Class TrajectoryEvalChain

A chain for evaluating ReAct style agents.

This chain is used to evaluate ReAct style agents by reasoning about the sequence of actions taken and their outcomes.

Hierarchy

  • AgentTrajectoryEvaluator
    • TrajectoryEvalChain

Constructors

Properties

outputKey: string = "text"
outputParser: TrajectoryOutputParser = ...
requiresInput: boolean = true
requiresReference: boolean = false
verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
criterionName?: string
evaluationName?: string = ...
memory?: BaseMemory
metadata?: Record<string, unknown>
skipInputWarning?: string = ...
skipReferenceWarning?: string = ...
tags?: string[]
lc_runnable: boolean = true

Accessors

Methods

  • Check if the evaluation arguments are valid.

    Parameters

    • Optional reference: string

      The reference label.

    • Optional input: string

      The input string.

    Returns void

    Throws

    If the evaluator requires an input string but none is provided, or if the evaluator requires a reference label but none is provided.

  • Invoke the chain with the provided input and returns the output.

    Parameters

    Returns Promise<ChainValues>

    Promise that resolves with the output of the chain run.

  • Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.

    Type Parameters

    • NewRunOutput

    Parameters

    • coerceable: RunnableLike<ChainValues, NewRunOutput>

      A runnable, function, or object whose values are functions or runnables.

    Returns RunnableSequence<ChainValues, Exclude<NewRunOutput, Error>>

    A new runnable sequence.

  • Format prompt with values and pass to LLM

    Parameters

    Returns Promise<EvalOutputType>

    Completion from LLM.

    Example

    llm.predict({ adjective: "funny" })
    
  • Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops can be applied in order to construct state.

    Parameters

    Returns AsyncGenerator<RunLogPatch, any, unknown>

  • Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated.

    Parameters

    Returns AsyncGenerator<ChainValues, any, unknown>

  • Parameters

    • values: ChainValues & {
          signal?: AbortSignal;
          timeout?: number;
      }

    Returns Promise<ChainValues & {
        signal?: AbortSignal;
        timeout?: number;
    }>

  • Helper method to transform an Iterator of Input values into an Iterator of Output values, with callbacks. Use this to implement stream() or transform() in Runnable subclasses.

    Type Parameters

    Parameters

    • inputGenerator: AsyncGenerator<I, any, unknown>
    • transformer: ((generator, runManager?, options?) => AsyncGenerator<O, any, unknown>)
        • (generator, runManager?, options?): AsyncGenerator<O, any, unknown>
        • Parameters

          Returns AsyncGenerator<O, any, unknown>

    • Optional options: BaseCallbackConfig & {
          runType?: string;
      }

    Returns AsyncGenerator<O, any, unknown>

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