- ADR-0003: modular monolith for Phase 0 with documented extraction triggers - ADR-0004: Auth.js + OIDC-shaped boundary; dedicated provider when mobile ships - ADR-0005: protobuf for events, OpenAPI for HTTP, schema-registry CI gate - New architecture docs: data-model, metrics (magic proxies), privacy (Phase-0 feature) - Prime directives updated: privacy-as-feature, modular-by-package-deployable-by-stage - Roadmap revised: Apple OAuth deferred to M1; web push in M1; k3s intermediate; tip-kind-aware UI - PLAN updated: Phase-0 deletion endpoint, metrics baseline, compose profiles, import-boundary lint - License decision in README (ARR with OSS plan in Phase 5)
91 lines
5.9 KiB
Markdown
91 lines
5.9 KiB
Markdown
# oO — Project Instructions
|
|
|
|
## What this is
|
|
|
|
**oO** is a recommendation system for personal tips. It collects signals across a user's life (tasks, habits, calendar, mood, context) to build a rich profile and deliver **one** perfectly-timed tip — an advice or a todo — that feels like magic.
|
|
|
|
The magic is the product. Precision + timing + minimalism. The UI shows a single black page with one tip. The complexity lives behind it.
|
|
|
|
## Prime directives
|
|
|
|
1. **Modular by package, deployable by stage.** Contracts live at package boundaries from day one so extraction to a service is cheap. Deploy topology evolves with real pressure (team size, scaling hotspots, language boundaries), not with wishful architecture. Phase 0 = **modular monolith + Python ML sidecar**. See ADR-0003.
|
|
2. **Recommendation engine is the core.** Every other module feeds it or renders its output. Design schemas, event contracts, and APIs with that in mind.
|
|
3. **Python owns ML.** Training, features, online scoring are Python (FastAPI + PyTorch/scikit + MLflow/Feast). Application code is TypeScript (Node, Next.js) unless there's a reason.
|
|
4. **OAuth-first for identity and integrations.** Never ask users for passwords or raw API keys when a delegated-auth flow exists. Store provider tokens encrypted, refresh transparently.
|
|
5. **Privacy is a feature, not a phase.** Consent capture, token revocation, and account deletion exist from the first real user. Data minimization: store the token + derivatives we need, not the raw feed.
|
|
6. **Feel-of-magic over feature count.** When in doubt, ship fewer things, polished. The tip page is a watch face.
|
|
|
|
## Architecture (high level)
|
|
|
|
The tree below is **logical module structure**. Directory layout is stable; how many processes you deploy is a stage decision (ADR-0003).
|
|
|
|
```
|
|
apps/ user-facing clients
|
|
web/ Next.js PWA — the first shipped client
|
|
mobile-ios/ Swift/SwiftUI (Phase 3)
|
|
mobile-android/ Kotlin/Compose (Phase 3)
|
|
|
|
services/ backend modules — each owns a contract; may share a deployable
|
|
gateway/ BFF for clients; auth check; fan-out
|
|
auth/ OAuth (Google, Apple, ...), sessions, JWT issuance
|
|
profile/ user profile, preferences, consents
|
|
integrations/ third-party connectors + token vault (Todoist first)
|
|
recommender/ orchestration: candidates → policy → tip; feedback sink
|
|
events/ event bus ingress + durable signal store
|
|
notifier/ push/email/web delivery (web push from Phase 1)
|
|
|
|
packages/ shared libraries (importable across services + apps)
|
|
shared-types/ HTTP types via OpenAPI; event types via protobuf (ADR-0005)
|
|
sdk-js/ client SDK used by web + mobile webviews
|
|
ui/ shared React components + design tokens
|
|
|
|
ml/ Python — separate deployable from day one
|
|
serving/ online scorer (FastAPI), called by recommender
|
|
features/ feature definitions + store adapter
|
|
pipelines/ batch feature + training DAGs (Prefect/Airflow)
|
|
registry/ MLflow model registry integration
|
|
experiments/ assignment + A/B + bandit policies
|
|
notebooks/ research only; never imported by production code
|
|
|
|
infra/ docker-compose (Phase 0), k3s/k8s (later), terraform, CI
|
|
docs/ architecture notes, ADRs, API specs
|
|
```
|
|
|
|
**Phase 0 deployables:** one Node process (`services/*` bundled via modular monolith) + one Python process (`ml/serving`, stubbed until M1) + Postgres + NATS. Services **extract to their own process** when a real reason appears: language boundary, scaling hotspot, team ownership, or SLA divergence. See ADR-0003.
|
|
|
|
## Contracts between modules
|
|
|
|
- **HTTP** (OpenAPI, in `packages/shared-types/http/`) — synchronous request/response. In-process today; over the network once extracted. Signatures are identical.
|
|
- **Events** (Protocol Buffers, in `packages/shared-types/events/`) — durable signals + feedback. Today: in-process event emitter. Tomorrow: NATS JetStream. Schema registry enforced in CI (ADR-0005).
|
|
- Do not redefine types per module. Regenerate from `shared-types`.
|
|
|
|
## Conventions
|
|
|
|
- Each module ships a `README.md` describing its contract, its `/health` story, and its extraction criteria (when it should become its own process).
|
|
- One PR = one concern. Conventional-commit prefixes (`feat:`, `fix:`, `chore:`, `docs:`, `refactor:`).
|
|
- ADRs go in `docs/adr/NNNN-title.md` for any decision that constrains future work.
|
|
- No secrets in repo. Local dev via `.env.local` (gitignored), prod via the server's secret store (Vaultwarden now; k8s secrets later).
|
|
- Compose profiles (`core`, `full`) so devs can run a subset without 16 GB of RAM.
|
|
|
|
## Definition of done (per feature)
|
|
|
|
1. Code + tests merged.
|
|
2. Module's `README.md` updated.
|
|
3. If it changes a contract → `shared-types` regenerated + consumers updated.
|
|
4. If it changes architecture → ADR added.
|
|
5. Deployable via `docker compose up` locally.
|
|
6. If it touches user data → a deletion path exists and is tested.
|
|
|
|
## Current phase
|
|
|
|
**Phase 0 — Prototype.** See `README.md` for the phase roadmap and `docs/architecture/` for diagrams. Work is tracked as Gitea milestones + issues on `alvis/oO`.
|
|
|
|
## What NOT to do
|
|
|
|
- Don't copy Todoist's data into our DB. Store the OAuth token + computed features/derivatives we need, fetch raw on demand.
|
|
- Don't implement auth by hand. Phase 0 uses **Auth.js** behind an OIDC-shaped boundary (ADR-0004); swap to a dedicated OIDC provider only when mobile ships.
|
|
- Don't hardwire a recommender. The "random todo" v0 must live behind the same interface the real ML model will implement (`POST /recommend` → `{tip}`). Swap internals, keep contract.
|
|
- Don't replace a policy in one step. New policies deploy shadow-first; promoted only after offline + online agreement with the incumbent (ADR-0002).
|
|
- Don't build an admin UI before the user-facing black page is polished.
|
|
- Don't over-split processes. Extract a service when pressure demands it, not in anticipation (ADR-0003).
|