# Calorie AI

Native Android and Dockerized web calorie tracker with meal images, AI nutrition estimates, server-backed plans, and admin-configurable AI models.

## Features

- Add meals by description, portion estimate, and uploaded image.
- Analyze meals through OpenAI-compatible chat completions.
- Uses a vision model for food image calorie and portion estimates.
- Uses an advice model to normalize calories, protein, carbs, fat, fruit servings, vegetable servings, food groups, and notes.
- Stores daily meal entries locally on Android or in browser local storage.
- Stores generated web weight-loss plans on the server in `web/data/plans.json`.
- Shows daily totals plus charts for macros, 7-day calories, and fruit/vegetable intake.
- Admin settings control API base URL, API key, image model, and nutrition/advice model. The two model fields can contain the same model name.

## Android Build

Open this folder in Android Studio and run the `app` configuration, or build with Gradle if available:

```bash
gradle :app:assembleDebug
```

Forgejo Actions builds the debug APK on every push to `main` and uploads it as the `calorie-ai-debug-apk` artifact.

Tagged versions also build an installable APK named `calorie-ai-vX.Y.Z.apk` and attach it to a Forgejo release through the Android Release workflow.

## Install With Obtainium

Use the Forgejo releases page as the source:

```text
https://git.danvics.com/danvics/calorie-ai-android/releases
```

If Obtainium asks for a direct APK URL, use the latest release asset URL pattern:

```text
https://git.danvics.com/danvics/calorie-ai-android/releases/download/v0.1.1/calorie-ai-v0.1.1.apk
```

Recommended Obtainium setup:

- App source: `HTML` or `Gitea/Forgejo` if your Obtainium version offers it.
- URL: `https://git.danvics.com/danvics/calorie-ai-android/releases`
- APK link filter: `calorie-ai-.*\.apk`
- Version extraction: release tag, for example `v0.1.1`.

The APK is a debug build, so Android may require allowing installs from Obtainium and accepting the debug signing certificate.

## Web Frontend

The web frontend lives in `web/`. It serves an authenticated browser UI and a tiny Node proxy at `/api/chat` so OpenAI-compatible endpoints are called server-side instead of directly from the browser.

Run it with Docker:

```bash
cd web
docker compose up -d --build
```

Then open:

```text
http://127.0.0.1:8095
```

The Docker web server creates credentials on first boot in `web/data/auth.json` if `CALORIE_AI_WEB_PASSWORD` and `CALORIE_AI_SESSION_SECRET` are not supplied. To pin credentials, copy `web/.env.example` to `web/.env` and set strong values before starting Docker Compose.

## AI Endpoint

The app expects an OpenAI-compatible endpoint at:

```text
{API base URL}/chat/completions
```

Example base URLs:

- `https://api.openai.com/v1`
- An emulator host-loopback URL ending in `:11434/v1` for a local OpenAI-compatible service

Default admin PIN is `admin`. Change it in the Admin AI Settings panel after first launch.

The web frontend stores AI settings in browser local storage after web login, while generated plan versions are stored server-side. The web login is separate from the Android admin PIN.