BTh VddlmZddlmZmZddlZddlmZeeee eejejfZ Gdde eZ ddejded e d ed eef d Zd e de d ejfdZ ddedeed e d ed eef dZd edeed ejfdZy))Enum)ListUnionN) SparseValuesceZdZdZdZdZdZy)DistanceStrategyzTEnumerator of the Distance strategies for calculating distances between vectors.EUCLIDEAN_DISTANCEMAX_INNER_PRODUCTCOSINEN)__name__ __module__ __qualname____doc__r r r o/var/www/catia.catastroantioquia-mas.com/valormas/lib/python3.12/site-packages/langchain_pinecone/_utilities.pyrr s.+ Frrquery_embeddingembedding_list lambda_multkreturnct|t|dkrgS|jdk(rtj|d}t ||d}t tj|}|g}tj||g}t|t|t|krtj }d} t ||} t|D]0\} } | |vr t| | } || zd|z | zz }||kDs-|}| } 2|j| tj||| gd}t|t|t|kr|S)z%Calculate maximal marginal relevance.raxis) minlenndimnp expand_dimscosine_similarityintargmaxarrayinf enumeratemaxappend)rrrrsimilarity_to_query most_similaridxsselected best_score idx_to_addsimilarity_to_selectedi query_scoreredundant_scoreequation_scores rmaximal_marginal_relevancer5s^ 1c.!"a' q ..qA+O^LQOryy!456L >Dxx 567H d)c!S01 1ffW  !2>8!L'(;< NA{Dy!"8";>?s,"A9DA"G>>8F?6 G>?G 7G>=G>cnt|t|dkrgSt||}tt j |}|g}||g}t|t|t|krtj }d} t|D]^\} } | |vr g} |D]&} t|| | gd}| j|(| r t| nd}|| zd|z |zz }||kDs[|}| } `|j| |j|| t|t|t|kr|S)aCalculate maximal marginal relevance for sparse vectors. Args: query_embedding: A sparse vector representation of the query embedding_list: A list of sparse vector representations to compare against lambda_mult: Controls the weight given to query similarity vs diversity k: The number of results to return Returns: A list of indices of the selected items in order of relevance rrr@r) rrsparse_cosine_similarityr#r r$r&r'r)r()rrrrr*r+r,r-r.r/r1r2redundant_scoresselected_embeddingsimr3r4s r!sparse_maximal_marginal_relevancerYRsn" 1c.!"a' 3?NSryy!456L >D|,-H d)c!S01 1ffW  ((;< NA{Dy " &. -".~a/@CUBVW!'',  -8Hc"23SOk)Q_,OO  *+  - 0 Jz23= d)c!S01 1@ Krc|stjgStjtd|jD}|dk(rtj t |Stj t |}t|j|jDcic]\}}|| }}}t|D]t\}}d} d} t|j|jD]\}}| ||zz } ||vs| |||zz } tj| } | dk(rd||<j| || zz ||<v|Scc}}w)zCalculate cosine similarity between sparse vectors without converting to dense. Args: X: A single sparse vector Y: A list of sparse vectors Returns: A numpy array of similarity scores c3&K|] }||z yw)Nr).0vals r z+sparse_cosine_similarity..s7ss7srr@) r r%sqrtsumvalueszerosrzipindicesr') r6r7x_norm similaritiesidxr]x_dictr1y_vec dot_producty_norms rrUrUs8 xx|WWS7ahh77 8F {xxA88CF#L(+199ahh'? @83c3h @F @aL>5 EMM5<<8 1HC cCi Ff}vc{S00  1  Q;!LO)Vf_=LO!>$ )As+ D?)g?)enumrtypingrrnumpyr pineconerfloatndarrayMatrixstrrlistr#r5r"rYrUrrrrvs! tDK $rzz"2BJJ> ?sD  ZZ   #Y DFrzz@  =!=&== =  #Y =@) )l1C) )r