dhJ5SSKJr SSKrSSKrSSKJrJrJrJrJ r J r J r SSK J r SSKJr SSKJr SSKJr SrS r"S S \5rg) ) annotationsN)AnyDictIterableListOptionalTupleType)Document) Embeddings)get_from_dict_or_env) VectorStoreilangchain_pg_embeddingc\rSrSrSr\\SS4SSjjrSSjr\ SSj5r \ SS\\S4SSjj5r SS jr SSS jjrSSS jjrSSS jjrSS S jjrSS!Sjjr\ S\\SS4S"Sjj5r\ S\\SS4S#Sjj5r\ \\S4S$Sjj5r\ S%Sj5r\ \\SS4S&Sjj5r\ S'Sj5rSrg)(Hologresa`Hologres API` vector store. - `connection_string` is a hologres connection string. - `embedding_function` any embedding function implementing `langchain.embeddings.base.Embeddings` interface. - `ndims` is the number of dimensions of the embedding output. - `table_name` is the name of the table to store embeddings and data. (default: langchain_pg_embedding) - NOTE: The table will be created when initializing the store (if not exists) So, make sure the user has the right permissions to create tables. - `pre_delete_table` if True, will delete the table if it exists. (default: False) - Useful for testing. FNcXlX0lX@lX lXPlU=(d [ R "[5UlUR5 gN) connection_stringndims table_nameembedding_functionpre_delete_tablelogging getLogger__name__logger __post_init__)selfrrrrrrs a/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/vectorstores/hologres.py__init__Hologres.__init__ sC"3 $"4 0; 1 1( ;  cSSKJn U"URURURSS0UR S9Ulg)z Initialize the store. r)HologresVectordocumenttext)rr table_schemarN)hologres_vectorr%rrrrstorage)rr%s r rHologres.__post_init__1s; 3%  " "**$f-!22   r#cUR$r)r)rs r embeddingsHologres.embeddingsAs&&&r#c   Uc-UV s/sH!n [[R"55PM# nn U(dUV s/sHn 0PM nn URU 5n U"U UUUUS9n U R"SXXES.U D6 U $s sn fs sn f)N)rrrrr)textsr- metadatasids)struuiduuid4get_connection_stringadd_embeddings) clsr0r-rr1r2rrrkwargs_rstores r __fromHologres.__fromEs ;.34e3tzz|$eC4%*+UUI+55f=/1!-    ) PV  '5,s 'A; Bc UVs/sHnSU0PM nnURRX$X75 gs snf![a%nURR U5 SnAgSnAff=f)zAdd embeddings to the vectorstore. Args: texts: Iterable of strings to add to the vectorstore. embeddings: List of list of embedding vectors. metadatas: List of metadatas associated with the texts. kwargs: vectorstore specific parameters r&N)r*upsert_vectors Exceptionr exception) rr0r-r1r2r:t schema_datases r r8Hologres.add_embeddingshs]  %5:;UZOUL; LL ' '  Q< % KK ! !! $ $ %s!7 277 A&A!!A&c Uc-UVs/sH!n[[R"55PM# nnURR [ U55nU(dUVs/sHn0PM nnUR "XX#40UD6 U$s snfs snf)a:Run more texts through the embeddings and add to the vectorstore. Args: texts: Iterable of strings to add to the vectorstore. metadatas: Optional list of metadatas associated with the texts. kwargs: vectorstore specific parameters Returns: List of ids from adding the texts into the vectorstore. )r4r5r6rembed_documentslistr8)rr0r1r2r:r;r-s r add_textsHologres.add_texts~s}" ;.34e3tzz|$eC4,,<"++77U7C //0  r#c ZURXUS9nUVVs/sHupgUPM snn$s snnf)a3Return docs most similar to embedding vector. Args: embedding: Embedding to look up documents similar to. k: Number of Documents to return. Defaults to 4. filter (Optional[Dict[str, str]]): Filter by metadata. Defaults to None. Returns: List of Documents most similar to the query vector. rM)&similarity_search_with_score_by_vector)rrNrOrPr:docs_and_scoresdocr;s r rR$Hologres.similarity_search_by_vectors;"EEVF #22//222s 'c\URRU5nURXBUS9nU$)a*Return docs most similar to query. Args: query: Text to look up documents similar to. k: Number of Documents to return. Defaults to 4. filter (Optional[Dict[str, str]]): Filter by metadata. Defaults to None. Returns: List of Documents most similar to the query and score for each rM)rrQrW)rrSrOrPrNdocss r similarity_search_with_score%Hologres.similarity_search_with_scores; ++77> ::V;  r#cURRXS/US9nUVs/sHn[USUSS9US4PM nnU$s snf)Nr&)rOselect_columnsmetadata_filtersmetadata) page_contentrbdistance)r*searchr )rrNrOrPresultsresultr\s r rW/Hologres.similarity_search_with_score_by_vectors| )- (;(; J<&)<) "  " !' !3#J/z"  "     sAc lUR[U55n UR"UU U4UUUUUS.UD6$)a Return VectorStore initialized from texts and embeddings. Hologres connection string is required "Either pass it as a parameter or set the HOLOGRES_CONNECTION_STRING environment variable. Create the connection string by calling HologresVector.connection_string_from_db_params r1r2rrr)rHrI_Hologres__from) r9r0rNr1rrr2rr:r-s r from_textsHologres.from_textssR(..tE{; zz      !-    r#c UV s/sHoSPM n n UV s/sHoSPM n n UR"U U U4UUUUUS.UD6$s sn fs sn f)aConstruct Hologres wrapper from raw documents and pre- generated embeddings. Return VectorStore initialized from documents and embeddings. Hologres connection string is required "Either pass it as a parameter or set the HOLOGRES_CONNECTION_STRING environment variable. Create the connection string by calling HologresVector.connection_string_from_db_params Example: .. code-block:: python from langchain_community.vectorstores import Hologres from langchain_community.embeddings import OpenAIEmbeddings embeddings = OpenAIEmbeddings() text_embeddings = embeddings.embed_documents(texts) text_embedding_pairs = list(zip(texts, text_embeddings)) faiss = Hologres.from_embeddings(text_embedding_pairs, embeddings) rrj)rk) r9text_embeddingsrNr1rrr2rr:rCr0r-s r from_embeddingsHologres.from_embeddingsss@ //!1/$34OqdO 4zz      !-    04s A Ac <URU5nU"UUUUUS9nU$)z Get instance of an existing Hologres store.This method will return the instance of the store without inserting any new embeddings )rrrrr)r7)r9rNrrrr:rr<s r from_existing_indexHologres.from_existing_indexFs5 55f=/!(-   r#c@[USSS9nU(d [S5eU$)NrHOLOGRES_CONNECTION_STRING)datakeyenv_keyzHologres connection string is requiredEither pass it as a parameteror set the HOLOGRES_CONNECTION_STRING environment variable.Create the connection string by callingHologresVector.connection_string_from_db_params)r ValueError)r9r:rs r r7Hologres.get_connection_stringas6!5#0"  !B ! r#c UVs/sHoRPM n nUVs/sHoRPM n nURU5n XS'UR"SU UUU UUUS.UD6$s snfs snf)a Return VectorStore initialized from documents and embeddings. Hologres connection string is required "Either pass it as a parameter or set the HOLOGRES_CONNECTION_STRING environment variable. Create the connection string by calling HologresVector.connection_string_from_db_params r)r0pre_delete_collectionrNr1r2rrr3)rcrbr7rl) r9 documentsrNrrr2r~r:dr0r1rs r from_documentsHologres.from_documentsts(*33A3)23AZZ 355f=&7"#~~  "7!    43s A$A)c $SUSUSUSUSU3 $)z2Return connection string from database parameters.zdbname=z user=z password=z host=z port=r3)r9hostportdatabaseuserpasswords r connection_string_from_db_params)Hologres.connection_string_from_db_paramss-hZvdV:hZvdV6RVQW X r#)rrrrrr*r)rr4rr rintrr4rboolrzOptional[logging.Logger]returnNone)rr)rr )r0 List[str]r-List[List[float]]rr r1Optional[List[dict]]r2Optional[List[str]]rrrr4rrr:rrr) r0 Iterable[str]r-rr1z List[dict]r2rr:rrr)NN) r0rr1rr2rr:rrr)N) rSr4rOrrPOptional[dict]r:rrList[Document]) rN List[float]rOrrPrr:rrr)rSr4rOrrPrrList[Tuple[Document, float]])rNrrOrrPrrr)r9Type[Hologres]r0rrNr r1rrrrr4r2rrrr:rrr)rpzList[Tuple[str, List[float]]]rNr r1rrrrr4r2rrrr:rrr)r9rrNr rrrr4rrr:rrr)r:zDict[str, Any]rr4)r9rrrrNr rrrr4r2rr~rr:rrr) rr4rrrr4rr4rr4rr4)r __module__ __qualname____firstlineno____doc__ADA_TOKEN_COUNT_LANGCHAIN_DEFAULT_TABLE_NAMEr!rpropertyr- classmethodrkr8rJrTrRr]rWrlrqrtr7rr__static_attributes__r3r#r rrs &%7!&+/'     ) "  '' +/#'$7!&  & '  (  !        D%%&% %  %  % %2+/#' (!     @!%           6!% 33 3 3  3  32!%    & 2!%    & , +/$7#'!&    (      !      B +/$7#'!&, 6, , ( ,  ,  , !, , ,  , , \%7!&        4!!$ %7#'&+" " !" "  "  " ! "  $" "  " " H                 r#r) __future__rrr5typingrrrrrr r langchain_core.documentsr langchain_core.embeddingsr langchain_core.utilsr langchain_core.vectorstoresrrrrr3r#r rs<" CCC-053 8U {U r#