Title / Abstract Mapping Tool
Langchain tools that execute zero-shot classification tasks over a local database of title/abstracts from papers previously imported into our database.
BaseTitleAbstractMappingTool
BaseTitleAbstractMappingTool (db:alhazen.utils.ceifns_db.Ceifns_Literatu reDb, llm:Optional[langchain_core.language_ models.chat_models.BaseChatModel]=None, slm :Optional[langchain_core.language_models.ch at_models.BaseChatModel]=None, name:str='tiab_mapping', description:str='Runs a specified document mapping pipeline over papers in a collection.', args_schema:Optional[Type[pyd antic.v1.main.BaseModel]]=None, return_direct:bool=True, verbose:bool=False, callbacks:Union[List[la ngchain_core.callbacks.base.BaseCallbackHan dler],langchain_core.callbacks.base.BaseCal lbackManager,NoneType]=None, callback_manag er:Optional[langchain_core.callbacks.base.B aseCallbackManager]=None, tags:Optional[List[str]]=None, metadata:Optional[Dict[str,Any]]=None, hand le_tool_error:Union[bool,str,Callable[[lang chain_core.tools.ToolException],str],NoneTy pe]=False, handle_validation_error:Union[bo ol,str,Callable[[pydantic.v1.error_wrappers .ValidationError],str],NoneType]=False)
Runs a specified document mapping pipeline over papers in a collection.
TitleAbstractMappingToolSchema
TitleAbstractMappingToolSchema (collection_id:str, repeat_run:Optional[bool]=None, run_label:Optional[str]=None)
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
TitleAbstractDiscourseMappingTool
TitleAbstractDiscourseMappingTool (db:alhazen.utils.ceifns_db.Ceifns_Lit eratureDb, llm:Optional[langchain_core .language_models.chat_models.BaseChatM odel]=None, slm:Optional[langchain_cor e.language_models.chat_models.BaseChat Model]=None, name:str='tiab_one_doc_cl assification', description:str='Runs through the text of each title + abstract and split them based on discourse.', args_schema:Optional[Type [pydantic.v1.main.BaseModel]]=None, return_direct:bool=True, verbose:bool=False, callbacks:Union[Li st[langchain_core.callbacks.base.BaseC allbackHandler],langchain_core.callbac ks.base.BaseCallbackManager,NoneType]= None, callback_manager:Optional[langch ain_core.callbacks.base.BaseCallbackMa nager]=None, tags:Optional[List[str]]=None, metadata:Optional[Dict[str,Any]]=None, handle_tool_error:Union[bool,str,Calla ble[[langchain_core.tools.ToolExceptio n],str],NoneType]=False, handle_valida tion_error:Union[bool,str,Callable[[py dantic.v1.error_wrappers.ValidationErr or],str],NoneType]=False)
Runs through the text of each title + abstract and split them based on discourse.