LangChain Crash Course - Build apps with language models

In this LangChain Crash Course you will learn how to build applications powered by large language models. We go over all important features of this framework.

Timeline:
00:00 - Introduction
01:09 - Installation
01:22 - LLMs
03:08 - Prompt Templates
04:58 - Chains
06:02 - Agents and Tools
09:54 - Memory
11:15 - Document Loaders
12:24 - Indexes

Resources:

Get my Free NumPy Handbook:

📓 ML Notebooks available on Patreon:

If you enjoyed this video, please subscribe to the channel:

~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~ SUPPORT ME ~~~~~~~~~~~~~~

#Python

----------------------------------------------------------------------------------------------------------
* This is an affiliate link. By clicking on it you will not have any additional costs, instead you will support me and my project. Thank you so much for the support! 🙏

[bassemgouty]

By far the most comprehensive and clear video about LangChain, Keep doing things like this !

[muhammadlufti]

I remember the struggle and effort on working with text-davinci-003 model with lots of API only to have the model updated with current knowledge, and modifying script for short or long term memory in chat. But now we have this amazing library, packed with several remarkable features.

[wadejohnson]

Hi Patrick. Thank you for this. You are undeniably in a league of your own when it comes to teaching. You set a high bar for others to follow. Well done.

[davidwu]

you are doing the lord's work Patrick

[williamgillett]

Great walk-through - good examples, like the colab page. Very helpful to bring all these parts together with relevant live examples.

[alejandrozaizar]

I haven’t found a full step by step tutorial on langchain importing several documents then storing them on pinecone and finally using a chat up to interact with it in a deployment environment, could you make some example about that?

[rajuchoudhari]

Thanks Patrick for sharing. enjoyed watching this, very useful.

[solidkundi]

Wowsers... i've been listening to alot of people talk about langchain. your teaching style really helped. Keep up the amazing work you do!

[janu]

Great summary! we need a second video on this.

[HIBaysal]

Best video so far, all the rest just do 1 trick pony with all of them doing the same 1 thing. Here we see multiple options. Thank you for your time making this

[anokimusic]

Thank you man! Love your teaching style. Pls do more about langchain 🙏🏼

[fomukomsam]

Phenomenal, such a blessing to be alive in this generation and to come across your video.

I am truly grateful..

Super Teacher.

[codeAI]

informative. diverse spectrum of code examples. builds the bigger picture. -> recommended video.

[GiovanneAfonso]

The best video I've seen about langchain! Please make more on langchain please

[abhishekgupta]

This is one of the best Videos I found on Langchain.

[omg]

This video is Short but CLEAR.VERY GOOD. KEEP GOING BRO.

[EmilioGagliardi]

thank you very much for this. its very helpful to see these concepts and step-by-step walkthroughs. :)

[rrtt]

Thank you Patrick for such a precious tutorial!

[Anannya_C]

Everything is explained so systematically and in a very concise manner. ❤

[jeffpowers]

love the creativity that went into making this. It's clear that a lot of thought and effort went into this. One clarification.. we have some sensitive data which should not be sent externally In this case such as langchain.vectorstores stores locally, what sort of information goes externally to openAI or else where