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JavaScriptlangchainindexStructuredTool
Class●Since v1.0

StructuredTool

Base class for Tools that accept input of any shape defined by a Zod schema.

Copy
class StructuredTool

Bases

BaseLangChain<StructuredToolCallInput<SchemaT, SchemaInputT>, ToolOutputT | ToolMessage>

Constructors

constructor
constructor

Properties

property
callbacks: Callbacks
property
defaultConfig: ToolRunnableConfig
property
description: string
property
extras: Record<string, unknown>
property
lc_kwargs: SerializedFields
property
lc_runnable: boolean
property
lc_serializable: boolean
property
metadata: Record<string, unknown>
property
name: string
property
responseFormat: string
property
returnDirect: boolean
property
schema: SchemaT
property
tags: string[]
property
verbose: boolean
property
verboseParsingErrors: boolean
property
lc_aliases: Record<string, string>
property
lc_attributes: SerializedFields | undefined
property
lc_id: string[]
property
lc_namespace: string[]
property
lc_secrets: __type | undefined
property
lc_serializable_keys: string[] | undefined

Methods

method
_addVersion
method
_batchWithConfig→ Promise<Error | ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>[]>
method
_call
method
_callWithConfig
method
_getOptionsList
method
_separateRunnableConfigFromCallOptions
method
_streamIterator→ AsyncGenerator<ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>>
method
_streamLog
method
_transformStreamWithConfig
method
assign→ Runnable
method
asTool→ RunnableToolLike<InteropZodType<ToolCall<string, Record<string, any>> | T>, ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>>
method
batch→ Promise<ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>[]>
method
getGraph→ Graph
method
getName→ string
method
invoke→ Promise<ToolReturnType<TInput, TConfig, ToolOutputT>>
method
pick→ Runnable
method
pipe→ Runnable<StructuredToolCallInput<SchemaT, SchemaInputT>, Exclude<NewRunOutput, Error>>
method
stream→ Promise<IterableReadableStream<ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>>>
method
streamEvents→ IterableReadableStream<StreamEvent>
method
toJSON→ Serialized
method
toJSONNotImplemented→ SerializedNotImplemented
method
transform→ AsyncGenerator<ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>>
method
withConfig→ Runnable<StructuredToolCallInput<SchemaT, SchemaInputT>, ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>, RunnableConfig<Record<string, any>>>
method
withFallbacks→ RunnableWithFallbacks<StructuredToolCallInput<SchemaT, SchemaInputT>, ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>>
method
withListeners→ Runnable<StructuredToolCallInput<SchemaT, SchemaInputT>, ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>, RunnableConfig<Record<string, any>>>
method
withRetry→ RunnableRetry<StructuredToolCallInput<SchemaT, SchemaInputT>, ToolOutputT | ToolMessage<MessageStructure<MessageToolSet>>, RunnableConfig<Record<string, any>>>
method
isRunnable→ thing is Runnable<any, any, RunnableConfig<Record<string, any>>>
method
lc_name→ string
deprecatedmethod
call→ Promise<ToolReturnType<NonNullable<TArg>, TConfig, ToolOutputT>>
deprecatedmethod
streamLog→ AsyncGenerator<RunLogPatch>

Inherited fromBaseLangChain(@langchain/core)

Properties

PcallbacksPlc_kwargsPlc_namespacePlc_runnablePlc_serializablePmetadataPnamePtagsPverbosePlc_aliasesPlc_attributesPlc_idPlc_secretsPlc_serializable_keys

Methods

M_addVersionM_batchWithConfigM_callWithConfigM_getOptionsListM_separateRunnableConfigFromCallOptionsM

Inherited fromRunnable(langchain_core)

Attributes

AInputTypeAOutputTypeAinput_schemaAoutput_schemaA
View source on GitHub
_streamIterator
M_streamLog
M_transformStreamWithConfig
Massign
MasTool
Mbatch
MgetGraph
MgetName
Minvoke
Mpick
Mpipe
Mstream
MstreamEvents
MstreamLog
MtoJSON
MtoJSONNotImplemented
Mtransform
MwithConfig
MwithFallbacks
MwithListeners
MwithRetry
MisRunnable
Mlc_name
config_specs

Methods

Mget_nameMget_input_schemaMget_input_jsonschemaMget_output_schemaMget_output_jsonschemaMconfig_schemaMget_config_jsonschemaMget_graphMget_promptsMainvokeMbatch_as_completedMabatchMabatch_as_completedMastreamMastream_logMastream_eventsMstream_eventsMatransformMbindMwith_configMwith_listenersMwith_alistenersMwith_typesMwith_retryMmapMwith_fallbacksMas_tool

Callbacks for this call and any sub-calls (eg. a Chain calling an LLM). Tags are passed to all callbacks, metadata is passed to handle*Start callbacks.

Default config object for the tool runnable.

A description of the tool.

Optional provider-specific extra fields for the tool.

This is used to pass provider-specific configuration that doesn't fit into standard tool fields.

Metadata for this call and any sub-calls (eg. a Chain calling an LLM). Keys should be strings, values should be JSON-serializable.

The name of the tool being called

The tool response format.

If "content" then the output of the tool is interpreted as the contents of a ToolMessage. If "content_and_artifact" then the output is expected to be a two-tuple corresponding to the (content, artifact) of a ToolMessage.

Whether to return the tool's output directly.

Setting this to true means that after the tool is called, an agent should stop looping.

A Zod schema representing the parameters of the tool.

Tags for this call and any sub-calls (eg. a Chain calling an LLM). You can use these to filter calls.

Whether to print out response text.

A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.

Internal method that handles batching and configuration for a runnable It takes a function, input values, and optional configuration, and returns a promise that resolves to the output values.

Default streaming implementation. Subclasses should override this method if they support streaming output.

Assigns new fields to the dict output of this runnable. Returns a new runnable.

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

Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.

Invokes the tool with the provided input and configuration.

Pick keys from the dict output of this runnable. Returns a new runnable.

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

Stream output in chunks.

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.

Bind config to a Runnable, returning a new Runnable.

Create a new runnable from the current one that will try invoking other passed fallback runnables if the initial invocation fails.

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.

Add retry logic to an existing runnable.

The name of the serializable. Override to provide an alias or to preserve the serialized module name in minified environments.

Implemented as a static method to support loading logic.

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.

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);
 }
}