Langchain Expression Language: The Ultimate Practical Guide

🔗 Deciphering LangChain Expression Language: A Comprehensive Guide 🔗
#langchainexpressionlanguage
#langchain
#langchain expression language

Dive deep into the realm of the LangChain Expression Language with us! As a potent tool within the LangChain ecosystem, langchain expression language makes writing code much simpler and is crucial for anyone aspiring to harness its full power.

0:00 Welcome
0:52 Introducing ChefBot
1:27 Environment Setup
2:29 PromptTemplate & LLM
3:32 PromptTemplate & OutputParser
4:13 Batch
5:01 Stream
5:41 Async
6:39 Function Calling
7:51 VectorStore, & Retriever
9:53 Conversational Retrieval Chain
12:14 Combining Multiple LLM Chains
13:47 Tools
14:57 Code Writing
16:26 Conclusion

Langchain Expression Language: Easy declarative way to code and lot more!

With the newly introduced Langchain Expression Language(LCEL),

1. Engaging with core components becomes as easy using pipe operation.
2. The black box behind how to optimize LLMs calls is taken away with batch, stream and a sync APIs.
3. Conversation Retrieval Chain, VectorStore retrieval & Memory based prompts are well structured with easily shared boiler plate using RunningPassThrough and ItemGetter.
4. Function calling, similar to OpenAI , is now here.
5. And lot more syntactical sugar is offered.

🔍 What We'll Cover:
🔹 Introduction to LangChain Expression Language
🔹 Key Syntax and Building Blocks
🔹 Practical Use-Cases and Real-World Applications
🔹 Tips, Tricks, and Best Practices for Seamless Coding

In this course, we introduce ChefBot: ChefBot is not your ordinary sous-chef; it's a recipe recommendation bot, designed to stir up your culinary world!   You give ChefBot your preferred ingredients or the type of dish you fancy, and voila, ChefBot whips up a perfect recipe recommendation just for you!

Whether you're just getting started with LangChain or seeking to elevate your existing skills, this video is designed to provide a clear and thorough overview of its expression language. By the end of this guide, you'll be confidently crafting efficient, powerful expressions tailored to your specific AI and conversational needs.

So, ready to unlock a new dimension in LangChain? Hit that subscribe button and embark on this enlightening journey with us!

🔖 Tags:
#langchain #langchainexpressionlanguage #langchain expression language #langchaintutorial #langchain ai #langchain agent
#langchain python #gpt4 #openai #llm #langchainexplained #langchain python

[waseemhnyc]

This video is gold. Thanks for sharing!

[bytesize]

Very well explained, thanks for sharing.

[csmaca]

Great explanation! Keep making videos please.

[pypypy]

How to pass `vebose=True` to the chain in this new expression language?

[nervous]

10:38 Where does the '{page_content}' arugument in the first line of code come from?

[nervous]

9:20 what if we have 2 or more questions we want to pass through the function without being transformed in the firs step?

[manohar]

Can u please... Explain code also, how to to take, which modules we need to import and why we need to import??, because all YouTube videos have already direct explanation.... None explained step by step, can u make videos step by step it's useful for all

[dheeraj]

If I have to guess, I would say that you're using some text to speech program. Can you please do a video on using the vocoders and synthesizers to extract an audio out of a pre-recorded clip and clone it. Will be really helpful. Not with Polly preferably