FREE: Langflow AI Python RAG Agent Self-Hosted On Coolify GUI Drag-N-Drop Builder🤖 Open-Source!🚀

What's going on everybody Josh pook here and in today's video we are going to be looking at Lang flow and I did a video on Lang flow uh a few weeks back and I showed you how to install and self-host langlow using python using pip install Etc and it's pretty uh simple to do it that way it's pretty simple to do it anyway regardless but I was getting some people ask hey how do I hosted on a server or coolify or

Whatever the case may be um a lot of people are very interested in langlow cuz this is a really really cool tool if you're new and you haven't seen that last video about Lang flow I'll uh quickly go over it and you'll see how awesome this tool is um but we're going to show you how to host it self-host it on coolify let's dive right into [Music] it all right guys so just a quick background on langlow um essentially uh it's

Somewhat of I would say maybe an alternative to tools like flow wise AI as well as Diffy Ai and these both are two really good tools I've done videos on them showing you how to self-host them on uh coolify self-host them and langlow is somewhat similar it's basically the easiest way to create and share automate autonomous agents discover simp a simpler way to build uh around foundation models so retrieval Pipelines um AI driven apps a bunch of stuff that you can

Do here and fine tuning prompt variables group components custom components and the cool thing I I really like about uh langlow is it's python based so at least as of now I haven't um I I don't think I've seen a tool like Lang flow um I you know I know there's so many tools out there maybe if you guys have seen something that's very similar to it that is python based and like uh can do the these sort of things let

Me know in the comments down below but that's why I'm really uh excited about this tool and excited to build on it because you can use the no code function to build things in Python basically with it and then you can even see the python code which is really useful I don't know about you guys but uh especially ever since you know AI I mean AI has been going on for a long time but really since I've been really really diving

Into to AI I've been re um definitely trying to fine-tune my python coding and whatnot even though you can always get AI to assist you um just really trying to um because python is the language uh the main go-to language around U machine learning AI Etc so anyways um yeah link for everything will be in the description down below link to langl flow. org as well as to the docs so like I said uh you can check out the video I

Did before where I basically show you how to install langlow uh using python all right so I'm not going to be doing the python install in this video uh we're going to be using coolify now the same thing applies to for really anything like if you're hosting it on a server examp for example I'm just using coolify um because one coolify is pretty good it's open source and you can self-hosted and I've done like probably about 10 12 videos maybe even

On kify so uh just to quickly summarize it if you go to coolify doio I'll leave a link in the description you can go to selfhosted and you literally just run this command and you'll get a nice self-hosted coolify and it's essentially an alternative to tools like netlify Heroku verel Etc it's 100% free it's pretty awesome I use it for many different apps and I really really like it so let's go ahead and go to the um oh also too I

Will mention you can sign up for the uh you know Cloud version and I'll leave a link for this too mentioned this in my last video but you don't even have to self-host langlow maybe if you just want to try it out to initially and then self-host it um you can go to data stacks.com as. datx I'll leave a link below you can sign up and uh you can give it a try Okay so this is the GitHub repo for langlow

I'll leave a link down below well actually this is just my Fork version but same thing I'll leave a link to the original version and and um it goes through the install of installing it with Pip or python um we're going to do it deploy it using Docker and initially I just didn't see you know the docker part but you just actually have to go into Docker right here and then just go into the docker read me um where is the

Docker read me Docker example sorry Docker example and then go into the docker read me and you'll see running Lang flow with Docker so um there's still a few configurations I'm doing and just uh with the install to get it to how I want it but the basics is what I'll show you here so running Lang flow with Docker and when you're installing many different tools or apps like on coolify or on a server some a lot of them can sometimes

Have different configurations or this or that that you want to do so um sometimes it can be tricky sometimes but this one's pretty somewhat like it's it's not too tricky so um what we're going to do is we're so if you're doing this just on your like your own you could do this just on your own computer and just like install it there and uh without using Python and just use Docker and you would just clone the repository CD into Lang

Flow Docker example and then Docker could compose up but since in this video I'm going to show you how to do it with um with uh kify okay so once we're in kify um I'm already in a project and a re uh an environment so I'm just and then I I'm in a resource once you create a new resource you're going to just click on for well for you can do it many different ways we're just going to click on public

Repository you're going to paste in the Lang flow repo check repo and then we're going to click on build pack and click on Docker compose okay from that point on we're going to put in the docker compos location which is Docker Docker example and then Docker compose so right here it will be Docker Dash example for Slash and then Docker compose ammo without an a like that so that's the docker location we'll click on continue all right and then you will

See um your basically your your whole configuration can reload the compos file right here to make sure that it's pulling it okay wait so it couldn't be found I may have to put the wrong location Docker oh it's Docker underscore example so here underscore and then save okay now let's reload this and we should get the docker compos okay perfect so I got the docker compos right here and as you can see like you could adjust this if um you need

To and you just obviously Fork the repo and change some stuff but um yeah and then coolify just adds the coolify tags to it the labels the traffic uh um okay and then from that point on you simply just deploy now I'm not going to deploy it right now because I actually already have an instance deployed on the same port and uh I'm not going to change the port um but once you deploy it you shouldn't get any issues it's pretty

Deployable right out of box okay once you do that you can go the port is uh 786 so you can go to your server IP sl7 860 and you'll see langlow loaded up okay um just a quick overview of langlow I'm not going to dive super super deep but if you want me to do more videos on it which I probably will regardless anyways especially once I start using it a lot more I will um but let's just go I I

You could do new project here and like select a specific project you can go to store as well and just to do this you have to connect your story API so you just go into your settings and it when you go to API um it will say you have to like sign up through the langlow store so you can go create a free account and then once you're in there it will give you an API and you just put it in

Your self-hosted version and then you'll be able to pull um the the different components flows bundles available on the Lang flow store if I go to um collections here let's just take a look at Vector store rag so I'll just show you kind of the power of this tool Lang flow um obviously I'm we're not going to run it and connect everything right now but you can see this is a rag a vector store rag the chat input open AI embeddings

Astra data uh database right there parse data prompt uh right here to open AI to chat output and then we have uh the vector store so that's the this is the querying right here and the embedding so the embedding query so betting the query into Astra parsing the data and Etc and then this is the um the vector store part so we got a file then split text um and embedding so chunking and embedding right here and then into Astra database

Right so not going to go through every single component but you that's the cool thing too in the store you can add like components you can build components yourself like it's very customizable um we got like embeddings Vector stores helpers models data prompts outputs and uh like all the different ones you could pretty much think of and another really cool thing is like if I hover over this and I click here I get the code for this whole workflow which is

Really insane like this is the python code I could literally copy this open up an IDE uh I could open up vs code or pie charm um and then I could just like maybe have to make a few changes and whatnot but you got um you really do have a the python code right here so I really like that um it gives you a lot of custom customization ability as well as even too if you're learning how to build out these

Like these pipelines and all these things like with within Pyon uh but python this is also a really good tool to help you because you also just like build it you could build it out in no code and then look at the the code and like see okay how did I do this like what how's it working um etc etc right so that's what I really like about this tool that's why I'm really excited about it um I think it's a

Very very kind of a tool a lot of people are excited about uh based on you know the comments and whatnot about the last YouTube videos so I know a lot of you guys on this channel use things like coolify to self host Etc use all these these other tools so um I just want to make a video showing you guys how to do that don't want to make it too too long since I did cover this tool already but I

Will be doing more videos showing you how to build things out in this tool as well as well as a bunch of other AI videos right if you're new to the channel we upload videos every single day on AI automation workflows business entrepreneurship Marketing sales Etc really anything uh coding with AI Etc so make sure to smash that like button smash that subscribe button if you got value here and you want to stay up to date with the daily uploads also

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If you have any questions let me know in the comments and I'll do my best to help but I will see you in tomorrow's video keep hustling keep grinding and of course guys accelerate your stride take care