gh2dZddlmZddlZddlZddlZddlZddlZddlm Z ddl m Z m Z m Z ddlmZddlmZmZmZmZmZddlZddlmZdd lmZmZmZdd lmZmZm Z m!Z!m"Z"m#Z#dd l$m%Z%dd l&m'Z'dd l(m)Z)ddl*m+Z+ddl,m-Z-ddl.m/Z/ddl0m1Z1ddl2m3Z3m4Z4m5Z5ddl6m7Z7ddl8m9Z9ddl:m;Z;ddlZ>m?Z?ddl@mAZAddlBmCZCddlDmEZEddlFmGZGddlHmIZIddlJmKZKddlLmMZMddlNmOZOejPeQZRGdd e=ZSGd!d"e=ZTGd#d$e+eeefZUGd%d&e+eeVeefZWGd'd(eSZXGd)d*eTZYed+eCd,-Gd.d/eSZZed+eCd,-Gd0d1eSZ[Gd2d3e9Z\eVeeeefZ]eeXeYfZ^Gd4d5eKZ_dS)6zEChain that takes in an input and produces an action and action input.) annotationsN)abstractmethod) AsyncIteratorIteratorSequence)Path)AnyCallableOptionalUnioncast) deprecated) AgentAction AgentFinish AgentStep)AsyncCallbackManagerForChainRunAsyncCallbackManagerForToolRunBaseCallbackManagerCallbackManagerForChainRunCallbackManagerForToolRun Callbacks)OutputParserException)BaseLanguageModel) BaseMessage)BaseOutputParser)BasePromptTemplate)FewShotPromptTemplate)PromptTemplate)RunnableRunnableConfig ensure_config) AddableDict)BaseTool)get_color_mapping) BaseModel ConfigDictmodel_validator)Self)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+dZd,fd Zd-d#Zd.d$ZxZS)/BaseSingleActionAgentzBase Single Action Agent class.return list[str]cdgSReturn values of the agent.outputselfs S/var/www/FlaskApp/flask-venv/lib/python3.11/site-packages/langchain/agents/agent.py return_valuesz#BaseSingleActionAgent.return_values< zOptional[list[str]]cdSNr8r9s r;get_allowed_toolsz'BaseSingleActionAgent.get_allowed_toolsAstr>Nintermediate_stepslist[tuple[AgentAction, str]] callbacksrkwargsr Union[AgentAction, AgentFinish]c 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. Nr8r:rCrErFs r;planzBaseSingleActionAgent.planDr>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. Nr8rJs r;aplanzBaseSingleActionAgent.aplanW r>cdS7Return the input keys. :meta private: Nr8r9s r; input_keysz BaseSingleActionAgent.input_keysjrLr>early_stopping_methodstrrc X|dkrtddidStd|d)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. **kwargs: User inputs. Returns: AgentFinish: Agent finish object. Raises: ValueError: If `early_stopping_method` is not supported. forcer73Agent stopped due to iteration limit or time limit.'Got unsupported early_stopping_method ``r ValueErrorr:rUrCrFs r;return_stopped_responsez-BaseSingleActionAgent.return_stopped_responsersP( !G + +PQSU R:ORRR r>llmrtoolsSequence[BaseTool]callback_managerOptional[BaseCallbackManager]c t)a.Construct 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: BaseSingleActionAgent: Agent object. NotImplementedError)clsrbrcrerFs r;from_llm_and_toolsz(BaseSingleActionAgent.from_llm_and_toolss &"!r>ctz#Return Identifier of an agent type.rhr9s r; _agent_typez!BaseSingleActionAgent._agent_type "!r> builtins.dictc t} |j}n#t$rd}YnwxYwt |t rt |j|d<n|||d<|S)z{Return dictionary representation of agent. Returns: Dict: Dictionary representation of agent. N_type)super model_dumprnri isinstancer+rVvalue)r:rF_dictrr __class__s r;dictzBaseSingleActionAgent.dicts ""$$ $EE"   EEE  eY ' ' # --E'NN  "E'N s + :: file_pathUnion[Path, str]NonecXt|trt|}n|}|j}|dd|}d|vrt d|d|jdkrBt|d5}tj ||d d d d d S#1swxYwYd S|j d rBt|d5}tj ||d d d d d S#1swxYwYd St|d)zSave the agent. Args: file_path: Path to file to save the agent to. 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""""["("""X""!B!B!B!BFr>r1ceZdZdZeddZddZe d d!dZe d d!dZ eeddZ d"dZ ed#dZ d$fd Z d%dZd&dZxZS)'BaseMultiActionAgentzBase Multi Action Agent class.r2r3cdgSr5r8r9s r;r<z"BaseMultiActionAgent.return_valuesr=r>r?cdS)z]Get allowed tools. Returns: Optional[List[str]]: Allowed tools. Nr8r9s r;rBz&BaseMultiActionAgent.get_allowed_toolss tr>NrCrDrErrFr %Union[list[AgentAction], AgentFinish]c dS)a5Given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Actions specifying what tool to use. Nr8rJs r;rKzBaseMultiActionAgent.planrLr>c KdS)a;Async given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Actions specifying what tool to use. Nr8rJs r;rOzBaseMultiActionAgent.aplanrPr>cdSrRr8r9s r;rTzBaseMultiActionAgent.input_keysrLr>rUrVrc X|dkrtddidStd|d)rXrYr7z$Agent stopped due to max iterations.r[r\r]r^r`s r;raz,BaseMultiActionAgent.return_stopped_response!sG( !G + +*PQSUVV VR:ORRR r>ctrmrhr9s r;rnz BaseMultiActionAgent._agent_type=ror>rpc t} t|j|d<n#t$rYnwxYw|S)*Return dictionary representation of agent.rr)rsrtrVrnrir:rFrwrxs r;ryzBaseMultiActionAgent.dictBsX""$$  !122E'NN"    D  s; AArzr{r|cXt|trt|}n|}|}d|vrt d|d|j}|dd|jdkrBt|d5}tj ||d d d d d S#1swxYwYd S|j d rBt|d5}tj ||d d d d d S#1swxYwYd St|d)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. 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Args: text: Text to parse. Returns: Union[List[AgentAction], AgentFinish]: List of agent actions or agent finish. Nr8rs r;rz"MultiActionAgentOutputParser.parserLr>N)rrVr2rrr8r>r;rrs>     ^    r>rceZdZUdZded< gZded<gZded<dZded < ed Z e dd Z e dd Z dddZ dddZdS) RunnableAgentAgent powered by Runnables.z/Runnable[dict, Union[AgentAction, AgentFinish]]runnabler3input_keys_argreturn_keys_argTboolstream_runnablearbitrary_types_allowedr2c|jSr6rr9s r;r<zRunnableAgent.return_values ##r>c|jS)zReturn the input keys.rr9s r;rTzRunnableAgent.input_keyss ""r>NrCrDrErrFr rGc 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. rCNrEconfigrrstreaminvoker:rCrErFinputs final_outputchunks r;rKzRunnableAgent.plans"JFI35GHI   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. rCNrErrrastreamainvokers r;rOzRunnableAgent.aplans(JFI35GHI    $}44 Y7 5   * * * * * * *e '#(LL E)LL   "&!6!6 Y7"7""LArrArrrrr__annotations__rrrr& model_configrr<rTrKrOr8r>r;rrs%%====/ "N""""!#O#### O    : $L$$$X$###X# $"""""N $(((((((r>rceZdZUdZded< gZded<gZded<dZded < ed Z e dd Z e dd Z dddZ dddZdS)RunnableMultiActionAgentrz5Runnable[dict, Union[list[AgentAction], AgentFinish]]rr3rrTrrrr2c|jSrrr9s r;r<z&RunnableMultiActionAgent.return_valuesrr>c|jS)QReturn the input keys. Returns: List of input keys. rr9s r;rTz#RunnableMultiActionAgent.input_keyss ""r>NrCrDrErrFr rc i|d|i}d}|jr,|j|d|iD] }||}||z } n|j|d|i}|Srrrs r;rKzRunnableMultiActionAgent.plan$s(JFI35GHI   Y--fk9=U-VV * *'#(LL E)LL  *  =// Y?W/XXLr>cKi|d|i}d}|jr2|j|d|i23d{V}||} ||z }6n$|j|d|id{V}|Srrrs r;rOzRunnableMultiActionAgent.aplanKs(JFI35GHI    $}44 Y7 5   * * * * * * *e '#(LL E)LL   "&!6!6 Y7"7""LrrrArrr8r>r;rrs%%CCCC0 "N""""!#O#### O    : $L$$$X$###X# $%%%%%T $)))))))r>rz0.1.0z1.0)messageremovalceZdZUdZded< ded< ded< edd Zdfd Z dddZ dddZ ddZ xZ S)LLMSingleActionAgentz$Base class for single action agents.r. llm_chainr output_parserr3stopr2cVtt|jjdhz S)rrClistsetrrTr9s r;rTzLLMSingleActionAgent.input_keyss(C1226J5KKLLLr>rFr rpc Nt}|d=|Srrrsryrs r;ryzLLMSingleActionAgent.dict!  / " r>NrCrDrErrGc 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. rCrrEr8)rrunrrrr:rCrErFr7s r;rKzLLMSingleActionAgent.plansR"$# 1      !''///r>c|K|jjd||j|d|d{V}|j|S)rNrNr8)rarunrrrrs r;rOzLLMSingleActionAgent.aplanst"+t~* 1            !''///r>cVdt|jdkrdn |jddS)rr[r llm_prefixobservation_prefix)lenrr9s r;rz,LLMSingleActionAgent.tool_run_logging_kwargss5(+DI!(;(;""1   r>rrrArr) rrrrrrrTryrKrOrrrs@r;rrws /.$$$$$)OOO% MMMXM $000008 $000002        r>rceZdZUdZded< ded< dZded< d8fd Zd9dZed:dZ d;dZ ed:dZ ddZ d=d>dZd?dZed:d Zed!"d@d$ZeedAd%ZeedAd&ZeedBd*ZedCd,ZeedDd-Ze dEdFd3ZdGd6ZdHd7ZxZS)IAgentzAgent that calls the language model and deciding the action. This is driven by a LLMChain. The prompt in the LLMChain MUST include a variable called "agent_scratchpad" where the agent can put its intermediary work. r.rrrNr? allowed_toolsrFr r2rpc Nt}|d=|Srrrs r;ryz Agent.dictrr>c|jS)zGet allowed tools.)rr9s r;rBzAgent.get_allowed_toolss !!r>r3cdgSr5r8r9s r;r<zAgent.return_valuesr=r>rrVc td)zsFix the text. Args: text: Text to fix. Returns: str: Fixed text. z(fix_text not implemented for this agent.r_rs r; _fix_textzAgent._fix_textsCDDDr>crd|jd|jgS)N z )r rstripr9s r;_stopz Agent._stopsB 4(//11 3 3 54*1133 5 5  r>rCrDUnion[str, list[BaseMessage]]c\d}|D]&\}}||jz }|d|j|d|jz }'|S)zJConstruct the scratchpad that lets the agent continue its thought process.r[r)logr r )r:rCthoughtsaction observations r;_construct_scratchpadzAgent._construct_scratchpadsW#5 W W FK  "H VT4VkVVT_VV VHHr>rErrGc z|j|fi|}|jjdd|i|}|j|S)rIrEr8)get_full_inputsrpredictrr)r:rCrErF full_inputs full_outputs r;rKz Agent.plansU"+d*+=HHHH ,dn,PPyPKPP !'' 444r>cK|j|fi|}|jjdd|i|d{V}|j|d{V}|S)rNrENr8)r!rapredictraparse)r:rCrErFr#r$ agent_outputs r;rOz Agent.aplan#s"+d*+=HHHH 3DN3WWiW;WWWWWWWW !/66{CCCCCCCC r>builtins.dict[str, Any]c P||}||jd}i||}|S)a1Create the full inputs for the LLMChain from intermediate steps. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. **kwargs: User inputs. Returns: Dict[str, Any]: Full inputs for the LLMChain. agent_scratchpadr)rr)r:rCrFr new_inputsr#s r;r!zAgent.get_full_inputs9s<--.@AA*2DJGG ..:. r>cVtt|jjdhz S)rSr,rr9s r;rTzAgent.input_keysKs( C1226H5IIJJJr>aftermoder(cn|jj}d|jvrtd|jdt |tr|xjdz c_nEt |tr|xj dz c_ ntdt||S)aFValidate that prompt matches format. Args: values: Values to validate. Returns: Dict: Validated values. Raises: ValueError: If `agent_scratchpad` is not in prompt.input_variables and prompt is not a FewShotPromptTemplate or a PromptTemplate. r,zl`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_variablesloggerwarningappendrurtemplaterrr_type)r:r3s r;validate_promptzAgent.validate_promptSs& V%; ; ; NN=     " ) )*< = = =&.11 O#99F$9:: O !77  !MtF||!M!MNNN r>cdS)z&Prefix to append the observation with.Nr8r9s r;r zAgent.observation_prefixprLr>cdS)z#Prefix to append the LLM call with.Nr8r9s r;r zAgent.llm_prefixurLr>rcrdrcdS)zCreate a prompt for this class. Args: tools: Tools to use. Returns: BasePromptTemplate: Prompt template. Nr8rjrcs r; create_promptzAgent.create_promptzrLr>r|cdS)zgValidate that appropriate tools are passed in. Args: tools: Tools to use. Nr8r>s r;_validate_toolszAgent._validate_toolss  r>c dS)z)Get default output parser for this class.Nr8)rjrFs r;_get_default_output_parserz Agent._get_default_output_parserrLr>rbrrerfOptional[AgentOutputParser]c ||t||||}d|D}|p|}|d|||d|S)aOConstruct an agent from an LLM and tools. Args: llm: Language model to use. tools: Tools to use. callback_manager: Callback manager to use. output_parser: Output parser to use. kwargs: Additional arguments. Returns: Agent: Agent object. )rbr3recg|] }|j Sr8name.0tools r; z,Agent.from_llm_and_tools..s222Ddi222r>)rrrr8)rAr.r?rC) rjrbrcrerrFr tool_names_output_parsers r;rkzAgent.from_llm_and_toolss* E"""$$U++-   32E222 &J#*H*H*J*Js $(      r>rUrc |dkrtddidS|dkrd}|D]&\}}||jz }|d|j|d|jz }'|dz }||jd}i||}|jjd i|} |j| } t| tr| Std| i| Std |) aReturn response when agent has been stopped due to max iterations. Args: early_stopping_method: Method to use for early stopping. intermediate_steps: Steps the LLM has taken to date, along with observations. **kwargs: User inputs. Returns: AgentFinish: Agent finish object. Raises: ValueError: If `early_stopping_method` is not in ['force', 'generate']. rYr7rZr[generaterzB I now need to return a final answer based on the previous steps:r+zBearly_stopping_method should be one of `force` or `generate`, got Nr8) rrr r rrr"rrrur_) r:rUrCrFrrrr-r#r$ parsed_outputs r;razAgent.return_stopped_responses;( !G + +PQSU #j 0 0H'9  # FJ&R0R+RRRR V H/7 KKJ2V2z2K0$.0??;??K .44[AAM-55 I$$#Hk#:KHHH/,// r>c |j|jdS)rrrr9s r;rzAgent.tool_run_logging_kwargss/"&"9   r>rrr)rrVr2rV)rCrDr2rrAr)rCrDrFr r2r)r2r(r)rcrdr2r)rcrdr2r|)rFr r2r)NN) rbrrcrdrerfrrDrFr r2r rr)rrrrrrryrBrr<rrrrKrOr!rTr'r:rr r rr?rArCrkrarrrs@r;r r s $$$$$))-M----F """"X E E E E   X  $555550 $,$KKKXK_'"""#"8555^X5222^X2   ^[    [ 888^[8 ;?59 ! ! ! ! [! F5555n        r>r cLeZdZUdZdZded< dZded< ddd Z dddZdS) ExceptionToolz!Tool that just returns the query. _ExceptionrVrHzException tool descriptionNquery run_manager#Optional[CallbackManagerForToolRun]r2c|SrAr8r:rXrYs r;_runzExceptionTool._runs  r>(Optional[AsyncCallbackManagerForToolRun]c K|SrAr8r\s r;_arunzExceptionTool._aruns  r>rA)rXrVrYrZr2rV)rXrVrYr^r2rV) rrrrrHrrWr]r`r8r>r;rUrUs++D'K''''" <@AEr>rUc4eZdZUdZded< ded< dZded< d Zd ed < d Zd ed< dZded< dZ ded< dZ ded< e didjdZ e ddkd Ze d!e dld$Zedmd&Zdnd*Zdnd+Z diddd,dod1Zedpd3Zedpd4Zdqd7Zdrd<Z didsdDZ didtdFZdudIZ didvdOZ didwdQZ didxdUZ didydVZ didzdXZ did{dYZ! did|dZZ" did}d[Z#d~d_Z$dd`Z% diddfZ& diddhZ'd S) AgentExecutorzAgent that is using tools.r/r0r(c|j}|j}|}|Jt|td|Dkr t d|dd|Dd|S)aValidate that tools are compatible with agent. Args: values: Values to validate. Returns: Dict: Validated values. Raises: ValueError: If allowed tools are different than provided tools. Ncg|] }|j Sr8rGrIs r;rLz0AgentExecutor.validate_tools..ns)F)F)F$))F)F)Fr>zAllowed tools (z!) different than provided tools (cg|] }|j Sr8rGrIs r;rLz0AgentExecutor.validate_tools..qs'D'D'Dd 'D'D'Dr>))rdrcrBrr_)r:rdrcrs r;validate_toolszAgentExecutor.validate_tools]s  //11  $=!!S)F)F)F)F)F%G%GGG HmHH'D'De'D'D'DHHH r>beforevaluesryct|d}|rt|tr |j}|tt t tfk}n#t$r }d}Yd}~nd}~wwxYw| dd}|rt|||d<nt|||d<|S)zConvert runnable to agent if passed in. Args: values: Values to validate. Returns: Dict: Validated values. rdFNrT)rr) getrur OutputTyper rrr Exceptionpoprr)rjrtrd output_type multi_action_rs r;validate_runnable_agentz%AgentExecutor.validate_runnable_agentus 7##  Zx00  T#.  +eD4E{4R.SS  % % %$  % %jj):DAAO ":"O###w#0"O###w sA A4(A//A42Union[BaseSingleActionAgent, BaseMultiActionAgent]cxt|jtrtt|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. )rurdrr RunnableAgentTyper9s r; _action_agentzAgentExecutor._action_agents3 dj( + + )4:66 6: r>rzr{r|c td)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(...)`rr:rzs r;rzAgentExecutor.saves !   r>c6|j|S)zZSave the underlying agent. Args: file_path: Path to save to. )rrrs r; save_agentzAgentExecutor.save_agents !&&y111r>)include_run_infoasync_rrrr*c4t||||j|S)agEnables 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: AgentExecutorIterator: Agent executor iterator object. )tagsr)r*r)r:rrErrs r;iterzAgentExecutor.iters,&%   -     r>r3c|jjS)rS)rrTr9s r;rTzAgentExecutor.input_keyss !,,r>cH|jr|jjdgzS|jjS)z@Return the singular output key. :meta private: rC)rerr<r9s r; output_keyszAgentExecutor.output_keyss0  ) 4%37K6LL L%3 3r>rHr#c0d|jD|S)zLookup tool by name. Args: name: Name of tool. Returns: BaseTool: Tool object. ci|] }|j| Sr8rGrIs r; z-AgentExecutor.lookup_tool..s777D 4777r>)rc)r:rHs r; lookup_toolzAgentExecutor.lookup_tools87DJ777==r> iterationsint time_elapsedfloatcV|j ||jkrdS|j ||jkrdSdS)NFT)rgrh)r:rrs r;_should_continuezAgentExecutor._should_continues>   *zT=P/P/P5  # / 7775tr>r7rrCrrY$Optional[CallbackManagerForChainRun]dict[str, Any]cj|r||d|j|j}|jr||d<|SNgreen)colorverboserCon_agent_finishrr<rer:r7rCrYrs r;_returnzAgentExecutor._returnsO  U  ' 'gt| ' T T T+  ) D1CL- .r>)Optional[AsyncCallbackManagerForChainRun]czK|r#||d|jd{V|j}|jr||d<|Srrrs r;_areturnzAgentExecutor._areturn s{  --gt|.       +  ) D1CL- .r>NextStepOutput1Union[AgentFinish, list[tuple[AgentAction, str]]]ct|dtrt|dksJ|dSd|DS)NrjcTg|]%}t|t|j|jf&Sr8)rurrrrJas r;rLz4AgentExecutor._consume_next_step..!s@./Z9=U=U1=)r>)rurr )r:rts r;_consume_next_stepz AgentExecutor._consume_next_steps\ fRj+ . . v;;!####": 39 r>name_to_tool_mapdict[str, BaseTool] color_mappingdict[str, str]rDc n|d||||||DS)Ncg|]}|Sr8r8rs r;rLz1AgentExecutor._take_next_step...s(      r>)r_iter_next_stepr:rrrrCrYs r;_take_next_stepzAgentExecutor._take_next_step%sW&&  --$!&       r>4Iterator[Union[AgentFinish, AgentAction, AgentStep]]c#K ||}|jj|fd|r|ndi|}n#t$r}t |jtr |j }nd}|rtdt|t|} t |jtr3|j r)t|j } t|j } n^d} n[t |jtr|j} n9t|jr||} ntdtd| | }|r||d |j} t#j|jf|jd|r|ndd | } t+|| VYd}~dSd}~wwxYwt |t,r|VdSt |tr|g} n|} | D]} | V| D]} |||| |VdS) Take a single step in the thought-action-observation loop. Override this to take control of how the agent makes and acts on choices. rENFAn output parsing error occurred. In order to pass this error back to the agent and have it try again, pass `handle_parsing_errors=True` to the AgentExecutor. This is the error: Invalid or incomplete response.Got unexpected type of `handle_parsing_errors`rVrrrrrErr)_prepare_intermediate_stepsrrK get_childrrurirr_rV send_to_llmr llm_outputcallableron_agent_actionrrUr tool_inputrrr_perform_agent_action)r:rrrrCrYr7e raise_errorrrtool_run_kwargsactions agent_actions r;rzAgentExecutor._iter_next_step:s. !%!A!ABT!U!U -T',"5@J+//111dFF %% % % $4d;; $"&"<< #   3+.a&&33 q66D$4d;; S=C"%am"4"4Kq|,,DD"BKKD6<< S"8 $455 S"88;;  !QRRR {DAAF C++F'+BBB"0HHJJO--//-! 5@J+//111d  " K6{CCC C C C FFFFFK% P fk * * LLL F fk * * hGGG#  L    #  L,, -{      sAA G-FG((G-rrrcB|r||d|j|vrt||j}|j}||j}|j}|rd|d<|j|jf|j||r|ndd|} ny|j}tj|jt| df|jd|r|ndd|} t|| S)Nrrr[r rrequested_tool_nameavailable_tool_namesr) rrK return_directrrrrrrr,rkeysr r:rrrrYrKrrrrs r;rz#AgentExecutor._perform_agent_actionso  E  ' ' G ' D D D   0 0 0#L$56D .M!,"34E"0HHJJO 302 -"$(' 5@J+//111d  " KK#0HHJJO++--++7+<,01A1F1F1H1H,I,I   5@J+//111d  "  K +FFFFr>c ~K|d||||||2d{VS)Nc$Kg|3d{V }| 6SrAr8rs r;rLz2AgentExecutor._atake_next_step..sO             s)r_aiter_next_steprs r;_atake_next_stepzAgentExecutor._atake_next_stepsy&&  #44$!&               r>9AsyncIterator[Union[AgentFinish, AgentAction, AgentStep]]cK |}jj|fdrndi|d{V}n#t$r}t jtr j }nd}|rtdt|t|} t jtr3|j r)t|j } t|j } n^d} n[t jtrj} n9tjr|} ntdtd| | }j} t!j|jfjdrndd| d{V} t)|| WVYd}~dSd}~wwxYwt |t*r|WVdSt |tr|g} n|} | D]} | WVt-jfd | Dd{V}|D]}|WVdS) rrENFrrrrVrrc@g|]}|Sr8)_aperform_agent_action)rJrrrrYr:s r;rLz2AgentExecutor._aiter_next_step.. sD!++$m\;r>)rrrOrrrurirr_rVrrrrrrrUrrrrrasynciogather)r:rrrrCrYr7rrrrrrrresultrs``` ` r;rzAgentExecutor._aiter_next_stepsk, !%!A!ABT!U!U 44-3"5@J+//111dFF %# # # $4d;; $"&"<< #   3+.a&&33 q66D$4d;; S=C"%am"4"4Kq|,,DD"BKKD6<< S"8 $455 S"88;;  !QRRR {DAAF"0HHJJO 4  4!! 5@J+//111d !! " !!K6{CCC C C C C FFFFFG# L fk * * LLLL F fk * * hGGG#  L     ~%,          EKKKKK  sAA G%E?G  G%cvK|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[r rrr) rrrKrrrrrrr,rrrrs r;rz$AgentExecutor._aperform_agent_actions  --dl'.          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| Sr8rGrIs r;rz'AgentExecutor._call..HCCCDItCCCr>cg|] }|j Sr8rGrIs r;rLz'AgentExecutor._call..K . . .4TY . . .r>rredexcluded_colorsrrYr)rcr$timerrrurrextendr _get_tool_returnrrarU r:rrYrrrCrr start_timenext_step_outputnext_step_action tool_returnr7s r;_callzAgentExecutor._callAsDC CCC) . .4: . . .%@P   =?  Y[[ ##J == 4#33 "' 4   *K88 ||$&8k$  % %&6 7 7 7#$$))#3A#6 "334DEE *<<#%7[( !OJ9;;3L/##J == 40<#;  &(:  >D  ||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| Sr8rGrIs r;rz(AgentExecutor._acall..wrr>cg|] }|j Sr8rGrIs r;rLz(AgentExecutor._acall..zrr>rrrrNrr)rcr$rr/rhrrrurrrr rrrarU TimeoutErrorrrs r;_acallzAgentExecutor._acallpsIDC CCC) . .4: . . .    =?  Y[[ * &t'>??! ! ! ! ! ! ! ! ++J EE<-1-B-B(%*$/ .C..(((((($""2K@@%)]],.(3&3&&      ! ! ! ! ! ! ! ! ! ! ! ! ! !  '--.>???+,,11+;A+>(&*&;&;BHF* '     sRG+)A*GG+&A$G G+A(GG+ G""G+%G"&G++A H;:H;rtuple[AgentAction, str]Optional[AgentFinish]c|\}}d|jD}d}t|jjdkr|jjd}|j|vr$||jjrt ||idSdS)z&Check if the tool is a returning tool.ci|] }|j| Sr8rGrIs r;rz2AgentExecutor._get_tool_return..rr>r7rr[N)rcr rr<rKrr)r:rrrrreturn_value_keys r;rzAgentExecutor._get_tool_returns%5! kCC CCC# t!/ 0 01 4 4#1?B    0 0 0 12@ "%{3tr>ct|jtr|jdkr||j dSt|jr||S|S)Nr)rurkrr)r:rCs r;rz)AgentExecutor._prepare_intermediate_stepssl t3S 9 9 &,q00%t'C&C&E&EF F d2 3 3 &//0BCC C% %r>inputUnion[dict[str, Any], Any]rOptional[RunnableConfig]Iterator[AddableDict]c + Kt|}t|||df|d|d|d|ddd|}|Ed{VdS) aEnables streaming over steps taken to reach final output. Args: input: Input to the agent. config: Config to use. kwargs: Additional arguments. Yields: AddableDict: Addable dictionary. rErmetadatarun_namerun_idTrrrr yield_actionsNr!r*rv)r:rrrFiterators r;rzAgentExecutor.streams v&&(   JJ{ # #  F##ZZ ++ZZ ++::h''      r>AsyncIterator[AddableDict]c 0Kt|}t|||df|d|d|d|ddd|}|23d{V}|WV 6dS) a Async enables streaming over steps taken to reach final output. Args: input: Input to the agent. config: Config to use. kwargs: Additional arguments. Yields: AddableDict: Addable dictionary. rErrrrTrNr)r:rrrFr steps r;rzAgentExecutor.astreams"v&&(   JJ{ # #  F##ZZ ++ZZ ++::h''      #       $JJJJJ#((sBrA) rdrcrcrdrErrFr r2rbrS)rtryr2r )r2r~r) rr rErrrrrr2r*r)rHrVr2r#)rrrrr2r)r7rrCrrYrr2r)r7rrCrrYrr2r)rtrr2r) rrrrrrrCrDrYrr2r) rrrrrrrCrDrYrr2r) rrrrrrrYrr2r) rrrrrrrCrDrYrr2r) rrrrrrrCrDrYrr2r) rrrrrrrYrr2r)rrrYrr2r)rrrYrr2r)rrr2r)rCrDr2rD)rrrrrFr r2r)rrrrrFr r2r )(rrrrrrergrhrUrirkrrmr'rrr}rrrrrrTrrrrrrrrrrrrrrrrrrr8r>r;rbrbs$$$GGGG3-&+++++3$&N&&&&9+/....")((((       $     [ 2_'"""#"._(###[$#:   X      2222 $ "'       6---X-444X4 > > > >    =A     "BF         "=A      6=A KKKKKd=A %G%G%G%G%GZBF      6BF SSSSStBF 'G'G'G'G'GX=A-Q-Q-Q-Q-QdBF<<<<<|$ & & & & ,0B,0r>rb)`r __future__rrbuiltinsrloggingrabcrcollections.abcrrrpathlibrtypingr r r r r rlangchain_core._apirlangchain_core.agentsrrrlangchain_core.callbacksrrrrrrlangchain_core.exceptionsrlangchain_core.language_modelsrlangchain_core.messagesrlangchain_core.output_parsersrlangchain_core.promptsrlangchain_core.prompts.few_shotrlangchain_core.prompts.promptrlangchain_core.runnablesrr r!langchain_core.runnables.utilsr"langchain_core.toolsr#langchain_core.utils.inputr$pydanticr%r&r'typing_extensionsr(langchain._api.deprecationr)langchain.agents.agent_iteratorr*langchain.agents.agent_typesr+langchain.agents.toolsr,langchain.chains.baser-langchain.chains.llmr.langchain.utilities.asyncior/ getLoggerrr5r1rrrrrrrr rUrrrbr8r>r;r,sKK""""""  ========== ******EEEEEEEEEE<;;;;;<<<<<<//////::::::555555AAAAAA888888LLLLLLLLLL666666))))))888888;;;;;;;;;;""""""@@@@@@AAAAAA222222......''''''))))))777777  8 $ $gggggIgggTRRRRR9RRRj33333({K/G)HI333     U4 ,k9:;   *jjjjj)jjjZrrrrr3rrrj  %  P P P P P 0P P  P f  %  a a a a a !a a  a H H.eKi?@A-)AABv v v v v Ev v v v v r>