LangChain Expression Language (LCEL)

Name: LangChain Expression Language (LCEL)
Uploaded: 2026-06-16T14:25:36.923Z
Duration: 18 min 11 s
Channel: James Briggs
Description: Tutorial on LangChain Expression Language (LCEL), explaining its functionality and implementation with OpenAI's LLMs. The video covers traditional chains, the pipe operator, RunnableLambda, and parallel execution.

James Briggs16 June 2026Watch on YouTube

Part of series

Ep. 3 · Langchain Full Agent

View the series

Description

This chapter will introduce LangChain's Expression Langauge (LCEL). We'll focus on understanding how LCEL works under the hood and how it is implemented with OpenAI's LLMs. We'll compare LCEL against the traditional methods. We will build a pipeline where the user inputs a specific topic, and then the LLM looks for and returns a report on the specified topic. This generates a research report for the user. 🔗 Full Course: https://www.aurelio.ai/course/langchain 📌 Article and Code: https://www.jamesbriggs.io/langchain-lcel 💡 Subscribe for Latest Courses and Tutorials: https://www.aurelio.ai/subscribe 👋🏼 AI Consulting: https://aurelio.ai 👾 Discord: https://discord.gg/c5QtDB9RAP Twitter: https://twitter.com/jamescalam LinkedIn: https://www.linkedin.com/in/jamescalam/ #ai #langchain #programming #aiagents 00:00 LangChain Expression Language 00:58 Traditional Chains in LangChain 03:02 LangChain LCEL 03:55 LCEL Pipe Operator 09:09 LangChain RunnableLambda 12:41 LCEL Runnable Parallel and Passthrough

What you'll learn

LCEL is LangChain's Expression Language, a modern approach that replaces traditional chains and can be composed more simply
The pipe operator (|) in LCEL efficiently connects components together, making workflows easier to read and maintain
RunnableLambda allows you to insert custom Python functions into your LCEL pipeline for specific processing steps
LCEL supports parallel execution, enabling multiple tasks to run simultaneously for improved performance

Frequently asked questions

What is the difference between traditional chains and LCEL?

Traditional chains in LangChain use methods like .run() to invoke components, while LCEL uses the pipe operator (|) for a cleaner and more intuitive composition pattern.

How does the pipe operator work in LCEL?

The pipe operator connects components in a linear workflow, where the output of one step automatically becomes the input of the next step. This makes pipelines easy to read.

When do you use RunnableLambda in LCEL?

You use RunnableLambda to insert custom Python functions into your pipeline when you need specific processing logic that is not available as standard components in LangChain.

What makes parallel execution in LCEL useful?

Parallel execution in LCEL enables multiple tasks to run simultaneously, improving performance and reducing wait times when tasks can run independently from each other.