tjJ5ddlmZddlZddlZddlmZmZmZmZm Z m Z m Z ddl m Z ddlmZddlmZddlmZdZd ZGd d eZdS) ) annotationsN)AnyDictIterableListOptionalTupleTypeDocument) Embeddings)get_from_dict_or_env) VectorStoreilangchain_pg_embeddingcpeZdZdZeeddfdBdZdCdZedDdZ e ddeedfdEdZ dFd!Z dGdHd"Z dIdJd)Z dIdKd,Z dIdLd.Z dIdMd/Ze deeddfdNd2Ze deeddfdOd5Ze eedfdPd6Ze dQd8Ze eeddfdRd;Ze dSdAZdS)THologresa`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. FNconnection_stringstrembedding_functionr ndimsint table_namepre_delete_tableboolloggerOptional[logging.Logger]returnNonec||_||_||_||_||_|pt jt|_| dSN) rrrrrlogging getLogger__name__r __post_init__)selfrrrrrrs g/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/vectorstores/hologres.py__init__zHologres.__init__ sY"3 $"4 0; 1( ; ;  chddlm}||j|j|jddi|j|_dS)z' Initialize the store. r)HologresVectordocumenttext)rr table_schemarN)hologres_vectorr*rrrrstorage)r%r*s r&r$zHologres.__post_init__1sP 322222%~  "*$f-!2     r(c|jSr )r)r%s r& embeddingszHologres.embeddingsAs &&r(texts List[str]r1List[List[float]] metadatasOptional[List[dict]]idsOptional[List[str]]kwargsrc  | d|D}|s d|D}|| } || ||||} | jd||||d| | S)NcNg|]"}ttj#Sruuiduuid4.0_s r& z#Hologres.__from..S&4443tz||$$444r(cg|]}iSr<r<r@s r&rCz#Hologres.__from..V++++++r()rrrrr)r2r1r5r7r<)get_connection_stringadd_embeddings) clsr2r1rr5r7rrrr9rstores r&__fromzHologres.__fromEs ;44e444C ,++U+++I55f==/1!-      J)  PV    r( Iterable[str] List[dict]c  d|D}|j||||dS#t$r%}|j|Yd}~dSd}~wwxYw)a/Add 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 cg|]}d|iS)r+r<rAts r&rCz+Hologres.add_embeddings..ys;;;ZO;;;r(N)r/upsert_vectors Exceptionr exception)r%r2r1r5r7r9 schema_datases r&rHzHologres.add_embeddingshs  %;;U;;;L L ' ' CL Q Q Q Q Q % % % K ! !! $ $ $ $ $ $ $ $ $ %s)- AAAc | d|D}|jt|}|s d|D}|j||||fi||S)arRun 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. NcNg|]"}ttj#Sr<r=r@s r&rCz&Hologres.add_texts..rDr(cg|]}iSr<r<r@s r&rCz&Hologres.add_texts..rFr()rembed_documentslistrH)r%r2r5r7r9r1s r& add_textszHologres.add_texts~sy" ;44e444C,<.s222Q222r()&similarity_search_with_score_by_vector)r%rer_r`r9docs_and_scoress r&rgz$Hologres.similarity_search_by_vectors<"EE1VF  32/2222r(List[Tuple[Document, float]]cj|j|}||||}|S)abReturn 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 rd)rrfrm)r%r^r_r`redocss r&similarity_search_with_scorez%Hologres.similarity_search_with_scoresB +77>> ::1V;   r(c\|j||dg|}d|D}|S)Nr+)r_select_columnsmetadata_filterscXg|]'}t|d|d|df(S)r+metadata) page_contentrwdistancer )rAresults r&rCzCHologres.similarity_search_with_score_by_vector..sX     !' !3#J/z"      r()r/search)r%rer_r`resultsrqs r&rmz/Hologres.similarity_search_with_score_by_vectorsR )- (;(; J<&)<) )    "     r(rIType[Hologres]c r|t|} |j|| |f|||||d|S)aM 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 r5r7rrr)rZr[_Hologres__from) rIr2rer5rrr7rr9r1s r& from_textszHologres.from_textssa(..tE{{;; sz      !-      r(text_embeddingsList[Tuple[str, List[float]]]c ^d|D} d|D} |j| | |f|||||d|S)a~Construct 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) cg|] }|d S)rr<rPs r&rCz,Hologres.from_embeddings..7s///!1///r(cg|] }|d S)r<rPs r&rCz,Hologres.from_embeddings..8s444qad444r(r)r) rIrrer5rrr7rr9r2r1s r&from_embeddingszHologres.from_embeddingsso@0////44O444 sz      !-      r(c P||}||||||}|S)z Get instance of an existing Hologres store.This method will return the instance of the store without inserting any new embeddings )rrrrr)rG)rIrerrrr9rrJs r&from_existing_indexzHologres.from_existing_indexFsD 55f==/!(-     r(Dict[str, Any]cLt|dd}|std|S)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)rIr9rs r&rGzHologres.get_connection_stringasJ!5#0" " "  ! B ! r( documentspre_delete_collectionc d|D}d|D} ||} | |d<|jd|||| |||d|S)aQ 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 cg|] }|j Sr<)rxrAds r&rCz+Hologres.from_documents..s333A333r(cg|] }|j Sr<)rwrs r&rCz+Hologres.from_documents..s333AQZ333r(r)r2rrer5r7rrr<)rGr) rIrrerrr7rr9r2r5rs r&from_documentszHologres.from_documentsts(4333333333 55f==&7"#s~  "7!      r(hostportdatabaseuserpasswordc $d|d|d|d|d| S)z2Return connection string from database parameters.zdbname=z user=z password=z host=z port=r<)rIrrrrrs r& connection_string_from_db_paramsz)Hologres.connection_string_from_db_paramss6 Yh X Xd X Xh X Xd X XRV X X r()rrrr rrrrrrrrrr)rr)rr )r2r3r1r4rr r5r6r7r8rrrrrrr9rrr) r2rLr1r4r5rMr7r3r9rrr)NN) r2rLr5r6r7r8r9rrr3)r]N) r^rr_rr`rar9rrrb) rerir_rr`rar9rrrb)r^rr_rr`rarro)rerir_rr`rarro)rIr}r2r3rer r5r6rrrrr7r8rrr9rrr)rrrer r5r6rrrrr7r8rrr9rrr)rIr}rer rrrrrrr9rrr)r9rrr)rIr}rrbrer rrrrr7r8rrr9rrr) rrrrrrrrrrrr)r# __module__ __qualname____doc__ADA_TOKEN_COUNT_LANGCHAIN_DEFAULT_TABLE_NAMEr'r$propertyr1 classmethodrrHr\rhrgrrrmrrrrGrrr<r(r&rrs|  &%7!&+/"    '''X' +/#'$7!&    [ D%%%%2+/#' @!%      6!% 333332!% 2!% , +/$7#'!&    [ B +/$7#'!&, , , , [, \%7!& [4!!![!$ %7#'&+" " " " [" H    [    r(r) __future__rr!r>typingrrrrrr r langchain_core.documentsr langchain_core.embeddingsr langchain_core.utilsrlangchain_core.vectorstoresrrrrr<r(r&rs"""""" CCCCCCCCCCCCCCCCCC------000000555555333333 8U U U U U {U U U U U r(