bvandeusen
541e2ed713
Settings is the densest button surface in the app. Per the surface-
phase spec, classify every button on a deliberate token.
Button reclassification per Hybrid rule
- btn-save (~13 instances across General/Account/Notifications/
Integrations/Data/Briefing/Admin tabs): flat accent → Moss
action-primary
- btn-primary (Groups tab "Save Retention", "+ New Group"): flat
accent → Moss action-primary
- btn-secondary (Detect timezone, Test SMTP, Refresh, Export, Add
slot, Preview voice, etc.): outline-on-bg-secondary +
hover-to-accent → Bronze action-secondary, filled
- btn-danger filled (Reset VAPID, Revoke API key Yes): added the
rule (was previously unstyled — relied on no-rule). Now Oxblood
action-destructive.
- btn-danger-outline (Invalidate sessions, Clear observations,
Delete personal data): generic --color-danger → Oxblood
action-destructive
- btn-danger-sm hover (group + member delete): --color-danger →
--color-action-destructive
- btn-delete row hover, btn-confirm-delete (user delete two-stage):
--color-danger → Oxblood. Confirm filled, cancel ghost.
- btn-toggle-open ("Open registration"): flat accent → Moss
- model-delete-btn hover: --color-danger → Oxblood
- btn-warn hover: muted-border-warning → filled-warning
Two-weights-only
- Snapped every font-weight 600/700 to 500.
Out of scope for this PR
- Voice/tone copy audit across labels and help text — per spec,
opportunistic only. Skipped.
- Settings row de-bordering — current section dividers are
structural; left as-is.
- Validation-state colors (.input-error etc.) keep --color-danger
(Error terracotta) per the doc — Error is for validation/error
messages, Oxblood is for destructive actions.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Fabled Scribe
A self-hosted second brain and project management application with integrated LLM capabilities. Write, organise, and act on your notes and tasks with the help of a local AI assistant — all running on your own hardware.
Features
Notes and tasks with a Markdown editor, sub-tasks, milestones, and kanban project workspaces. AI chat with streaming responses, RAG over your notes, and tool use (web search, calendar, weather). A daily briefing that digests your tasks, RSS feeds, and weather on a schedule. Knowledge graph, per-user/group sharing, PWA with push notifications, an MCP server for external AI clients, and an Android companion app.
Quick Start
Prerequisites: Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.
Download docker-compose.quickstart.yml from this repo, then:
# Optional but recommended — set a secret key
export SECRET_KEY=your-random-secret-here
docker compose -f docker-compose.quickstart.yml up -d
Open http://localhost:5000. The first user to register becomes admin. Go to Settings → General to pull an LLM model — qwen3:8b or llama3.1:8b are good starting points.
GPU: Ollama runs CPU-only by default. See the comments in
docker-compose.quickstart.ymlto enable NVIDIA GPU passthrough.
Development: To build from source, see Development.
Documentation
| Doc | Contents |
|---|---|
| Architecture | Stack, design decisions, data models, key services |
| Configuration | Environment variables, Docker Compose, production setup, security |
| Features | Detailed feature breakdown and keyboard shortcuts |
| Development | Dev workflow, CI/CD, migrations, release process |
| API Keys & MCP | API key management and Fable MCP install guide |
| SSO / OAuth | OIDC setup for Authentik, Keycloak, and other providers |
| API Reference | All REST API endpoints |
| Android App | Flutter companion app architecture and feature status |
License
This project is privately maintained.