l idZddlmZddlZddlZddlZddlZddlZddlZddl m Z ddl m Z m Z mZmZddlmZddlmZmZddlZddlmZdd lmZmZmZdd lmZmZmZm Z m!Z!m"Z"dd l#m$Z$dd l%m&Z&dd l'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2m3Z3m4Z4ddl5m6Z6ddl7m8Z8ddl9m:Z:ddl;mZ>ddl?m@Z@mAZAddlBmCZCddlDmEZEddlFmGZGddlHmIZIddlJmKZKddlLmMZMddlNmOZOejPeQZRGdd e<ZSGd!d"e<ZTGd#d$e*eezZUGd%d&e*eVeezZWGd'd(eSZXGd)d*eTZYed+eCd,-Gd.d/eSZZed+eCd,-Gd0d1eSZ[Gd2d3e8Z\eVeezezZ]eXeYzZ^Gd4d5eKZ_dS)6zEChain that takes in an input and produces an action and action input.) annotationsN)abstractmethod) AsyncIteratorCallableIteratorSequence)Path)Anycast) deprecated) AgentAction AgentFinish AgentStep)AsyncCallbackManagerForChainRunAsyncCallbackManagerForToolRunBaseCallbackManagerCallbackManagerForChainRunCallbackManagerForToolRun Callbacks)OutputParserException)BaseLanguageModel) BaseMessage)BaseOutputParser)BasePromptTemplate)FewShotPromptTemplate)PromptTemplate)RunnableRunnableConfig ensure_config) AddableDict)BaseTool)get_color_mapping) BaseModel ConfigDictmodel_validator)Selfoverride)AGENT_DEPRECATION_WARNING)AgentExecutorIterator) AgentType) InvalidTool)Chain)LLMChain)asyncio_timeoutceZdZdZed&dZd'dZe d(d)dZe d(d)dZ eed&dZ d*dZ e d(d+dZ ed,dZed-fd Zd.d$Zd/d%ZxZS)0BaseSingleActionAgentzBase Single Action Agent class.return list[str]cdgSReturn values of the agent.outputselfs C:\Users\Dell Inspiron 16\Desktop\tws\AgrotaPowerBi\back-agrota-powerbi\mcp-client-agrota\venv\Lib\site-packages\langchain_classic/agents/agent.py return_valuesz#BaseSingleActionAgent.return_values: zlist[str] | NonecdS)Get allowed tools.Nr7r8s r:get_allowed_toolsz'BaseSingleActionAgent.get_allowed_tools?str=Nintermediate_stepslist[tuple[AgentAction, str]] callbacksrkwargsr AgentAction | AgentFinishc dS)0Given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. Nr7r9rBrDrEs r:planzBaseSingleActionAgent.planCr=c KdS)6Async given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. Nr7rIs r:aplanzBaseSingleActionAgent.aplanV r=cdSReturn the input keys.Nr7r8s r: input_keysz BaseSingleActionAgent.input_keysirKr=early_stopping_methodstr_rc \|dkrtddidSd|d}t|)Return response when agent has been stopped due to max iterations. Args: early_stopping_method: Method to use for early stopping. intermediate_steps: Steps the LLM has taken to date, along with observations. Returns: Agent finish object. Raises: ValueError: If `early_stopping_method` is not supported. forcer63Agent stopped due to iteration limit or time limit.'Got unsupported early_stopping_method ``r ValueErrorr9rTrBrVmsgs r:return_stopped_responsez-BaseSingleActionAgent.return_stopped_responsensM& !G + +PQ Q8MPPPoor=llmrtoolsSequence[BaseTool]callback_managerBaseCallbackManager | Nonec t)aConstruct an agent from an LLM and tools. Args: llm: Language model to use. tools: Tools to use. callback_manager: Callback manager to use. kwargs: Additional arguments. Returns: Agent object. NotImplementedError)clsrcrdrfrEs r:from_llm_and_toolsz(BaseSingleActionAgent.from_llm_and_toolss &"!r=ctz#Return Identifier of an agent type.rir8s r: _agent_typez!BaseSingleActionAgent._agent_type "!r= builtins.dictc t} |j}n#t$rd}YnwxYwt |t rt |j|d<n|||d<|S)zuReturn dictionary representation of agent. Returns: Dictionary representation of agent. N_type)super model_dumprorj isinstancer*rUvalue)r9rE_dictrs __class__s r:dictzBaseSingleActionAgent.dicts""$$ $EE"   EEE  eY ' ' # --E'NN  "E'N s + :: file_path Path | strNonecrt|trt|n|}|j}|dd|}d|vrd|d}t ||jdkrG|d5}tj ||d d d d d S#1swxYwYd S|j d rG|d5}tj ||d d d d d S#1swxYwYd S|d}t|)zSave the agent. Args: file_path: Path to file to save the agent to. Example: ```python # If working with agent executor agent.agent.save(file_path="path/agent.yaml") ``` Tparentsexist_okrsAgent z does not support saving.jsonwindentNz.yamlz.ymlFdefault_flow_style must be json or yaml)rvrUr parentmkdirrzrjsuffixopenjsondumpendswithyamlr_)r9r{ save_pathdirectory_path agent_dictrafs r:savezBaseSingleActionAgent.saves(2)S'A'APDOOOy ")TD999YY[[ * $ $94999C%c** *  w & &$$ 3 *a2222 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3   & &'8 9 9 "$$ C *aEBBBB C C C C C C C C C C C C C C C C C C555CS// !$B77B;>B;3DDDciS#Return logging kwargs for tool run.r7r8s r:tool_run_logging_kwargsz-BaseSingleActionAgent.tool_run_logging_kwargs r=r1r2r1r>NrBrCrDrrEr r1rFrTrUrBrCrVr r1r) rcrrdrerfrgrEr r1r0r1rUrEr r1rqr{r|r1r}r1rq)__name__ __module__ __qualname____doc__propertyr;rArrJrNrSrb classmethodrlror'rzrr __classcell__rys@r:r0r07s)) X $    ^ $ $    ^ $%%%^X%8 8< """"["("""X"X" " " " "Dr=r0ceZdZdZeddZd dZe d!d"dZe d!d"dZ eeddZ d#dZ ed$dZ e d%fd Zd&dZd'dZxZS)(BaseMultiActionAgentzBase Multi Action Agent class.r1r2cdgSr4r7r8s r:r;z"BaseMultiActionAgent.return_valuesr<r=r>cdS)zHGet allowed tools. Returns: Allowed tools. Nr7r8s r:rAz&BaseMultiActionAgent.get_allowed_toolss tr=NrBrCrDrrEr list[AgentAction] | AgentFinishc dS)a5Given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Actions specifying what tool to use. Nr7rIs r:rJzBaseMultiActionAgent.planrKr=c KdS)a;Async given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Actions specifying what tool to use. Nr7rIs r:rNzBaseMultiActionAgent.aplanrOr=cdSrQr7r8s r:rSzBaseMultiActionAgent.input_keysrKr=rTrUrVrc \|dkrtddidSd|d}t|)rXrYr6z$Agent stopped due to max iterations.r[r\r]r^r`s r:rbz,BaseMultiActionAgent.return_stopped_responsesC& !G + +*PQSUVV VP8MPPPoor=ctrnrir8s r:roz BaseMultiActionAgent._agent_type1rpr=rqc t}tjt5t |j|d<dddn #1swxYwY|S)*Return dictionary representation of agent.rsN)rtru contextlibsuppressrjrUror9rErxrys r:rzzBaseMultiActionAgent.dict6s""$$  !4 5 5 3 3 !122E'N 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 sAA#&A#r{r|r}crt|trt|n|}|}d|vrd|d}t ||j}|dd|jdkrG|d5}tj ||d d d d d S#1swxYwYd S|j d rG|d5}tj ||d d d d d S#1swxYwYd S|d}t|)aSave the agent. Args: file_path: Path to file to save the agent to. Raises: NotImplementedError: If agent does not support saving. ValueError: If `file_path` is not json or yaml. Example: ```python # If working with agent executor agent.agent.save(file_path="path/agent.yaml") ``` rsrz does not support saving.TrrrrrNrFrr)rvrUr rzrjrrrrrrrrr_)r9r{rrrarrs r:rzBaseMultiActionAgent.save>s"(2)S'A'APDOOOy YY[[ * $ $:4:::C%c** *")TD999  w & &$$ 3 *a2222 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3   & &'8 9 9 "$$ C *aEBBBB C C C C C C C C C C C C C C C C C C555CS// !rciSrr7r8s r:rz,BaseMultiActionAgent.tool_run_logging_kwargsdrr=rrrrBrCrDrrEr r1rrrrrr)rrrrrr;rArrJrNrSrbror'rzrrrrs@r:rrs\(( X $    ^ $ $    ^ $%%%^X%2"""X"X$"$"$"$"Lr=rc*eZdZdZeddZdS) AgentOutputParserz=Base class for parsing agent output into agent action/finish.textrUr1rFcdS)z$Parse text into agent action/finish.Nr7r9rs r:parsezAgentOutputParser.parselrKr=N)rrUr1rFrrrrrrr7r=r:rris8GG333^333r=rc*eZdZdZeddZdS) MultiActionAgentOutputParserzBase class for parsing agent output into agent actions/finish. This is used for agents that can return multiple actions. rrUr1rcdS)zParse text into agent actions/finish. Args: text: Text to parse. Returns: List of agent actions or agent finish. Nr7rs r:rz"MultiActionAgentOutputParser.parseyrKr=N)rrUr1rrr7r=r:rrqs>    ^   r=rceZdZUdZded< gZded<gZded<dZded < ed Z e dd Z e dd Z dddZ dddZdS) RunnableAgentAgent powered by Runnables.z)Runnable[dict, AgentAction | AgentFinish]runnabler2input_keys_argreturn_keys_argTboolstream_runnablearbitrary_types_allowedr1c|jSr5rr8s r:r;zRunnableAgent.return_values ##r=c|jSrRrr8s r:rSzRunnableAgent.input_keyss ""r=NrBrCrDrrEr rFc i|d|i}d}|jr,|j|d|iD] }||}||z } n|j|d|i}|SaPBased on past history and current inputs, decide what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. rBNrDconfigrrstreaminvoker9rBrDrEinputs final_outputchunks r:rJzRunnableAgent.plan"FFE02DEE   Y--fk9=U-VV * *'#(LL E)LL  *  =// Y?W/XXLr=cKi|d|i}d}|jr2|j|d|i23d{V}||} ||z }6n$|j|d|id{V}|SaRAsync based on past history and current inputs, decide what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. rBNrDrrrastreamainvokers r:rNzRunnableAgent.aplans"FFE02DEE    $}44#Y/ 5   * * * * * * *e '#(LL E)LL  "&!6!6#Y/"7""LArrrrrrr__annotations__rrrr$ model_configrr;rSrJrNr7r=r:rrs%%7777/ "N""""!#O#### O    : $L$$$X$###X# $"""""N $'''''''r=rceZdZUdZded< gZded<gZded<dZded < ed Z e dd Z e dd Z dddZ dddZdS)RunnableMultiActionAgentrz/Runnable[dict, list[AgentAction] | AgentFinish]rr2rrTrrrr1c|jSrrr8s r:r;z&RunnableMultiActionAgent.return_valuesrr=c|jS)QReturn the input keys. Returns: List of input keys. rr8s r:rSz#RunnableMultiActionAgent.input_keys s ""r=NrBrCrDrrEr rc i|d|i}d}|jr,|j|d|iD] }||}||z } n|j|d|i}|Srrrs r:rJzRunnableMultiActionAgent.planrr=cKi|d|i}d}|jr2|j|d|i23d{V}||} ||z }6n$|j|d|id{V}|Srrrs r:rNzRunnableMultiActionAgent.aplan7s"FFE02DEE    $}44#Y/ 5   * * * * * * *e '#(LL E)LL  "&!6!6#Y/"7""L rrrrrr7r=r:rrs%%====0 "N""""!#O#### O    : $L$$$X$###X# $"""""N $(((((((r=rz0.1.0z1.0)messageremovalceZdZUdZded< ded< ded< edd Zedfd Z dddZ dddZ ddZ xZ S)LLMSingleActionAgentz$Base class for single action agents.r- llm_chainr output_parserr2stopr1cVtt|jjdhz S)rrBlistsetrrSr8s r:rSzLLMSingleActionAgent.input_keysqs(C1226J5KKLLLr=rEr rqc Nt}|d=|Srrrtrzrs r:rzzLLMSingleActionAgent.dictz#  / " r=NrBrCrDrrFc l|jjd||j|d|}|j|S)a4Given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. rBrrDr7)rrunrrrr9rBrDrEr6s r:rJzLLMSingleActionAgent.plansR"$# 1      !''///r=c|K|jjd||j|d|d{V}|j|S)rMr Nr7)rarunrrrr s r:rNzLLMSingleActionAgent.aplanst"+t~* 1            !''///r=cVdt|jdkrdn |jddS)rr[r llm_prefixobservation_prefix)lenrr8s r:rz,LLMSingleActionAgent.tool_run_logging_kwargss5(+DI!(;(;""1   r=rrrrr) rrrrrrrSr'rzrJrNrrrs@r:rrbs /.$$$$$)OOO% MMMXMX $000008 $000002        r=rceZdZUdZded< ded< dZded< ed6fd Zd7dZe d8dZ e d8dZ d9dZ d:d;dZ d:d;dZdd#Ze ed>d$Zeed?d(Zed@d*ZeedAd+Ze dBdCd1ZdDd4ZdEd5ZxZS)FAgentzAgent that calls the language model and deciding the action. This is driven by a LLMChain. 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Args: intermediate_steps: Steps the LLM has taken to date, along with observations. **kwargs: User inputs. Returns: Full inputs for the LLMChain. agent_scratchpadr)r#r)r9rBrEr  new_inputss r:r%zAgent.get_full_inputss7--.@AA*2DJGG '&'J''r=cVtt|jjdhz S)rRr0rr8s r:rSzAgent.input_keys.s(C1226H5IIJJJr=aftermoder&cr|jj}d|jvrtd|jdt |tr|xjdz c_nGt |tr|xj dz c_ n!dt|}t||S)aCValidate that prompt matches format. Args: values: Values to validate. Returns: Validated values. Raises: ValueError: If `agent_scratchpad` is not in prompt.input_variables and prompt is not a FewShotPromptTemplate or a PromptTemplate. r0zl`agent_scratchpad` should be a variable in prompt.input_variables. Did not find it, so adding it at the end.z {agent_scratchpad}zGot unexpected prompt type ) rpromptinput_variablesloggerwarningappendrvrtemplaterrtyper_)r9r7ras r:validate_promptzAgent.validate_prompt3s& V%; ; ; NN=     " ) )*< = = =&.11 &#99F$9:: & !77 BDLLBB oo% r=rUcdS)z&Prefix to append the observation with.Nr7r8s r:rzAgent.observation_prefixQrKr=cdS)z#Prefix to append the LLM call with.Nr7r8s r:rzAgent.llm_prefixVrKr=rdrercdS)zCreate a prompt for this class. Args: tools: Tools to use. Returns: Prompt template. Nr7rkrds r: create_promptzAgent.create_prompt[rKr=r}cdS)zgValidate that appropriate tools are passed in. Args: tools: Tools to use. Nr7rBs r:_validate_toolszAgent._validate_toolsgrKr=c dS)z)Get default output parser for this class.Nr7)rkrEs r:_get_default_output_parserz Agent._get_default_output_parserorKr=rcrrfrgAgentOutputParser | Nonec ||t||||}d|D}|p|}|d|||d|S)aHConstruct an agent from an LLM and tools. 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Raises: ValueError: If `early_stopping_method` is not in ['force', 'generate']. rYr6rZr[generaterzB I now need to return a final answer based on the previous steps:r/zBearly_stopping_method should be one of `force` or `generate`, got Nr7) rrrrrrr&rrrvr_) r9rTrBrEr r!r"r1r(r) parsed_outputras r:rbzAgent.return_stopped_responses;( !G + +PQ  !J . .H'9  # FJ&R0R+RRRR V H/7 KKJ2V2z2K0$.0??;??K .44[AAM-55 %$$+6 DD D +( + + oor=c |j|jdS)rrrr8s r:rzAgent.tool_run_logging_kwargss/"&"9   r=rrr)rBrCr1rrr)rBrCrEr r1r-r1r&r)rdrer1r)rdrer1r})rEr r1r)NN) rcrrdrerfrgrrHrEr r1r)rTrUrBrCrEr r1rr)rrrrrrr'rzrArr;rr#rJrNr%rSr%r>rrrrrCrErGrlrbrrrs@r:rrs $$$$$)&*M****H X """"X   X     $555550 $<<<<<*((((&KKKXK_'"""#":555^X5222^X2   ^[    [ 888^[8 8<26 ! ! ! ! [! F5555n        r=rcleZdZUdZdZded< dZded< e ddd Ze dddZ dS) ExceptionToolz!Tool that just returns the query. _ExceptionrUrLzException tool descriptionNquery run_manager CallbackManagerForToolRun | Noner1c|Srr7r9r\r]s r:_runzExceptionTool._runs  r=%AsyncCallbackManagerForToolRun | Nonec K|Srr7r`s r:_arunzExceptionTool._aruns  r=r)r\rUr]r^r1rU)r\rUr]rbr1rU) rrrrrLrr[r'rardr7r=r:rYrYs++D'K''''" 9=X>BXr=rYcdeZdZUdZded< ded< dZded< d Zd ed < d Zd ed< dZded< dZ ded< dZ ded< e didjdZ e ddkd Ze d!e dld$Zedmd&Zednd*Zdnd+Z diddd,dod1Zedpd3Zedpd4Zdqd7Zdrd<Z didsdDZ didtdFZdudIZ didvdOZ didwdQZ didxdUZ didydVZ didzdXZ! did{dYZ" did|dZZ# did}d[Z$d~d_Z%dd`Z&e diddfZ'e diddhZ(d S) AgentExecutorzAgent that is using tools.7BaseSingleActionAgent | BaseMultiActionAgent | RunnableagentrerdFrreturn_intermediate_stepsz int | Nonemax_iterationsNz float | Nonemax_execution_timerYrUrTz3bool | str | Callable[[OutputParserException], str]handle_parsing_errorszNint | Callable[[list[tuple[AgentAction, str]]], list[tuple[AgentAction, str]]]trim_intermediate_stepsrDrrEr r1c |d|||d|S)zCreate from agent and tools. Args: agent: Agent to use. tools: Tools to use. callbacks: Callbacks to use. kwargs: Additional arguments. Returns: Agent executor object. )rhrdrDr7r7)rkrhrdrDrEs r:from_agent_and_toolsz"AgentExecutor.from_agent_and_tools"s5&s       r=r3r4r&c|j}|j}|}|?t|d|Dkr"d|dd|Dd}t ||S)zValidate that tools are compatible with agent. Args: values: Values to validate. Returns: Validated values. Raises: ValueError: If allowed tools are different than provided tools. Nch|] }|j Sr7rKrMs r: z/AgentExecutor.validate_tools..Ls-@ @ @ DI@ @ @ r=zAllowed tools (z!) different than provided tools (cg|] }|j Sr7rKrMs r:rPz0AgentExecutor.validate_tools..Qs#@#@#@$DI#@#@#@r=))rhrdrArr_)r9rhrdrras r:validate_toolszAgentExecutor.validate_tools<s  //11  $]););@ @ "'@ @ @ * * D-DD#@#@%#@#@#@DDD S// ! r=beforevaluesrzc|d}|rt|tr |j}|tt t zk}n9#t$rd}Yn+t$rt dd}YnwxYw| dd}|rt|||d<nt|||d<|S)zConvert runnable to agent if passed in. Args: values: Values to validate. Returns: Validated values. rhFz.Unexpected error getting OutputType from agentrT)rr)getrvr OutputTyperr r TypeError Exceptionr9 exceptionpoprr)rkryrh output_type multi_actionrs r:validate_runnable_agentz%AgentExecutor.validate_runnable_agentVs 7##  Zx00  N#.  +d;.?+.MM  % % %$  % % %  !QRRR$  % %jj):DAAO ":"$3###w #0"$3###w sA B "%B  B ,BaseSingleActionAgent | BaseMultiActionAgentcnt|jtrtd|jS|jS)aCType cast self.agent. If the `agent` attribute is a Runnable, it will be converted one of RunnableAgentType in the validate_runnable_agent root_validator. To support instantiating with a Runnable, here we explicitly cast the type to reflect the changes made in the root_validator. RunnableAgentType)rvrhrr r8s r: _action_agentzAgentExecutor._action_agentzs3 dj( + + 9+TZ88 8zr=r{r|r}c$d}t|)zRaise error - saving not supported for Agent Executors. Args: file_path: Path to save to. Raises: ValueError: Saving not supported for agent executors. zpSaving not supported for agent executors. If you are trying to save the agent, please use the `.save_agent(...)`)r_)r9r{ras r:rzAgentExecutor.saves ! oor=c6|j|S)zZSave the underlying agent. Args: file_path: Path to save to. )rr)r9r{s r: save_agentzAgentExecutor.save_agents !&&y111r=)include_run_infoasync_rrrr)c4t||||j|S)aPEnables iteration over steps taken to reach final output. Args: inputs: Inputs to the agent. callbacks: Callbacks to run. include_run_info: Whether to include run info. async_: Whether to run async. (Ignored) Returns: Agent executor iterator object. )tagsr)r)r)r9rrDrrs r:iterzAgentExecutor.iters,&%   -     r=r2c|jjSr)rrSr8s r:rSzAgentExecutor.input_keyss!,,r=cH|jrg|jjdS|jjS)zReturn the singular output key.rB)rirr;r8s r: output_keyszAgentExecutor.output_keyss3  ) MLT'5L7KL L!//r=rLr!c0d|jD|S)zwLookup tool by name. Args: name: Name of tool. 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" !!K6{CCC C C C C FFFFFK% P fk * * LLLL F)==I6((6#  L     ~%,          EKKKKK  sAA GE8GGcvK|r#|||jdd{V|j|vrz||j}|j}||j}|j}|rd|d<|j|jf|j||r|ndd|d{V} n|j}tj|jt| df|jd|r|ndd|d{V} t|| S)Nr)rrr[rrrr) rrrOrrrr rrr+rrrrs r:rz$AgentExecutor._aperform_agent_actions  -- .          0 0 0#L$56D .M!,"34E"0HHJJO 302 - ) '! 5@J+//111d !! " !!KK#0HHJJO 2 2+7+<,01A1F1F1H1H,I,I !  5@J+//111d ! !" ! !      K +FFFFr=cd|jD}td|jDddg}g}d}d}tj}|||r||||||} t | t r|| ||S|| t| d kr7| d} | | } | || ||S|d z }tj|z }||||j j |j |fi|} || ||S) z(Run text through and get agent response.ci|] }|j| Sr7rKrMs r:rz'AgentExecutor._call..)CCCDItCCCr=cg|] }|j Sr7rKrMs r:rPz'AgentExecutor._call.., . . .4TY . . .r=rredexcluded_colorsrr]r)rdr"timerrrvrrextendr_get_tool_returnrrbrT r9rr]rrrBrr start_timenext_step_outputnext_step_action tool_returnr6s r:_callzAgentExecutor._call"sDC CCC) . .4: . . .$e,   =?  Y[[ ##J == 4#33 "' 4   *K88 ||$& +$  % %&6 7 7 7#$$))#3A#6 "334DEE *<<#*$/( !OJ9;;3L7##J == 48<#;  &      ||F$6K|PPPr=c|Kd|jD}td|jDdg}g}d}d}tj} t|j4d{V|||r||||||d{V} t| tr0| | ||d{Vcdddd{VS| | t| d krO| d} | | } | 0| | ||d{Vcdddd{VS|d z }tj|z }||||j j|j|fi|} | | ||d{Vcdddd{VS#1d{VswxYwYdS#t t"jf$r:|j j|j|fi|} | | ||d{VcYSwxYw) z.Async run text through and get agent response.ci|] }|j| Sr7rKrMs r:rz(AgentExecutor._acall.._rr=cg|] }|j Sr7rKrMs r:rPz(AgentExecutor._acall..brr=rrrrNrr)rdr"rr.rlrrrvrrrrrrrbrT TimeoutErrorrrs r:_acallzAgentExecutor._acallXsRDC CCC) . .4: . . .$I   =?  Y[[ 4 &t'>??' ' ' ' ' ' ' ' ++J EE<-1-B-B(%*$/ .C..(((((($""2K@@%)]],.(3&3&&      ' ' ' ' ' ' ' ' ' ' ' ' ' '  '--.>???+,,11+;A+>(&*&;&;.rr=r6rr[N)rdrrr;rOrr)r9rrr"rreturn_value_keys r:rzAgentExecutor._get_tool_returns %5! kCC CCC# t!/ 0 01 4 4#1?B   !1 1 1 !23A 2!;/ tr=ct|jtr|jdkr||j dSt|jr||S|S)Nr)rvrorr)r9rBs r:rz)AgentExecutor._prepare_intermediate_stepssn t3S 9 9 G,q00%t'C&C&E&EF F D0 1 1 D//0BCC C!!r=inputdict[str, Any] | AnyrRunnableConfig | NoneIterator[AddableDict]c + Kt|}t|||df|d|d|d|ddd|}|Ed{VdS) zEnables streaming over steps taken to reach final output. Args: input: Input to the agent. config: Config to use. kwargs: Additional arguments. Yields: Addable dictionary. rDrmetadatarun_namerun_idTrrrr  yield_actionsNrr)r{)r9rrrEiterators r:rzAgentExecutor.streams"v&&(   JJ{ # #  F##ZZ ++ZZ ++::h''      r=AsyncIterator[AddableDict]c 0Kt|}t|||df|d|d|d|ddd|}|23d{V}|WV 6dS) zAsync enables streaming over steps taken to reach final output. 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Yields: Addable dictionary. rDrrrr Tr Nr )r9rrrEr steps r:rzAgentExecutor.astreams"v&&(   JJ{ # #  F##ZZ ++ZZ ++::h''      #       $JJJJJ#((sBr) rhrgrdrerDrrEr r1rfrW)ryrzr1r )r1rr) rr rDrrrrrr1r)r)rLrUr1r!)rrrrr1r)r6rrBrr]rr1r)r6rrBrr]rr1r)ryrr1r) rrrrrrrBrCr]rr1r) rrrrrrrBrCr]rr1r) rrrrrr r]rr1r) rrrrrrrBrCr]rr1r) rrrrrrrBrCr]rr1r) rrrrrr r]rr1r)rrr]rr1r)rrr]rr1r)rrr1r)rBrCr1rC)rrrrrEr r1r)rrrrrEr r1r))rrrrrrirkrlrTrmrorrqr%rwrrrr'rrrrSrrrrrrrrrrrrrrrrrrr7r=r:rfrfsC$$BBBB3-&+++++3!#N####9(,++++")((((RWVVVV      $     [ 2_'"""#"2_(###   [$# D   X X 2222 $ "'       6---X-000X0 > > > >YYYY:>     "?C " W W W W":>      4:> MMMMMh:> %G%G%G%G%GZ?C      6?C UUUUUx?C )G)G)G)G)G\:>4Q4Q4Q4Q4Qr?CGGGGGR* " " " ")-X<)-Xr=rf)`r __future__rrbuiltinsrrloggingrabcrcollections.abcrrrrpathlibr typingr r rlangchain_core._apir langchain_core.agentsr rrlangchain_core.callbacksrrrrrrlangchain_core.exceptionsrlangchain_core.language_modelsrlangchain_core.messagesrlangchain_core.output_parsersrlangchain_core.promptsrlangchain_core.prompts.few_shotrlangchain_core.prompts.promptrlangchain_core.runnablesrrrlangchain_core.runnables.utilsr langchain_core.toolsr!langchain_core.utils.inputr"pydanticr#r$r%typing_extensionsr&r'"langchain_classic._api.deprecationr('langchain_classic.agents.agent_iteratorr)$langchain_classic.agents.agent_typesr*langchain_classic.agents.toolsr+langchain_classic.chains.baser,langchain_classic.chains.llmr-#langchain_classic.utilities.asyncior. getLoggerrr9r0rrrrrrrrrYrrrfr7r=r:r0slKK""""""  GGGGGGGGGGGG  ******EEEEEEEEEE<;;;;;<<<<<<//////::::::555555AAAAAA888888LLLLLLLLLL666666))))))888888;;;;;;;;;;,,,,,,,,HHHHHHIIIIII::::::666666//////111111??????  8 $ $cccccIcccLIIIII9IIIX33333({)BC333     T+&45   (iiiii)iiiXnnnnn3nnnb  %  Q Q Q Q Q 0Q Q  Q h  %  T T T T T !T T  T nH2kK/);<!$<<L L L L L EL L L L L r=