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RunnableLambda

As explained in Build AI-Enhanced Web Apps

RunnableLambda is a LangChain runnable abstraction that wraps a function so it can participate in an executable chain.

RunnableLambda wraps a generic JavaScript function as a LangChain runnable, allowing custom application logic to participate in executable chains and LCEL compositions. section 6.5.1

Use RunnableLambda when a chain needs to:

  • Adapt application logic, such as fetching weather data, before passing results to a prompt template, language model, and output parser. section 6.1.2
  • Compose custom functions with other runnables through pipe, while retaining compatibility with LCEL chains. section 6.5.1
  • Stream chain output into a Next.js interface by consuming chain.stream results and forwarding updates to createStreamableUI. section 6.1.2

Weather chain with streamed UI output

Create a runnable from fetchWeatherData, then pipe it through promptTemplate, llm, and StringOutputParser. Call chain.stream({ city }), iterate over the results, append each item to textContent, and update a streamable chat component until the stream completes. section 6.1.2

const someFunc = RunnableLambda.from((input) => {
return input; 
}); 
const chain = someFunc.pipe(runnable1);

The compact runnable pattern shows how RunnableLambda.from turns a JavaScript function into a chain component and connects it with pipe. section 6.5.1

How Build AI-Enhanced Web Apps covers it

How deep it goes
Explains function wrapping, pipe composition, and streaming consumption, but does not detail Runnable internals.
Examples
Uses a weather-data function, a city input, a chained language-model response, and incremental chat-bubble updates.
What it assumes
Assumes JavaScript functions, LangChain runnables, pipe composition, and asynchronous iteration; demonstrates the wrapping pattern directly.
What you can do after
Build custom runnable chains and stream their results into a real-time user interface.
How it connects
Connects RunnableLambda with LCEL, RunnableSequence, RunnableParallel, prompt templates, language models, output parsers, and streaming UI.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Build AI-Enhanced Web Apps. The section links point to the parts of the book it draws on.