Replace the direct Anthropic and OpenAI integrations with a single
provider that talks to Switchboard, an OpenAI-compatible gateway that
routes each request to the best available model. The app no longer pins
a model id anywhere: it sends switchboard/auto and lets the gateway
choose, then logs which model answered and what it cost.
Routing levers are set per feature in src/lib/ai/routing.ts. Three of
those choices came from measuring against the live gateway:
- category and prefer_free are set explicitly on every request. An API
key carries its own routing defaults, and anything left unset inherits
them - drink prompts were being sent to a free coding model.
- Token budgets are generous because the router may pick a reasoning
model, and reasoning tokens come out of the same max_tokens budget as
the answer. At 512 tokens a request returned null content; at 4096 the
same request returned correct JSON.
- No tier lever on text features. tier "cheap" pinned a slow reasoning
model (42-180s, two timeouts and one truncated response in five
trials) and tier "frontier" escalated as far as Opus at $0.02 a call,
while unconstrained routing answered in about a second. Vision keeps
"frontier", where the accuracy is worth a few tenths of a cent.
Gateway failures are mapped to actionable messages rather than passed
through: a 401 relayed as 401 would read as an expired session and
bounce the user to login, and a 429 would collide with the app's own
rate limiter.
Also collapses the key lookup that was duplicated across ten call sites
into getUserProvider(), which fixes a latent bug where a bare findFirst
with no ordering let different features pick different providers.
Existing claude/openai key rows are ignored at runtime and offered for
removal in Settings, so no migration is needed before deploying.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
network_mode: host avoids Docker creating separate network namespaces
which trigger sysctl writes blocked in LXC containers. All service
references updated from container names to localhost.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Push app image to jpscott84/drinktracker on Docker Hub
- docker-compose.prod.yml uses image instead of build
- install.sh pulls image instead of building from source
- Much faster deploys (no npm ci/build on target server)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- install.sh: Interactive setup script for Linux VPS/LXC deployment
- Checks prerequisites (Docker, Docker Compose, OpenSSL)
- Auto-generates all secrets (Postgres, MinIO, NextAuth, encryption)
- Creates .env.production with proper Docker service hostnames
- Builds and starts all services via docker-compose.prod.yml
- Health check loop with status reporting
- Idempotent (safe to re-run)
- docker-compose.prod.yml: Add migrate service
- One-shot container that runs prisma db push before app starts
- App depends on migrate completing successfully
- Override DATABASE_URL and MINIO_ENDPOINT for Docker networking
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Next.js 14 drink collection tracker with AI-powered search,
menu scanning, ratings, wishlist, sharing, and CSV backup/restore.
Features:
- Auth (credentials + OAuth ready)
- Drink collection with ratings and reviews
- AI search via Claude/OpenAI with search history
- Menu photo scanning with AI extraction
- Wishlist / Try Later system
- Public sharing via slug URLs
- CSV backup and restore (merge/replace modes)
- Docker Compose for Postgres + MinIO + dev server
Security: docker-compose files use env var interpolation
instead of hardcoded secrets.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
