Flowise AI Tutorial (2025) #2 - Self Hosting on Render Cloud

FlowiseAI Full Tutorial (2025)Recent📅 2025-01-11

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Deployment Architecture

┌─────────────────────────────────────────────────────────────────────┐
│                     DEPLOYMENT PIPELINE                             │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│   LOCAL DEVELOPMENT              CI/CD                PRODUCTION    │
│   ─────────────────              ────                 ──────────    │
│                                                                     │
│   ┌─────────────┐           ┌─────────────┐      ┌─────────────┐   │
│   │    Code     │           │    Build    │      │    Render   │   │
│   │   + Test    │  ──────►  │   + Check   │ ───► │   Server    │   │
│   │   Locally   │           │   Quality   │      │             │   │
│   └─────────────┘           └─────────────┘      └─────────────┘   │
│         │                         │                     │           │
│         │                         │                     │           │
│    git commit               auto deploy            live app         │
│    git push                                             │           │
│                                                         ▼           │
│                                                  ┌───────────┐      │
│                                                  │   USERS   │      │
│                                                  └───────────┘      │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘

Deployment Steps

• Core concepts explained
• Step-by-step implementation
• Practical examples

Transcript

[00:00] Finally, let's have a look at deploying Flowwise to our very own cloud service. This option can be cheaper than the official Flowwise cloud service, and in the documentation, you can see all sorts of articles for deploying Flowwise to AWS, Azure, and many other service providers. I've personally used Render for my Flowwise instances, and these instances I've been running for nearly two years without any issues. So for this tutorial, I will also recommend going with Render.

[00:30] So first, go over to render.com and create a free account. Then from your dashboard, click on Add New, then Add a Web Service, and from this page, you will be asked to connect to your GitHub repository. So go over to GitHub.com and sign up for a free account. Then in the description of this video, you will find a link to the Flowwise repository on GitHub. Open up this page, then click on Fork, leave everything on the default values, and click on Create Fork.

[01:01] This will create a copy of the Flowwise repository in your very own namespace. So back in Render, you should see an option to connect to GitHub repo, so go ahead and do that, and in the list of repositories, select Flowwise AI, then click on Connect, then give your web service a name. And because I already have an instance of Flowwise deployed, I'll just call this one Flowwise AI Tutorial. In scrolling down, we can leave the language as Docker, leave the branch as Main, and then

[01:31] under the instance type. With a free plan, your flows won't be persisted, and you will lose all of your work when the server is restarted. So it might be perfect for following along with this tutorial, but I definitely recommend upgrading to the starter package if you do want to continue working with Flowwise. But for now, we'll simply start with a $7 per month package. Scrolling down, we can also add environment variables. For the first variable, let's create a variable called Flowwise_username, and let's set our

[02:03] username value. I'll simply call mine admin. Let's add another variable for the Flowwise password, and I'll simply enter the password as password123. I would suggest that you use something way more secure than this. Let's add a few more variables. Let's set the port as 3000. Let's add another variable for the node version, which we can set as 18.18.1. Now, the following variables are not needed if you are using the free plan, but if you

[02:33] do want persisted storage, in other words, you don't want to lose your flows whenever the server is restarted, we can go ahead and add the following variables. Let's set the API key path as slash opt slash render slash dot Flowwise. Let's add another variable for the database path, and this is the exact same value as the API key path. So I'll simply copy this value as we will be using it a few more times.

[03:04] Let's add another variable for the log path, which we'll also set equal to this value, but we'll also add slash logs. Let's add one more variable, and this is the secret path with the value of opt render dot Flowwise. I know that was tedious, but we are nearly done. All we need to do now is to attach the drive or the volume. Let's go to advanced, then under disk, let's click on add disk. And for the mount path, we're pasting that same value that we used earlier.

[03:36] And for the disk size, I'll simply go with one gig. And believe it or not, but we are done. We simply click on deploy web service. The deployment will take a few minutes to complete. And we're now live. Great. So all we have to do to access Flowwise is to click on this URL, and we will be prompted for a username and password, which we set as admin and password 123. And we can now access Flowwise. So do take note that if you self host Flowwise, the responsibility to keep Flowwise up to

[04:07] date falls with you. But thankfully, that's super easy. Flowwise is constantly adding new updates and fixes to their main GitHub repo. This text is currently saying that this branch is up to date. But if you are behind, it will say something in the lines of this branch is behind a certain amount of commits. All you have to do in that example is to click on sync fork, and there will be a button here that will allow you to update your fork. In fact, let me show you an example from another repo, like this

[04:37] innate end fork that I have. So this innate end instance is sitting within my own namespace. And here we can see that this is actually 28 commits behind the main innate end repo. So when I go to sync fork, I can simply click on update branch. So now it's saying that this branch is up to date with the innate end master branch. And if I go back to my render dashboard, we can see that my innate end instance is now being redeployed with those new changes. For the remainder of this tutorial, I

[05:09] will be using a local instance of Flowwise. There is a bonus section towards the end of the course where we'll integrate Flowwise with Telegram. And for that, we won't need a cloud instance of Flowwise. But for everything else, we will be using the local instance of Flowwise. But of course, you can follow along using the cloud instance as well.