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Defaults to 20. lambda_mult: Number between 0 and 1 that determines the degree of diversity among the results with 0 corresponding to maximum diversity and 1 to minimum diversity. Defaults to 0.5 filters (str, optional): Filtering expression. Defaults to None. Returns: List of Documents most similar to the query and score for each rjrrrs rM/hybrid_max_marginal_relevance_search_with_scorez;AzureSearch.hybrid_max_marginal_relevance_search_with_scores`8$$U+ %$%% ug /6 :@ @ RXXi%8kUV  rOcK|j|d{}|j|||fd|i|d{}t|tj|||d{S7M707w)rNrjrrrs rM0ahybrid_max_marginal_relevance_search_with_scorez6 > 8>>c |j|fd|i|}|dk(r!|D cgc]\}}} |||k\r||fc} }}S|dk(r!|D cgc]\}} } || |k\r|| fc} } }Sycc} }}wcc} } }w) Returns the most similar indexed documents to the query text. Args: query (str): The query text for which to find similar documents. k (int): The number of documents to return. Default is 4. score_type: Must either be "score" or "reranker_score". Defaulted to "score". filters: Filtering expression. 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Returns: List of Documents most similar to the query and score for each rrrrsemantic extractiverrr query_typer query_caption query_answerrr highlights@search.captionsrtcaptionsanswers page_contentr2 @search.score@search.reranker_scorer)rrrrrrrrrrr get_answersrrr*rrKrrrr loadsrrhfloat) rKrFr-rjrVrrysemantic_answerssemantic_answers_dictsemantic_answerrar.rGs rMrz8AzureSearch.semantic_hybrid_search_with_score_and_reranksA B$$++$$ 88D$4$4U$;2::NUUW()0!(,(H(H&%  $#..06B&(/ O',,-88: !/"5"5 6 `"U+ + TQ!'N!;! )F2' 9(=>!# ! /&8!JJvo'>?-3LLN"$(Aq#$(=#=!"1"!2$*::.@#A-3JJ7IB4,P()-&&*d28**=ORTQU2V()3&&0j !"&('<'@'@ & 9b 9 "(!$Jf_-.f567O( + + X ?"+ s AB&(/ O',,-88: !/"5"5 6 `!(U+ + TQ!'N!;! )F2' 9(=>!# ! /&8!JJvo'>?-3LLN"$(Aq#$(=#=!"1"!2$*::.@#A-3JJ7IB4,P()-&&*d28**=ORTQU2V()3&&0j !"&('<'@'@ & 9b 9 "(!$Jf_-.f567O( 91 $8+ "+ + + X sxIH"A5IH%I+H(,=I)H6+H4 /H+0H4 3A7H6*H.B"H6"I%I(I+H4 .H65Irtlangchain-indexc  L|||||f||d| } | j||fi| | SN)rr)r clsrr+rrrrrrrV azure_searchs rM from_textszAzureSearch.from_textssP !     "7     ui:6:rOc hK|||||f||d| } | j||fi| d{| S7wr)rrs rM afrom_textszAzureSearch.afrom_textss` !     "7   &l%%eYA&AAA Bs '202)rrrrc Kt|\}} | tdt| d} |d|||||| d|} | j||fi|d{| S7wNz0Cannot create AzureSearch from empty embeddings.r^)rrrrrrr)_peekrrr rr(r+rrrrrrVfirst_text_embeddingrrs rMafrom_embeddingszAzureSearch.afrom_embeddingss16o0F--  'OP P#&';A'>#?  "7-!(%=   +l**?IPPPP QsAAAAc t|\}} | tdt| d} |d|||||| d|} | j||fi|| Sr)rrrrrs rMfrom_embeddingszAzureSearch.from_embeddingss16o0F--  'OP P#&';A'>#?  "7-!(%=    $ ##OYI&IrOc |jd|j}||d<|jddxsg}|j|j t dd|i|d|iS)aReturn AzureSearchVectorStoreRetriever initialized from this VectorStore. Args: search_type (Optional[str]): Overrides the type of search that the Retriever should perform. Defaults to `self.search_type`. Can be "similarity", "hybrid", or "semantic_hybrid". search_kwargs (Optional[Dict]): Keyword arguments to pass to the search function. Can include things like: score_threshold: Minimum relevance threshold for similarity_score_threshold fetch_k: Amount of documents to pass to MMR algorithm (Default: 20) lambda_mult: Diversity of results returned by MMR; 1 for minimum diversity and 0 for maximum. (Default: 0.5) filter: Filter by document metadata Returns: AzureSearchVectorStoreRetriever: Retriever class for VectorStore. rtagsN vectorstorer)rhrrKextend_get_retriever_tagsAzureSearchVectorStoreRetriever)rKrVrrs rM as_retrieverzAzureSearch.as_retriever&sg&jj0@0@A +}zz&$'-2 D,,./.U4U6UPTUUrO)r?NNNNNNN)$rrXrrYrrXrzUnion[Callable, Embeddings]rrXrrYrOptional[List[SearchField]]rOptional[VectorSearch]rCOptional[Union[SemanticConfiguration, List[SemanticConfiguration]]]rOptional[List[ScoringProfile]]rrYrOptional[CorsOptions]rz Optional[int]rOptional[Dict[str, Any]]rrYrOptional[TokenCredential]rOptional[AsyncTokenCredential]rVr)r[None)r[zOptional[Embeddings])rrXr[ List[float]rT) rz Iterable[str]rOptional[List[dict]]rOptional[List[str]]rVrr[ List[str])r(!Iterable[Tuple[str, List[float]]]rrrrr[r)rrrVrr[rZ)ro) rFrXr-rHrrYrVrr[List[Document])rFrXr-rHrVrr[List[Tuple[Document, float]]) rFrXr-rHr[Optional[float]rVrr[r) rFrXr-rHrjrYrVrr[r)roN) rFrXr-rHrjrYrVrr[r)ro?)rFrXr-rHrrHrrrjrYrVrr[r)rFrXr-rHrVrr[r) r+rrrXr-rHrjrYrVrr[zSearchItemPaged[dict]) r+rrrXr-rHrjrYrVrr[zAsyncSearchItemPaged[dict])ror) rFrXr-rHrz"Literal['score', 'reranker_score']r[rrVrr[r) rFrXr-rHrjrYrVrr[z#List[Tuple[Document, float, float]])NrtrtNrN)rType[AzureSearch]rrr+rrrrrXrrXrrYrrXrrrVrr[r)rrr(rr+rrrrrXrrXrrXrrrVrr[r)rVrr[r)1r\r]r^__doc__rNrpropertyrrrrrrr9r;rHrPrUrZrbrgrrRrLrWrrrCrSrMrXrrrrrvr|rDrTrNrYrr classmethodrrrrrrrOrMrrs 0$59.204 ;?15.2{*"37EI/36:AE+{*"{*({* {* 8 {*  {*&3{*,{*.{*" {*9{*"/{*,{*"#0#{*$+C%{*& -'{*(4){**!?+{*,-{*z!2  A+/Q %) QQ(Q " Q  Q QB+/X %) XX(X " X  X XB+/;/ %) ;/:;/(;/ " ;/  ;/@+/7/ %) 7/:7/(7/ " 7/  7/r & &*   #    ('( K K # K36 K % K$ &*   #    ('( K K # K36 K % K"  ,0       )     &  $  ,0       )     &  $%3BF33 32?3RU3 3"$%3BF33 32?3RU3 3*!% .. . .  . & .4!% 55 5 5  5 & 58  "&                &  J % "&% %  %  %  % % %  &% N 3$%33 3033 3&!% .. . .  . & .2!% 55 5 5  5 & 56  ,0       )     &  $  ,0       )     &  $ # "&# #  #  #  # # #  &# P & "&& &  &  &  & & &  && \"& " " "   "  " "  " T"& " " "   "  " "  $" J$%66 6036 6($%66 6036 6,9@ % ,0 %% %7 % ) %% &%T9@ % ,0 %% %7 % ) %% &%P$%UBFUU U2?URUU ,Up$%VBFVV V2?VRUV ,Vp +/%' "/3+.2 (  #    -, 2 +/%' "/3+.2 (  #    -, 2 +/  &( "+.2 :(  # , : +/  &( "+.2 :(  # , <VrOrceZdZUdZded< dZded< dZded < iZd ed < d Zd ed<e dZ e de ddZ ddZ ddZy)rz-Retriever that uses `Azure Cognitive Search`.rrr?rXrrorHr-dict search_kwargs)r>similarity_score_thresholdr?hybrid_score_thresholdr@semantic_hybrid_score_thresholdzClassVar[Collection[str]]allowed_search_typesT)arbitrary_types_allowedbefore)modecjd|vr.|d}||jvrtd|d|j|S)zValidate search type.rrAz not allowed. Valid values are: )r r)rvaluesrs rMvalidate_search_typez4AzureSearchVectorStoreRetriever.validate_search_typecsS F " /K#":":: %k]2R//02 rOc i|j|}|jdk(r+|jj|fd|ji|}|S|jdk(r=|jj |fd|ji|Dcgc]\}}| }}}|S|jdk(r+|jj |fd|ji|}|S|jdk(r=|jj|fd|ji|Dcgc]\}}| }}}|S|jdk(r+|jj|fd|ji|}|S|jdk(r=|jj|fd|ji|Dcgc]\}}| }}}|Std|jd cc}}wcc}}wcc}}w Nr>r-r r?r r@r rArB) rrrrr-rbrCrrDrNr)rKrF run_managerrVparamsrGr,rps rM_get_relevant_documentsz7AzureSearchVectorStoreRetriever._get_relevant_documentsps- 2D&&1&1   | +14##11%L466LVLD8 7  != =Wd..VV!VV'-CD4 )   )14##11%L466LVLD& %  !9 9Sd..RR!VV'-CD"   !2 2:4##::5UDFFUfUD   !B BQd..PP!VV'-CD t/?/?.@ NO O3s F< G Gc*Ki|j|}|jdk(r3|jj|fd|ji|d{}|S|jdk(rG|jj |fd|ji|d{}|Dcgc]\}}| }}}|S|jdk(r3|jj |fd|ji|d{}|S|jdk(rG|jj|fd|ji|d{}|Dcgc]\}}| }}}|S|jdk(r3|jj|fd|ji|d{}|S|jdk(rE|jj|fd|ji|d{Dcgc]\}}| }}}|Std|jd 77ecc}}w77cc}}w77Jcc}}wwr) rrrrRr-rgrSrrTrYr) rKrFrrVrrGror,rps rM_aget_relevant_documentsz8AzureSearchVectorStoreRetriever._aget_relevant_documentssn2D&&1&1   | +8))88S$&&SFSSD< ;  != =Od&&OO!VV'-  '66FCC6D6. -   )8))88S$&&SFSSD* )  !9 9Kd&&KK!VV'-  '66FCC6D6   !2 2A))AA#)D   !B B%XD$4$4$W$W%!VV%'-%CD t/?/?.@ NO O;T7S7 sA HG2AHG5 H G8&AH&G>'AH(H) H2 H>AH>H ?AHH H H H5H8HHH H HN)rr r[r)rFrXrrrVrr[r)rFrXrrrVrr[r)r\r]r^r__annotations__rr-rr r model_configrrrrrrrOrMrrAs7?K-AsJ(M473 $L(# $ %%4% %  %N((9 (  (  (rOrc\|Dcgc]}t|t|df}}|Scc}wNr_result_to_documentrryrarGs rMrwrwsF     ' &) *  D  K s )ctK|2cgc3d{}t|t|df#76}}|Scc}wwrrr s rMr}r}sU$      ' &) *   D  K s$83., .3.3 8c,K|2cgc3d{}t|t|d|tf+7&6ncc}w}}ttt |\}}}t ||||} g} | D]#} | dk(r| S| j|| || f%| SwNr)r-rrrrmaprrrr# ryrrr-rarGr scoresvectors new_orderingretrjs rMrrs$      ' &) * ( )    D "%T3:!6Ivw.A;L )+C . 7  J IaL&),- . 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