Class LLMChain<T, Model>

Chain to run queries against LLMs.

Example

import { LLMChain } from "langchain/chains";
import { OpenAI } from "langchain/llms/openai";
import { PromptTemplate } from "langchain/prompts";

const prompt = PromptTemplate.fromTemplate("Tell me a {adjective} joke");
const llm = new LLMChain({ llm: new OpenAI(), prompt });

Type Parameters

  • T extends string | object = string

  • Model extends LLMType = LLMType

Hierarchy

Implements

Constructors

constructor

Properties

llm outputKey prompt llmKwargs? memory? outputParser?

Accessors

inputKeys outputKeys

Methods

apply call invoke predict prepOutputs run serialize deserialize

Constructors

constructor

  • Type Parameters

    • T extends string | object = string

    • Model extends LLMType = LLMType

    Parameters

    Returns LLMChain<T, Model>

Properties

llm

llm: Model

LLM Wrapper to use

outputKey

outputKey: string = "text"

Key to use for output, defaults to text

prompt

prompt: BasePromptTemplate<any, BasePromptValue, any>

Prompt object to use

Optional llmKwargs

llmKwargs?: CallOptionsIfAvailable<Model>

Kwargs to pass to LLM

Optional memory

memory?: BaseMemory

Optional outputParser

outputParser?: BaseLLMOutputParser<T>

OutputParser to use

Accessors

inputKeys

  • get inputKeys(): string[]

  • Returns string[]

outputKeys

  • get outputKeys(): string[]

  • Returns string[]

Methods

apply

  • Call the chain on all inputs in the list

    Parameters

    • inputs: ChainValues[]
    • Optional config: (BaseCallbackConfig | Callbacks)[]

    Returns Promise<ChainValues[]>

call

  • Run the core logic of this chain and add to output if desired.

    Wraps _call and handles memory.

    Parameters

    • values: ChainValues & CallOptionsIfAvailable<Model>
    • Optional config: BaseCallbackConfig | Callbacks

    Returns Promise<ChainValues>

invoke

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

    Parameters

    • input: ChainValues

      Input values for the chain run.

    • Optional config: BaseCallbackConfig

      Optional configuration for the Runnable.

    Returns Promise<ChainValues>

    Promise that resolves with the output of the chain run.

predict

  • Format prompt with values and pass to LLM

    Parameters

    • values: ChainValues & CallOptionsIfAvailable<Model>

      keys to pass to prompt template

    • Optional callbackManager: CallbackManager

      CallbackManager to use

    Returns Promise<T>

    Completion from LLM.

    Example

    llm.predict({ adjective: "funny" })

prepOutputs

  • Parameters

    • inputs: Record<string, unknown>
    • outputs: Record<string, unknown>
    • returnOnlyOutputs: boolean = false

    Returns Promise<Record<string, unknown>>

run

  • Parameters

    • input: any
    • Optional config: BaseCallbackConfig | Callbacks

    Returns Promise<string>

serialize

Static deserialize

  • Load a chain from a json-like object describing it.

    Parameters

    Returns Promise<LLMChain<string, BaseLanguageModel<any, BaseLanguageModelCallOptions>>>

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