Piotr Oleszczyk 8f7d893a63 Initial commit: backend API, data models, and test suite

FastAPI backend for personal health and skincare data with MCP export.
Includes SQLModel models for products, inventory, medications, lab results,
routines, and skin condition snapshots. Pytest suite with 111 tests running
on SQLite in-memory (no PostgreSQL required).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-02-26 15:10:24 +01:00

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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

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

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)

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