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Piotr Oleszczyk c87d1b8581 feat(api): implement Phase 2 token optimization and reasoning capture
- Add tiered context system (summary/detailed/full) to reduce token usage by 70-80%
- Replace old _build_products_context with build_products_context_summary_list (Tier 1: ~15 tokens/product vs 150)
- Optimize function tool responses: exclude INCI list by default (saves ~15KB/product)
- Reduce actives from 24 to top 5 in function tools
- Add reasoning_chain field to AICallLog model for observability
- Implement _extract_thinking_content to capture LLM reasoning (MEDIUM thinking level)
- Strengthen prompt enforcement for prohibited fields (dose, amount, quantity)
- Update get_creative_config to use MEDIUM thinking level instead of LOW

Token Savings:
- Routine suggestions: 9,613 → ~1,300 tokens (-86%)
- Batch planning: 12,580 → ~1,800 tokens (-86%)
- Function tool responses: ~15KB → ~2KB per product (-87%)

Breaks discovered in log analysis (ai_call_log.json):
- Lines 10, 27, 61, 78: LLM returned prohibited dose field
- Line 85: MAX_TOKENS failure (output truncated)

Phase 2 complete. Next: two-phase batch planning with safety verification.
2026-03-06 10:26:29 +01:00
backend feat(api): implement Phase 2 token optimization and reasoning capture 2026-03-06 10:26:29 +01:00
docs feat(profile): add profile settings and LLM user context 2026-03-05 15:57:21 +01:00
frontend feat(profile): add profile settings and LLM user context 2026-03-05 15:57:21 +01:00
nginx refactor(api): remove MCP server integration and docs references 2026-03-04 12:28:30 +01:00
systemd feat(backend): move product pricing to async persisted jobs 2026-03-04 22:46:16 +01:00
.gitignore fix: load .env via python-dotenv; SQLite default for local dev 2026-02-26 20:51:13 +01:00
AGENTS.md docs(repo): define agent skills and frontend cookbook workflow 2026-03-05 10:49:07 +01:00
deploy.sh feat(backend): move product pricing to async persisted jobs 2026-03-04 22:46:16 +01:00
PHASE1_COMPLETE.md feat(api): add LLM response validation and input sanitization 2026-03-06 10:16:47 +01:00
README.md feat(profile): add profile settings and LLM user context 2026-03-05 15:57:21 +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 and a web UI to an LLM agent.

Repository layout

backend/    Python backend — FastAPI REST API + 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
/profile User profile (birth date, sex at birth)
/health-check Liveness probe

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
/profile User profile

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)
  • 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).