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Piotr Oleszczyk 81b1cacc5c refactor(llm): use response_schema with typed enums in all Gemini calls
Pass response_schema to all three generate_content calls so Gemini
constrains its output to valid enum values and correct JSON structure:

- routines.py: _StepOut.action_type Optional[str] → Optional[GroomingAction]
- skincare.py: add _SkinAnalysisOut(PydanticBase) with OverallSkinState,
  SkinType, SkinTexture, BarrierState, SkinConcern enums; add response_schema
- products.py: pass ProductParseResponse directly as response_schema;
  remove NaN/Infinity/undefined regex cleanup, markdown-fence extraction,
  finish_reason logging, and re import — all now unnecessary

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-01 00:46:23 +01:00
backend refactor(llm): use response_schema with typed enums in all Gemini calls 2026-03-01 00:46:23 +01:00
docs fix(docs): correct Debian 13 deployment steps 2026-02-28 21:05:01 +01:00
frontend feat: AI-generated skincare routine suggestions (single + batch) 2026-03-01 00:34:43 +01:00
nginx feat: add deployment guide, nginx/systemd configs, switch to adapter-node 2026-02-28 20:09:00 +01:00
systemd fix(docs): correct Debian 13 deployment steps 2026-02-28 21:05:01 +01:00
.gitignore fix: load .env via python-dotenv; SQLite default for local dev 2026-02-26 20:51:13 +01:00
CLAUDE.md Initial commit: backend API, data models, and test suite 2026-02-26 15:10:24 +01:00
README.md fix(docs): correct Debian 13 deployment steps 2026-02-28 21:05:01 +01:00

innercontext

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

Repository layout

backend/    Python backend — FastAPI REST API + MCP server + SQLModel models
frontend/   SvelteKit web UI (Svelte 5, TypeScript, Tailwind CSS v4)
docs/       Deployment guides
nginx/      nginx config for production
systemd/    systemd service units

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.

Frontend quick start

Requirements: Node.js 24 LTS+, pnpm

cd frontend

# Install dependencies
pnpm install

# Start dev server (proxies API calls to localhost:8000)
pnpm dev

UI available at http://localhost:5173.

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
/skincare Weekly skin condition snapshots
/health-check Liveness probe

MCP server

innercontext exposes 14 tools via FastMCP at the StreamableHTTP endpoint http://localhost:8000/mcp/mcp.

Tools include: get_products, get_product, get_open_inventory, get_recent_routines, get_latest_skin_snapshot, get_skin_history, get_medications, get_expiring_inventory, get_grooming_schedule, get_recent_lab_results, and more.

Connect an MCP-compatible LLM agent by pointing it at http://<host>/mcp/mcp.

Frontend routes

Route Description
/ Dashboard
/products Product list
/products/new Add product
/products/[id] Product detail / edit
/routines Routine list
/routines/new Create routine
/routines/[id] Routine detail
/health/medications Medications
/health/lab-results Lab results
/skin Skin condition snapshots

Development

cd backend

# Lint
uv run ruff check .

# Format
uv run black .
uv run isort .

# Tests
uv run pytest

Stack

  • Backend: Python 3.12, FastAPI, Uvicorn, SQLModel 0.0.37 + SQLAlchemy, Pydantic v2, PostgreSQL (psycopg3)
  • MCP: FastMCP 3.0.2 (StreamableHTTP transport)
  • Frontend: SvelteKit 2, Svelte 5 (Runes), TypeScript, Tailwind CSS v4, shadcn-svelte

Deployment

See docs/DEPLOYMENT.md for a step-by-step guide for a Proxmox LXC setup (Debian 13, nginx, systemd services).