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v0.27.0:0 - in-app settings gear + swap-lock route fix

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Move the ~20 optional cluster knobs out of the StartOS "Configure Sparks"
action (now just the 4 required fields) and into a dashboard ⚙ Settings gear,
backed by a /data/app_settings.json overlay keyed by env-var names. One shared
mutable Settings instance + Settings.reload() applies edits live without a
restart; existing installs' values migrate automatically on first boot.

Also: support-service ports (parakeet/kokoro/embed/qdrant + vllm) are now
configurable, and GET /api/swap/lock no longer 404s (it was shadowed by the
/api/swap/{job_id} catch-all). WebhookNotifier is re-pointed on save so its
url/secret reload live too.
This commit is contained in:
Keysat
2026-06-18 13:41:28 -05:00
parent b67e001642
commit 7e0759846f
15 changed files with 797 additions and 268 deletions
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README.md
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@@ -118,7 +118,7 @@ Fields: `service` (required), `ok` (required), `source` (optional, free-form), `
- **Service discovery API** (`/api/endpoints`) for other LAN services
- **Kokoro-82M TTS** replaces Magpie/Riva NIM as the default TTS backend (v0.14.0). Magpie's decoder had a ~30-50% truncation rate on multi-sentence inputs and ate 49 GB of GPU memory; Kokoro is 24/24 reliable at every input length tested, uses 1.3 GB GPU, and renders in ~1s. See HANDOFF.md and the release notes for the migration story.
- **Always-on services panel** with Start/Stop/Restart for Parakeet + Kokoro, plus per-service host configuration in Configure Sparks (so they can live on Spark 1, Spark 2, or anywhere)
- **Always-on services panel** with Start/Stop/Restart for Parakeet + Kokoro, plus per-service host/port/container configuration in the in-app **⚙ Settings** gear (so they can live on Spark 1, Spark 2, or anywhere, on any port)
- **Model download** from the dashboard — paste an HF repo (with autocomplete for known models), pick solo or cluster, watch percent progress with bytes/rate/ETA. After completion the model appears on the menu automatically; if it's unrecognized, a pre-filled "set up this model" dialog offers to configure it.
- **spark-vllm-docker update check** — banner shows "N commits behind upstream"; Apply Update runs `git pull && ./build-and-copy.sh -c` over SSH with a streamed log
- **Per-model Advanced settings** — knobs for max context, GPU memory %, and three optimization toggles (fastsafetensors, prefix caching, FP8 KV cache). Persisted to `/data/models-overrides.yaml` so they survive package updates. Bundled and custom models alike.