feat: scaffold Brain of Reese — FastAPI RAG chat over Postgres 17 + pgvector

Foundation (phase 01, verified):
- FastAPI app: /api/health, /api/suggestions, /api/chat (placeholder),
  static frontend served locally (no CDN)
- Postgres 17 + pgvector via db/Containerfile + compose.yaml
  (podman compose up -d db), Alembic initial migration (documents,
  chunks with vector(768), query_log)
- LLM client targeting https://aipi.reeseapps.com/v1 (turbo/embed);
  scripts/llm_probe.py verified models + 768-dim embeddings live
- Conditional debugpy: imported only when DEBUGPY=1 (attach on demand,
  :5678); logging config for clean single-line logs
- Frontend shell: mobile-first chat + Sources pages, tokens, a11y baselines
- Tests: 24 unit+integration (99% coverage on app/), ruff + pyright clean,
  Playwright smoke E2E (3 tests) against a deterministic mock LLM
- Planning: .agent/PLAN.md (architecture + LOCKED decisions), AGENTS.md,
  6 user stories, 7 phase files (one story / one phase / one Playwright
  suite each)

tests/fixtures/docs/homelab/backups.md

@@ -0,0 +1,14 @@
+# Backup Strategy
+
+## Philosophy
+3-2-1 rule: three copies, two media types, one offsite.
+
+## Tooling
+BorgBase for offsite backups. Restic for local nightly snapshots, orchestrated via Ansible.
+
+## Schedule
+- Nightly 02:00 — restic local snapshots
+- Weekly Sunday 03:00 — borg offsite push
+
+## Restore
+Restores are documented per-service in each deployment README. Test a restore quarterly.