Immich

# MISSION: Scaffold "Immich" Production Architecture
You are an expert Senior Staff Software Architect and Full-Stack Engineer. Your mission is to scaffold and implement a production-grade, highly reliable, and modular codebase following the proven architecture of **Immich**.
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## 1. PROJECT SPECIFICATIONS & BENCHMARK
- **Reference Architecture**: Immich
- **What It Does**: Immich is a self-hosted photo and video management platform with a NestJS/PostgreSQL/Redis server, a SvelteKit web app, Flutter mobile apps, and a separate Python FastAPI service that runs machine-learning features such as face recognition and smart search.
- **Domain & Category**: Photo & Video Management Platform
- **Production Scale**: 6-20 people
- **Development Mode**: HYBRID
- **Architectural Rationale**: Machine-learning inference is split into its own FastAPI/Python service with pluggable CPU/GPU backends so heavy models stay off the request-serving NestJS process, while BullMQ and Redis move thumbnailing and job dispatch out of the request/response path.
- **Live Website Reference**: https://immich.app
- **Source Repository**: https://github.com/immich-app/immich
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## 2. PRODUCTION TECH STACK
- **Full Stack Array**: SvelteKit, TypeScript, NestJS, Flutter, Dart, Python, FastAPI, PostgreSQL, Redis, Kysely, Docker
- **Primary Language(s)**: TypeScript, Dart, Svelte, Python
- **License of the reference repo**: AGPL-3.0
- **Frontend**: SvelteKit — Builds the web gallery UI as a static-adapter SvelteKit app served alongside the server.; Vite — Dev server and bundler for the web app.; MapLibre GL — Renders the map view for geotagged photos in the web app.; Flutter — Cross-platform Dart client for iOS and Android, with its own local sync and camera-backup logic.
- **Backend & APIs**: NestJS — Structures the main API server (auth, assets, albums, jobs, websockets) into modules and controllers.; Kysely — Typed SQL query builder over Postgres, paired with a custom migration CLI (@immich/sql-tools) instead of a full ORM.; BullMQ — Runs background jobs (thumbnail generation, ML triggers, library scans) as a NestJS module backed by Redis.; FastAPI — Serves the separate machine-learning service that runs face recognition, CLIP search, and OCR models.; Extism — WebAssembly plugin runtime the server loads compiled plugins through, via @extism/extism.
- **Data & persistence**: PostgreSQL — Primary datastore for assets, users, and metadata, reached through Kysely with the postgres.js and pg drivers.; Redis — Backs the BullMQ job queue and the Socket.IO Redis adapter for realtime events, via ioredis.; Drift (SQLite) — Local on-device database for the mobile app, used for offline-capable asset and sync state.
- **Infrastructure & deploy**: Docker — Multi-stage server image built from immich-app base images; the machine-learning service has its own Dockerfile with CPU/CUDA/OpenVINO/ROCm variants.; OpenTelemetry — Instruments HTTP, Postgres, and Redis calls in the server, exported to Prometheus.; mise — Pins the toolchain used to compile server plugins to WebAssembly inside the Docker build.
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## 3. KEY ARCHITECTURAL DECISIONS (audited from https://github.com/immich-app/immich @ e8c6218)
1. **Machine learning runs as a separate FastAPI/Python service, not inside the NestJS API**: machine-learning/pyproject.toml defines a FastAPI app with onnxruntime and CPU/CUDA/OpenVINO/ROCm/RKNN optional dependency groups; machine-learning/Dockerfile builds it as its own image, so GPU-heavy inference is isolated from the request-serving server process.
2. **The API layer uses Kysely with a custom migration CLI instead of a traditional ORM**: server/package.json depends on kysely, kysely-postgres-js, and the workspace tool @immich/sql-tools, with migrations:generate/migrations:run scripts driving typed SQL migrations against Postgres rather than an ORM like TypeORM or Prisma.
3. **Background work is offloaded to Redis-backed BullMQ queues**: server/package.json pulls in @nestjs/bullmq, bullmq, and ioredis so jobs such as thumbnail generation, library scanning, and ML job dispatch run asynchronously outside the request/response cycle.
4. **Server plugins are compiled to WebAssembly and loaded through Extism**: packages/plugin-sdk and packages/plugin-core build plugin code with extism-js into a plugin.wasm artifact; server/package.json depends on @extism/extism to load and run those plugins inside the Node server, sandboxing third-party plugin code from the host process.
5. **The mobile app keeps its own local SQLite database for offline-capable browsing**: mobile/pubspec.yaml depends on drift, drift_sqlite_async, and sqlite_async, giving the Flutter app a local relational cache of assets and sync state instead of relying on the server being reachable for every screen.
6. **One Dockerfile builds the SDK, server, web, CLI, and plugins as separate stages**: server/Dockerfile chains FROM builder AS sdk -> plugin-sdk -> server / web / cli / plugins stages from a shared immich-app base image, then copies only the built output of each into the final production image.
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## 4. NON-NEGOTIABLE ARCHITECTURAL GUARDRAILS
1. **Monorepo & Modular Separation**:
   - Structure as a Turborepo monorepo with strict package boundaries:
     - `apps/web`: Application UI, routing, layouts, and server endpoints.
     - `packages/ui`: Shared design tokens, CSS variables, and Radix UI primitive components.
     - `packages/db`: Database schemas, client singleton, declarative migrations, and seed scripts.
     - `packages/config`: Shared TypeScript, ESLint, and build configurations.
2. **Strict Type Safety & Zero `any` Policy**:
   - Enable `strict: true`, `noImplicitAny: true`, and `strictNullChecks: true`.
   - Validate ALL external inputs, API request bodies, and query parameters with **Zod** schemas before execution.
3. **Frontend & Rendering Guidelines**:
   - Isolate interactive UI state to leaf components. Keep core pages lightweight and performant.
4. **Design System & Aesthetics**:
   - Keep every color, radius, shadow and font in a single token file (CSS variables) and consume tokens everywhere; never hardcode hex values in components.
   - Prefer crisp 1px borders and one subtle shadow scale over blurry default shadows. Pair one sans-serif for body/headings with one monospace for tags, badges, metrics, and code.
5. **Data Layer & Reliability**:
   - Write declarative schema definitions with foreign keys, composite indexes on queried filters, and automated timestamp triggers.
   - Use connection pooling and prepared statements for serverless database execution.
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## 5. STEP-BY-STEP SCAFFOLDING ROADMAP
- **Phase 1: Workspace & Root Config**: Initialize package manager, monorepo configuration (`turbo.json`, `tsconfig.base.json`, `package.json`).
- **Phase 2: Database Schema & Client**: Set up the data layer (PostgreSQL, Redis, Drift (SQLite)): client, connection pool, models, and migration scripts.
- **Phase 3: Design Tokens & UI Primitives**: Build accessible `Button`, `Input`, `Card`, `Badge`, and layout wrappers inside `packages/ui`.
- **Phase 4: Core Application Routes & Handlers**: Implement primary authentication, user session handling, and application routes.
- **Phase 5: Quality Assurance & Build Verification**: Run `tsc --noEmit`, ESLint, Prettier, and smoke test suites to ensure zero compilation or runtime errors.
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## 6. EXECUTION INSTRUCTIONS
1. Review all specifications, architectural guardrails, and stack choices above.
2. Present the full monorepo directory tree structure.
3. Systematically generate the complete, production-ready codebase according to the 5-phase roadmap above — starting with the root workspace setup, followed by the database schema, UI design system package, and full-stack application routes until the repository is fully scaffolded and ready to run.