Class ChatConversationalAgent

Agent for the MRKL chain.

Hierarchy

  • Agent
    • ChatConversationalAgent

Constructors

constructor

Properties

ToolType llmChain outputParser

Accessors

allowedTools inputKeys returnValues

Methods

constructScratchPad finishToolName llmPrefix observationPrefix plan prepareForOutput returnStoppedResponse createPrompt deserialize fromLLMAndTools getDefaultOutputParser validateTools

Constructors

constructor

Properties

ToolType

ToolType: Tool

llmChain

llmChain: LLMChain<string, LLMType>

outputParser

outputParser: undefined | AgentActionOutputParser

Accessors

allowedTools

  • get allowedTools(): undefined | string[]

  • Returns undefined | string[]

inputKeys

  • get inputKeys(): string[]

  • Returns string[]

returnValues

  • get returnValues(): string[]

  • Returns string[]

Methods

constructScratchPad

  • Constructs the agent scratchpad based on the agent steps. It returns an array of base messages representing the thoughts of the agent.

    Parameters

    • steps: AgentStep[]

      The agent steps to construct the scratchpad from.

    Returns Promise<BaseMessage[]>

    An array of base messages representing the thoughts of the agent.

finishToolName

  • Name of tool to use to terminate the chain.

    Returns string

llmPrefix

  • Prefix to append the LLM call with.

    Returns string

observationPrefix

  • Prefix to append the observation with.

    Returns string

plan

  • Decide what to do given some input.

    Parameters

    • steps: AgentStep[]

      Steps the LLM has taken so far, along with observations from each.

    • inputs: ChainValues

      User inputs.

    • Optional callbackManager: CallbackManager

      Callback manager to use for this call.

    Returns Promise<AgentAction | AgentFinish>

    Action specifying what tool to use.

prepareForOutput

  • Prepare the agent for output, if needed

    Parameters

    • _returnValues: Record<string, any>
    • _steps: AgentStep[]

    Returns Promise<Record<string, any>>

returnStoppedResponse

  • Return response when agent has been stopped due to max iterations

    Parameters

    • earlyStoppingMethod: StoppingMethod
    • steps: AgentStep[]
    • inputs: ChainValues
    • Optional callbackManager: CallbackManager

    Returns Promise<AgentFinish>

Static createPrompt

  • Create prompt in the style of the ChatConversationAgent.

    Parameters

    • tools: Tool[]

      List of tools the agent will have access to, used to format the prompt.

    • Optional args: ChatConversationalCreatePromptArgs

      Arguments to create the prompt with.

    Returns ChatPromptTemplate<any, any>

Static deserialize

  • Load an agent from a json-like object describing it.

    Parameters

    • data: Object

    Returns Promise<Agent>

Static fromLLMAndTools

  • Creates an instance of the ChatConversationalAgent class from a BaseLanguageModel and a set of tools. It takes optional arguments to customize the agent.

    Parameters

    • llm: BaseLanguageModel<any, BaseLanguageModelCallOptions>

      The BaseLanguageModel to create the agent from.

    • tools: Tool[]

      The set of tools to create the agent from.

    • Optional args: ChatConversationalCreatePromptArgs & AgentArgs

      Optional arguments to customize the agent.

    Returns ChatConversationalAgent

    An instance of the ChatConversationalAgent class.

Static getDefaultOutputParser

  • Returns the default output parser for the ChatConversationalAgent class. It takes optional fields as arguments to customize the output parser.

    Parameters

    • Optional fields: OutputParserArgs & {
          toolNames: string[];
      }

      Optional fields to customize the output parser.

    Returns AgentActionOutputParser

    The default output parser for the ChatConversationalAgent class.

Static validateTools

  • Validate that appropriate tools are passed in

    Parameters

    • tools: Tool[]

    Returns void

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