Fitness Web

Multi-user fitness tracking web app with AI coaching.

Track workouts, log daily check-ins, explore exercise history, and chat with an AI coach powered by opencode.

Features

• Workouts — Plan and log workouts with set-level detail (reps, weight, RPE)
• Exercises — Catalog with body-part filtering and history
• Check-ins — Daily weight, calories, steps, sleep tracking
• AI Coach — Chat interface backed by opencode (Big Pickle model, free)
• Multi-user — Login-based, each user has independent data
• Calendar view — See your training history at a glance

Quick Start

# Install dependencies
uv sync

# Initialize and seed the database
uv run python scripts/schema.py
uv run python scripts/seed.py

# Start the dev server
uv run uvicorn app.main:app --reload

Open http://localhost:8000, register a user, and you're ready.

Docker

docker compose up -d

Architecture

app/
├── main.py          — FastAPI app factory with lifespan
├── config.py        — Settings from environment
├── auth.py          — Auth helpers (hash, verify, session)
├── models/          — SQLAlchemy ORM models
├── routers/         — Route handlers per feature
├── services/        — External service integrations (opencode)
├── templates/       — Jinja2 templates (Pico.css)
└── static/          — CSS overrides
scripts/
├── schema.py        — DB table creation
└── seed.py          — Seed exercises and phases
data/                — SQLite database (gitignored)

Related

• fitness-agent — Original training repo with markdown logs and Juggernaut history. This web app replaces it.