User-feedback-driven release after testing v1.1.0:3. Nine themes:
1. Multi-config persistence
- New AIConfigProfile table (per-user). Save N configs, toggle one
active. Switching providers no longer wipes the previous setup.
- UserPreferences gains activeAIConfigId; legacy single-config
columns are mirrored from the active profile so existing reads
keep working without conditional logic.
- Idempotent boot migration lifts any existing single-config row
into a default profile.
2. Ollama auto-detect
- The "Add config" form probes /api/tags on the StartOS internal
addresses (ollama.startos / ollama.embassy on :11434). If
reachable: URL pre-fills, model field becomes a dropdown of
installed models. Fixes the copy-paste UX.
3. Curated model dropdowns for major providers
- Claude: Opus 4.7, Sonnet 4.6 (1M ctx), Haiku 4.5
- OpenAI: GPT-5.5, 5.4, 5.4-mini, 5.4-nano
- Gemini: 3.1-pro-preview, 2.5-pro, 2.5-flash, etc.
- "Other (type your own)" stays for niche models.
- Fixes "I tried gemini-3.0-pro and got 404."
4. Background generation
- lib/ai/generationRunner.ts: detached runner with in-memory
pub/sub bus. POST /api/ai/generate kicks it off and returns
immediately. SSE stream attaches by id. The runner survives
request cancellation; navigating away no longer kills it.
- New AIGeneration columns: progressText (in-flight stream),
durationMs (final wall-clock).
- Generate UI shows a banner explaining background-safety.
- History detail page polls progress + renders partial JSON
live for cross-process resume (page refresh, new tab).
5. System prompt overhaul
- lib/ai/systemPromptBase.ts: structural contract prepended to
every template. Forces JSON-only output, library-exerciseId
usage (kills "exerciseId doesn't belong to this user" errors),
and per-resistance-exercise suggestedWeight (with-history vs
without-history variants).
- aiExerciseSchema + ProgramExercise gain suggestedWeight +
suggestedWeightUnit. Starting a workout from a ProgramDay
pre-populates SetLog.weight from the suggestion.
6. Test connection improvements
- Latency in seconds (was ms — confusing for slow Ollama).
- Stale "✓ Connected" clears on form change.
- Per-config Test (no need to activate first).
- Generous maxOutputTokens for thinking models.
- Gemini surfaces finishReason on empty response (e.g. "blocked
by safety filter") instead of generic "empty response."
- Test endpoint accepts a draft body so you can verify before
saving + before activating.
7. History detail view
- Click row → full program tree + exact prompts sent. Apply from
here without re-generating. Pending rows poll for progress.
8. Sidebar sub-navigation
- AI: Generate / History / Templates
- Settings: General / Password / Sessions / AI integration /
Export / Instance (admin) / Danger zone, with anchor scroll.
9. API key UX
- "Key saved" indicator on saved configs (was confusing to see
an empty input after a successful save).
Schema migrations (additive, idempotent in entrypoint):
- AIConfigProfile table created
- UserPreferences.activeAIConfigId
- AIGeneration.progressText + durationMs
- ProgramExercise.suggestedWeight + suggestedWeightUnit
Tests: 16 new (systemPromptBase, modelMenu, generationRunner). 177
total pass.
Proof of Work
Self-hosted multi-user workout planner and logger. Plan training cycles, log daily workouts, search your history, and curate a shared exercise library across everyone on the instance. Distributed as a StartOS 0.4 sideload package.
Repo layout
proof-of-work/ Next.js app (TypeScript, Prisma + SQLite, Tailwind, PWA)
start9/0.4/ StartOS 0.4 package wrapper (manifest, Dockerfile,
entrypoint, version graph, change-credentials action)
Everything else is generated at build time.
Local development
cd proof-of-work
npm install
npx prisma generate # important after schema changes
npx prisma db push # create the dev DB at prisma/data/app.db
npm run db:seed # ONLY seeds the InstanceSettings singleton — no admin
npm run dev # http://localhost:3000
For local dev you'll need to create an admin manually since the
StartOS action isn't available — easiest is npx tsx a one-off
script, or just open Prisma Studio (npm run db:studio) and add a
User row with isAdmin: true + a bcrypt hash you generate with
node -e 'require("bcrypt").hash("yourpassword", 10).then(console.log)'.
Multi-user
Fresh installs ship with no admin user on purpose — the operator
must run the StartOS Action Set admin credentials (Services → Proof
of Work → Actions) before anyone can log in. This eliminates the
default-credentials footgun.
Once the admin exists, they can open sign-ups for additional users:
- In-app: log in as admin -> Settings -> Instance Settings -> Allow new sign-ups.
- StartOS: Services -> Proof of Work -> Actions -> Set new signups.
Both write to the same InstanceSettings row; either path works.
When sign-ups are open, anyone reaching the URL can create an account at
/auth/signup. New users start with no admin privileges and are
automatically seeded the full curated exercise library.
Building the StartOS package
See start9/0.4/DEPLOY_040.md for the full deployment / cutover guide. Short version:
cd start9/0.4
npm ci
make clean
make x86 # produces proof-of-work_x86_64.s9pk
make install # sideload to the host in ~/.startos/config.yaml
Curated exercise library
proof-of-work/prisma/exercises.seed.json is the canonical library
shipped to every install. It seeds fresh installs (via prisma/seed.ts)
and is re-applied on every boot to existing installs (via
docker_entrypoint.sh + ensureExerciseLibrary.cjs) so updates flow to
all users on package upgrade.
Refresh the JSON from the maintainer's live host:
./start9/0.4/refresh_seed.sh <ssh-target> # pull a fresh /data snapshot
cd proof-of-work && npm run sync-library # extract Exercise table -> JSON
git diff prisma/exercises.seed.json
The system is additive only — removing an exercise from the JSON does
not delete it from existing installs (users may have logged sets against
it). Users' own custom exercises (isCustom = true) are never touched.
Privacy
start9/0.4/seed/data/app.db is your live /data snapshot. It contains
real workout history and a bcrypt'd password hash. The top-level
.gitignore keeps it out of git; do NOT commit it to any public repo.