jddlmZddlmZmZmZmZmZddlm Z ddl m Z ddl m Z ddlmZddlmZddlmZmZe d d d Gd deZy)) annotations)AnyDictListOptionalcast)uuid4) deprecated)CallbackManagerForRetrieverRun)Document) BaseRetriever) ConfigDictmodel_validatorz0.3.18z1.0z&langchain_weaviate.WeaviateVectorStore)sinceremovalalternative_importceZdZUdZdZded< ded< ded< dZd ed < d Zd ed < ded< dZded< e de ddZ e dZ ddZdddd ddZy)WeaviateHybridSearchRetrieverz{`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)modec ddl}t|d|js|d}t dt ||j dg|d<tt|dj|d|j ddrP|d |dd gd gd d }|djj|d s|djj||S#t$r tdwxYw)Nrz_Could not import weaviate python package. Please install it with `pip install weaviate-client`.rz5client should be an instance of weaviate.Client, got rrr!Trtext)namedataTypeztext2vec-openai)class properties vectorizer) weaviate ImportError isinstanceClient ValueErrortypegetrrappendschemaexists create_class)clsvaluesr+r class_objs /var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/retrievers/weaviate_hybrid_search.pyvalidate_clientz-WeaviateHybridSearchRetriever.validate_client(s    &*HOO<H%FGV ~V  ::l # +#%F<  T6,'(//z0BC ::0$ 7 -(.z(:QR/I (#**11&2FGx ''44Y? 3 H  s CC/)arbitrary_types_allowedc ddlm}|jj5}g}t |D]z\}}|j xsi}|j |ji|} d|vr |d|} n|t} |j| |j| |j| | ddd|S#1swYSxYw)zUpload documents to Weaviate.r)get_valid_uuiduuidsN) weaviate.utilr=rbatch enumeratemetadatar page_contentr add_data_objectrr2) selfdocskwargsr=r@idsidocrBdata_properties_ids r9 add_documentsz+WeaviateHybridSearchRetriever.add_documentsPs0 [[  %C#D/3<<-2#'==#2B2B"Oh"Of$ /!,C(1C%%otL 3*  s B B33B=F) where_filterscorehybrid_search_kwargsc.|jjj|j|j}|r|j |}|r|j ddg}|i}|j|fd|ji|j|jj}d|vrtd|dg}|dd|jD]9} | j|j} |jt!| | ;|S) aDLook 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 rO explainScorererrorszError during query: dataGet)rCrB)rqueryr1rr with_wherewith_additional with_hybridr with_limitrdor/poprr2r ) rErV run_managerrNrOrP query_objresultrFresr%s r9_get_relevant_documentsz5WeaviateHybridSearchRetriever._get_relevant_documentses XKK%%))$//4??K !,,\:I !117N2KLI  '#%  "I ! !% Rtzz R=Q R Z  RT  v 3F84D3EFG G&>%(9C774==)D KKdSA B: )r7zDict[str, Any]returnr)rFList[Document]rGrrcr) rVrr]r rNOptional[Dict[str, object]]rOr rPrercrd)__name__ __module__ __qualname____doc__r__annotations__rrr!r classmethodr:r model_configrMrarbr9rr s  FC;O'M*E5: AsJ*2%)d);(# $B $L 459<@CC4 C 2 C  C:C CrbrN) __future__rtypingrrrrruuidr langchain_core._apir langchain_core.callbacksr langchain_core.documentsr langchain_core.retrieversr pydanticrrrrmrbr9rvsL"22*C-30  ? VMV  Vrb