dh;SSKJr SSKrSSKJrJrJrJrJrJ r J r J r J r \(aSSK r SSKr SSKJrJrJrJr SSKJr SSKJr SSKJr SSKJr S rSS jrSS jr"S S \5rg)) annotationsN) TYPE_CHECKINGAnyCallableDictIterableListOptionalTupleType)ID OneOrManyWhere WhereDocument)Document) Embeddings)xor_args) VectorStorecL[U5VVs/sHupUPM snn$s snnfN)_results_to_docs_and_scores)resultsdoc_s ^/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/vectorstores/bagel.py_results_to_docsrs#9'B CBFCCB CC Cs c[USSUSSUSS5Vs/sH!n[USUS=(d 0S9US4PM# sn$s snf)N documentsr metadatas distances) page_contentmetadata)zipr)rresults rrr!su K  # K  # K  #   F vay6!9? CVAYO   s'A c l\rSrSr%SrSrS\S'\SSSSS4SSjjr\SSj5r \ "S 5SSS jj5r SSS jjr \ S4SS jjr\ S4SS jjr\SSS\SSSS4S Sjj5rS!Sjr\ S4S"Sjjr\ S4S#SjjrS$Sjr\SS\SSS4S%Sjj5rS&SjrS'S(SjjrS)S*SjjrSrg)+Bagel,a ``Bagel.net`` Inference platform. To use, you should have the ``bagelML`` python package installed. Example: .. code-block:: python from langchain_community.vectorstores import Bagel vectorstore = Bagel(cluster_name="langchain_store") langchainstr_LANGCHAIN_DEFAULT_CLUSTER_NAMENc@SSKnSSKnUb X lXPlOAU(aUnOUR R SSS9nXlUR"U5UlURRUUS9Ul X`l X0l g![a [S5ef=f)zInitialize with bagel clientrN+Please install bagel `pip install bagelML`.restzapi.bageldb.ai)bagel_api_implbagel_server_host)namer$) bagel bagel.config ImportError_client_settings_clientconfigSettingsClientget_or_create_cluster_clusteroverride_relevance_score_fn_embedding_function) self cluster_nameclient_settingsembedding_functioncluster_metadataclientrelevance_score_fnr4r7s r__init__Bagel.__init__:s M    $3 !!L#2 #(<<#8#8#)&6$9$ %5 ! <<(89DL ::%;  ,>(#5 + MKL L Ms BBcUR$r)r?r@s r embeddingsBagel.embeddings^s''') query_textsquery_embeddingsc SSKnUR(a2Uc/U(a([U5nURR U5nSnUR R "SUUUUS.UD6$![a [S5ef=f)z9Query the Bagel cluster based on the provided parameters.rNr/)rNrO n_resultswhere)r4r6r?listembed_documentsr=find)r@rNrOrQrRkwargsr4textss r__query_clusterBagel.__query_clusterbs M   # #(8(@[%E#77GGN K}}!! #-      MKL L Ms A**Bc 2Uc-UVs/sH!n[[R"55PM# nn[U5nUR(a%Uc"U(aURR U5nU(GaJ[ U5[ U5- nU(a U0/U--n/n/n [U5H0upU (aU RU 5 MURU 5 M2 U (arU V s/sHoU PM nn U V s/sHoU PM n n U(aU V s/sHoU PM sn OSn U V s/sHoU PM nn URRU UU US9 U(a^UVs/sHoUPM nnU(aUVs/sHoUPM snOSnUVs/sHoUPM nnURRUUUS9 U$0/[ U5-nURRUUUUS9 U$s snfs sn fs sn fs sn fs sn fs snfs snfs snf)a Add texts along with their corresponding embeddings and optional metadata to the Bagel cluster. Args: texts (Iterable[str]): Texts to be added. embeddings (Optional[List[float]]): List of embeddingvectors metadatas (Optional[List[dict]]): Optional list of metadatas. ids (Optional[List[str]]): List of unique ID for the texts. Returns: List[str]: List of unique ID representing the added texts. N)rKr rids)rKrr\)rKrr r\) r,uuiduuid4rTr?rUlen enumerateappendr=upsert)r@rXr r\rKrWr length_diff empty_ids non_empty_idsidxr$texts_with_metadatasembeddings_with_metadatasids_with_metadatajtexts_without_metadatasembeddings_without_metadatasids_without_metadatass r add_textsBagel.add_texts~s, ;.34e3tzz|$eC4U   # # (:u11AA%HJ e*s9~5K%{(:: IM!*9!5 !((-$$S) "6 7DE}s^} E>K'Lmsc m$'LBL > _ >RV*:G$G#X!$G $$8'2) % =F*GY8Y'*G:DI6Iq]I6$-:C(CAQ%(C $$;5-% s5z)I MM %# !   a5"F'L>$G+H6(Cs/'G1/ G6 G; H2 H( H  H Hc ZURXUS9nUVVs/sHupgUPM snn$s snnf)a_ Run a similarity search with Bagel. Args: query (str): The query text to search for similar documents/texts. k (int): The number of results to return. where (Optional[Dict[str, str]]): Metadata filters to narrow down. Returns: List[Document]: List of documents objects representing the documents most similar to the query text. )rR)similarity_search_with_score)r@querykrRrWdocs_and_scoresrrs rsimilarity_searchBagel.similarity_searchs3&;;EE;R"12//222s 'c :URU/X#S9n[U5$)a Run a similarity search with Bagel and return documents with their corresponding similarity scores. Args: query (str): The query text to search for similar documents. k (int): The number of results to return. where (Optional[Dict[str, str]]): Filter using metadata. Returns: List[Tuple[Document, float]]: List of tuples, each containing a Document object representing a similar document and its corresponding similarity score. )rNrQrR_Bagel__query_clusterr)r@rrrsrRrWrs rrq"Bagel.similarity_search_with_scores&,&&E7a&U*733rMc BU"SUUUUUS.U D6n U RXX4S9n U $)aU Create and initialize a Bagel instance from list of texts. Args: texts (List[str]): List of text content to be added. cluster_name (str): The name of the Bagel cluster. client_settings (Optional[bagel.config.Settings]): Client settings. cluster_metadata (Optional[Dict]): Metadata of the cluster. embeddings (Optional[Embeddings]): List of embedding. metadatas (Optional[List[dict]]): List of metadata. ids (Optional[List[str]]): List of unique ID. Defaults to None. client (Optional[bagel.Client]): Bagel client instance. Returns: Bagel: Bagel vectorstore. )rArCrBrErD)rXrKr r\rS)rn) clsrX embeddingr r\rArBrDrEtext_embeddingsrW bagel_clusterrs r from_textsBagel.from_textssP< %(+-      # #y $ rMcbURRURR5 g)zDelete the cluster.N)r8delete_clusterr=r3rJs rrBagel.delete_cluster!s ##DMM$6$67rMc 8URXUS9n[U5$)zD Return docs most similar to embedding vector and similarity score. rOrQrRrx)r@rOrsrRrWrs r1similarity_search_by_vector_with_relevance_scores7Bagel.similarity_search_by_vector_with_relevance_scores%s+&&-%' +733rMc 8URXUS9n[U5$)z-Return docs most similar to embedding vector.r)ryr)r@r}rsrRrWrs rsimilarity_search_by_vector!Bagel.similarity_search_by_vector4s+&&&5'  ((rMcUR(a UR$SnSnURRnU(a X#;aX2nUS:Xa UR$US:Xa UR$US:Xa UR $[ SUS35e)zt Select and return the appropriate relevance score function based on the distance metric used in the Bagel cluster. l2z hnsw:spacecosineipzANo supported normalization function for distance metric of type: z=. Consider providing relevance_score_fn to Bagel constructor.)r>r=r$_cosine_relevance_score_fn_euclidean_relevance_score_fn%_max_inner_product_relevance_score_fn ValueError)r@distance distance_keyr$s r_select_relevance_score_fn Bagel._select_relevance_score_fnAs  + +33 3# ==))  0-H x 22 2  55 5  == =$$,:.<< rMc UV s/sHoRPM n n UV s/sHoRPM n n UR"SU UU UUUUUS.UD6$s sn fs sn f)a Create a Bagel vectorstore from a list of documents. Args: documents (List[Document]): List of Document objects to add to the Bagel vectorstore. embedding (Optional[List[float]]): List of embedding. ids (Optional[List[str]]): List of IDs. Defaults to None. cluster_name (str): The name of the Bagel cluster. client_settings (Optional[bagel.config.Settings]): Client settings. client (Optional[bagel.Client]): Bagel client instance. cluster_metadata (Optional[Dict]): Metadata associated with the Bagel cluster. Defaults to None. Returns: Bagel: Bagel vectorstore. )rXr}r r\rArBrErDrS)r#r$r) r|rr}r\rArBrErDrWrrXr s rfrom_documentsBagel.from_documents]sr:.77Yc!!Y7-67Yc\\Y 7~~  %+-    87s AAcpURnURnURRU/U/U/S9 g)zUpdate a document in the cluster. Args: document_id (str): ID of the document to update. document (Document): Document to update. )r\rr N)r#r$r=update)r@ document_iddocumenttextr$s rupdate_documentBagel.update_documents@$$$$  fj  rMcXUUUUUS.nUbXgS'URR"S0UD6$)zGets the collection.)r\rRlimitoffsetwhere_documentincluderS)r=get)r@r\rRrrrrrWs rr Bagel.getsB,     '9 }}  *6**rMc 6URRUS9 g)z7 Delete by IDs. Args: ids: List of ids to delete. )r\N)r=delete)r@r\rWs rr Bagel.deletes %rM)r8r7r=r?r>)rAr,rBOptional[bagel.config.Settings]rCOptional[Embeddings]rDOptional[Dict]rEOptional[bagel.Client]rFz"Optional[Callable[[float], float]]returnNone)rr)NNN) rNOptional[List[str]]rOOptional[List[List[float]]]rQintrROptional[Dict[str, str]]rWrrList[Document])NNN) rXz Iterable[str]r Optional[List[dict]]r\rrKrrWrr List[str]) rrr,rsrrRrrWrrr) rrr,rsrrRrrWrrList[Tuple[Document, float]])r| Type[Bagel]rXrr}rr rr\rrAr,rBrrDrrErr~rrWrrr))rr) rO List[float]rsrrRrrWrrr) r}rrsrrRrrWrrr)rzCallable[[float], float])r|rrrr}rr\rrAr,rBrrErrDrrWrrr))rr,rrrr)NNNNNN)r\zOptional[OneOrMany[ID]]rRzOptional[Where]r Optional[int]rrrzOptional[WhereDocument]rrrzDict[str, Any]r)r\rrWrrr)__name__ __module__ __qualname____firstlineno____doc__r-__annotations__rGpropertyrKrryrn DEFAULT_Krurq classmethodrrrrrrrrr__static_attributes__rSrMrr)r),s ,7#S6<;?37+/)-AE"6"69"61 "6 ) "6 ' "6?"6 "6H((12,08<*.  ( 6   (      3 <+/#'26 GG(G! G 0 G  G GX*. 33 3( 3  3  32*. 44 4( 4  4 & 42+/*.#';;?+/)-7;( ((((( ( ! (  (9()('(5(( ((T8*. 4% 4  4( 4  4 & 4$*. ) )  )( )  )  )8+/#';;?)-+/( ( !( (( ! (  ( 9 ( '( )( (  ( ( T  "(,!%# $26'++ $++ +  + 0 +%+ +.&&rMr))rrrr)rrrr) __future__rr]typingrrrrrr r r r r4r5bagel.api.typesr rrrlangchain_core.documentsrlangchain_core.embeddingsrlangchain_core.utilsrlangchain_core.vectorstoresrrrrr)rSrMrrsU"    CC-0)3 DI&KI&rM