dhSSKJr SSKJrJrJrJrJr SSKJ r SSK J r SSK J r SSKJr SSKJr SSKJrJr \ "S S S S 9"S S\55rg)) annotations)AnyDictListOptionalcast)uuid4) deprecated)CallbackManagerForRetrieverRun)Document) BaseRetriever) ConfigDictmodel_validatorz0.3.18z1.0z&langchain_weaviate.WeaviateVectorStore)sinceremovalalternative_importc\rSrSr%SrSrS\S'S\S'S\S'S rS \S 'S rS \S'S\S'Sr S\S'\ "SS9\ SSj55r \ "SS9rSSjrSSSS.SSjjrSrg) WeaviateHybridSearchRetriever zo`Weaviate hybrid search` retriever. See the documentation: https://weaviate.io/blog/hybrid-search-explained Nrclientstr index_nametext_keyg?floatalphaintk List[str] attributesTboolcreate_schema_if_missingbefore)modecSSKn[USUR5(dUSn[ S[ U535eUR S5c/US'[[US5RUS5 UR SS5(aUUS USS /S ./S S .nUSRRUS 5(dUSRRU5 U$![a [S5ef=f)Nrz_Could not import weaviate python package. Please install it with `pip install weaviate-client`.rz5client should be an instance of weaviate.Client, got r rr"Trtext)namedataTypeztext2vec-openai)class properties vectorizer) weaviate ImportError isinstanceClient ValueErrortypegetrrappendschemaexists create_class)clsvaluesr,r class_objs m/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/retrievers/weaviate_hybrid_search.pyvalidate_client-WeaviateHybridSearchRetriever.validate_client(s    &*HOO<<H%FGV ~V  ::l # +#%F<  T6,'(//z0BC ::0$ 7 7 -(.z(:QR/I (#**11&2FGGx ''44Y? 3 H  s C**D)arbitrary_types_allowedc SSKJn URRn/n[ U5HupgUR =(d 0nUR UR0UEn SU;a USUn OU"[55n URXRU 5 URU 5 M SSS5 U$!,(df  W$=f)zUpload documents to Weaviate.r)get_valid_uuiduuidsN) weaviate.utilr?rbatch enumeratemetadatar page_contentr add_data_objectrr3) selfdocskwargsr?rBidsidocrDdata_properties_ids r: add_documents+WeaviateHybridSearchRetriever.add_documentsPs0 [[  %C#D/<<-2#'==#2B2B"Oh"Of$ /!,C(1C%%oL 3*   s BB99 CF) where_filterscorehybrid_search_kwargscDURRRURUR5nU(aUR U5nU(aUR SS/5nUc0nUR"U4SUR0UD6RUR5R5nSU;a[SUS35e/nUSSURH6n U RUR5n UR[!XS95 M8 U$) alLook up similar documents in Weaviate. query: The query to search for relevant documents of using weviate hybrid search. where_filter: A filter to apply to the query. https://weaviate.io/developers/weaviate/guides/querying/#filtering score: Whether to include the score, and score explanation in the returned Documents meta_data. hybrid_search_kwargs: Used to pass additional arguments to the .with_hybrid() method. The primary uses cases for this are: 1) Search specific properties only - specify which properties to be used during hybrid search portion. Note: this is not the same as the (self.attributes) to be returned. Example - hybrid_search_kwargs={"properties": ["question", "answer"]} https://weaviate.io/developers/weaviate/search/hybrid#selected-properties-only 2) Weight boosted searched properties - Boost the weight of certain properties during the hybrid search portion. Example - hybrid_search_kwargs={"properties": ["question^2", "answer"]} https://weaviate.io/developers/weaviate/search/hybrid#weight-boost-searched-properties 3) Search with a custom vector - Define a different vector to be used during the hybrid search portion. Example - hybrid_search_kwargs={"vector": [0.1, 0.2, 0.3, ...]} https://weaviate.io/developers/weaviate/search/hybrid#with-a-custom-vector 4) Use Fusion ranking method Example - from weaviate.gql.get import HybridFusion hybrid_search_kwargs={"fusion": fusion_type=HybridFusion.RELATIVE_SCORE} https://weaviate.io/developers/weaviate/search/hybrid#fusion-ranking-method rR explainScorererrorszError during query: dataGet)rErD)rqueryr2rr with_wherewith_additional with_hybridr with_limitrdor0poprr3r ) rGrY run_managerrQrRrS query_objresultrHresr&s r:_get_relevant_documents5WeaviateHybridSearchRetriever._get_relevant_documentsesXKK%%))$//4??K !,,\:I !117N2KLI  '#%   ! !% Rtzz R=Q R Z  RT  v 3F84D3EFG G&>%(9C774==)D KKdA B: )r8zDict[str, Any]returnr)rHList[Document]rIrrhr) rYrr`r rQOptional[Dict[str, object]]rRr!rSrjrhri)__name__ __module__ __qualname____firstlineno____doc__r__annotations__rrr"r classmethodr;r model_configrOrd__static_attributes__rgrfr:rr s  FC;O'M*E5: AsJ*2%)d);(# $B $L 459<@CC4 C 2 C  C:C CCrfrN) __future__rtypingrrrrruuidr langchain_core._apir langchain_core.callbacksr langchain_core.documentsr langchain_core.retrieversr pydanticrrrrgrfr:r|sL"22*C-30  ? VMV  Vrf