NgMddlmZddlZddlZddlZddlmZmZmZm Z m Z m Z m Z m Z ddlZddlmZddlmZddlmZerddlZdZGdd eZdS) ) annotationsN) TYPE_CHECKINGAnyDictIterableListOptionalTupleType)Document) Embeddings) VectorStorec2eZdZdZdZdZdeeefddZ e ddeeefd?dZ d d!d d"d#d d"gfd@d'Z dAdBd(Z dCdDd*ZdEd+Ze deeefdFd,ZefdGd/ZefdHd1ZefdId3Z dJdId5Z dCdKd9Z dCdLd;ZdS)MVearchlangchain_vearchcluster_client_dbNembedding_functionr path_or_url Optional[str] table_namestrdb_nameflagintkwargsrreturnNonec  |rddl}nddl}n#t$rtdwxYw|r|td|sH|j}|dz }|t t jddz }||_ ||_ | ||_n|(tj dd } n|} tj| stj| tj| d } tj| stj| |j| | |_| |_|sH|j}|dz }|t t jddz }||_||_||_dS) zSInitialize vearch vector store flag 1 for cluster,0 for standalone rNzhCould not import suitable python package. Please install it with `pip install vearch or vearch_cluster`.zPlease input url of cluster_-\/log)vearch_clustervearch ImportError ValueError_DEFAULT_CLUSTER_DB_NAMEruuiduuid4split using_db_nameurl VearchClusterosgetcwdreplacepathisdirmakedirsjoinEngineusing_metapath_DEFAULT_TABLE_NAMEusing_table_nameembedding_funcr) selfrrrrrrr'r( metadata_pathlog_paths c/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/vectorstores/vearch.py__init__zVearch.__init__s  %%%%%    Q    0" !>??? <733tz||,,22377;;!(D "DH(66{CCDKK" " 3 3D# > > + 7==// + M***w||M599H7==** & H%%%'&- x@@DK"/D  ;1J # J #djll++11#66r: :J *0 s (Optional[Embeddings]c|jSN)r=r>s rA embeddingszVearch.embeddingsNs ""cls Type[Vearch] documentsList[Document] embeddingc \d|D}d|D} |jd||| ||||d|S)Return Vearch VectorStorecg|] }|j S) page_content.0ds rA z)Vearch.from_documents.._s333A333rHcg|] }|j SrQ)metadatarSs rArVz)Vearch.from_documents..`s333AQZ333rH)textsrM metadatasrrrrrQ) from_texts) rIrKrMrrrrrrYrZs rAfrom_documentszVearch.from_documentsRsi4333333333 s~  #!      rHrY List[str]rZOptional[List[dict]]c V|||||||} | ||| S)rO)rrMrrrr)rYrZ) add_texts) rIrYrMrZrrrrr vearch_dbs rAr[zVearch.from_textsmsMC(#!     %9===rHtextfieldtyperXdim field_list List[dict]c tjjtjjddddddd}fd|D}tjd tjjd |d d d did}|j||j||}|S)z Create VectorStore Table Args: dim:dimension of vector fields_list: the field you want to store Return: code,0 for success,1 for failed )rri'IVFPQi ) ncentroids nsubvector) index_sizeretrieval_typeretrieval_paramc^g|])}tj|d|d*Srd)r(GammaFieldInfo)rTfi type_dicts rArVz(Vearch._create_table..sC     !"W+yF/D E E   rHtext_embeddingT MemoryOnly cache_sizeF)namerfis_index dimensionmodel_id store_type store_param has_source)rzfields vector_field)r(dataTypeINTSTRINGGammaVectorInfoVECTOR create_tabler<)r>rgrh engine_inforr response_coderus @rA _create_tablezVearch._create_tables"#O/8NOO %.2"EE          -!'#%u-     00 &% 1  rHc |jdddddddidddiddid d |d d d d}|j|j|}|S)z Create VectorStore space Args: dim:dimension of vector Return: code,0 failed for ,1 for success rgammaFLAT metric_typeL2)rzrorprqrfstringvectorTrx)rfindexr|r~)rcrXrv)rz partition_num replica_numengine properties)r<r( create_spacer/)r>rg space_configrs rA _create_spacezVearch._create_spaces)"(!4$ HH%!!$". ##    6 001C\RR rH Iterable[str]c Vd}|j'|jt|}|td|jr|j}|j|vr0|j|j}|std|j |j}|j |vr9| t|d}|stdg} | |t|||D]\} } } i} | | d<| d| d<tj| }d |tj|z i| d <|j|j|j | }|d d kr| |d |j|j|j | }| |d nt*j|j|j dz}t*j|s;t|d}||}|rtd||g}t|||D]f\} } } i}| |d<| d|d<tj| }|tj|z |d <||g|j|} d}t| t|kr@t9jd|dkrn%|dz }t| t|k@|j| S)z^ Returns: List of ids from adding the texts into the vectorstore. Nzembeddings is Nonezcreate db failed!!!rzcreate space failed!!!rcsourcerXfeaturervstatus_id.schemazcreate table failed!!!g?r)r=embed_documentslistr*rr(list_dbsr/ create_db list_spacesr<rlenzipnparraylinalgnormtolist insert_oneappendr2r5r8r:existsraddtimesleepdump)r>rYrZrrGdbs_listcreate_db_code space_listcreate_space_codedocidrcrXembedprofilesembed_np insert_res retry_insert table_pathrgr doc_items profiles_vt_times rAr`zVearch.add_textss   *,<>>E%)*?-0 :-N-N!!)D(E/1H'+HV$+3H+=HZ(!xH!Hry~~h/G/G$G#O#O#Q#Q2H-."&!7!7*D,A8""J"(+s22 Z%6777 '+{'='= .0Ex((  \%%8999 #T%:Y%FJ7>>*-- ?*Q-(( $ 2 23 7 7  ?$%=>>>%)*? -0 :-N-N11)D(E13J)-Jv&-5h-?Jz*!xH3;binnX>V>V3VJ/0$$Z0000  22%jjC OO33JsOOOzzaKF %jjC OO33    """ rHc8|jdS)z: load vearch engine for standalone vearch N)r(loadrFs rA_loadz Vearch._load*s rHc 4|std|stdtj||dz}tj|std||||||}||S)zLoad the local specified table of standalone vearch. Returns: Success or failure of loading the local specified table zNo metadata path!!!zNo table name!!!rz$vearch vectorbase table not exist!!!)rrrrr)r*r2r5r8rr) rIrMrrrrrrras rA load_localzVearch.load_local0s 4233 3 1/00 0W\\+zI/EFF w~~j)) ECDD DC(#!     rHquerykc |jtd|j|}|||}|S)z5 Return docs most similar to query. Nembedding_func is None!!!)r=r* embed_querysimilarity_search_by_vector)r>rrrrGdocss rAsimilarity_searchzVearch.similarity_searchPsL   &899 9(44U;; // A>> rH List[float]c tj|}|jrudd|tj|z dgi|ddgd}|j|j|j |}|dd}nWd|tj|z dggdd d d |d }|j|}|d d}g}|D]_} d} i} |jr| d} | D]#} | dkr | | } | dkr | | | d<#$| t| | `|S)The most k similar documents and scores of the specified query. Args: embeddings: embedding vector of the query. k: The k most similar documents to the text query. min_score: the score of similar documents to the text query Returns: The k most similar documents to the specified text query. 0 is dissimilar, 1 is the most similar. sumrvrerrcrXrsizerhitsr InnerProductrnproberris_brute_searchrqtopnr result_itemsrw_sourcerrRrX) rrrrrrr(searchr/r<rr ) r>rMrrr query_data query_resultresritemcontent meta_dataitem_keys rArz"Vearch.similarity_search_by_vector`s## 9 2%5(- u0E0E(E'M'M'O'O!:.  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Args: ids: The ids of the embedding vectors. **kwargs: Other keyword arguments that subclasses might use. Returns: Optional[bool]: True if deletion is successful. False otherwise, None if not implemented. Nrc3"K|] }|dkV dS)rNrQ)rTis rA z Vearch.delete.. s&**Q!q&******rH) __len__rr(deleter/r<del_docrall)r>rrretrrs rArz Vearch.deletes# ;#++--1,,J  Cy /k(();T=RTWXXk))#.. NN3    **'***** rHDict[str, Document]c Ji}||dkr|S|jrdd|ii}|j|j|j|}|D]c}|ddur d}i}|dD]/} | d kr|d| }| d kr|d| |d </0t || ||d <dnj|D]g} |j| }|ikr#d}i}|D]#} | d kr || }| d kr || |d <#$t || ||d <h|S)zReturn docs according ids. Args: ids: The ids of the embedding vectors. Returns: Documents which satisfy the input conditions. NrrrfoundFrwrrcrXrrr)rrr( mget_by_idsr/r<r get_doc_by_id) r>rrrr docs_detailrecordr meta_inforeids rAgetz Vearch.get s(* ;#++--1,,N 9$ !E3<0J+11"D$9:K&  '?e++ #I.!!E"("3E": *,,.4Y.?.F (+ -*2!(9***u &&    "k77;; "$$ (!!E"-e"4 *,,.9%.@ (+ -/7!(9/// E*++rH)rr rrrrrrrrrrrr)rrC)rIrJrKrLrMr rrrrrrrrrrrr)rIrJrYr]rMr rZr^rrrrrrrrrrrr)rgrrhrirr)rb)rgrrrrE)rYrrZr^rrrr])rr)rMr rrrrrrrrrrrr)rrrrrrrrL)rMrrrrrrrL)rrrrrrrr)r)rrrrrr)rrrrrr)__name__ __module__ __qualname__r;r+_DEFAULT_VERSIONrBpropertyrG classmethodr\r[rrr`rr DEFAULT_TOPNrrrrrr rQrHrArrs\,2 &*-/$ 44444l###X# &*-/$    [ 4 +/%)-/$[4e , , % 0 0" +++++^(((((Z+/KKKKKZ &*-/$ [D&>>>>>FFFFFFVEEEEE$(<$(5555555rHr) __future__rr2rr,typingrrrrrr r r numpyrlangchain_core.documentsr langchain_core.embeddingsr langchain_core.vectorstoresrr(rrrQrHrArs"""""" RRRRRRRRRRRRRRRRRRRR------000000333333MMM nnnnn[nnnnnrH