Class FewShotPromptTemplate

Prompt template that contains few-shot examples.

Example

const examplePrompt = PromptTemplate.fromTemplate(
"Input: {input}\nOutput: {output}",
);

const exampleSelector = await SemanticSimilarityExampleSelector.fromExamples(
[
{ input: "happy", output: "sad" },
{ input: "tall", output: "short" },
{ input: "energetic", output: "lethargic" },
{ input: "sunny", output: "gloomy" },
{ input: "windy", output: "calm" },
],
new OpenAIEmbeddings(),
HNSWLib,
{ k: 1 },
);

const dynamicPrompt = new FewShotPromptTemplate({
exampleSelector,
examplePrompt,
prefix: "Give the antonym of every input",
suffix: "Input: {adjective}\nOutput:",
inputVariables: ["adjective"],
});

// Format the dynamic prompt with the input 'rainy'
console.log(await dynamicPrompt.format({ adjective: "rainy" }));

Hierarchy

Implements

Constructors

Properties

PromptValueReturnType: StringPromptValue
examplePrompt: PromptTemplate<any, any>

An PromptTemplate used to format a single example.

exampleSeparator: string = "\n\n"

String separator used to join the prefix, the examples, and suffix.

inputVariables: string[]

A list of variable names the prompt template expects

partialVariables: PartialValues<any>

Partial variables

prefix: string = ""

A prompt template string to put before the examples.

Default Value

""

suffix: string = ""

A prompt template string to put after the examples.

templateFormat: "f-string" = "f-string"

The format of the prompt template. Options are: 'f-string'

validateTemplate: boolean = true

Whether or not to try validating the template on initialization.

exampleSelector?: BaseExampleSelector

An BaseExampleSelector Examples to format into the prompt. Exactly one of this or examples must be provided.

examples?: InputValues[]

Examples to format into the prompt. Exactly one of this or exampleSelector must be provided.

outputParser?: BaseOutputParser<unknown>

How to parse the output of calling an LLM on this formatted prompt

Methods

  • Formats the prompt with the given values.

    Parameters

    • values: InputValues

      The values to format the prompt with.

    Returns Promise<string>

    A promise that resolves to a string representing the formatted prompt.

  • Formats the prompt given the input values and returns a formatted prompt value.

    Parameters

    • values: TypedPromptInputValues<any>

      The input values to format the prompt.

    Returns Promise<StringPromptValue>

    A Promise that resolves to a formatted prompt value.

  • Invokes the prompt template with the given input and options.

    Parameters

    • input: any

      The input to invoke the prompt template with.

    • Optional options: BaseCallbackConfig

      Optional configuration for the callback.

    Returns Promise<StringPromptValue>

    A Promise that resolves to the output of the prompt template.

  • Merges partial variables and user variables.

    Parameters

    • userVariables: TypedPromptInputValues<any>

      The user variables to merge with the partial variables.

    Returns Promise<InputValues<any>>

    A Promise that resolves to an object containing the merged variables.

  • 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

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

    A new runnable sequence.

  • 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

    • input: any
    • Optional options: Partial<BaseCallbackConfig>
    • Optional streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">

    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<StringPromptValue, any, unknown>

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