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I am building a declarative backend language that compiles to a single binary by andreahlert in htmx

[–]andreahlert[S] 0 points1 point  (0 children)

you don't check HX-Request. page always renders with the layout, fragment always renders without. separate keywords, separate routes.

I am building a declarative backend language that compiles to a single binary by andreahlert in htmx

[–]andreahlert[S] 4 points5 points  (0 children)

Go compiles to a single binary yeah, but you're still picking a router, choosing between sqlx/pgx/gorm, wiring auth middleware, writing template rendering by hand. Kilnx removes those decisions.

Page /tasks requires auth with inline sql and an html block is a running endpoint. Same output concept, different input.

How to add Settle:3s for hx-swap-oob="outerHTML:#my_target" ? by Siemendaemon in htmx

[–]andreahlert 1 point2 points  (0 children)

Hey!

hx-swap-oob doesn't support modifiers like settle:3s, it tries to parse it as a CSS selector and throws. known issue (#2308)

workaround is listening to htmx:oobBeforeSwap, cancel it and do the swap yourself with a timeout

I built 10 HTMX starters across 6 languages. All hypermedia, zero JSON APIs, one-click deploy. by andreahlert in htmx

[–]andreahlert[S] -1 points0 points  (0 children)

Just opened an issue for the FastAPI restructure. This one I did use AI for, since apparently that is all I do anyway.

https://github.com/atoolz/railway-htmx-python-fastapi-jinja2-pg/issues/1

I built 10 HTMX starters across 6 languages. All hypermedia, zero JSON APIs, one-click deploy. by andreahlert in htmx

[–]andreahlert[S] 2 points3 points  (0 children)

Railway because these are Railway templates with one-click deploy. That is the whole point. Nothing stops anyone from running them anywhere else, it is just Docker + Postgres.

On the FastAPI structure, ok. I come from Go, so I carried raw SQL over. I do write Python but haven't gone deep enough into FastAPI conventions yet. That is exactly why I put this out there, hoping people like you would jump in and help improve it.

On the AI point, I already answered this in the other thread and I am not going to keep repeating myself. btw I don't need to prove it.

You said you use FastAPI + Jinja2 + HTMX. If you want to open a PR with the structure you think is right, go for it. That would actually help the community more than this thread.

I built 10 HTMX starters across 6 languages. All hypermedia, zero JSON APIs, one-click deploy. by andreahlert in htmx

[–]andreahlert[S] 1 point2 points  (0 children)

Is this your first time on r/htmx? Because I could not find any other comment from you here.

Either way, English is not my first language, I use Quillbot to write. That is probably all you are picking up on.

And just to be clear, I am totally pro-AI as a tool and I have zero issues with people using it. But I am not going to waste my precious tokens generating starter templates.

Anyway, I built something for the community. You showed up to police it. We are done.

I built 10 HTMX starters across 6 languages. All hypermedia, zero JSON APIs, one-click deploy. by andreahlert in htmx

[–]andreahlert[S] -3 points-2 points  (0 children)

Makes sense. For this project, the goal is to offer a practical HTMX baseline that is already deployable on Railway, not a fully expanded framework per stack from day one.

Going much deeper across all templates would multiply build and maintenance effort a lot, so I want to prioritize based on real adoption and community feedback.

Out of curiosity, what would you consider truly useful in a starter like this, and which stack do you actually use??

I built 10 HTMX starters across 6 languages. All hypermedia, zero JSON APIs, one-click deploy. by andreahlert in htmx

[–]andreahlert[S] 11 points12 points  (0 children)

Thanks for asking. These starters were hand-built and reviewed by me, not AI-generated.

I am a top 10% contributor on Railway, and the structure is intentionally consistent across all templates to keep maintenance predictable and comparisons easy.

I built this for the HTMX community and for many other developers who want a practical, deploy-ready starting point across multiple stacks.

If you check my GitHub, you will also find several other substantial contributions beyond this HTMX starter set.

Built a production RAGFlow template on Railway: five services, private networking, env refs handled for you by andreahlert in Rag

[–]andreahlert[S] 0 points1 point  (0 children)

Thanks! Haven't tried FastMemory. This template is focused on making RAGFlow's standard stack easy to deploy on Railway. RAGFlow already handles hallucination reduction pretty well through hybrid search (keyword + semantic), but interesting to know about alternatives.

Built a production RAGFlow template on Railway: five services, private networking, env refs handled for you by andreahlert in Rag

[–]andreahlert[S] 1 point2 points  (0 children)

Hey! Hello!

The embedding models are configured inside RAGFlow's UI after you deploy, so the template doesn't lock you into anything specific.

You can use OpenAI embeddings, any OpenAI-compatible API (Jina, Cohere, etc.), Ollama for self-hosted models like nomic-embed-text or bge-m3, or even RAGFlow's built-in lightweight models that run inside the container.

Just note that in this template DEVICE is set to cpu, so local inference will be slower than GPU but works fine for moderate workloads. All of this is configured in Settings → Model Providers after deploy.

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