tj""ddlmZddlmZmZmZmZmZmZm Z ddl Z ddl m Z ddl mZmZmZGddeeZGdd eeZGd d eZGd d eZGddeZGddZGddZdS))Enum)AnyDictListLiteralMappingOptionalUnionN)Document) BaseModel SecretStrmodel_validatorceZdZdZdZdZdZdS) ArceeRoutez1Routes available for the Arcee API as enumerator.zmodels/generatezmodels/retrievezmodels/status/{id_or_name}N)__name__ __module__ __qualname____doc__generateretrievemodel_training_statusa/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/utilities/arcee.pyrr s&;; H H8rrceZdZdZdZdZdS)DALMFilterTypez:Filter types available for a DALM retrieval as enumerator. fuzzy_search strict_searchN)rrrrrrrrrrrsDD!L#MMMrrceZdZUdZeed<eed<eed<dZeed<e de d e d e fd Z d S) DALMFilteraXFilters available for a DALM retrieval and generation. Arguments: field_name: The field to filter on. Can be 'document' or 'name' to filter on your document's raw text or title. Any other field will be presumed to be a metadata field you included when uploading your context data filter_type: Currently 'fuzzy_search' and 'strict_search' are supported. 'fuzzy_search' means a fuzzy search on the provided field is performed. The exact strict doesn't need to exist in the document for this to find a match. Very useful for scanning a document for some keyword terms. 'strict_search' means that the exact string must appear in the provided field. This is NOT an exact eq filter. ie a document with content "the happy dog crossed the street" will match on a strict_search of "dog" but won't match on "the dog". Python equivalent of `return search_string in full_string`. value: The actual value to search for in the context data/metadata field_name filter_typevalueF _is_metadatabefore)modevaluesreturnc:|ddv|d<|S)zDdocument and name are reserved arcee keys. Anything else is metadatar!)documentname_is_meta)get)clsr's rset_metazDALMFilter.set_meta6s%$ZZ 55=QQz rN)rrrrstr__annotations__rr$boolr classmethodrrr/rrrr r s(OOO JJJL$_(###ds[$#rr c2eZdZUdZeed<eed<eed<dS)ArceeDocumentSourcezSource of an Arcee document.r*r+idN)rrrrr0r1rrrr5r5>s1&&MMM III GGGGGrr5c<eZdZUdZeed<eed<eed<eed<dS) ArceeDocumentzArcee document.indexr6scoresourceN)rrrrr0r1floatr5rrrr8r8Fs? JJJ GGG LLL rr8c2eZdZdZededefdZdS)ArceeDocumentAdapterzAdapter for Arcee documentsarcee_documentr(c t|jj|jj|jj|j|j|jdS)z=Adapts an `ArceeDocument` to a langchain's `Document` object.)r+ source_idr9r6r:) page_contentmetadata)r r;r*r+r6r9r:)r.r?s radaptzArceeDocumentAdapter.adaptRsT'.7'-2+25'-$''-    rN)rrrrr3r8r rDrrrr>r>OsF%%  =  X    [    rr>c eZdZdZdeeefdededeeee fdef dZ dd Z dd e d d ee efdeeee fdeedeedef dZddeedefdZd ee efdefdZdedeee fdeee ffdZdede defdZdede deefdZd S) ArceeWrapperzMWrapper for Arcee API. For more details, see: https://www.arcee.ai/ arcee_api_key arcee_api_urlarcee_api_version model_kwargs model_namect|trt|}n|}||_||_||_||_ tjj |}| d|}| d|_ | d|_dS#t$r} td|d| | d} ~ wwxYw)a5Initialize ArceeWrapper. Arguments: arcee_api_key: API key for Arcee API. arcee_api_url: URL for Arcee API. arcee_api_version: Version of Arcee API. model_kwargs: Keyword arguments for Arcee API. model_name: Name of an Arcee model. ) id_or_namer-model_idstatusz2Error while validating model training status for 'z': N) isinstancer0r rGrJrHrIrrr#format _make_requestr-rN Exception ValueError) selfrGrHrIrJrKarcee_api_key_routeresponsees r__init__zArceeWrapper.__init__is" mS ) ) +&}55NN*N(6(*!2 4:AAZAXXE))%77H$LL44DM)1h)?)?D & & &   WZWWTUWW  sA/B66 CCCr(NcL|jdkrtd|jddS)Ntraining_completezModel z4 is not ready. Please wait for training to complete.)rrSrN)rUs rvalidate_model_training_statusz+ArceeWrapper.validate_model_training_statussC  %)< < <8888  = z>ArceeWrapper._make_request_body_for_models..s"GGGq:????GGGrfilterssize)rNqueryrrr6)rJr-dictrN)rUrxry _model_kwargs_paramsrs r_make_request_body_for_modelsz*ArceeWrapper._make_request_body_for_modelssy)/R -]-f-GGGKK 2,F,FGGG]VQ''}     rc z|dtjj|jdd|i|}|dS)a+Generate text from Arcee DALM. Args: prompt: Prompt to generate text from. size: The max number of context results to retrieve. Defaults to 3. (Can be less if filters are provided). filters: Filters to apply to the context dataset. r_rxr^rWr`rlr)rRrrr#r)rUrxryrXs rrzArceeWrapper.generates^%%%+33&  rrc |dtjj|jdd|i|}d|dDS)aIRetrieve {size} contexts with your retriever for a given query Args: query: Query to submit to the model size: The max number of context results to retrieve. Defaults to 3. (Can be less if filters are provided). filters: Filters to apply to the context dataset. r_rxrc Vg|]&}ttdi|'Sr|)r>rDr8)r}docs rrz)ArceeWrapper.retrieve..sD    ! & &}';';s';'; < <   rresultsr)rRrrr#r)rUrryrXs rrzArceeWrapper.retrievesw%%%+33&     *    r)r(N)NNN)N)rrrrr r0r r rrrZr]rrrrrRrgrhrrrr rrrrrFrFcs  "S)^,"" " tCH~. "  """"H-1!%"&  &Z_%wsCx()    $  4  Xd^ t    HuZ_'=H#HHHH  %,S#X%6 c             0    h       rrF)enumrtypingrrrrrr r rjlangchain_core.retrieversr pydanticr r rr0rrr r5r8r>rFrrrrs EEEEEEEEEEEEEEEEEE......::::::::::99999d999$$$$$S$$$$D     )        I           (] ] ] ] ] ] ] ] ] ] r