3fiUdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZmZmZddlZddlmZddlmZddlmZddlmZdd lmZdd lmZdd lm Z m!Z!erdd l"m#Z#e jHd e jJdiZ&de'd<dddddddZ(dddZ)dZ*dZ+dddZ,e jHZ-d Z.d!e'd"<d#Z/d!e'd$<d%Z0d!e'd&<d'Z1d!e'd(<d)Z2d*e'd+<ed,d-d.d/d01Gd2d3eZ3y)4zSAP HANA Cloud Vector Engine) annotationsN) TYPE_CHECKINGAnyCallableDictIterableListOptionalPatternTuple) deprecated)Document) Embeddings)run_in_executor) VectorStore)Self)DistanceStrategymaximal_marginal_relevance)dbapi)COSINE_SIMILARITYDESC) L2DISTANCEASCdictHANA_DISTANCE_FUNCTION=z<>z>=)z$eqz$nez$ltz$ltez$gtz$gteINzNOT IN)z$inz$ninz$betweenz$likeANDOR)z$andz$or EMBEDDINGSstrdefault_table_nameVEC_TEXTdefault_content_columnVEC_METAdefault_metadata_column VEC_VECTORdefault_vector_columnintdefault_vector_column_lengthz0.3.23z1.0zThis class is deprecated and will be removed in a future version. Please use HanaDB from the langchain_hana package instead. 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N)specific_metadata_columnsc  6tjjd tdd} tj D] } | |usd} | st dj|||_||_ ||_ tj||_ tj||_tj||_tj||_tj#||_tj'| xsg|_|j+|jsd|jd|jd|jd|j d } |j$d vr| d z } n| d |j$d z } |jj-} | j/| | j1|j3|j|jddg|j3|j|jddg|j3|j|j dg|j$|j(D]}|j3|j| y# j1wxYw)NhdbclizTCould not import hdbcli python package. Please install it with `pip install hdbcli`.FT!Unsupported distance_strategy: {}zCREATE TABLE "z"("z " NCLOB, "z" REAL_VECTOR )r+r);(z));NCLOBNVARCHAR REAL_VECTOR) importlibutil find_spec ImportErrorrkeys ValueErrorformat connection embeddingdistance_strategyr4_sanitize_name table_namecontent_columnmetadata_column vector_column _sanitize_intvector_column_length#_sanitize_specific_metadata_columnsr5 _table_existscursorexecuteclose _check_column)selfrErFrGrIrJrKrLrNr5valid_distancekeysql_strcur column_names i/var/www/auto_recruiter/arenv/lib/python3.12/site-packages/langchain_community/vectorstores/hanavector.py__init__zHanaDB.__init__asq >> # #H - 5?  )..0 &C''!% &3::;LM %"!2 // ;$33NC%44_E#22=A$*$8$89M$N!)/)S)S % +* & !!$//2  12''()(()*&&'~7  ((G34Qt889== oo,,. G$  4??D,?,?':AVW 4??D,@,@7JBWX  OO    O  % %   99 =K   t < = s +JJc&d} |jj}|j|||jr-|j }|dddk(r |j y|j y#j wxYw)NzUSELECT COUNT(*) FROM SYS.TABLES WHERE SCHEMA_NAME = CURRENT_SCHEMA AND TABLE_NAME = ?rTF)rErQrRhas_result_setfetchallrS)rUrIrXrYrowss r[rPzHanaDB._table_existss{ "  //((*C KK* .!!#||~71:? IIKCIIK IIKs AA>>Bcd} |jj}|j|||f|jr||j }t |dk(rt d|d|r!|dd|vrt d|d|dd|9|dkDr4|dd|k7r)t d|d|ddd|t d|d|jy#jwxYw) Nz~SELECT DATA_TYPE_NAME, LENGTH FROM SYS.TABLE_COLUMNS WHERE SCHEMA_NAME = CURRENT_SCHEMA AND TABLE_NAME = ? 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Returns: List of tuples (containing a Document and a score) that are most similar to the query rFrr)rF embed_query&similarity_search_with_score_by_vector)rUrrrrFs r[rz#HanaDB.similarity_search_with_scores7NN..u5 ::1V;  rkcg}tj|}tj|}t|jd}ddj t t|zdz}d|d|jd|jd|jd |d |jd |jd }d t|jd}|j|\} } |ft| z} || z}||z} |jj} | j!|| | j#rn| j%} | D]Y}t'j(|d}t+|d|}tj-|d}|j/||d|f[| j1|S# j1wxYw)aReturn docs most similar to the given embedding. Args: query: Text to look up documents similar to. k: Number of Documents to return. Defaults to 4. filter: A dictionary of metadata fields and values to filter by. Defaults to None. Returns: List of Documents most similar to the query and score and the document's embedding vector for each rrrrz SELECT TOP z "z", "z", TO_NVARCHAR("z"), z("z#", TO_REAL_VECTOR (?)) AS CS FROM "rz order by CS r^) page_contentr|)r4rMrxrrGrrr#rJrKrLrI_create_where_by_filtertuplerErQrRr_r`rloadsr_parse_float_array_from_stringrrS)rUrFrrresultrembedding_as_strrX order_str where_str query_tuple query_paramsrYrarowjsr result_vectors r[1similarity_search_with_score_and_vector_by_vectorz8HanaDB.similarity_search_with_score_and_vector_by_vectors   #// : 3D4J4JKAN#c9*=!>>D!$%%&'&&'("0012#$Bt'9'9&:;__%Q  ( $$:4;Q;Q$RST$U#VW !%!=!=f!E ;(*U;-?? I%I% //((*C KK .!!#||~@CCF+B"ADC$*$I$I#a&$QMMM3A ">? @ IIK  IIKs 9B*F55Gcd|j|||}|Dcgc] }|d|dfc}Scc}w)aReturn docs most similar to the given embedding. Args: query: Text to look up documents similar to. k: Number of Documents to return. Defaults to 4. filter: A dictionary of metadata fields and values to filter by. Defaults to None. 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AND ?LIKErzUnsupported value for z: zUnsupported operator: zUnsupported filter data-type: z "rz JSON_VALUE(z, '$.z'))rrBLOGICAL_OPERATORS_TO_SQLrrvboolrr,r#rnextiterCOMPARISONS_TO_SQLrwrBETWEEN_OPERATOR LIKE_OPERATORIN_OPERATORS_TO_SQLrrcrCrr5rK)rUrrrrrW filter_valuelogical_operatorlogical_operandsjlogical_operandwhere_str_logicalquery_tuple_logicaloperator sql_param special_op special_val between_from between_to list_entryselectors r[rzHanaDB._process_filter_objectWsj  #FKKM2Z B3%c{ 6(I22'?'D$'3$.78H.I;*?6%1-=,>a)@@I!77H-/!S+<%09CI09CI + 2 2: >?#-"8 "[M R#)+A*)NOO$8l9K8LM d<<<QK&t';';&ST T!%!=!=f!E ;!$//!2"YK@ //((*C KK - IIK IIKs ,A??BcPKtd|j||d{S7w)zDelete by vector ID or other criteria. Args: ids: List of ids to delete. Returns: Optional[bool]: True if deletion is successful, False otherwise, None if not implemented. N)rr)rr)rUrrs r[adeletezHanaDB.adeletes#%T4;;COOOOs &$&cd|jj|}|j|||||S)aReturn docs selected using the maximal marginal relevance. 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Defaults to 0.5. filter: Filter on metadata properties, e.g. { "str_property": "foo", "int_property": 123 } Returns: List of Documents selected by maximal marginal relevance. )rFrfetch_k lambda_multr)rFr'max_marginal_relevance_search_by_vector)rUrrrrrrFs r[max_marginal_relevance_searchz$HanaDB.max_marginal_relevance_searchs?:NN..u5 ;;# <  rkcf|dd}|jdDcgc] }t|c}Scc}w)Nr^r+r)splitrw)array_as_stringarray_wo_bracketsxs r[rz%HanaDB._parse_float_array_from_string s2+Ab1"3"9"9#">?Qa???s.c|j|||}|Dcgc]}|d }}ttj||||} | D cgc] } || d c} Scc}wcc} w)Nrr)rrr)rrnparray) rUrFrrrrrrrjmmr_doc_indexesrs r[rz.HanaDB.max_marginal_relevance_search_by_vectors~MM76N 9EEk!nE E4 HHY  -<F=$F=F=, F=  F=  F=F=F="F=$7F=P(,0'+ %%%) % % %  %N77## ",,F!GwG #,    * )-#'$( Q Q'Q! Q " Q  Ql+/26 @@(@0 @  @  @D +/'+.G,462$@#:>###( # % # , #####"#$7# ##L@D33 3.<3 3(@D    .< % *LP-$-),-:H- 2-`LPR$R),R:HR %R(LP3$3),3:H3 3&&`&FIM&7E BIM P& P7E P  P" !% $ $  $  $  $  $  $ L@ !% == = =  =  = =*           "rkr4)4r* __future__rimportlib.utilr>rrntypingrrrrrr r r r numpyr langchain_core._apir langchain_core.documentsrlangchain_core.embeddingsrlangchain_core.runnables.configrlangchain_core.vectorstoresrtyping_extensionsr&langchain_community.vectorstores.utilsrrr7rrrrr/rrrrrr+r$r&r(r*r-r4rrkr[r<s/""    *-0;3" :'')>            $)$7-33&C&(()))s)$&c&    5  x [x  x rk