Adding Keycloak Authentication to an Existing .NET Aspire Application

By the end of this post, you'll have a working login/logout flow backed by Keycloak, running locally via Aspire and deployable via Docker Compose.

If your Aspire app doesn't have authentication yet, this is your fastest path to a real identity provider. This tutorial walks through wiring Keycloak OIDC into an existing .NET Aspire + Blazor Server app: from AppHost registration to login/logout UI, using production code from NoteBookmark, an open-source bookmark manager built with .NET Aspire and Blazor.\

[version en français disponible]

Step 1: Add Aspire.Hosting.Keycloak to AppHost

Aspire provides first-class Keycloak support through the Aspire.Hosting.Keycloak package. Add it to your AppHost project:

For AppHost project

dotnet add package Aspire.Hosting.Keycloak

Run dotnet restore to pull the package.


Step 2: Register Keycloak in AppHost.cs

With the package installed, register Keycloak as a resource in your AppHost. Aspire will spin up a Keycloak container, wire its connection details into dependent projects, and ensure proper startup ordering.


// ...

// Add Keycloak authentication server
var keycloak = builder.AddKeycloak("keycloak", port: 8080)
    .WithDataVolume(); // Persist Keycloak data across container restarts

if (builder.Environment.IsDevelopment())
{
    // ...

    builder.AddProject<NoteBookmark_BlazorApp>("blazor-app")
        // ...
        .WithReference(keycloak)  // <-- reference Keycloak
        .WaitFor(keycloak)  // <-- wait for Keycloak to be ready
        .WithExternalHttpEndpoints()
        .PublishAsDockerComposeService((resource, service) =>
        {
            service.ContainerName = "notebookmark-blazor";
        });
}

Key Changes:

  • AddKeycloak("keycloak", port: 8080): Registers a Keycloak resource listening on port 8080.
  • WithDataVolume(): Persists Keycloak's configuration and realm data across container restarts. Without this, you'd lose your realm setup every time the container stops.
  • .WithReference(keycloak): Injects Keycloak connection settings (base URL, etc.) into the BlazorApp as environment variables.
  • .WaitFor(keycloak): Ensures Keycloak is fully started before launching the Blazor app. This is critical: if your app starts before Keycloak is ready, OIDC discovery will fail.

 

Step 3: Set Up Keycloak for Non-Aspire (aka prod) Deployments

This post focuses on the Aspire dev setup, but for production (Docker Compose, Kubernetes), you need a standalone Keycloak. Here's what that looks like and why.

Aspire can actually help you bridge the gap. AddDockerComposeEnvironment() in AppHost generates a draft Docker Compose file from your Aspire model, a great starting point before customizing for production. Worth checking out if you want a head start.

The final compose files for both Keycloak and the NoteBookmark app are available in the NoteBookmark repo:

A few things worth noting about the setup:

  • Postgres as the backing store: Keycloak uses a dedicated Postgres instance (not the app's database) to persist realm configuration, users, and sessions.
  • KC_HTTP_ENABLED: "true": Allows HTTP traffic internally. In production, Keycloak runs behind a reverse proxy (nginx, Traefik) that handles TLS termination: HTTPS externally, HTTP internally.
  • KC_FEATURES: "token-exchange": Enables the token exchange feature, needed if you want service-to-service auth flows.

Step 4: Configure Keycloak Realm and OIDC Client

This configuration is required in both production and development environments, but only needs to be done once per environment. In dev, thanks to .WithDataVolume(), all Keycloak settings are persisted between run and debug sessions, so you only configure it once and it survives restarts.

Once Keycloak is running, configure it:

  1. Navigate to http://localhost:8080 and log in with your admin credentials.
  2. Create a new realm:
    • Click Create Realm
    • Name: notebookmark (match the realm in your Authority URL below)
  3. Create an OIDC client:
    • Clients → Create Client
    • Client ID: notebookmark
    • Client Protocol: openid-connect
    • Access Type: confidential (generates a client secret)
    • Valid Redirect URIs: http://localhost:5173/* (adjust for your Blazor app's URL)
    • Web Origins: http://localhost:5173
  4. Go to the Credentials tab and copy the Client Secret: you'll need this in your app config.
Keycloak client configuration screen


Step 5: Add OpenID Connect to the Blazor App

Now wire up the authentication pipeline in your Blazor Server app.

Add the NuGet Package


For BlazorApp project

dotnet add package Microsoft.AspNetCore.Authentication.OpenIdConnect

Update Program.cs

BlazorApp/Program.cs:

using Microsoft.AspNetCore.Authentication;
using Microsoft.AspNetCore.Authentication.Cookies;
using Microsoft.AspNetCore.Authentication.OpenIdConnect;

//...

// Add authentication
builder.Services.AddAuthentication(options =>
{
    options.DefaultScheme = CookieAuthenticationDefaults.AuthenticationScheme;
    options.DefaultChallengeScheme = OpenIdConnectDefaults.AuthenticationScheme;
})
.AddCookie(CookieAuthenticationDefaults.AuthenticationScheme)
.AddOpenIdConnect(OpenIdConnectDefaults.AuthenticationScheme, options =>
{
    var authority = builder.Configuration["Keycloak:Authority"];
    options.Authority = authority;
    options.ClientId = builder.Configuration["Keycloak:ClientId"];
    options.ClientSecret = builder.Configuration["Keycloak:ClientSecret"];
    options.ResponseType = "code";
    options.SaveTokens = true;
    options.GetClaimsFromUserInfoEndpoint = true;

    // Allow overriding RequireHttpsMetadata via configuration.
    // Relax the requirement when running in a container against HTTP Keycloak.
    var requireHttpsConfigured = builder.Configuration.GetValue<bool?>("Keycloak:RequireHttpsMetadata");
    var isRunningInContainer = string.Equals(
        System.Environment.GetEnvironmentVariable("DOTNET_RUNNING_IN_CONTAINER"),
        "true",
        StringComparison.OrdinalIgnoreCase);

    if (requireHttpsConfigured.HasValue)
    {
        options.RequireHttpsMetadata = requireHttpsConfigured.Value;
    }
    else
    {
        var defaultRequireHttps = !builder.Environment.IsDevelopment();
        if (isRunningInContainer &&
            !string.IsNullOrEmpty(authority) &&
            authority.StartsWith("http://", StringComparison.OrdinalIgnoreCase))
        {
            defaultRequireHttps = false;
        }
        options.RequireHttpsMetadata = defaultRequireHttps;
    }

    options.Scope.Clear();
    options.Scope.Add("openid");
    options.Scope.Add("profile");
    options.Scope.Add("email");

    options.TokenValidationParameters = new()
    {
        NameClaimType = "preferred_username",
        RoleClaimType = "roles"
    };

    // Configure logout to pass id_token_hint to Keycloak
    options.Events = new OpenIdConnectEvents
    {
        OnRedirectToIdentityProviderForSignOut = async context =>
        {
            var idToken = await context.HttpContext.GetTokenAsync("id_token");
            if (!string.IsNullOrEmpty(idToken))
            {
                context.ProtocolMessage.IdTokenHint = idToken;
            }
        }
    };
});

builder.Services.AddAuthorization();
builder.Services.AddCascadingAuthenticationState();
builder.Services.AddHttpContextAccessor();

// ... existing Razor Components, FluentUI, etc. ...

var app = builder.Build();
app.MapDefaultEndpoints();

// ... existing middleware ...

// CRITICAL: UseAuthentication BEFORE UseAuthorization
app.UseAuthentication();
app.UseAuthorization();

app.MapRazorComponents<App>()
    .AddInteractiveServerRenderMode();

// Authentication endpoints
app.MapGet("/authentication/login", async (HttpContext context, string? returnUrl) =>
{
    var authProperties = new AuthenticationProperties { RedirectUri = returnUrl ?? "/" };
    await context.ChallengeAsync(OpenIdConnectDefaults.AuthenticationScheme, authProperties);
});

app.MapGet("/authentication/logout", async (HttpContext context) =>
{
    var authProperties = new AuthenticationProperties { RedirectUri = "/" };
    await context.SignOutAsync(CookieAuthenticationDefaults.AuthenticationScheme);
    await context.SignOutAsync(OpenIdConnectDefaults.AuthenticationScheme, authProperties);
});

app.Run();


Configuration


Create or update appsettings.json in the BlazorApp project:

{
  "Keycloak": {
    "Authority": "http://localhost:8080/realms/notebookmark",
    "ClientId": "notebookmark",
    "ClientSecret": "your-client-secret-from-keycloak",
    "RequireHttpsMetadata": false
  }
}

For your Prod, Docker Compose deployments, use environment variables in your docker-compose.yaml:

environment:
  Keycloak__Authority: ${KEYCLOAK_AUTHORITY}
  Keycloak__ClientId: ${KEYCLOAK_CLIENT_ID}
  Keycloak__ClientSecret: ${KEYCLOAK_CLIENT_SECRET}
In the development enviroment, Aspire's .WithReference(keycloak) automatically injects environment variables like services__keycloak__http__0 for the Keycloak base URL. You can read this in your config or manually set the Authority URL as shown above.

 

Handling HTTP vs HTTPS: The RequireHttpsMetadata Gotcha

By default, the OpenID Connect middleware requires HTTPS for metadata discovery (RequireHttpsMetadata = true). This is a security best practice for production, but it causes problems in local/container dev environments where Keycloak runs on HTTP.

The code above implements a smart fallback:

  1. Check explicit configuration first: If Keycloak:RequireHttpsMetadata is set in config, use that value.
  2. Detect container environment: If running in a container (DOTNET_RUNNING_IN_CONTAINER=true) and the Authority URL is HTTP, disable the HTTPS requirement.
  3. Default to HTTPS in production: Outside of Development mode, default to requiring HTTPS.

This ensures:

  • Local dev works seamlessly with HTTP Keycloak
  • Container-to-container communication works (HTTP internally)
  • Production enforces HTTPS (assuming you've configured it properly)

Note: In production, run Keycloak behind a reverse proxy (nginx, Traefik, etc.) that handles TLS termination. Your app sees https://yourdomain.com, Keycloak internally runs on HTTP.

That's the server-side setup done. Now let's build the Blazor UI pieces that make auth visible to users.


Step 6: Blazor UI: Login, Logout, and Route Protection

With the backend authentication pipeline configured, it's time to build the UI components that let users actually log in, log out, and interact with protected content. We'll create three key pieces: the login/logout pages, a login display component, and routing configuration that enforces authorization.

Keycloak login screen

The Login and Logout Razor Pages

First, we need pages to trigger authentication flows. These aren't typical Blazor pages with markup—they're redirect triggers that hand off control to Keycloak.

Login.razor

Create Components/Pages/Login.razor:

@page "/login"
@attribute [AllowAnonymous]
@using Microsoft.AspNetCore.Authorization
@using Microsoft.AspNetCore.Authentication
@using Microsoft.AspNetCore.Authentication.OpenIdConnect
@inject NavigationManager Navigation
@inject IHttpContextAccessor HttpContextAccessor

@code {
    protected override async Task OnInitializedAsync()
    {
        var uri = new Uri(Navigation.Uri);
        var query = System.Web.HttpUtility.ParseQueryString(uri.Query);
        var returnUrl = query["returnUrl"] ?? "/";

        var httpContext = HttpContextAccessor.HttpContext;
        if (httpContext != null)
        {
            var authProperties = new AuthenticationProperties
            {
                RedirectUri = returnUrl
            };
            await httpContext.ChallengeAsync(OpenIdConnectDefaults.AuthenticationScheme, authProperties);
        }
    }
}

What's happening here?

  • No markup: This page doesn't render anything. Its job is to initiate the OpenID Connect authentication challenge, which redirects the browser to Keycloak.
  • ChallengeAsync: This triggers the OIDC middleware to redirect the user to Keycloak's login page.
  • Return URL: We capture the returnUrl query parameter so users land back where they started after logging in.
  • [AllowAnonymous]: Critical! Without this, the page would require authentication to access, creating a redirect loop.

Logout.razor

Create Components/Pages/Logout.razor:

@page "/logout"
@attribute [AllowAnonymous]
@using Microsoft.AspNetCore.Authorization
@using Microsoft.AspNetCore.Authentication
@using Microsoft.AspNetCore.Authentication.Cookies
@using Microsoft.AspNetCore.Authentication.OpenIdConnect
@inject IHttpContextAccessor HttpContextAccessor

@code {
    protected override async Task OnInitializedAsync()
    {
        var httpContext = HttpContextAccessor.HttpContext;
        if (httpContext != null)
        {
            var properties = new AuthenticationProperties
            {
                RedirectUri = "/"
            };
            await httpContext.SignOutAsync(OpenIdConnectDefaults.AuthenticationScheme, properties);
            await httpContext.SignOutAsync(CookieAuthenticationDefaults.AuthenticationScheme);
        }
    }
}


Why sign out of TWO schemes?


This is where many implementations fail. OpenID Connect uses a dual authentication scheme:

  1. OpenIdConnect scheme: Handles the protocol dance with Keycloak (redirects, token exchange, logout).
  2. Cookie scheme: Manages the local session in your Blazor app.

When logging out, you must sign out of both, in this order:

  1. OIDC first: This redirects to Keycloak's logout endpoint, ending the SSO session.
  2. Cookie second: This clears the local authentication cookie.

Signing out of only the cookie leaves the Keycloak session active—users can click "Login" and get back in without re-entering credentials. Signing out only from OIDC leaves the local cookie intact, so the app still thinks they're logged in.

The RedirectUri in the authentication properties controls where users land after the Keycloak logout completes. We send them to the home page.

 

Step 7: The LoginDisplay Component

Now we need a UI element to show login state and provide login/logout actions. This typically lives in your app's header or navigation bar.

Note: NoteBookmark uses FluentUI Blazor (the <Fluent...> components), it's not a requirement, but it definitely looks great ;)

Create Components/Layout/LoginDisplay.razor:

@rendermode InteractiveServer
@using Microsoft.AspNetCore.Components.Authorization
@inject NavigationManager Navigation

<AuthorizeView>
    <Authorized>
        <FluentStack Orientation="Orientation.Horizontal" HorizontalGap="8" 
                     HorizontalAlignment="HorizontalAlignment.Right" 
                     VerticalAlignment="VerticalAlignment.Center">
            <span>Hello, @context.User.Identity?.Name</span>
            <FluentButton Appearance="Appearance.Lightweight" OnClick="Logout" 
                          IconStart="@(new Icons.Regular.Size16.ArrowExit())">
                Logout
            </FluentButton>
        </FluentStack>
    </Authorized>
    <NotAuthorized>
        <FluentButton Appearance="Appearance.Accent" OnClick="Login" 
                      IconStart="@(new Icons.Regular.Size16.Person())">
            Login
        </FluentButton>
    </NotAuthorized>
</AuthorizeView>

@code {
    private void Login()
    {
        var returnUrl = Navigation.ToBaseRelativePath(Navigation.Uri);
        if (string.IsNullOrEmpty(returnUrl)) returnUrl = "/";
        Navigation.NavigateTo($"/login?returnUrl={Uri.EscapeDataString(returnUrl)}", forceLoad: false);
    }

    private void Logout()
    {
        Navigation.NavigateTo("/logout", forceLoad: false);
    }
}

Key implementation details:

  • @rendermode InteractiveServer: This is essential. <AuthorizeView> needs to access AuthenticationStateProvider, which requires an interactive render mode. Without this, the component renders as static HTML and won't respond to auth state changes.
  • <AuthorizeView>: This component automatically shows/hides content based on authentication state. The context parameter provides access to the User claims principal.
  • Return URL on login: We pass the current page URL so users return to where they were after authenticating.
  • forceLoad: false: We use in-app navigation. The Login.razor and Logout.razor pages will handle the actual HTTP redirects.

Add this component to your MainLayout.razor or header component:<LoginDisplay />

visual of the LoginDisplay

Step 8: Protecting Routes and Pages

With login/logout working, you need to enforce authorization rules. Blazor provides two mechanisms: page-level protection with [Authorize] and inline content protection with <AuthorizeView>.

Updating Routes.razor

First, modify Components/Routes.razor to support authorization-aware routing:

@using Microsoft.AspNetCore.Components.Authorization
@using Microsoft.AspNetCore.Authorization

<FluentDesignTheme StorageName="theme" @rendermode="@InteractiveServer" />

<CascadingAuthenticationState>
    <Router AppAssembly="typeof(Program).Assembly">
        <Found Context="routeData">
            <AuthorizeRouteView RouteData="routeData" DefaultLayout="typeof(Layout.MainLayout)">
                <NotAuthorized>
                    @if (context.User.Identity?.IsAuthenticated != true)
                    {
                        <FluentStack Orientation="Orientation.Vertical" VerticalGap="20" 
                                     HorizontalAlignment="HorizontalAlignment.Center" 
                                     Style="margin-top: 100px;">
                            <FluentIcon Value="@(new Icons.Regular.Size48.LockClosed())" Color="Color.Accent" />
                            <h2>Authentication Required</h2>
                            <p>You need to be logged in to access this page.</p>
                            <FluentButton Appearance="Appearance.Accent" 
                                OnClick="@(() => NavigationManager.NavigateTo(
                                    "/login?returnUrl=" + Uri.EscapeDataString(
                                        NavigationManager.ToBaseRelativePath(NavigationManager.Uri)), 
                                    forceLoad: false))">
                                Login
                            </FluentButton>
                        </FluentStack>
                    }
                    else
                    {
                        <FluentStack Orientation="Orientation.Vertical" VerticalGap="20" 
                                     HorizontalAlignment="HorizontalAlignment.Center" 
                                     Style="margin-top: 100px;">
                            <FluentIcon Value="@(new Icons.Regular.Size48.ShieldError())" Color="Color.Error" />
                            <h2>Access Denied</h2>
                            <p>You don't have permission to access this page.</p>
                            <FluentButton Appearance="Appearance.Accent" 
                                OnClick="@(() => NavigationManager.NavigateTo("/", forceLoad: false))">
                                Go to Home
                            </FluentButton>
                        </FluentStack>
                    }
                </NotAuthorized>
            </AuthorizeRouteView>
            <FocusOnNavigate RouteData="routeData" Selector="h1" />
        </Found>
    </Router>
</CascadingAuthenticationState>

@code {
    [Inject] private NavigationManager NavigationManager { get; set; } = default!;
}


What changed?

  1. <CascadingAuthenticationState>: This wraps the entire router and makes authentication state available to all child components. Without it, <AuthorizeView> and [Authorize] attributes won't work.

  2. <AuthorizeRouteView>: Replaces the standard RouteView. This component checks the [Authorize] attribute on routed pages and enforces authorization rules.

  3. <NotAuthorized> with two states: This is subtle but important. The <NotAuthorized> content renders when authorization fails, but there are two scenarios:

    • Not authenticated (context.User.Identity?.IsAuthenticated != true): The user isn't logged in. Show a "Login" button.
    • Authenticated but not authorized (else): The user is logged in but lacks permission (e.g., wrong role). Show an "Access Denied" message.

Protecting Pages with [Authorize]

To require authentication for an entire page, add the [Authorize] attribute:

@page "/posts"
@attribute [Authorize]
@using Microsoft.AspNetCore.Authorization

<PageTitle>My Posts</PageTitle>

<h1>My Posts</h1>

<!-- Your protected content here -->

Now, unauthenticated users who navigate to /posts will see the "Authentication Required" message from Routes.razor, not the page content.

Note: [Authorize] also supports roles and policies (e.g. [Authorize(Roles = "Admin")]) for more granular access control, that's a topic for a future post.


Testing it out:

  1. Run your Aspire app host: dotnet run --project NoteBookmark.AppHost
  2. Navigate to your Blazor app in the browser.
  3. Click "Login"—you should redirect to Keycloak, authenticate, and return.
  4. You'll see "Hello, [your name]" in the header.
  5. Navigate to a page marked [Authorize] without logging in—you'll see the auth required message.
  6. Click "Logout"—you'll sign out of both the app and Keycloak.

Your Blazor app now has full OpenID Connect authentication with Keycloak, with a clean separation between the auth mechanics (Login/Logout pages), UI (LoginDisplay), and enforcement (Routes.razor + [Authorize]).


Conclusion

You've now integrated Keycloak authentication into your .NET Aspire application. The key pieces:

  1. Aspire orchestration: AddKeycloak(), .WithReference(), and .WaitFor() handle container lifecycle and configuration injection.
  2. OIDC pipeline: The standard ASP.NET Core authentication middleware, configured for Keycloak's OIDC endpoints.
  3. HTTP flexibility: Logic to handle HTTP Keycloak in dev while enforcing HTTPS in production.
  4. Persistent data: WithDataVolume() ensures your Keycloak realm config survives restarts.

This pattern scales beyond Keycloak, Aspire's resource model works the same way for databases, message queues, and other services. Once you've mastered .WithReference() and .WaitFor(), you can compose complex distributed systems with confidence.

The full working implementation is available in the NoteBookmark repository, including the AppHost configuration, Blazor components, and Docker Compose files referenced throughout this post.


Useful links


Reading Notes #691

This week’s notes bounce between terminals, copilots, and the shifting shape of AI tools in our daily work. From real-world experiments in large .NET projects to small quality-of-life improvements that just make coding smoother, there’s a lot to chew on. A few links stood out more than expected and might change how you approach your setup or your workflow.

All ready the end of the month!

Open Source

AI

Miscellaneous

~frank


Reading Notes #690

AI keeps changing how we build, think, and even feel about software. This batch of posts & episodes mixes practical agent skills, vibe coding, and faster shipping with a bit of reflection on the old internet and why it still sticks with us.


AI


Podcasts

  • Your Images are Out of Date (probably) - The Silent Rebuilds problem (DevOps and Docker Talk: Cloud Native Interviews and Tooling) - Very interesting episode. I guess I never realized how true it is that as soon as you download your image, they are outdated. This episode talks about the concept of silent rebuilds and tools to help us solve that issue.

  • 503: Welcome to Tiny Tool Town (Merge Conflict) - With a name like Tiny Tool Town, my head always goes to Looney Tunes. No idea why, but this episode is not about that. It's about the collection of open source tools named: Tiny Tool Town, and they also talk about different models in GitHub Copilot.

  • Building Software using Squad with Brady Gaster (.NET Rocks!) - Turn your Coplot to 11 with Squad. Carl and Richard talk to Brady Gaster about Squad, a tool for creating an AI development team using GitHub Copilot.

  • Daniel Ward: AI Agents - Episode 393 (Azure & DevOps Podcast) - In this episode, they talk about the different AI tools used by developers and DevOps people, and the trends.

  • Everything Is a Graph (Even Your Dad Jokes) with Roi Lipman (Screaming in the Cloud) - Nice episode about different database and most obviously about graph databases. Very interesting to learn more about all that explosion of database types.


Miscellaneous


Sharing my Reading Notes is a habit I started a long time ago, where I share a list of all the articles, blog posts, podcasts and books that catch my interest during the week.

If you have interesting content, share it!

~frank


Private Vision AI: Run Reka Edge Entirely on Your Machine

Reka just released Reka Edge, a compact but powerful vision-language model that runs entirely on your own machine. No API keys, no cloud, no data leaving your computer. I work at Reka and putting together this tutorial was genuinely fun; I hope you enjoy running it as much as I did.

[Originally published at dev.to/reka]

In three steps, you'll go from zero to asking an AI what's in any image or video.

What You'll Need

  • A machine with enough RAM to run a 7B parameter model (~16 GB recommended)
  • Git
  • uv, a fast Python package manager. Install it with:
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    This works on macOS, Linux, and Windows (WSL). If you're on Windows without WSL, grab the Windows installer instead.

Step 1: Get the Model and Inference Code

Clone the Reka Edge repository from Hugging Face. This includes both the model weights and the inference code:

git clone https://huggingface.co/RekaAI/reka-edge-2603
cd reka-edge-2603

Step 2: Fetch the Large Files

Hugging Face stores large files (model weights and images) using Git LFS. After cloning, these files exist on disk but contain only small pointer files, not the actual content.

First, make sure Git LFS is installed. The command varies by platform:

# macOS
brew install git-lfs

# Linux / WSL (Ubuntu/Debian)
sudo apt install git-lfs

Then initialize it:

git lfs install

Then pull all large files, including model weights and media samples:

git lfs pull

Grab a coffee while it downloads, the model weights are several GB.


Step 3: Ask the Model About an Image or Video

To analyze an image, use the sample included in the media/ folder:

uv run example.py \
  --image ./media/hamburger.jpg \
  --prompt "What is in this image?"
the prompt and the burger image

Or pass a video with --video:

uv run example.py \
  --video ./media/many_penguins.mp4 \
  --prompt "What is in this?"

The model will load, process your input, and print a description, all locally, all private.

Try different prompts to unlock more:

  • "Describe this scene in detail."
  • "What text is visible in this image?"
  • "Is there anything unusual or unexpected here?"

What's Actually Happening? 

You don't need this to use the model, but if you're anything like me and can't help wondering what's going on under the hood, here's the magic behind example.py:

1. It picks the best hardware available. The script checks whether your machine has a GPU (CUDA for Nvidia, Metal for Apple Silicon) and uses it automatically. If neither is available, it falls back to the CPU. This affects speed, not quality.

if torch.cuda.is_available():
    device = torch.device("cuda")
elif mps_ok:
    device = torch.device("mps")
else:
    device = torch.device("cpu")

2. It loads the model into memory. The 7 billion parameter model is read from the folder you cloned. This is the "weights": billions of numbers that encode everything the model has learned. Loading takes ~30 seconds depending on your hardware.

processor = AutoProcessor.from_pretrained(args.model, trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained(args.model, ...).eval()

3. It packages your input into a structured message. Your image (or video) and your text prompt are wrapped together into a conversation-style format, the same way a chat message works, except one part is visual instead of text.

messages = [{
    "role": "user",
    "content": [
        {"type": "image", "image": args.image},
        {"type": "text", "text": args.prompt},
    ],
}]

4. It converts everything into numbers. The processor translates your image into a grid of numerical patches and your prompt into tokens (small chunks of text, each mapped to a number). The model only understands numbers, so this step bridges the gap.

inputs = processor.apply_chat_template(
    messages, tokenize=True, return_tensors="pt", return_dict=True
)

5. The model generates a response, token by token. Starting from your input, the model predicts the most likely next word, then the next, up to 256 tokens. It stops when it hits a natural end-of-response marker.

output_ids = model.generate(**inputs, max_new_tokens=256, do_sample=False)

6. It converts the numbers back into text and prints it. The token IDs are decoded back into human-readable words and printed to your terminal. No internet involved at any point.

output_text = processor.tokenizer.decode(new_tokens, skip_special_tokens=True)
print(output_text)


Here the video

If you prefer watching and reading, here is the video version:

 

That's Pretty Cool, Right?

A single script. No API key. No cloud. You just ran a 7 billion parameter vision-language model entirely on your own machine, and it works whether you're on a Mac, Linux, or Windows with WSL, which is what I was using when I wrote this.

This works great as a one-off script: drop in a file, ask a question, get an answer. But what if you wanted to build something on top of it? A web app, a tool that watches a folder, or anything that needs to talk to the model repeatedly?

That's exactly what the next post is about. I'll show you how to wrap Edge as a local API, so instead of running a script, you have a service running on your machine that any app can plug into. Same model, same privacy, but now it's a proper building block.


~frank 

Reading Notes #689

Another week, another batch of interesting reads. This edition covers AI video experiments, extending coding agents with .NET skills, open source contributions, and a few podcast episodes worth adding to your queue.


AI

Programming

Open Source

Podcasts

Sharing my Reading Notes is a habit I started a long time ago, where I share a list of all the articles, blog posts, podcasts and books that catch my interest during the week.

If you have interesting content, share it!

~frank


Reading Notes #688

I'm always on the lookout for innovative ideas to streamline my development workflow. This week, I stumbled upon some fascinating reads that caught my eye, among them, an article about building an AI-powered pull request agent using GitHub Copilot SDK, and another demonstrating the secure use of OpenClaw in Docker sandboxes.


AI

Programming

~frank


Reading Notes #687

Welcome to this new Reading Notes post, a collection of interesting articles and resources I've been absorbing lately! This week's roundup dives into a variety of topics, from practical storage solutions and leveraging AI for code upgrades to exploring the intersection of AI and business value. Get ready for a diverse mix of tech insights and management reflections.


Programming

AI

Books



The Making of a Manager: What to Do When Everyone Looks to You
(Julie Zhuo) - Most management books are written by advanced managers, people with a lot of experience who already have the "manager" mindset well established in their heads. This book feels different, more accessible, closer to a conversational tone. In this book, Julie shares her stories of becoming a manager and the advice she learned along the way. I think it's a good book to get started on this topic, especially if you are new to that position or thinking about it, to understand and be better equipped for the new challenges coming your way.


Miscellaneous

~frank



Reading Notes #686

This week's Reading Notes is packed with AI insights, open-source discoveries, programming tips, and podcast episodes that will leave you eager to dive in. From Ralph Wiggum's coding secrets to the dangers of one-shot glamour, we've got it all covered. So grab your favourite beverage, settle in, and get ready to level up your tech game!

AI


Open Source


Programming


Podcast

~frank


Reading Notes #685

This week's collection of interesting articles, blog posts, and insights from the world of technology, programming, and AI. From the latest developments in Claude code and AI models for coding to discussions on the security of AI assistants and the future of the craft of programming, there's something for everyone in this edition of Reading Notes. 

Enjoy!

snow in a forest with the shadow of the trees
zebra snow

AI

Programming

  • Is the craft dead? (Scott Hanselman) - Good question! What do you think? Is it still there? I'm personally sure it still is.

Miscellaneous

~frank

Reading Notes #684

Balancing cloud innovation with AI practicality, this week’s notes blend Azure updates, .NET’s AI roadmap, and clever Python hacks. A sharp reminder on burnout prevention anchors the mix, while creative teams and DevOps culture inspire fresh perspectives. From Docker model runners to Git worktrees, every corner here offers actionable insights or a spark of curiosity, no clichés, just tools and truths for developers navigating the stormy seas of tech.


Suggestion of the week

Cloud

AI

Podcasts

Miscellaneous

~frank

Reading Notes #683

A lot of good stuff crossed my radar this week. From Aspire’s continued evolution and local AI workflows with Ollama, to smarter, more contextual help in GitHub Copilot, the theme is clear: better tools, used more intentionally. I also bookmarked a few thoughtful pieces on leadership and communication that are worth slowing down for. Plenty here to explore, whether you’re deep in code or thinking about how teams actually work.

Meetup MsDevMtl

Programming

AI

Open Source

  • The end of the curl bug-bounty (Daniel Stenberg) - I didn't know about this effort, and it's sad to learn about it too now, of course, but I'm glad those programs exist.

Miscellaneous

  • Why I Still Write Code as an Engineering Manager (James Sturtevant) - There is still hope, everyone! But more seriously, an inspiring post that managers should read.

  • The Art of the Oner (Golnaz) - Another great post from Golnaz talks about how to help the message to land. How and why one takes are helping when presenting and the effort it represents.

Sharing my Reading Notes is a habit I started a long time ago, where I share a list of all the articles, blog posts, and books that catch my interest during the week.

If you have interesting content, share it!

~frank



Automatically Create AI Clips with This n8n Template

I'm excited to share that my new n8n template has been approved and is now available for everyone to use! This template automates the process of creating AI-generated video clips from YouTube videos and sending notifications directly to your inbox.

French version of this post here

Try the template here: https://link.reka.ai/n8n-template-api


What Does This Template Do?

If you've ever wanted to automatically create short clips from long YouTube videos, this template is for you. It watches a YouTube channel of your choice, and whenever a new video is published, it uses AI to generate engaging short clips perfect for social media. You get notified by email when your clip is ready to download.

How It Works

The workflow is straightforward and runs completely on autopilot:

  1. Monitor YouTube channels - The template watches the RSS feed of any YouTube channel you specify. When a new video appears, the automation kicks off.

  2. Request AI clip generation - Using Reka's Vision API, the workflow sends the video for AI processing. You have full control over the output:

    • Write a custom prompt to guide the AI on what kind of clip to create
    • Choose whether to include captions
    • Set minimum and maximum clip duration
  3. Smart status checking - When the clips are ready, you receive a success email with your download link. As a safety feature, if the job takes too long, you'll get an error notification instead.

Getting Started is Easy

The best part? You can install this template with just one click from the n8n Templates page. No complex setup required!

After installation, you'll just need two quick things:

  • A free Reka AI API key (get yours from Reka)
  • A Gmail account (or use any email provider you like)

That's it! The template comes ready to use. Simply add your YouTube channel RSS feed, connect your API key, and you're ready to start generating clips automatically. The whole setup takes just a few minutes.

If you run into any questions or want to share what you've built, join the Reka Discord community. I'd love to hear how you're using this template!

Show Me

In this short  video I show you how to get that template into your n8n and how to configure it.

Happy clipping!

Reading Notes #682

This week’s Reading Notes bring together programming tips, AI experiments, and cloud updates. Learn to build Python CLI tools. Untangle GitHub issue workflows. Try running AI models locally. Catch up on Azure news. And explore ideas around privacy and cloud architecture. Short reads. Useful takeaways.


Programming

AI

Miscellaneous

~frank

Writing My First Custom n8n Node: A Step-by-Step Guide

Recently, I decided to create a custom node for n8n, the workflow automation tool I've been using. I'm not an expert in Node.js development, but I wanted to understand how n8n nodes work under the hood. This blog post shares my journey and the steps that actually worked for me.

French version here

Why I Did This

Before starting this project, I was curious about how n8n nodes are built. The best way to learn something is by doing it, so I decided to create a simple custom node following n8n's official tutorial. Now that I understand the basics, I'm planning to build a more complex node featuring AI Vision capabilities, but that's for another blog post!

The Challenge

I started with the official n8n tutorial: Build a declarative-style node. While the tutorial is well-written, I ran into some issues along the way. The steps didn't work exactly as described, so I had to figure out what was missing. This post documents what actually worked for me, in case you're facing similar challenges. I already have an n8n instance running in a container. In Step 8, I'll explain how I run a second instance for development purposes.

Prerequisites

Before you start, you'll need:

  • Node.js and npm - I used Node.js version 24.12.0
  • Basic understanding of JavaScript/TypeScript - you don't need to be an expert

Step 1: Fixing the Missing Prerequisites

I didn't have Node.js installed on my machine, so my first step was getting that sorted out. Instead of installing Node.js directly, I used nvm (Node Version Manager), which makes it easy to manage different Node.js versions. Installation details are available on the nvm GitHub repository. Once nvm was set up, I installed Node.js version 24.12.0.

Most of the time, I use VS Code as my code editor. I created a new profile and used the template for Node.js development to get the right extensions and settings.

Step 2: Cloning the Starter Repository

n8n provides a n8n-nodes-starter on GitHub that includes all the basic files and dependencies you need. You can clone it or use it as a template for your own project. Since this was just a "learning exercise" for me, I cloned the repository directly:

git clone https://github.com/n8n-io/n8n-nodes-starter
cd n8n-nodes-starter

Step 3: Getting Started with the Tutorial

I won't repeat the entire tutorial here; it's clear enough, but I'll highlight some details along the way that I found useful.

The tutorial makes you create a "NasaPics" node and provides a logo for it. It's great, but I suggest you use your own logo images and have light and dark versions. Add both images in a new folder icons (same level as nodes and the credentials folder). Having two versions of the logo will make your node look better, whatever theme the user is using in n8n (light or dark). The tutorial only adds the logo in NasaPics.node.ts, but I found that adding it also in the credentials file NasaPicsApi.credentials.ts makes the node look more consistent.

Replace or add the logo line with this, and add Icon to the import statement at the top of the file:

icon: Icon = { light: 'file:MyLogo-dark.svg', dark: 'file:MyLogo-light.svg' };

Note: the darker logo should be used in light mode, and vice versa.

Step 4: Following the Tutorial (With Adjustments)

Here's where things got interesting. I followed the official tutorial to create the node files, but I had to make some adjustments that weren't mentioned in the documentation.

Adjustment 1: Making the Node Usable as a Tool

In the NasaPics.node.ts file, I added this line just before the properties array:

requestDefaults: {
      baseURL: 'https://api.nasa.gov',
      headers: {
         Accept: 'application/json',
         'Content-Type': 'application/json',
      },
   },
   usableAsTool: true, // <-- Added this line
   properties: [
      // Resources and operations will go here

This setting allows the node to be used as a tool within n8n workflows and also fixes warnings from the lint tool.

Adjustment 2: Securing the API Key Field

In the NasaPicsApi.credentials.ts file, I added a typeOptions to make the API key field a password field. This ensures the API key is hidden when users enter it, which is a security best practice.

properties: INodeProperties[] = [
   {
      displayName: 'API Key',
      name: 'apiKey',
      type: 'string',
      typeOptions: { password: true }, // <-- Added this line
      default: '',
   },
];

A Note on Errors

I noticed there were some other errors showing up in the credentials file. If you read the error message, you'll see that it's complaining about missing test properties. To fix this, I added a test property at the end of the class that implements ICredentialTestRequest. I also added the interface import at the top of the file.

authenticate: IAuthenticateGeneric = {
   type: 'generic',
   properties: {
      qs: {
         api_key: '={{$credentials.apiKey}}',
      },
   },
};

// Add this at the end of the class
test: ICredentialTestRequest = {
   request: {
      baseURL: 'https://api.nasa.gov/',
      url: '/user',
      method: 'GET',
   },
};

Step 5: Building and Linking the Package

Once I had all my files ready, it was time to build the node. From the root of my node project folder, I ran:

npm i
npm run build
npm link

During the build process, pay attention to the package name that gets generated. In my case, it was n8n-nodes-nasapics. You'll need this name in the next steps.

> n8n-nodes-nasapics@0.1.0 build
> n8n-node build

┌   n8n-node build 
│
◓  Building TypeScript files│
◇  TypeScript build successful
│
◇  Copied static files
│
└  ✓ Build successful

Step 6: Setting Up the n8n Custom Folder

n8n looks for custom nodes in a specific location: ~/.n8n/custom/. If this folder doesn't exist, you need to create it:

mkdir -p ~/.n8n/custom
cd ~/.n8n/custom

Then initialize a new npm package in this folder: run npm init and press Enter to accept all the defaults.

Step 7: Linking Your Node to n8n

Now comes the magic part - linking your custom node so n8n can find it. Replace n8n-nodes-nasapics with whatever your package name is. From the ~/.n8n/custom folder, run:

npm link n8n-nodes-nasapics

Step 8: Running n8n

This is where my setup differs from the standard tutorial. As mentioned at the beginning, I already have an instance of n8n running in a container and didn't want to install it. So I decided to run a second container using a different port. Here's the command I used:

docker run -d --name n8n-DEV -p 5680:5678 \
  -e N8N_COMMUNITY_PACKAGES_ENABLED=true \
  -v ~/.n8n/custom/node_modules/n8n-nodes-nasapics:/home/node/.n8n/custom/node_modules/n8n-nodes-nasapics \
  n8nio/n8n

Let me break down what this command does:

  • -d: Runs the container in detached mode (in the background)
  • --name n8n-DEV: Names the container for easy reference
  • -p 5680:5678: Maps port 5678 from the container to port 5680 on my machine so it doesn't conflict with my existing n8n instance
  • -e N8N_COMMUNITY_PACKAGES_ENABLED=true: Enables community packages — you need this to use custom nodes
  • -v: Mounts my custom node folder into the container, which lets me try my custom node without having to publish it.
  • n8nio/n8n: The official n8n container image

If you're running n8n directly on your machine (not in a container), you can simply start it.

Step 9: Testing Your Node

Once n8n-DEV is running, open your browser and navigate to it. Create a new workflow and search for your node. In my case, I searched for "NasaPics" and my custom node appeared!

To test it:

  1. Add your node to the workflow
  2. Configure the credentials with a NASA API key (you can get one for free at api.nasa.gov)
  3. Execute the node
  4. Check if the data is retrieved correctly

Updating Your Node

During development, you'll likely need to make changes to your code (aka node). Once done, you have to rebuild npm run build and restart the n8n container docker restart n8n-DEV to see the changes.

What's Next?

Now that I understand the basics of building custom n8n nodes, I'm ready to tackle something more ambitious. My next project will be creating a node that uses AI Vision capabilities. Spoiler alert: It's done and I'll be sharing the details in an upcoming blog post!

If you're interested in creating your own custom nodes, I encourage you to give it a try. Start with something simple, like I did, and build from there. Don't be afraid to experiment and make mistakes - that's how we learn!

Resources

Reading Notes #681

This week’s reads blend cutting-edge tech with practical insights, like how Aspire elevates JavaScript to a first-class citizen in modern development, or why AI’s push toward typed languages might just be the future. From building a self-hosted model registry to uncovering AI’s surprising role in video

little snowman

production (who knew Adobe had a sound AI gem?), there’s plenty to unpack. And if data-driven wardrobe experiments count as quirky, this week’s got you covered too.

Programming

  • Aspire for JavaScript developers (David Pine) - JavaScript and all its frameworks are now first citizen in Aspire. This post explains what it means and what the benefits are for developers.

AI

Miscellaneous

~frank


Reading Notes #680

In this edition of Reading Notes, I’m sharing articles about the evolving tech landscape, exploring WebAssembly’s potential through Blazor, uncovering the simplicity of .NET’s file-based apps, and reflecting on how 2025 reshaped software development. From podcasts dissecting 2026’s challenges to a heartfelt tech community milestone, this round-up blends cutting-edge tools with practical wisdom, proving innovation thrives in unexpected corners.


Ready to geek out? Let’s roll.

DevOps

Programming

  • File-based apps - .NET - Amazing source of information. It's all in one place. I used to call it projectless, but from now on, it's file-based

AI

Podcasts

Miscellaneous

~Frank


Exposing Home Container with Traefik and Cloudflare Tunnel

I love the cloud, in fact most people probably know me because of my shared content related to that. But sometimes our apps don't need scaling, or redundancy. Sometimes we just want to host them somewhere.

(post en français ici)

It was the holidays, and during my time off I worked on a few small personal projects. I packaged them in containers so it's easy to deploy anywhere. I deployed them on a mini-PC that I have at home and it is great... as long as I stay home. But what if I would like to access it from elsewhere (ex: my in-laws' house)?

I set up a nice Cloudflare tunnel to a Traefik container that proxies the traffic to the correct container based on the prefix or second-level domain. So dev.c5m.ca goes to container X and test.c5m.ca goes to container Y. In this post, I wanted to share how I did it (and also have it somewhere for me in case I need to do it again 😉). It's simple once you know all the pieces work together.

generated by Microsoft designer
generated by Microsoft designer

The Setup

The architecture is straightforward: Cloudflare Tunnel creates a secure connection from my home network to Cloudflare's edge, and Traefik acts as a reverse proxy that routes dynamically incoming requests to the appropriate container based on the subdomain. This way, I can access multi ple services through different subdomains without exposing my home network directly to the internet.

Step 1: Cloudflare Tunnel

First, assuming you already owne a domain name, you'll need to create a Cloudflare tunnel. You can do this through the Cloudflare dashboard under Zero Trust → Networks → Tunnels. Once created, you'll get a tunnel token that you'll use in the configuration.

Here's my cloudflare-docker-compose.yaml:

name: cloudflare-tunnel

services:
  cloudflared:
    image: cloudflare/cloudflared:latest
    container_name: cloudflared
    restart: unless-stopped
    env_file:
      - .env
    environment:
      - TUNNEL_TOKEN=${TUNNEL_TOKEN}
    command: ["tunnel", "--no-autoupdate", "run", "--token", "${TUNNEL_TOKEN}"]

The tunnel token is stored in a .env file for security. The --no-autoupdate flag prevents the container from trying to update itself automatically, which is useful in a controlled environment.

Step 2: DNS Configuration

In Cloudflare dashboard, create a CNAME Record with a wildcard. For example for my domain "c5m.ca" that record will look like this: *.c5m.ca.

Step 3: Traefik Configuration

Traefik is the reverse proxy that will route traffic to your containers. I have two configuration files: one for Traefik itself and one for the Docker Compose setup.

Here's my traefik.yaml:

global:
  checkNewVersion: false
  sendAnonymousUsage: false

api:
  dashboard: false #true
  insecure: true

entryPoints:
  web:
    address: :8082
  websecure:
    address: :8043

providers:
  docker:
    endpoint: "unix:///var/run/docker.sock"
    exposedByDefault: false 

I've configured two entry points: web on port 8082 (HTTP) and websecure on port 8043 (HTTPS). I did it that way because the default 80 and 443 where already taken. The Docker provider watches for containers with Traefik labels and automatically configures routing. exposedByDefault: false means containers won't be exposed unless explicitly enabled with labels. You won't have to change Traefik config to add more containers, it's all dynamic.

And here's the traefik-docker-compose.yaml:

name: traefik

services:
  traefik:
    image: "traefik:v3.4"
    container_name: "traefik-app"
    restart: unless-stopped
    networks:
      - proxy

    ports:
      - "8888:8080" # Dashboard port
      - "8082:8082"
      - "8043:8043" # remap 443
    volumes:
      - "/var/run/docker.sock:/var/run/docker.sock:ro"
      - "./config/traefik.yaml:/etc/traefik/traefik.yaml:ro"

networks:
  proxy:
    name: proxy

The key points here:

  • Traefik is connected to a Docker network called proxy that will be shared with other containers. You can name it the way you like.
  • Port 8888 maps to Traefik's dashboard (currently disabled in the config)
  • Ports 8082 and 8043 are exposed for HTTP and HTTPS traffic
  • The Docker socket is mounted read-only so Traefik can discover containers
  • The configuration file is mounted from ./config/traefik.yaml

Step 4: Configuring Services

Now, any container you want to expose through Traefik needs to:

  1. Be on the same proxy network
  2. Have Traefik labels configured

Here's a simple example with an nginx container (nginx-docker-compose.yaml):

name: "test-tools"

services:
  nginx:
    image: "nginx:latest"
    container_name: "nginx-test"
    restart: unless-stopped
    networks:
      - proxy
    volumes:
      - "./html:/usr/share/nginx/html:ro"
      
    labels:
      - traefik.enable=true
      - traefik.http.routers.nginxtest.rule=Host(`test.c5m.ca`) 
      - traefik.http.routers.nginxtest.entrypoints=web

networks:
  proxy:
    external: true

The labels tell Traefik:

  • traefik.enable=true: This container should be exposed
  • nginxtest is the unique name for routing this container.
  • traefik.http.routers.nginxtest.rule=Host(...): Route requests for test.c5m.ca to this container
  • traefik.http.routers.nginxtest.entrypoints=web: Use the web entry point (port 8082)

Bonus: A More Complex Example

For a more realistic scenario, let's share how I could expose 2D6 Dungeon App here's a simplified version of my 2d6-docker-compose.yaml which includes a multi-container application:

name: 2d6-dungeon

services:
  database:
    container_name: 2d6_db
    ports:
      - "${MYSQL_PORT:-3306}:3306"
    networks:
      - proxy
    ...

  dab:
    container_name: 2d6_dab
    ...
    depends_on:
      database:
        condition: service_healthy
    ports:
      - "${DAB_PORT:-5000}:5000"
    networks:
      - proxy

  webapp:
    container_name: 2d6_app
    depends_on:
      - dab
    environment:
      ConnectionStrings__dab: http://dab:5000
      services__dab__http__0: http://dab:5000

    labels:
      - traefik.enable=true
      - traefik.http.routers.twodsix.rule=Host(`2d6.c5m.ca`)
      - traefik.http.routers.twodsix.entrypoints=web,websecure
      - traefik.http.services.twodsix.loadbalancer.server.port=${WEBAPP_PORT:-8080}

    networks:
      - proxy

    ports:
      - "${WEBAPP_PORT:-8080}:${WEBAPP_PORT:-8080}"

networks:
  proxy:
    external: true

This example shows:

  • Multiple services working together (database, API, web app)
  • Only the webapp is exposed through Traefik (the database and API are internal)
  • The webapp uses both web and websecure entry points
  • Important note here is that container part of the same network can use their internal port (ex: 5000 for DAB, 3306 for MySQL)
  • The external network is the proxy created previously

Cloudflare Tunnel Configuration

In your Cloudflare dashboard, you'll need to configure the tunnel to route traffic to Traefik. Create a public hostname that points to http://<local-ip>:8082. Use the local IP of your server something like "192.168.1.123" You can use wildcards like *.c5m.ca to route all subdomains to Traefik, which will then handle the routing based on the hostname.

Wrapping Up

That's it! Once everything is set up:

  1. The Cloudflare tunnel creates a secure connection from your home to Cloudflare
  2. Traffic comes in through Cloudflare and gets routed to Traefik
  3. Traefik reads the hostname and routes to the appropriate container
  4. Each service can be accessed via its own subdomain
  5. Only the containers with the Traefik labels are accessible from outside my network
  6. It's dynamic! Any new container, with the labels, will be routed without changing the config in Traefik nor Cloudflare

It's a simple setup that works great for personal projects. The best part is that you don't need to expose any ports on your router or deal with dynamic DNS, Cloudflare handles all of that.

Next step will be to add some authentication and authorization (ex: using Keycloak), but that's for another post. For now, this gives me a way to access my home-hosted services from anywhere, and I thought it could be useful to share.