o Jjg@sdZddlmZddlZddlZddlZddlZddlmZddl m Z ddl m Z m Z mZmZmZmZmZmZmZmZmZddlZddlmZddlmZmZmZdd lmZm Z m!Z!m"Z"m#Z#m$Z$dd l%m&Z&dd l'm(Z(dd l)m*Z*dd l+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2ddl3m4Z4m5Z5m6Z6ddl7m8Z8ddl9m:Z:ddl;mZ>m?Z?m@Z@ddlAmBZBddlCmDZDddlEmFZFddlGmHZHddlImJZJddlKmLZLddlMmNZNeOePZQGddde>ZRGdd d e>ZSGd!d"d"e,eeefZTGd#d$d$e,eeeefZUGd%d&d&eRZVGd'd(d(eSZWed)d*d+d,Gd-d.d.eRZXed)d*d+d,Gd/d0d0eRZYGd1d2d2e:ZZeeeeefZ[eeVeWfZ\Gd3d4d4eJZ]dS)5zEChain that takes in an input and produces an action and action input.) annotationsN)abstractmethod)Path) Any AsyncIteratorCallableDictIteratorListOptionalSequenceTupleUnioncast) 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)AgentExecutorIterator) AgentType) InvalidTool)Chain)LLMChain)asyncio_timeoutcseZdZdZed0ddZd1ddZe d2d3ddZe d2d3ddZ eed0ddZ d4ddZ e d2d5d"d#Z ed6d$d%Zd7fd'd( Zd8d,d-Zd9d.d/ZZS):BaseSingleActionAgentzBase Single Action Agent class.return List[str]cCdgSReturn values of the agent.outputselfr8r8N/var/www/html/zoom/venv/lib/python3.10/site-packages/langchain/agents/agent.py return_values?z#BaseSingleActionAgent.return_valuesOptional[List[str]]cCsdSNr8r9r8r8r;get_allowed_toolsDsz'BaseSingleActionAgent.get_allowed_toolsNintermediate_stepsList[Tuple[AgentAction, str]] callbacksrkwargsrUnion[AgentAction, AgentFinish]cKdS)0Given input, decided what to do. 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Raises: ValueError: If `early_stopping_method` is not supported. forcer73Agent stopped due to iteration limit or time limit.'Got unsupported early_stopping_method ``r ValueErrorr:rRrArDr8r8r;return_stopped_responseus z-BaseSingleActionAgent.return_stopped_responsellmrtoolsSequence[BaseTool]callback_managerOptional[BaseCallbackManager]cKt)a.Construct an agent from an LLM and tools. Args: llm: Language model to use. tools: Tools to use. callback_manager: Callback manager to use. kwargs: Additional arguments. Returns: BaseSingleActionAgent: Agent object. NotImplementedError)clsr_r`rbrDr8r8r;from_llm_and_toolssz(BaseSingleActionAgent.from_llm_and_toolscCrdz#Return Identifier of an agent type.rer9r8r8r; _agent_typez!BaseSingleActionAgent._agent_typerc s\t}z|j}Wn tyd}Ynwt|tr$t|j|d<|S|dur,||d<|S)z{Return dictionary representation of agent. Returns: Dict: Dictionary representation of agent. 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Nr8r9r8r8r;r@sz&BaseMultiActionAgent.get_allowed_toolsNrArBrCrrDr%Union[List[AgentAction], AgentFinish]cKrF)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. Nr8rHr8r8r;rIrJzBaseMultiActionAgent.plancrK)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. Nr8rHr8r8r;rM rNzBaseMultiActionAgent.aplancCrFrOr8r9r8r8r;rQrJzBaseMultiActionAgent.input_keysrRrSrcKrT)rUrVr7z$Agent stopped due to max iterations.rXrYrZr[r]r8r8r;r^$s  z,BaseMultiActionAgent.return_stopped_responsecCrdrirer9r8r8r;rj@rkz BaseMultiActionAgent._agent_typerc s4t}z t|j|d<W|StyY|Sw)*Return dictionary representation of agent.rl)rmrnrSrjrfr:rDrqrrr8r;rtEs  zBaseMultiActionAgent.dictrurvrwcCst|tr t|}n|}|}d|vrtd|d|j}|jddd|jdkrKt|d}t j ||dd Wd d S1sDwYd S|j d rqt|d}t j ||d d Wd d S1sjwYd 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. Example: .. code-block:: python # If working with agent executor agent.agent.save(file_path="path/agent.yaml") rlr{z does not support saving.Trxr|r}r~rNrFrr)rorSrrtrfrrrrrrrrr\)r:rurrrrr8r8r;rNs"    "  "zBaseMultiActionAgent.savecCrrr8r9r8r8r;rurkz,BaseMultiActionAgent.tool_run_logging_kwargsrrr?rArBrCrrDrr2rrrrrr)rrrrrr<r@rrIrMrQr^rjrtrrrr8r8rrr;rs(     'rc@eZdZdZed ddZdS) AgentOutputParserz=Base class for parsing agent output into agent action/finish.textrSr2rEcCrF)z$Parse text into agent action/finish.Nr8r:rr8r8r;parse~rJzAgentOutputParser.parseN)rrSr2rErrrrrrr8r8r8r;r{src@r) MultiActionAgentOutputParserzBase class for parsing agent output into agent actions/finish. This is used for agents that can return multiple actions. rrSr2rcCrF)zParse text into agent actions/finish. Args: text: Text to parse. Returns: Union[List[AgentAction], AgentFinish]: List of agent actions or agent finish. Nr8rr8r8r;rrJz"MultiActionAgentOutputParser.parseN)rrSr2rrr8r8r8r;rsrc@eZdZUdZded< gZded<gZded<dZded < edd Z e dd d Z e dddZ ddddZ ddddZdS) RunnableAgentAgent powered by Runnables.z/Runnable[dict, Union[AgentAction, AgentFinish]]runnabler3input_keys_argreturn_keys_argTboolstream_runnablearbitrary_types_allowedr2cC|jSr6rr9r8r8r;r<r=zRunnableAgent.return_valuescCr)zReturn the input keys.rr9r8r8r;rQr=zRunnableAgent.input_keysNrArBrCrrDrrEcKfi|d|i}d}|jr'|jj|d|idD] }|dur |}q||7}q|S|jj|d|id}|SaPBased on past history and current inputs, decide what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with the observations. callbacks: Callbacks to run. **kwargs: User inputs. Returns: Action specifying what tool to use. rANrCconfigrrstreaminvoker:rArCrDinputs final_outputchunkr8r8r;rIs zRunnableAgent.plancxi|d|i}d}|jr-|jj|d|id2z3dHW}|dur%|}q||7}q6|S|jj|d|idIdH}|SaRAsync based on past history and current inputs, decide what to do. 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Returns: List of input keys. rr9r8r8r;rQsz#RunnableMultiActionAgent.input_keysNrArBrCrrDrrcKrrrrr8r8r;rI's zRunnableMultiActionAgent.plancrrrrr8r8r;rMNs    zRunnableMultiActionAgent.aplanrr?rrr8r8r8r;rs&       *rz0.1.0zpUse new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc.z1.0)messageremovalcsveZdZUdZded< ded< ded< edd d Zdfdd Z ddddZ ddddZ d ddZ Z S)!LLMSingleActionAgentz$Base class for single action agents.r/ llm_chainr output_parserr3stopr2cCtt|jjdhS)rrAlistsetrrQr9r8r8r;rQszLLMSingleActionAgent.input_keysrDrrc t}|d=|Srrrmrtrrrr8r;rt zLLMSingleActionAgent.dictNrArBrCrrEcKs(|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. rArrCNr8)rrunrrrr:rArCrDr7r8r8r;rIs zLLMSingleActionAgent.plancs0|jjd||j|d|IdH}|j|S)rLrNr8)rarunrrrrr8r8r;rMs zLLMSingleActionAgent.aplancCs&dt|jdkr ddS|jddS)rrXr llm_prefixobservation_prefix)lenrr9r8r8r;rs z,LLMSingleActionAgent.tool_run_logging_kwargsrrr?rr) rrrrrrrQrtrIrMrrr8r8rrr;rzs     rcsFeZdZUdZded< ded< dZded< dKfd d ZdLddZedMddZ dNddZ edMddZ dOddZ dPdQd"d#Z dPdQd$d%ZdRd'd(ZedMd)d*Zed+d,dSd.d/ZeedTd0d1ZeedTd2d3ZeedUd7d8ZedVd:d;ZeedWd allowed_toolsrDrr2rc rrrrrrr8r;rtrz Agent.dictcCr)zGet allowed tools.)rr9r8r8r;r@szAgent.get_allowed_toolsr3cCr4r5r8r9r8r8r;r<r=zAgent.return_valuesrrScCtd)zsFix the text. Args: text: Text to fix. 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Args: values: Values to validate. Returns: Dict: Validated values. r,FNrT)rr) getror! OutputType Exceptionrr rrpoprr)rgr8r, output_type_ multi_actionrr8r8r;validate_runnable_agent~s&     z%AgentExecutor.validate_runnable_agent2Union[BaseSingleActionAgent, BaseMultiActionAgent]cCst|jtr tt|jS|jS)aGType cast self.agent. The .agent attribute type includes Runnable, but is converted to 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. )ror,r!rRunnableAgentTyper9r8r8r; _action_agents zAgentExecutor._action_agentrurvrwcCr)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. 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Returns: BaseTool: Tool object. cSi|]}|j|qSr8rrr8r8r; z-AgentExecutor.lookup_tool..)r`)r:rr8r8r; lookup_tools zAgentExecutor.lookup_tool iterationsint time_elapsedfloatcCs4|jdur ||jkr dS|jdur||jkrdSdS)NFT)r/r0)r:rOrQr8r8r;_should_continues   zAgentExecutor._should_continuer7rrArr$$Optional[CallbackManagerForChainRun]rcCs.|r |j|d|jd|j}|jr||d<|SNgreen)colorverboserAon_agent_finishrXr<r-r:r7rAr$rr8r8r;_returns zAgentExecutor._return)Optional[AsyncCallbackManagerForChainRun]cs6|r|j|d|jdIdH|j}|jr||d<|SrUrYr[r8r8r;_areturns zAgentExecutor._areturnNextStepOutput1Union[AgentFinish, List[Tuple[AgentAction, str]]]cCs4t|dtrt|dksJ|dSdd|DS)Nr2cSs"g|] }t|tr|j|jfqSr8)rorrrrar8r8r;r*s   z4AgentExecutor._consume_next_step..)rorr)r:r8r8r8r;_consume_next_step#s z AgentExecutor._consume_next_stepname_to_tool_mapDict[str, BaseTool] color_mappingDict[str, str]rBc Cs"|dd||||||DS)NcSsg|]}|qSr8r8rbr8r8r;r7sz1AgentExecutor._take_next_step..)rd_iter_next_stepr:rergrrAr$r8r8r;_take_next_step.szAgentExecutor._take_next_step4Iterator[Union[AgentFinish, AgentAction, AgentStep]]c csz||}|jj|fd|r|ndi|}Wnty}zt|jtr-|j }nd}|r:tdt |t |} t|jtrU|j rRt |j } t |j } nd} nt|jt r_|j} nt |jrj||} ntdtd| | }|r}|j|dd |j} tj|jf|jd|r|ndd | } t|| d VWYd}~dSd}~wwt|tr|VdSt|tr|g} n|} | D]} | Vq| D] } |||| |VqdS) Take a single step in the thought-action-observation loop. Override this to take control of how the agent makes and acts on choices. rCNFAn 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`r!rVrWrXrWrCrr)_prepare_intermediate_stepsrCrI get_childrror1rr\rS send_to_llmr llm_outputcallableron_agent_actionrr r tool_inputrXrr_perform_agent_action)r:rergrrAr$r7e raise_errorrrtool_run_kwargsactions agent_actionr8r8r;riCsz             ( zAgentExecutor._iter_next_steprrrc Cs|r |j|dd|j|vr<||j}|j}||j}|j}|r&d|d<|j|jf|j||r4|ndd|} n"|j}t j|jt | df|jd|rW|ndd|} t || dS)NrVrqrXrrrrequested_tool_nameavailable_tool_namesrs) ryr return_directrCrrrzrXrur-rkeysr r:rergrr$rrrWr~rr8r8r;r{s>       z#AgentExecutor._perform_agent_actionc s*|dd||||||2IdHS)Ncsg|z3dHW}|q6Sr?r8rbr8r8r;rs z2AgentExecutor._atake_next_step..)rd_aiter_next_steprjr8r8r;_atake_next_steps zAgentExecutor._atake_next_step9AsyncIterator[Union[AgentFinish, AgentAction, AgentStep]]c sz|}jj|fdrndi|IdH}Wnty}z~tjtr0j }nd}|r=tdt |t |} tjtrX|j rUt |j } t |j } nd} ntjt rbj} nt jrm|} ntdtd| | }j} tj|jfjdrndd| IdH} t|| d VWYd}~dSd}~wwt|tr|VdSt|tr|g} n|} | D]} | Vqtjfd d | DIdH}|D]}|VqdS) rmrCNFrnrorpr!rrrscsg|] }|qSr8)_aperform_agent_action)rrrgrer$r:r8r;rs z2AgentExecutor._aiter_next_step..)rtrCrMrurror1rr\rSrvrrwrxrrr rrzrXrrasynciogather)r:rergrrAr$r7r|r}rrr~rrresultrr8rr;rs|             &   zAgentExecutor._aiter_next_stepc s|r|j||jddIdH|j|vrE||j}|j}||j}|j}|r,d|d<|j|jf|j||r:|ndd|IdH} n%|j}t j|jt | df|jd|r`|ndd|IdH} t || dS)NrV)rXrWrXrrrrrs) ryrXrrrCrrrzrur-rrrrr8r8r;r!sD       z$AgentExecutor._aperform_agent_actionc Csdd|jD}tdd|jDddgd}g}d}d }t}|||rm|j|||||d } t| tr=|j| ||d S|| t | d kr]| d} | | } | d ur]|j| ||d S|d 7}t|}|||s&|j j |j |fi|} |j| ||d S) z(Run text through and get agent response.cSrKr8rrr8r8r;rLQrMz'AgentExecutor._call..cSrr8rrr8r8r;rTrz'AgentExecutor._call..rVredexcluded_colorsrr$raN)r`r&timerSrkrorr\extendr_get_tool_returnrCr^rR r:rr$rergrArOrQ start_timenext_step_outputnext_step_action tool_returnr7r8r8r;_callJsJ       zAgentExecutor._callc sdd|jD}tdd|jDdgd}g}d}d}t}zt|j4Id H|||r|j|||||d Id H} t| trY|j | ||d Id HWd Id HWS| | t | d kr| d} | | } | d ur|j | ||d Id HWd Id HWS|d 7}t|}|||s1|j j|j|fi|} |j | ||d Id HWd Id HWS1Id HswYWd Sttjfy|j j|j|fi|} |j | ||d Id HYSw) z.Async run text through and get agent response.cSrKr8rrr8r8r;rLrMz(AgentExecutor._acall..cSrr8rrr8r8r;rrz(AgentExecutor._acall..rVrrrNrra)r`r&rr0r0rSrrorr^rrrrCr^rR TimeoutErrorrrr8r8r;_acallysr          4"zAgentExecutor._acallrTuple[AgentAction, str]Optional[AgentFinish]cCs`|\}}dd|jD}d}t|jjdkr|jjd}|j|vr.||jjr.t||idSdS)z&Check if the tool is a returning tool.cSrKr8rrr8r8r;rLrMz2AgentExecutor._get_tool_return..r7rrXN)r`rrCr<rrr)r:rrrrereturn_value_keyr8r8r;rs   zAgentExecutor._get_tool_returncCs>t|jtr|jdkr||j dSt|jr||S|S)Nr)ror3rPrx)r:rAr8r8r;rts    z)AgentExecutor._prepare_intermediate_stepsinputUnion[Dict[str, Any], Any]rOptional[RunnableConfig]Iterator[AddableDict]cks\t|}t|||df|d|d|d|ddd|}|D]}|Vq&dS) aEnables streaming over steps taken to reach final output. Args: input: Input to the agent. config: Config to use. kwargs: Additional arguments. Yields: AddableDict: Addable dictionary. rCrHmetadatarun_namerun_idTrHrrr yield_actionsNr#r+r9r:rrrDiteratorstepr8r8r;rs$  zAgentExecutor.streamAsyncIterator[AddableDict]cKsft|}t|||df|d|d|d|ddd|}|2z 3dHW}|Vq&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. rCrHrrrTrNrrr8r8r;rs$  zAgentExecutor.astreamr?) r,r+r`rarCrrDrr2r*r)r8rr2r)r2rAr) rrrCrrFrrGrr2r+r)rrSr2r%)rOrPrQrRr2r)r7rrArr$rTr2r)r7rrArr$r]r2r)r8r_r2r`) rerfrgrhrrhrArBr$rTr2r`) rerfrgrhrrhrArBr$rTr2rl) rerfrgrhrrr$rTr2r) rerfrgrhrrhrArBr$r]r2r`) rerfrgrhrrhrArBr$r]r2r) rerfrgrhrrr$r]r2r)rrhr$rTr2r)rrhr$r]r2rh)rrr2r)rArBr2rB)rrrrrDrr2r)rrrrrDrr2r)(rrrrrr-r/r0rRr1r3rr4r)r6r@rrCrrErIrQrJrNrSr\r^rdrkrir{rrrrrrrtrrr8r8r8r;r*s                   R -  Z , 2 >  "r*)^r __future__rrrloggingrabcrpathlibrtypingrrrrr r r r r rrrlangchain_core._apirlangchain_core.agentsrrrlangchain_core.callbacksrrrrrrlangchain_core.exceptionsrlangchain_core.language_modelsrlangchain_core.messagesrlangchain_core.output_parsersrlangchain_core.promptsrlangchain_core.prompts.few_shotrlangchain_core.prompts.promptr langchain_core.runnablesr!r"r#langchain_core.runnables.utilsr$langchain_core.toolsr%langchain_core.utils.inputr&pydanticr'r(r)typing_extensionsr*langchain.agents.agent_iteratorr+langchain.agents.agent_typesr,langchain.agents.toolsr-langchain.chains.baser.langchain.chains.llmr/langchain.utilities.asyncior0 getLoggerrrr1rrrrrrrr r_rBr*r8r8r8r;sz   4                    + muS&