Class SystemMessagePromptTemplate<RunInput>

Class that represents a system message prompt template. It extends the BaseMessageStringPromptTemplate.

const message = SystemMessagePromptTemplate.fromTemplate("{text}");
const formatted = await message.format({ text: "Hello world!" });

const chatPrompt = ChatPromptTemplate.fromMessages([message]);
const formattedChatPrompt = await chatPrompt.invoke({
text: "Hello world!",
});

Type Parameters

Hierarchy

  • _StringImageMessagePromptTemplate<RunInput>
    • SystemMessagePromptTemplate

Constructors

Properties

additionalOptions: _StringImageMessagePromptTemplateOptions<TemplateFormat> = {}
chatMessageClass?: typeof ChatMessage
inputVariables: Extract<keyof RunInput, string>[] = []
messageClass?: MessageClass
name?: string
prompt: BaseStringPromptTemplate<InputValues<Extract<keyof RunInput, string>>, string> | (BaseStringPromptTemplate<InputValues<Extract<keyof RunInput, string>>, string> | ImagePromptTemplate<InputValues<Extract<keyof RunInput, string>>, string> | MessageStringPromptTemplateFields<InputValues<Extract<keyof RunInput, string>>>)[]

Methods

  • Convert a runnable to a tool. Return a new instance of RunnableToolLike which contains the runnable, name, description and schema.

    Type Parameters

    Parameters

    • fields: {
          description?: string;
          name?: string;
          schema: ZodType<T, ZodTypeDef, T>;
      }
      • Optionaldescription?: string

        The description of the tool. Falls back to the description on the Zod schema if not provided, or undefined if neither are provided.

      • Optionalname?: string

        The name of the tool. If not provided, it will default to the name of the runnable.

      • schema: ZodType<T, ZodTypeDef, T>

        The Zod schema for the input of the tool. Infers the Zod type from the input type of the runnable.

    Returns RunnableToolLike<ZodType<ToolCall | T, ZodTypeDef, ToolCall | T>, BaseMessage[]>

    An instance of RunnableToolLike which is a runnable that can be used as a tool.

  • Method that takes an object of TypedPromptInputValues and returns a promise that resolves to an array of BaseMessage instances.

    Parameters

    • values: RunInput

      Object of TypedPromptInputValues

    Returns Promise<BaseMessage[]>

    Formatted array of BaseMessages

  • Parameters

    • name: string

    Returns
        | "human"
        | "ai"
        | "system"
        | "chat"

  • Generate a stream of events emitted by the internal steps of the runnable.

    Use to create an iterator over StreamEvents that provide real-time information about the progress of the runnable, including StreamEvents from intermediate results.

    A StreamEvent is a dictionary with the following schema:

    • event: string - Event names are of the format: on_[runnable_type]_(start|stream|end).
    • name: string - The name of the runnable that generated the event.
    • run_id: string - Randomly generated ID associated with the given execution of the runnable that emitted the event. A child runnable that gets invoked as part of the execution of a parent runnable is assigned its own unique ID.
    • tags: string[] - The tags of the runnable that generated the event.
    • metadata: Record<string, any> - The metadata of the runnable that generated the event.
    • data: Record<string, any>

    Below is a table that illustrates some events that might be emitted by various chains. Metadata fields have been omitted from the table for brevity. Chain definitions have been included after the table.

    ATTENTION This reference table is for the V2 version of the schema.

    +----------------------+-----------------------------+------------------------------------------+
    | event                | input                       | output/chunk                             |
    +======================+=============================+==========================================+
    | on_chat_model_start  | {"messages": BaseMessage[]} |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_chat_model_stream |                             | AIMessageChunk("hello")                  |
    +----------------------+-----------------------------+------------------------------------------+
    | on_chat_model_end    | {"messages": BaseMessage[]} | AIMessageChunk("hello world")            |
    +----------------------+-----------------------------+------------------------------------------+
    | on_llm_start         | {'input': 'hello'}          |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_llm_stream        |                             | 'Hello'                                  |
    +----------------------+-----------------------------+------------------------------------------+
    | on_llm_end           | 'Hello human!'              |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_chain_start       |                             |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_chain_stream      |                             | "hello world!"                           |
    +----------------------+-----------------------------+------------------------------------------+
    | on_chain_end         | [Document(...)]             | "hello world!, goodbye world!"           |
    +----------------------+-----------------------------+------------------------------------------+
    | on_tool_start        | {"x": 1, "y": "2"}          |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_tool_end          |                             | {"x": 1, "y": "2"}                       |
    +----------------------+-----------------------------+------------------------------------------+
    | on_retriever_start   | {"query": "hello"}          |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_retriever_end     | {"query": "hello"}          | [Document(...), ..]                      |
    +----------------------+-----------------------------+------------------------------------------+
    | on_prompt_start      | {"question": "hello"}       |                                          |
    +----------------------+-----------------------------+------------------------------------------+
    | on_prompt_end        | {"question": "hello"}       | ChatPromptValue(messages: BaseMessage[]) |
    +----------------------+-----------------------------+------------------------------------------+
    

    The "on_chain_*" events are the default for Runnables that don't fit one of the above categories.

    In addition to the standard events above, users can also dispatch custom events.

    Custom events will be only be surfaced with in the v2 version of the API!

    A custom event has following format:

    +-----------+------+------------------------------------------------------------+
    | Attribute | Type | Description                                                |
    +===========+======+============================================================+
    | name      | str  | A user defined name for the event.                         |
    +-----------+------+------------------------------------------------------------+
    | data      | Any  | The data associated with the event. This can be anything.  |
    +-----------+------+------------------------------------------------------------+
    

    Here's an example:

    import { RunnableLambda } from "@langchain/core/runnables";
    import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch";
    // Use this import for web environments that don't support "async_hooks"
    // and manually pass config to child runs.
    // import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch/web";

    const slowThing = RunnableLambda.from(async (someInput: string) => {
    // Placeholder for some slow operation
    await new Promise((resolve) => setTimeout(resolve, 100));
    await dispatchCustomEvent("progress_event", {
    message: "Finished step 1 of 2",
    });
    await new Promise((resolve) => setTimeout(resolve, 100));
    return "Done";
    });

    const eventStream = await slowThing.streamEvents("hello world", {
    version: "v2",
    });

    for await (const event of eventStream) {
    if (event.event === "on_custom_event") {
    console.log(event);
    }
    }

    Parameters

    • input: RunInput
    • options: Partial<RunnableConfig> & {
          version: "v1" | "v2";
      }
    • OptionalstreamOptions: Omit<EventStreamCallbackHandlerInput, "autoClose">

    Returns IterableReadableStream<StreamEvent>

  • Parameters

    • input: RunInput
    • options: Partial<RunnableConfig> & {
          encoding: "text/event-stream";
          version: "v1" | "v2";
      }
    • OptionalstreamOptions: Omit<EventStreamCallbackHandlerInput, "autoClose">

    Returns IterableReadableStream<Uint8Array>

  • 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<BaseMessage[], any, unknown>

  • Bind lifecycle listeners to a Runnable, returning a new Runnable. The Run object contains information about the run, including its id, type, input, output, error, startTime, endTime, and any tags or metadata added to the run.

    Parameters

    • params: {
          onEnd?: ((run: Run, config?: RunnableConfig) => void | Promise<void>);
          onError?: ((run: Run, config?: RunnableConfig) => void | Promise<void>);
          onStart?: ((run: Run, config?: RunnableConfig) => void | Promise<void>);
      }

      The object containing the callback functions.

      • OptionalonEnd?: ((run: Run, config?: RunnableConfig) => void | Promise<void>)

        Called after the runnable finishes running, with the Run object.

          • (run, config?): void | Promise<void>
          • Parameters

            Returns void | Promise<void>

      • OptionalonError?: ((run: Run, config?: RunnableConfig) => void | Promise<void>)

        Called if the runnable throws an error, with the Run object.

          • (run, config?): void | Promise<void>
          • Parameters

            Returns void | Promise<void>

      • OptionalonStart?: ((run: Run, config?: RunnableConfig) => void | Promise<void>)

        Called before the runnable starts running, with the Run object.

          • (run, config?): void | Promise<void>
          • Parameters

            Returns void | Promise<void>

    Returns Runnable<RunInput, BaseMessage[], RunnableConfig>

  • Parameters

    • template: string | (string | _TextTemplateParam | _ImageTemplateParam)[]
    • OptionaladditionalOptions: _StringImageMessagePromptTemplateOptions<TemplateFormat>

    Returns _StringImageMessagePromptTemplate<any, BaseMessage[]>