Ng.dZddlmZddlZddlZddlmZddlmZm Z m Z m Z ddl m Z ddlmZmZmZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZmZmZddl m!Z!ddl"m#Z#ddl$m%Z%ddl&m'Z'ddl(m)Z)ddl*m+Z+e dddGdde!Z,e dddGdde,Z-e dddGdde,Z.dS)7Chain for question-answering against a vector database.) annotationsN)abstractmethod)AnyDictListOptional) deprecated)AsyncCallbackManagerForChainRunCallbackManagerForChainRun Callbacks)Document)BaseLanguageModel)PromptTemplate) BaseRetriever) VectorStore) ConfigDictFieldmodel_validator)Chain)BaseCombineDocumentsChain)StuffDocumentsChain)LLMChain load_qa_chain)PROMPT_SELECTORz0.2.13z1.0zThis class is deprecated. Use the `create_retrieval_chain` constructor instead. See migration guide here: https://python.langchain.com/docs/versions/migrating_chains/retrieval_qa/)sinceremovalmessageceZdZUdZded< dZded<dZded<d Zd ed < ed d d Z e d0dZ e d0dZ e d1d2dZe d3d4d"Zed5d'Z d6d7d+Zed8d-Z d6d9d/ZdS):BaseRetrievalQAz)Base class for question-answering chains.rcombine_documents_chainquerystr input_keyresult output_keyFboolreturn_source_documentsTforbid)populate_by_namearbitrary_types_allowedextrareturn List[str]c|jgS)z,Input keys. :meta private: )r%selfs ^/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain/chains/retrieval_qa/base.py input_keyszBaseRetrievalQA.input_keys8s c0|jg}|jr|dgz}|S)z-Output keys. :meta private: source_documents)r'r))r2 _output_keyss r3 output_keyszBaseRetrievalQA.output_keys@s- (  ' ?'+=*>>Lr5NllmrpromptOptional[PromptTemplate] callbacksr llm_chain_kwargsOptional[dict]kwargsrc |ptj|}td|||d|pi}tdgd}t |d||} |d| |d|S) zInitialize from LLM.)r:r;r= page_contentzContext: {page_content})input_variablestemplatecontext) llm_chaindocument_variable_namedocument_promptr=)r"r=)r get_promptrrr) clsr:r;r=r>r@_promptrFrHr"s r3from_llmzBaseRetrievalQA.from_llmKs;O6s;; Gy  =M=SQS  )+,7Q   #6#,+ # # # s $;     r5stuff chain_typechain_type_kwargsc <|pi}t|fd|i|}|dd|i|S)zLoad chain from chain type.rOr"rIr)rKr:rOrPr@_chain_type_kwargsr"s r3from_chain_typezBaseRetrievalQA.from_chain_typeisU/4""/ # # &# *<# # sMM+BMfMMMr5question run_managerr List[Document]cdSz,Get documents to do question answering over.NrIr2rTrUs r3 _get_docszBaseRetrievalQA._get_docsxsr5inputsDict[str, Any]$Optional[CallbackManagerForChainRun]cx|ptj}||j}dtj|jjv}|r|||}n||}|j||| }|j r |j |d|iS|j |iS)hRun get_relevant_text and llm on input query. If chain has 'return_source_documents' as 'True', returns the retrieved documents as well under the key 'source_documents'. Example: .. code-block:: python res = indexqa({'query': 'This is my query'}) answer, docs = res['result'], res['source_documents'] rUrUinput_documentsrTr=r7) r get_noop_managerr%inspect signaturerZ parametersr"run get_childr)r'r2r[rU _run_managerrTaccepts_run_managerdocsanswers r3_callzBaseRetrievalQA._calls #S&@&Q&S&S $.) W.t~>>I I   ,>>( >EEDD>>(++D-11 8|?U?U?W?W2    ' -OV-?F FOV, ,r5r c KdSrXrIrYs r3 _aget_docszBaseRetrievalQA._aget_docss r5)Optional[AsyncCallbackManagerForChainRun]cK|ptj}||j}dtj|jjv}|r|||d{V}n||d{V}|j||| d{V}|j r |j |d|iS|j |iS)r_rUr`Nrar7) r rcr%rdrerprfr"arunrhr)r'ris r3_acallzBaseRetrievalQA._acalls #X&E&V&X&X $.) W.t??J J   3|LLLLLLLLDD22222222D388 8|?U?U?W?W9          ' -OV-?F FOV, ,r5)r.r/)NNN) r:rr;r<r=r r>r?r@rr.r!)rNN) r:rrOr$rPr?r@rr.r!rTr$rUr r.rV)N)r[r\rUr]r.r\rTr$rUr r.rV)r[r\rUrqr.r\)__name__ __module__ __qualname____doc____annotations__r%r'r)r model_configpropertyr4r9 classmethodrMrSrrZrnrprtrIr5r3r!r!s4366660IJ$)))))-: $L    X X,0#+/     [ :",0 N N N N[ N;;;^;=A - - - - -D;;;^;BF - - - - - - -r5r!z0.1.17c^eZdZUdZedZded<dd ZddZe ddZ dS) RetrievalQAaChain for question-answering against an index. This class is deprecated. See below for an example implementation using `create_retrieval_chain`: .. code-block:: python from langchain.chains import create_retrieval_chain from langchain.chains.combine_documents import create_stuff_documents_chain from langchain_core.prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI retriever = ... # Your retriever llm = ChatOpenAI() system_prompt = ( "Use the given context to answer the question. " "If you don't know the answer, say you don't know. " "Use three sentence maximum and keep the answer concise. " "Context: {context}" ) prompt = ChatPromptTemplate.from_messages( [ ("system", system_prompt), ("human", "{input}"), ] ) question_answer_chain = create_stuff_documents_chain(llm, prompt) chain = create_retrieval_chain(retriever, question_answer_chain) chain.invoke({"input": query}) Example: .. code-block:: python from langchain_community.llms import OpenAI from langchain.chains import RetrievalQA from langchain_community.vectorstores import FAISS from langchain_core.vectorstores import VectorStoreRetriever retriever = VectorStoreRetriever(vectorstore=FAISS(...)) retrievalQA = RetrievalQA.from_llm(llm=OpenAI(), retriever=retriever) T)excluder retrieverrTr$rUr r.rVcb|j|d|iS) Get docs.r=config)rinvokerhrYs r3rZzRetrievalQA._get_docss9~$$ k;+@+@+B+BC%   r5r crK|j|d|id{VS)rr=rN)rainvokerhrYs r3rpzRetrievalQA._aget_docss[^++ k;+@+@+B+BC,         r5cdS)Return the chain type. retrieval_qarIr1s r3 _chain_typezRetrievalQA._chain_type ~r5Nrurvr.r$) rwrxryrzrrr{rZrpr}rrIr5r3rrs++Z %uT222I2222          Xr5rceZdZUdZeddZded< dZded< d Zd ed < ee Z d ed< e de d dZ e de d dZd!dZd"dZed#dZdS)$ VectorDBQArT vectorstore)raliasrintk similarityr$ search_type)default_factoryr\ search_kwargsbefore)modevaluesrr.rc.tjd|S)NzR`VectorDBQA` is deprecated - please use `from langchain.chains import RetrievalQA`)warningswarn)rKrs r3raise_deprecationzVectorDBQA.raise_deprecation9s%   D    r5cLd|vr|d}|dvrtd|d|S)zValidate search type.r)rmmrsearch_type of not allowed.) ValueError)rKrrs r3validate_search_typezVectorDBQA.validate_search_typeBsD F " " /K"777 !M;!M!M!MNNN r5rTrUr rVc|jdkr |jj|fd|ji|j}nC|jdkr |jj|fd|ji|j}nt d|jd|S)rrrrrr)rrsimilarity_searchrrmax_marginal_relevance_searchr)r2rTrUrls r3rZzVectorDBQA._get_docsLs  | + +54#5 F&*&8DD  & &A4#A F&*&8DDNt/?NNNOO O r5r c$Ktd)rz!VectorDBQA does not support async)NotImplementedErrorrYs r3rpzVectorDBQA._aget_docs_s""EFFFr5cdS)r vector_db_qarIr1s r3rzVectorDBQA._chain_typehrr5N)rrr.rrurvr)rwrxryrzrrr{rrdictrrr~rrrZrpr}rrIr5r3rr$sABA$uTGGGKGGGG( AJJJJ+#K####E$)E$$?$?$?M????_(###[$#_(###[$#&GGGGXr5r)/rz __future__rrdrabcrtypingrrrr langchain_core._apir langchain_core.callbacksr r r langchain_core.documentsrlangchain_core.language_modelsrlangchain_core.promptsrlangchain_core.retrieversrlangchain_core.vectorstoresrpydanticrrrlangchain.chains.baser'langchain.chains.combine_documents.baser(langchain.chains.combine_documents.stuffrlangchain.chains.llmr#langchain.chains.question_answeringr0langchain.chains.question_answering.stuff_promptrr!rrrIr5r3rs=="""""",,,,,,,,,,,,****** .-----<<<<<<1111113333333333337777777777''''''MMMMMMHHHHHH))))))======LLLLLL    T d-d-d-d-d-ed-d-d-N    T IIIII/IIIX    T >>>>>>>>>>r5