o Jjg.@sZdZddlmZddlZddlZddlmZddlmZm 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 ddddGddde!Z,e ddddGddde,Z-e ddddGddde,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/v0.2/docs/versions/migrating_chains/retrieval_qa/)sinceremovalmessagec@seZdZUdZded< dZded<dZded<d Zd ed < ed d d dZ e d8ddZ e d8ddZ e   d9d:d d!Ze " d;dd?d0d1Zed@d3d4Z d>dAd6d7ZdS)BBaseRetrievalQAz)Base class for question-answering chains.rcombine_documents_chainquerystr input_keyresult output_keyFboolreturn_source_documentsTforbid)populate_by_namearbitrary_types_allowedextrareturn List[str]cCs|jgS)z,Input keys. :meta private: )r#selfr0Z/var/www/html/zoom/venv/lib/python3.10/site-packages/langchain/chains/retrieval_qa/base.py input_keys8szBaseRetrievalQA.input_keyscCs|jg}|jr |dg}|S)z-Output keys. :meta private: source_documents)r%r')r/ _output_keysr0r0r1 output_keys@s zBaseRetrievalQA.output_keysNllmrpromptOptional[PromptTemplate] callbacksr llm_chain_kwargsOptional[dict]kwargsrc KsZ|pt|}td |||d|pi}tdgdd}t|d||d} |d | |d|S) zInitialize from LLM.)r6r7r9 page_contentzContext: {page_content})input_variablestemplatecontext) llm_chaindocument_variable_namedocument_promptr9)r r9Nr0)r get_promptrrr) clsr6r7r9r:r<_promptrArCr r0r0r1from_llmKs* zBaseRetrievalQA.from_llmstuff chain_typechain_type_kwargscKs.|pi}t|fd|i|}|dd|i|S)zLoad chain from chain type.rIr Nr0r)rEr6rIrJr<_chain_type_kwargsr r0r0r1from_chain_typeis zBaseRetrievalQA.from_chain_typequestion run_managerr List[Document]cCdSz,Get documents to do question answering over.Nr0r/rMrNr0r0r1 _get_docsxszBaseRetrievalQA._get_docsinputsDict[str, Any]$Optional[CallbackManagerForChainRun]cCsz|pt}||j}dt|jjv}|r|j||d}n||}|jj||| d}|j r8|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'] rNrNinput_documentsrMr9r3) r get_noop_managerr#inspect signaturerS parametersr run get_childr'r%r/rTrN _run_managerrMaccepts_run_managerdocsanswerr0r0r1_calls     zBaseRetrievalQA._callr csdSrQr0rRr0r0r1 _aget_docsszBaseRetrievalQA._aget_docs)Optional[AsyncCallbackManagerForChainRun]cs|pt}||j}dt|jjv}|r"|j||dIdH}n||IdH}|jj||| dIdH}|j rB|j |d|iS|j |iS)rWrNrXNrYr3) r r[r#r\r]rgr^r arunr`r'r%rar0r0r1_acalls     zBaseRetrievalQA._acall)r,r-)NNN) r6rr7r8r9r r:r;r<rr,r)rHN) r6rrIr"rJr;r<rr,rrMr"rNr r,rO)N)rTrUrNrVr,rUrMr"rNr r,rO)rTrUrNrhr,rU)__name__ __module__ __qualname____doc____annotations__r#r%r'r model_configpropertyr2r5 classmethodrGrLrrSrfrgrjr0r0r0r1rsD          "  rz0.1.17c@sFeZdZUdZeddZded<dd d ZdddZe dddZ 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 retrieverrMr"rNr r,rOcCs|jj|d|idS) Get docs.r9config)rwinvoker`rRr0r0r1rSs zRetrievalQA._get_docsr cs |jj|d|idIdHS)rxr9ryN)rwainvoker`rRr0r0r1rgs  zRetrievalQA._aget_docscCrP)Return the chain type. retrieval_qar0r.r0r0r1 _chain_typezRetrievalQA._chain_typeNrkrlr,r") rmrnrorprrwrqrSrgrsrr0r0r0r1rus  -   ruc@seZdZUdZedddZded< dZded< d Zd ed < ee d Z d ed< e dde d%ddZ e dde d%ddZd&ddZd'd d!Zed(d"d#Zd$S)) VectorDBQArT vectorstore)rvaliasrintk similarityr" search_type)default_factoryrU search_kwargsbefore)modevaluesrr,rcCstd|S)NzR`VectorDBQA` is deprecated - please use `from langchain.chains import RetrievalQA`)warningswarn)rErr0r0r1raise_deprecation9szVectorDBQA.raise_deprecationcCs,d|vr|d}|dvrtd|d|S)zValidate search type.r)rmmrsearch_type of not allowed.) ValueError)rErrr0r0r1validate_search_typeBs zVectorDBQA.validate_search_typerMrNr rOcCsf|jdkr|jj|fd|ji|j}|S|jdkr*|jj|fd|ji|j}|Std|jd)rxrrrrr)rrsimilarity_searchrrmax_marginal_relevance_searchr)r/rMrNrdr0r0r1rSLs&  zVectorDBQA._get_docsr cs td)rxz!VectorDBQA does not support async)NotImplementedErrorrRr0r0r1rg_szVectorDBQA._aget_docscCrP)r} vector_db_qar0r.r0r0r1rhrzVectorDBQA._chain_typeN)rrr,rrkrlr)rmrnrorprrrqrrdictrrrtrrrSrgrsrr0r0r0r1r$s(       r)/rp __future__rr\rabcrtypingrrrrlangchain_core._apir langchain_core.callbacksr r r langchain_core.documentsr langchain_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_promptrrrurr0r0r0r1sN               ( L