# innercontext

Personal health and skincare data hub. Collects structured data (products, routines, lab results, medications, skin snapshots) and exposes it via a REST API and MCP to an LLM agent.

## Repository layout

```
backend/   Python backend — FastAPI REST API + SQLModel models
```

A frontend will be added in the future.

## Backend quick start

**Requirements:** Python 3.12+, PostgreSQL, [uv](https://docs.astral.sh/uv/)

```bash
cd backend

# Install dependencies
uv sync

# Set database URL (defaults to postgresql+psycopg://localhost/innercontext)
export DATABASE_URL=postgresql+psycopg://user:password@localhost/innercontext

# Start the API server (creates tables on first run)
uv run uvicorn main:app --reload
```

API docs available at `http://localhost:8000/docs`.

## API overview

| Prefix | Resource |
|---|---|
| `/products` | Skincare / medication products + inventory |
| `/inventory` | Individual inventory entries |
| `/health/medications` | Medication entries and usage history |
| `/health/lab-results` | Lab test results |
| `/routines` | AM/PM skincare routines and steps |
| `/routines/grooming-schedule` | Weekly grooming schedule |
| `/skin-snapshots` | Weekly skin condition snapshots |
| `/health-check` | Liveness probe |

## Development

```bash
cd backend

# Lint
uv run ruff check .

# Format
uv run black .
uv run isort .
```

## Stack

- **Runtime:** Python 3.12, FastAPI, Uvicorn
- **ORM:** SQLModel 0.0.37 + SQLAlchemy, Pydantic v2
- **Database:** PostgreSQL (psycopg3)