Project: hutfx platform
- Created: 2026-08-16
- Status: Planned
- Owner: hutfx
Goal
hutfx is a web workspace for machine learning and science: researchers sign in and manage their ML work in one place — experiments, datasets, models, and the jobs that connect them — with a public landing page and docs site for discovery.
Scope
In (proposed — confirm before building):
- Account system with a personal workspace per user (done)
- Public landing page +
/docbrowser (done) - Projects/experiments: structured record of ML runs (params, metrics, notes)
- Datasets: upload, version, link to runs
- Artifacts/files: store outputs (plots, checkpoints, logs) next to the runs
- Model registry: register versions, compare, link to runs
- Jobs: queue and monitor training/processing jobs on the server
- Public API so external programs (e.g. Python scripts) can report runs
Out (explicitly not doing, for now):
- Serving models / inference API
- In-browser notebooks (Jupyter-style)
- Team/organization accounts (single-user first)
- Billing / subscriptions
Milestones
| # | Milestone | Status |
|---|---|---|
| 0 | Foundation: auth, dashboard, profile, landing, docs, health API | Done |
| 1 | Experiments: projects, runs with params + metrics, list/detail | Not started |
| 2 | Datasets & artifacts: upload, store, link to runs | Not started |
| 3 | Jobs: enqueue jobs, live status + logs | Not started |
| 4 | Model registry: versions, comparison, downloads | Not started |
| 5 | Public API: tokens + REST endpoints + API docs | Not started |
- M1 — Experiments (MVP). The smallest useful product: a user creates a project, logs runs (name, parameters, metrics, notes) and sees them in a filterable table with a detail page. No files or compute yet.
- M2 — Datasets & artifacts. Dataset upload + artifact storage on local disk (Postgres metadata), linked to runs; image preview for plots.
- M3 — Jobs. Server-side job queue (Laravel queues) with status + log tail. Requires a decision on where jobs execute (see open questions).
- M4 — Model registry. Register model versions, compare side-by-side, download files, link back to the run that trained them.
- M5 — Public API. Token-authenticated REST endpoints for reporting runs, metrics, artifacts, and jobs from external programs.
Notes
- The feature set is proposed, not confirmed — open questions live in
../plans/2026-08-16-product-vision.md. - Stack stays Laravel + PostgreSQL; no new infrastructure is expected before M3.
- Each milestone gets its own plan file in
../plans/before its code is built. - The Pipeline Engine — website spec section 3 ("Model Builder") — is
described in
../plans/2026-08-17-pipelineengine.md. It is the reusable base for the website's services and processes and underpins later milestones (datasets, jobs/exports).
source: DOCS/hutfx/projects/hutfx.md · edit this page · rebuilt by build-wiki