Bar items added by barcode stored the Open Food Facts image URL
directly. The CSP in next.config.mjs restricts img-src to our own
origin, so the browser blocked those and showed a broken image - the
picture was fine, we just could not display it.
Copy externally-hosted images into MinIO at lookup time and hand back a
/minio-images path instead. That fixes the class rather than the
instance: no CSP entry is needed per image source, the picture survives
the source deleting or reorganising it, and the user's browser never
has to talk to a third party to render their own bar.
Also fixes a latent bug this uncovered: imageUrl was validated with
z.string().url(), which rejects the relative /minio-images/... paths
that uploadImage returns, so saving an uploaded drink image would fail
validation. That matches production having zero drinks with an image.
Both schemas now accept either form.
CSP keeps two third-party entries for OAuth avatars, which the provider
hosts and we only ever receive as a URL at sign-in.
Existing rows were backfilled separately.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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>
- Fuzzy ingredient matching for bar inventory against recipes
- AI photo identification API for bottles/labels (drink + bar context)
- Barcode scanner with photo toggle for My Bar
- Barcode scan + photo ID buttons on Add Drink form
- Auto-pull product images from Open Food Facts barcode lookup
- Recipes section on drink detail pages with bar availability
- Dedicated Recipes page in sidebar navigation
- Bar item image support (schema, upload, display)
- Drink detail image upload component
- MinIO image proxy through Next.js rewrites (fixes broken image links)
- Improved category mapping (energy drinks → Mixers, not Spirits)
- Re-process saved recipe ingredients against current bar inventory
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Drink Images: upload/display photos of bottles/cans on drink cards and detail pages
- My Bar: inventory tracker for spirits, liqueurs, mixers, bitters, garnishes, tools
- Bartender: AI-powered cocktail recipe generation, "what can I make" suggestions,
saved recipes. Cross-references bar inventory for ingredient availability.
- Recommend: AI flavor profile analysis, personalized drink recommendations,
"find similar" drinks based on highly-rated favorites
- Navigation: desktop sidebar with all 8 routes, mobile bottom nav with
4 primary items + "More" popup menu
- New Prisma models: BarItem, Recipe, FlavorProfile
- Backup/restore updated to include bar items
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>
