I like the way each panel is its own separate package on PyPI and the system picks them up via setuptools entry points. It's a neat implementation of a plugin pattern.
I mean docs are largely written for an LLM-in-a-harness. That’s how it goes! If the LLM bootstraps with the right understanding of the universe and knows how to quickly build specific context flavors… life is good.
i like it, but I think i would rather have a proxy, or atleast an auth redirect to those different tools.
I used to have flower at myapp.com/flower using an auth redirect in nginx to a simple view in django that made sure it was an admin user. I think if you can make that setup easier to leverage existing tools that would be nicer than rebuilding everything.
Totally understand - I am a long time flower user for example, and I am familiar with having to harden that installation a bit.
What I'm aiming for here is slightly different - keeping everything inside Django so there are no extra services to run or configure or proxy. As long as you surface the admin somewhere, then that is the place to find your tooling (including celery monitoring)
There will always be room for both approaches. A lightweight proxy/redirect could be something to explore in the future.
I love this idea. I see the AI era having 2 competing views when building something new:
1. Build X with pure <language of choice>. Why? LLMs will have less context needed, and onboarding engineers would be easier since there’ll be less overhead and opinionated frameworks knowledge required
2. Build X using well establish frameworks. Painful in the beginning since you’ll not only need language knowledge, but framework knowledge. The upshot, is scaling and maintainability
I love that this ecosystem will heavily pressure teams to consider (2) more and more — solving the very real “AI slop” problem
In my view. Building things with AI creates the need for common patterns and guardrails (i.e. frameworks) Then as these new apps become productionalized - tooling that fits your framework starts to become more important.
In that sense, AI increases the need for good patterns around observability. This project aims to make this a little easier to do for Django right from inside the framework as opposed to an external service.
I like the way each panel is its own separate package on PyPI and the system picks them up via setuptools entry points. It's a neat implementation of a plugin pattern.
Thanks. Part of the reason this exists is simply wanting to toy around with the entrypoints system
I've built an official website for this project here: https://djangocontrolroom.com/
I think that explains some of the value for this project a bit better
Great project, Django admin totally needs some love! You rock!
Thank you. I wholeheartedly agree; The Django admin a great surface to stand up tooling
A vibe-coded website built on a vibe-coded README, can't get any better than this
Fair.
README and site were definitely optimized for speed over perfection. The panels themselves got a bit more attention.
Curious what you’d want to see improved on the docs/site side.
It’s the initial starting point, calm down.
I like the idea it can help for initial inspection and smell detection
toxic.
Not all negativity is toxic. My sense of hunger is unpleasant but it keeps me healthy.
I mean docs are largely written for an LLM-in-a-harness. That’s how it goes! If the LLM bootstraps with the right understanding of the universe and knows how to quickly build specific context flavors… life is good.
Tell your parents i said thank you for making you exist.
Good idea. If you add a kind of skill/prompt you’ll get a lot of other components from the community ;)
i like it, but I think i would rather have a proxy, or atleast an auth redirect to those different tools.
I used to have flower at myapp.com/flower using an auth redirect in nginx to a simple view in django that made sure it was an admin user. I think if you can make that setup easier to leverage existing tools that would be nicer than rebuilding everything.
Totally understand - I am a long time flower user for example, and I am familiar with having to harden that installation a bit.
What I'm aiming for here is slightly different - keeping everything inside Django so there are no extra services to run or configure or proxy. As long as you surface the admin somewhere, then that is the place to find your tooling (including celery monitoring)
There will always be room for both approaches. A lightweight proxy/redirect could be something to explore in the future.
I love this idea. I see the AI era having 2 competing views when building something new:
1. Build X with pure <language of choice>. Why? LLMs will have less context needed, and onboarding engineers would be easier since there’ll be less overhead and opinionated frameworks knowledge required
2. Build X using well establish frameworks. Painful in the beginning since you’ll not only need language knowledge, but framework knowledge. The upshot, is scaling and maintainability
I love that this ecosystem will heavily pressure teams to consider (2) more and more — solving the very real “AI slop” problem
Thats an interesting way to frame it.
In my view. Building things with AI creates the need for common patterns and guardrails (i.e. frameworks) Then as these new apps become productionalized - tooling that fits your framework starts to become more important.
In that sense, AI increases the need for good patterns around observability. This project aims to make this a little easier to do for Django right from inside the framework as opposed to an external service.
this is pretty dope
Thanks. I hope you find it useful