uv run python app.py 

React/Tailwind frontend

cd frontend
bun install          # first time only
VITE_API_BASE="http://localhost:5000" bun run dev

• Build: recommended to run from inside the frontend/ folder:

cd frontend
bun run build

This emits the production bundle to frontend/dist/ (served automatically by Flask when present). If you only run uv run python app.py, make sure to rebuild after frontend changes so Flask serves the latest UI:

cd frontend && bun run build

Then reload the browser. The camera modal and capture flow will be available on the “Add” view.

Camera capture UX

• Full-screen camera modal for preview and capture.
• Visible spinner overlay while parsing the image.
• Manual focus slider appears when supported by the device; otherwise a hint is shown.
• Ingredient order is preserved exactly as parsed (no alphabetic sort).
• Adding a new ingredient/extra row prepends at the top for quick entry.

OpenAI API configuration

The backend auto-loads .env at startup and uses these variables:

• OPENAI_API_KEY (required)
• OPENAI_BASE_URL (optional for custom endpoints)
• RECIPE_IMAGE_MODEL (optional; defaults to gpt-5-mini)

Setup

• Copy ./.env.example to ./.env and fill values:
  • cp .env.example .env
• Start the app: uv run python app.py

Notes

• Do not commit keys to source control. Prefer a password manager or OS keychain for storage.

• Menu Planner parity lives in the React shell: spinner suggestions, search, serving adjustments, menu export, and ingredient rename tooling all run off the existing /api/* routes.

• Add Recipe lives in the same UI: drag/drop or camera capture, optional AI prompt, YAML preview, and manual form edits before posting to /api/recipes.

• Edit Recipes is React-native too: search/filter, adjust name/slug/servings/flags, tweak ingredients/extras, and PATCH via /api/recipes/<slug>.

• Config dashboard (categories, ingredient mappings, staples + label) is now in React with shortcuts into the rename tools.

• If the frontend dev server runs on another port, keep the Flask API running via uv run python app.py and point VITE_API_BASE to that origin.

podman build -t menu-app .
podman run -p 80:5000 menu-app

Podman + GitHub Container Registry (GHCR) Guide

Creating a Personal Access Token (PAT)

1. Go to GitHub Settings → Developer Settings → Personal Access Tokens
2. Choose "Tokens (classic)" or "Fine-grained tokens"
3. Generate new token with required permissions:
   • write:packages
   • read:packages
   • delete:packages (optional)
4. Save the token securely (e.g., in 1Password)
5. Note the token name shown in GitHub settings (this will be your username for podman login)

Pushing Images to GHCR

1. Login to GitHub Container Registry:

# Replace TOKEN_NAME with the name of your token from GitHub settings
# Replace YOUR_PAT with your actual PAT
echo YOUR_PAT | podman login ghcr.io -u TOKEN_NAME --password-stdin

2. Tag your local image:

podman tag menu-app:latest ghcr.io/julietkiloromeo/menu-app:latest

3. Push the image:

podman push ghcr.io/julietkiloromeo/menu-app:latest

Pulling Images on a New Machine

1. Login to GHCR:

# Replace TOKEN_NAME and YOUR_PAT as before
echo YOUR_PAT | podman login ghcr.io -u TOKEN_NAME --password-stdin

2. Pull the image:

podman pull ghcr.io/julietkiloromeo/menu-app:latest

Troubleshooting

• If login fails, verify:
  • Token name is correct (from GitHub settings, not your GitHub username)
  • PAT hasn't expired
  • PAT has correct permissions
• If push fails, ensure:
  • Repository exists and is properly configured for packages
  • You have appropriate permissions on the repository
  • Image is tagged correctly with the ghcr.io prefix

Security Notes

• Never commit your PAT to version control
• Use environment variables or secure secret management (like 1Password) to store PATs
• Consider using fine-grained tokens with minimal necessary permissions
• Regularly rotate your PATs