Chain to prioritize tasks.

Hierarchy

Constructors

Properties

llm: LLMType

LLM Wrapper to use

outputKey: string = "text"

Key to use for output, defaults to text

Prompt object to use

verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
llmKwargs?: any

Kwargs to pass to LLM

memory?: BaseMemory
metadata?: Record<string, unknown>
outputParser?: BaseLLMOutputParser<string>

OutputParser to use

tags?: string[]

Accessors

Methods

  • Format prompt with values and pass to LLM

    Parameters

    • values: any

      keys to pass to prompt template

    • Optional callbackManager: CallbackManager

      CallbackManager to use

    Returns Promise<string>

    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>

  • Static method to create a new TaskPrioritizationChain from a BaseLanguageModel. It generates a prompt using the PromptTemplate class and the task prioritization template, and returns a new instance of TaskPrioritizationChain.

    Parameters

    • fields: Omit<LLMChainInput<string, LLMType>, "prompt">

      Object with fields used to initialize the chain, excluding the prompt.

    Returns LLMChain<string, LLMType>

    A new instance of TaskPrioritizationChain.

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