tjU#dZddlmZddlmZmZddlmZddlm Z m Z ddl m Z ddl mZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZddlmZmZm Z ddl!m"Z#GddeZ$e#dddddddde dede%de&de&de&de dzd e d!ed"efd#Z'dddddd$de dedzde&de%dzde dzd e d!ed"efd%Z(ddd&dddddddd'd( de d)edzd*edzd+e&d,e&d-edzd.e dzd/e dzde%dzde dzd e d0e)d!ed"efd1Z*ddd2d3ddddd4de d)edzd5edzde&d6e&d7e dzde%dzde dzd e d!ed"efd8Z+ed9d:d;d<= dAde d?e&de%dzde dzd!ed"ef d@Z,dS)BzLoad question answering chains.)Mapping)AnyProtocol) deprecated)BaseCallbackManager Callbacks)BaseLanguageModel)BasePromptTemplate)ReduceDocumentsChain)BaseCombineDocumentsChain)MapReduceDocumentsChain)MapRerankDocumentsChain)RefineDocumentsChain)StuffDocumentsChain)LLMChain)map_reduce_promptrefine_prompts stuff_prompt)PROMPTc&eZdZdZdededefdZdS)LoadingCallablez2Interface for loading the combine documents chain.llmkwargsreturnc dS)z-Callable to load the combine documents chain.N)selfrrs o/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_classic/chains/question_answering/chain.py__call__zLoadingCallable.__call__#sN)__name__ __module__ __qualname____doc__r rr rrr rrr sJ<<< << # <<<<<r?r@rAc |ptj|} |ptj|}t || || | }|p|}t |||| | }t |||| | }|d}|d}t |n)|p|}t t |||| | ||| }t||| |}td||||| | d| S)Nr0r4zfcollapse_llm provided, but collapse_prompt was not: please provide one or stop providing collapse_llm.)r1r*r)r-)combine_documents_chaincollapse_documents_chainrAr))r1r*reduce_documents_chainr)r-r.r) rQUESTION_PROMPT_SELECTORr6COMBINE_PROMPT_SELECTORrr ValueErrorr r )rr:r;r<r=r>r?r@r)r-r.rAr_question_prompt_combine_prompt map_chain _reduce_llm reduce_chainrCcollapse_chainmsg _collapse_llmrEs r_load_map_reduce_chainrQfs" U,EPPQTUU S+CNNsSS ) I#K ) L2=)   #> S// ! $%+ ,!&!1# $B-    2 7!/  # @5)      r context_strexisting_answer)r: refine_promptr*initial_response_name refine_llmr)r-r.rTrUrVc |ptj|} |ptj|} t || |||} |p|} t | | |||}t d| ||||||d| S)Nr0)initial_llm_chainrefine_llm_chainr*rUr)r-r.r)rrFr6REFINE_PROMPT_SELECTORrr)rr:rTr*rUrVr)r-r.rrI_refine_prompt initial_chain _refine_llm refine_chains r_load_refine_chainr_s R>BMMcRR#n&K&V&V ''N ) M#K ) L '%53)      r z0.2.13z2.0.0zlangchain.agents.create_agentzuBuild new RAG flows with `create_agent` and a retrieval tool. See https://docs.langchain.com/oss/python/langchain/rag)sinceremoval alternativeaddendumstuff chain_typec ttttd}||vr)d|d|}t ||||f||d|S)a/Load question answering chain. Args: llm: Language Model to use in the chain. chain_type: Type of document combining chain to use. Should be one of "stuff", "map_reduce", "map_rerank", and "refine". verbose: Whether chains should be run in verbose mode or not. Note that this applies to all chains that make up the final chain. callback_manager: Callback manager to use for the chain. **kwargs: Additional keyword arguments. Returns: A chain to use for question answering. )rd map_reducerefine map_rerankzGot unsupported chain type: z. Should be one of )r)r-)r8rQr_r2keysrH)rrer)r-rloader_mappingrOs r load_qa_chainrls>#,$, 55N '' 8: 8 8 . 3 3 5 5 8 8 oo %>* %  )      r )rdNN)-r$collections.abcrtypingrrlangchain_core._apirlangchain_core.callbacksrrlangchain_core.language_modelsr langchain_core.promptsr langchain_classic.chainsr /langchain_classic.chains.combine_documents.baser 5langchain_classic.chains.combine_documents.map_reducer 5langchain_classic.chains.combine_documents.map_rerankr1langchain_classic.chains.combine_documents.refiner0langchain_classic.chains.combine_documents.stuffrlangchain_classic.chains.llmr+langchain_classic.chains.question_answeringrrr=langchain_classic.chains.question_answering.map_rerank_promptrMAP_RERANK_PROMPTrboolstrr2r8intrQr_rlrr rrs%%###### ******CCCCCCCC<<<<<<555555999999UUUUUUSRRRRRPPPPPP111111  <<<< 37 && &&D[&*D0 &  &  &&&&&&r