m i):ddlmZddlZddlZddlmZddlmZddlm Z ddl m Z ddl m Z ddlmZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZddlmZmZmZddl m!Z!ej"e#Z$d%dZ%Gdde!Z&d&d"Z'Gd#d$eZ(dS)') annotationsN)Sequence)Any)CallbackManagerForChainRun)BaseLanguageModel) AIMessage)StrOutputParser)BasePromptTemplate) BaseRetriever)Runnable)Field)override)Chain)PROMPTQUESTION_GENERATOR_PROMPTFinishedOutputParser)LLMChainresponserreturntuple[list[str], list[float]]cg}g}|jddD]8}||d||d9||fS)z>Extract tokens and log probabilities from chat model response.logprobscontenttokenlogprob)response_metadataappend)rtokens log_probsrs C:\Users\Dell Inspiron 16\Desktop\tws\AgrotaPowerBi\back-agrota-powerbi\mcp-client-agrota\venv\Lib\site-packages\langchain_classic/chains/flare/base.py_extract_tokens_and_log_probsr!se FI+J7 B++ eGn%%%y)**** 9 cdeZdZUdZeZded< eed dZ e d dZ d S) QuestionGeneratorChainz4Chain that generates questions from uncertain spans.r promptrboolcdS)NF)clss r is_lc_serializablez)QuestionGeneratorChain.is_lc_serializable/s ur" list[str]c gdS)Input keys for the chain. user_inputcontextrr(selfs r input_keysz!QuestionGeneratorChain.input_keys4s5444r"N)rr&rr+) __name__ __module__ __qualname____doc__rr%__annotations__ classmethodrr*propertyr3r(r"r r$r$)sx>>!:F::::( X[555X555r"r$r Sequence[str]rSequence[float]min_probfloat min_token_gapintnum_pad_tokensr+cJ ddl}|||kd}nJ#t$r=tdddl fdt|D}YnwxYwfd|D}t|dkrgS|d|d|zdzgg}t|ddD]?\} } | |zdz} | || z |kr | |dd<(| | | g@fd|DS)NraNumPy not found in the current Python environment. FlareChain will use a pure Python implementation for internal calculations, which may significantly impact performance, especially for large datasets. For optimal speed and efficiency, consider installing NumPy: pip install numpycLg|] \}}|k|!Sr()exp).0idxlog_probmathr>s r z)_low_confidence_spans..Os>   Xxx!!H,, ,,,r"cJg|]}tjd|| S)z\w)research)rFirs r rJz)_low_confidence_spans..Ts.BBBQbivay&A&ABqBBBr"cPg|]"\}}d||#S))join)rFstartendrs r rJz)_low_confidence_spans..^s2 ? ? ?:5#BGGF59% & & ? ? ?r") numpywhererE ImportErrorloggerwarningrI enumeratelenr) rrr>r@rBnp_low_idxlow_idxspansrNrGrUrIs ` ` @r _low_confidence_spansra:s 88BFF9--899!<               !*9!5!5    CBBB(BBBG 7||q aj'!*~59 : ;EGABBK((%%3N"Q&  m + +E"IaLL LL#s $ $ $ $ ? ? ? ? ? ? ??s6<ABBceZdZUdZded< ded< eeZded< ded < d Zd ed < d Z ded< dZ ded< dZ ded< dZ ded< e d3dZe d3dZd4d"Zd5d%Z d6d7d+Ze d8d9d2Zd&S): FlareChainzFlare chain. Chain that combines a retriever, a question generator, and a response generator. See [Active Retrieval Augmented Generation](https://arxiv.org/abs/2305.06983) paper. r question_generator_chainresponse_chain)default_factoryr output_parserr retrieverg?r?r>rAr@rB max_iterTr&start_with_retrievalrr+cdgS)r-r/r(r1s r r3zFlareChain.input_keys}s ~r"cdgS)zOutput keys for the chain.rr(r1s r output_keyszFlareChain.output_keyss |r" questionsr/strr _run_managerrtuple[str, bool]c|}g}|D]/}||j|0dd|D}|j|||dd|i} t | tr| j} |j | \} } | | fS)Nz c3$K|] }|jV dSN) page_content)rFds r z,FlareChain._do_generation..s$;;an;;;;;;r"r. callbacks) get_childextendrhinvokerSre isinstancerrrgparse) r2rqr/rrsr{docsquestionr0resultmarginalfinisheds r _do_generationzFlareChain._do_generations!**,, ! 9 9H KK--h77 8 8 8 8++;;d;;;;;$++("$   ) $    fi ( ( $^F!/55f==(!!r"low_confidence_spansinitial_responseczfd|D}|}tjtr+j||}fd|D} nj|d|i} |d| dd | ||S) Ncg|]}|d S))r/current_responseuncertain_spanr()rFspanrr/s r rJz,FlareChain._do_retrieval..s;    )$4"&     r")r{c@g|]}|jjdS)r)rdrp)rFoutputr2s r rJz,FlareChain._do_retrieval..s9t4@CDr"r{)configzGenerated Questions: yellow colorrU)r|rrdrapplybatchon_textr) r2rrsr/rrquestion_gen_inputsr{question_gen_outputsrqs ` ` ` r _do_retrievalzFlareChain._do_retrievals"     -    !**,, d3X > > #'#@#F#F##$G$$ 2II 5;;##Y/<I  /I / /    ""9j(LQQQr"Ninputsdict[str, Any] run_manager!CallbackManagerForChainRun | Nonec |ptj}||jd}d}t|jD]!}|d|dd|d|d}t |j|d| i\}} t|| |j |j |j } |d zd|z} | s3| }|j|\} } | r|jd| icS|| |||| \}} |d z|z}| rn#|jd|iS) NrrRzCurrent Response: bluerrr.r{ )rget_noop_managerr3rangerlrr!rer~r|rar>r@rBstriprSrgrrpr)r2rrrsr/r_i_inputrrrrfinal_responserrs r _callzFlareChain._calls #S&@&Q&S&S DOA./  &&% % B  /X// !    %/28TTF =#** ,"8"8":":;!! FI $9 "# $$  (~~//#5G ' ++/+=+C+CH+M+M(A ,Q/@@@@!%!3!3$ "" Hh ~~''#-8H   #X..r" llmBaseLanguageModel | Nonemax_generation_lenkwargsrc  ddlm}n$#t$r}d}t||d}~wwxYw|||dd}nt||s'dt |jd}t |t|d d sd }t|t|d d}|"||krt d ||t|z}t|ztz} |d| |d|S)aHCreates a FlareChain from a language model. Args: llm: Language model to use. max_generation_len: Maximum length of the generated response. kwargs: Additional arguments to pass to the constructor. Returns: FlareChain class with the given language model. r) ChatOpenAIz_OpenAI is required for FlareChain. Please install langchain-openai.pip install langchain-openaiNT)max_completion_tokensr temperaturez-FlareChain.from_llm requires ChatOpenAI; got .rFzSProvided ChatOpenAI instance must be constructed with logprobs=True for FlareChain.rzFlareChain.from_llm: supplied llm max_completion_tokens=%s differs from requested max_generation_len=%s; leaving model unchanged.)rdrer()langchain_openairrXrtyper5 TypeErrorgetattr ValueErrorrYdebugrrr ) r)rrrremsg current_maxrequestion_gen_chains r from_llmzFlareChain.from_llms" * 3 3 3 3 3 3 3 * * */  c"" )  * ;*&8CC c:.. %-Cyy)--- nn$3 E22 &4!oo%!#'>EEK&;:L+L+L / &  #6<?P?PPs %7)     s *%*r4) rqr+r/rrrrrrsrrrt) rr+rsrr/rrrrrrrrrrtrw)rrrrrr)r)rrrrArrrrc)r5r6r7r8r9r rrgr>r@rBrlrmr;r3rprrrr:rr(r"r rcrcas'&&&>E*/%@T*U*U*UMUUUU?HHJMDN?H'!%%%%%* XX""""2$R$R$R$RR:>1/1/1/1/1/f#%= = = = [= = = r"rc)rrrr) rr<rr=r>r?r@rArBrArr+)) __future__rloggingrLcollections.abcrtypingrlangchain_core.callbacksrlangchain_core.language_modelsrlangchain_core.messagesrlangchain_core.output_parsersr langchain_core.promptsr langchain_core.retrieversr langchain_core.runnablesr pydanticr typing_extensionsrlangchain_classic.chains.baser&langchain_classic.chains.flare.promptsrrrlangchain_classic.chains.llmr getLoggerr5rYr!r$rarcr(r"r rs"""""" $$$$$$=<<<<<------999999555555333333------&&&&&&////// 211111  8 $ $55555X555"$@$@$@$@NV V V V V V V V V V r"