04 / Flagship Engineering
Shipped
AI Engineering Starter Kit
A reusable FastAPI foundation for production-minded AI services with typed configuration, persistence, testing, security guardrails, and CI.
FastAPIPythonGeminiSQLAlchemyAlembicPostgreSQLDockerGitHub Actions
Case study
What this project demonstrates
A foundation project built to eliminate repeated setup work while keeping production constraints visible from day one.
Architecture
Client → FastAPI routes → service/provider layer → typed schemas → persistence/migrations → observability + tests + CI
Engineering highlights
- Typed configuration, Gemini integration, structured output, logging, exception handling, and health endpoints.
- SQLite/PostgreSQL-ready persistence with SQLAlchemy and Alembic migrations.
- Optional API-key authentication plus production guardrails for debug mode, credentials, CORS, and weak keys.
- Async tests, mocked provider calls, Ruff, Docker/Compose, CI, Bandit, pip-audit, and migration smoke tests.
Boundaries / limitations
It is a starter architecture, not a substitute for application-specific threat modeling, scaling, observability, or domain logic.