| name | kouchou-ai-development |
| description | Local development setup, build and lint commands, environment configuration, and deployment helpers for the kouchou-ai repo. Use when starting services, building images, running lint/format, or working with Azure/static builds. |
Kouchou-AI Development
Overview
Use this skill for setup, build, and operational commands.
Local development setup
- Copy
.env.example to .env before starting services.
- Start all services with
docker compose up.
- Initialize frontend dependencies with
make client-setup.
- Run the public viewer, admin, and dummy server with
make client-dev -j 3.
Build and static exports
- Build all Docker images with
make build.
- Generate static exports with
make client-build-static.
- Build individual frontends with
pnpm run build in apps/public-viewer/ or apps/admin/.
Linting and formatting
- Run root lint/format with
pnpm run lint and pnpm run format.
- Run frontend linting with
pnpm run lint inside each frontend app.
- Run backend linting with
rye run ruff check . inside apps/api/.
Server development
- Run the API locally with
rye run uvicorn src.main:app --reload --port 8000 in apps/api/.
- Use
make lint/check and make lint/format in apps/api/.
- Use
make lint/api-check and make lint/api-format for Docker-based linting.
Environment configuration
- Keep
.env files scoped per service directory and reference .env.example for defaults.
- Restart and rebuild Docker images if you change environment variables that are baked at build time.
Pull Request workflow
- Follow
.github/PULL_REQUEST_TEMPLATE.md when creating a PR.
Documentation conventions
- Add language identifiers to fenced code blocks in docs (for example,
bash or text).
Azure deployment helpers
- Use
make azure-setup-all for full Azure setup.
- Use
make azure-build, make azure-push, make azure-deploy, and make azure-info for individual steps.
Local LLM notes
- Enable Ollama with
docker compose --profile ollama up -d when GPU support is available.
- Plan for 8GB+ GPU memory for local LLM usage.
