Optional
callbacksOptional callbacks to handle various events in the retrieval process.
Protected
Optional
childKProtected
childOptional
documentProtected
idOptional
metadataMetadata to provide additional context or information about the retrieval operation.
Optional
nameProtected
Optional
parentKProtected
Optional
parentOptional
tagsTags to label or categorize the retrieval operation.
Optional
verboseIf set to true
, enables verbose logging for the retrieval process.
Adds documents to the docstore and vectorstores. If a retriever is provided, it will be used to add documents instead of the vectorstore.
The documents to add
Optional
config: { Optional
addBoolean of whether to add documents to docstore.
This can be false if and only if ids
are provided. You may want
to set this to False if the documents are already in the docstore
and you don't want to re-add them.
Optional
childOptional
ids?: string[]Optional list of ids for documents. If provided should be the same length as the list of documents. Can provided if parent documents are already in the document store and you don't want to re-add to the docstore. If not provided, random UUIDs will be used as ids.
Convert a runnable to a tool. Return a new instance of RunnableToolLike
which contains the runnable, name, description and schema.
Optional
description?: stringThe description of the tool. Falls back to the description on the Zod schema if not provided, or undefined if neither are provided.
Optional
name?: stringThe name of the tool. If not provided, it will default to the name of the runnable.
The Zod schema for the input of the tool. Infers the Zod type from the input type of the runnable.
An instance of RunnableToolLike
which is a runnable that can be used as a tool.
Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.
Array of inputs to each batch call.
Optional
options: Partial<RunnableConfig<Record<string, any>>> | Partial<RunnableConfig<Record<string, any>>>[]Either a single call options object to apply to each batch call or an array for each call.
Optional
batchOptions: RunnableBatchOptions & { An array of RunOutputs, or mixed RunOutputs and errors if batchOptions.returnExceptions is set
Optional
options: Partial<RunnableConfig<Record<string, any>>> | Partial<RunnableConfig<Record<string, any>>>[]Optional
batchOptions: RunnableBatchOptions & { Optional
options: Partial<RunnableConfig<Record<string, any>>> | Partial<RunnableConfig<Record<string, any>>>[]Optional
batchOptions: RunnableBatchOptionsBind arguments to a Runnable, returning a new Runnable.
A new RunnableBinding that, when invoked, will apply the bound args.
The query string to retrieve relevant documents for.
Optional
config: Callbacks | BaseCallbackConfigOptional configuration object for the retrieval process.
A promise that resolves to an array of Document
objects.
Use .invoke() instead. Will be removed in 0.3.0.
Main method used to retrieve relevant documents. It takes a query
string and an optional configuration object, and returns a promise that
resolves to an array of Document
objects. This method handles the
retrieval process, including starting and ending callbacks, and error
handling.
Executes a retrieval operation.
The query string used to search for relevant documents.
Optional
options: RunnableConfig<Record<string, any>>(optional) Configuration options for the retrieval run, which may include callbacks, tags, and metadata.
A promise that resolves to an array of DocumentInterface
instances
representing the most relevant documents to the query.
Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input.
Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.
A runnable, function, or object whose values are functions or runnables.
A new runnable sequence.
Stream output in chunks.
Optional
options: Partial<RunnableConfig<Record<string, any>>>A readable stream that is also an iterable.
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);
}
}
Optional
streamOptions: Omit<EventStreamCallbackHandlerInput, "autoClose">Optional
streamOptions: Omit<EventStreamCallbackHandlerInput, "autoClose">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.
Optional
options: Partial<RunnableConfig<Record<string, any>>>Optional
streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">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.
New configuration parameters to attach to the new runnable.
A new RunnableBinding with a config matching what's passed.
Create a new runnable from the current one that will try invoking other passed fallback runnables if the initial invocation fails.
A new RunnableWithFallbacks.
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.
The object containing the callback functions.
Optional
onCalled after the runnable finishes running, with the Run object.
Optional
config: RunnableConfig<Record<string, any>>Optional
onCalled if the runnable throws an error, with the Run object.
Optional
config: RunnableConfig<Record<string, any>>Optional
onCalled before the runnable starts running, with the Run object.
Optional
config: RunnableConfig<Record<string, any>>Add retry logic to an existing runnable.
Optional
fields: { Optional
onOptional
stopA new RunnableRetry that, when invoked, will retry according to the parameters.
Static
is
A type of document retriever that splits input documents into smaller chunks while separately storing and preserving the original documents. The small chunks are embedded, then on retrieval, the original "parent" documents are retrieved.
This strikes a balance between better targeted retrieval with small documents and the more context-rich larger documents.
Example