Build Your Own Auto-GPT Apps with LangChain (Python Tutorial)

This video is an introduction to the Python LangChain library. LangChain is a framework for developing applications powered by language models like OpenAI's GPT-3.5 and GPT-4. I will go over all the modules, provide examples, explain the quick start guide, and then show a demo of an intelligent assistant that can answer questions about any specific YouTube video. You can use LangChain to build your own intelligent systems, similar to Auto-GPT and BabyAGI. I believe there is an amazing opportunity right now for data scientists and AI engineers to become a front-runner using these tools.

🔗 Links

⚙️ Copy my VS Code Setup

⏱️ Timestamps
00:00 Introduction
00:26 What is LangChain
01:19 Job opportunities
02:55 LangChain's Modules
03:47 Models
05:37 Prompts
06:43 Memory
08:21 Indexes
08:58 Chains
11:06 Agents
14:32 Use Case: YouTube Video Assistant
27:45 Why I am all in on this
28:15 What is Data Freelancer?

👋🏻 About Me
Hey there, my name is @daveebbelaar and I work as a freelance data scientist and coach. You've stumbled upon my YouTube channel, where I give away all my secrets when it comes to working with data. I'm not here to sell you any data course — everything you need is right here on YouTube. Making videos is my passion, and I've been doing it for 18 years. I just genuinely enjoy helping people.

[daveebbelaar]

What are you going to build with this? 🤑

[bwilliams]

This is an excellent video. I’ve been deep diving into LangChain for about a month and this summarised pretty much the extent of what I’ve learnt in 30 mins. Brilliant! Looking forward to watching many more LangChain vids from you Dave. Cheers!

[PeterDrewSEO]

Dude, you are killing it with these videos. Such clear instruction, so helpful Thank you. Got so many script ideas running around my head :)

[psjjeyk]

This is THE best LangChain tutorial on YouTube

[patrickwhite]

This is the first youtube vid that I've seen that talks about embeddings with LangChain. This for me is an lightbulb moment as the small context window is the major limitation for ChatGPT atm. Giving it the ability to take new source data and chunk it to referenceable bites feels like a work-around for the context window limitation, but it's an awesome work-around nonetheless. Good stuff!

[Deco]

Great tutorial, thanks for this.

For any python noobs who get stuck like I did with the dependencies not being found within the downloadable langchain-experiments example. Be sure to open the entire folder and not just the python file within VSCode otherwise the environment you setup won't be used.

[johnpaul]

Great video! Just started working as a developer and got assigned a task that uses langchain. This is very helpful

[mavreyn]

Man I love this video! Followed along with it this afternoon and everything worked well. Sometimes stuff just doesn't work from some video tutorials but this one really made me feel like the time I spent was worth it! Having a working 'applet' at the end! Thanks so much

[topvladis]

Great vid! A funny thing though: in the python year *3 example, the model didn't use the llm-math, and hallucinated the calculation (5783 instead of 1991*3=5973). 👻👻

[tejasvinnarayan]

This i the best AI tutorial I have watched! So much clearer, all codes are given, and more! And there is nothing left to touch to check other videos, go ahead and build apps lol. Amazing github! I will create an app to know when you post new videos lol. Thank you so much, Dave! Please release more on AutoGPT.

[arifsoylu]

Finally a video that mentiones the technical details and capabilities, not AI-influence hype!

[kushagrgoyal]

glad to see ur video on langchain!! awesome work as usual!

[simonraj]

Very clear tutorial. How do you do it with text documents instead of transcripts from YouTube. 1. Read the text from a text file 2. Carries out the document splitting. 3. Get a query from user . 4) writes the response to another text file. Do let me know if you with to collab on this.

[davediamond]

This has been extremely helpful. As a total noob coder you've made it so easily to understand.
Thank you so much!

[WillSteffen]

Killer demo, straight to the point and left me with a really clear idea of how to start implementing in projects. This stuff is turning low code hackers like me into Harry Prompters 😅

[rahulmahaseth]

Can you make tutorial on converting this to a website

[dmartin]

I can feel the doors of understanding unlocking with your great explanation mate! I’m gonna add this video to my assistant’s db so I can always use this awesome resource. Keep it up! I want to see a lot more from you!

[MrKferi]

The multiplication in 14:02 (year of python creation * 3) is wrong. Is llangchain able to call multiple tools in a single prompt? After the wikipedia info it should have called llm-math.
Awesome vid btw!

[kylarosborne]

Hey Dave, I really love this video. I had heard about langchain, but with so many new things popping up I didn’t give it a lot of attention until now.

In terms of things to build with this, I’d like to use all of my past long form journal entries to create a virtual representation of myself.

I’m on Upwork, but my domain of expertise is embedded systems. I have a little experience with data science, but not enough to easily market myself in that way.

Anyway, thanks for sharing this info about langchain! Looking forward to more videos

[rafaelmartinsdecastro]

After the similarity search, I got kinda lost between the definition of docs_page_content and the injection of {docs} in your "template parameter". I was under the impression that you would have passed docs_page_content instead.