feat(trainer): training from the collector UI — the trainer becomes a job service, the review page gains a Training section
Trainer: `parking-trainer serve` — a stdlib HTTP job API on the compose network (never
published): /health, /readiness, /versions, /versions/<v>/report, /jobs. One job at a
time; each job runs the CLI as a subprocess with its output captured, state + log
persisted under /out/jobs/ so a restart keeps history. `publish` takes its URL from
TRAINER_PUBLISH_URL. Dockerfile: CMD serve, EXPOSE 8091, healthcheck.
Collector: COLLECTOR_TRAINER_URL + /api/training/{status,jobs,jobs/:id,versions/:v/report}
— a reviewer-gated proxy that forwards a fixed set of paths and whitelisted knobs and
passes the trainer's status codes through (409 while a job runs; 503 unconfigured, 502
unreachable). /review gains the Training section: labels per class vs the minimum with
Train disabled until two classes clear it, mode / backbone / floor, the running job's
live log, the versions with Report / Evaluate / Publish (publish confirms), and the
reminder that pinning stays a git commit. Fixed on the way: an apostrophe in the page's
inline script broke the whole page — a test now parses the script.
Compose: `trainer` is a service (restart: unless-stopped, read-only data volume, its own
trainer-out volume), the `train` profile and TRAINER_OUT are gone; the Docker-socket
route was rejected (root on the host for a service booths upload to). Verified with both
images running together: a Train started through the proxy finished, version and report
came back, the page rendered.
Wiki: bodytype-classifier-training (loop, running it, operating notes superseded),
vision-review-outbox, fleet-deployment-komodo, log.
Claude-Session: https://claude.ai/code/session_01FWncR69HgGPuei1dLrW3cU
This commit is contained in:
@@ -130,9 +130,14 @@ Three surfaces, nothing else — it must not grow into a fleet console:
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label, the operator's category + classes, the camera's class + confidence, downgraded, at.
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Crops are not packaged: the phase-B trainer runs **on the same host** and reads the SQLite
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+ crops straight off the volume, read-only ([[bodytype-classifier-training]]: CPU-only, the
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Xeon is enough) — `docker-compose.collector.yml` carries it as the `trainer` service under
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`profiles: ["train"]`, a one-off job never started by a deploy (built 2026-09-07; the CSV
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export stays for a human with a spreadsheet).
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Xeon is enough) — the `trainer` service beside the collector in
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`docker-compose.collector.yml` (the CSV export stays for a human with a spreadsheet).
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- **Training section on `/review`** (+ `/api/training/status|jobs|jobs/:id|versions/:v/report`)
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— a thin proxy, behind the same reviewer login, to the trainer's job API on the compose
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network (`COLLECTOR_TRAINER_URL`, unset = hidden): labels per class vs the minimum, Train
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(mode / backbone / floor), the running job's log, the versions with Report / Evaluate /
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Publish. The collector forwards only a fixed set of paths and knobs; the trainer validates
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values and answers 409 while a job runs.
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**Where the data lives.** The collector writes to `/data` in its container: `collector.sqlite`
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and one JPEG per item at `crops/<booth-id>/<item-id>.jpg`. `/data` is the named Docker volume
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