!#B+2w +DvvdA*BtH ++ $&CK J&&q/HHa'kC/GcMBSHID Jxsxwx3x"$F:&2 MM#  BK ^ 9D3D),BQwb1f IrQUQVe^%;<rQs  3C3DI3 d s & U U4jU U U  %[ Ur