bvandeusen
efb3534f3a
Per the surface-phase spec for the Notes/Tasks viewers and editors:
Long-form line-height
- prose.css: bumped global .prose from 1.6 to 1.7. Applies to Note
viewer body, Task viewer body, anywhere markdown renders into a
reading surface. Chat assistant bubble already had the explicit
override; now consistent with the rest.
Button reclassification per Hybrid rule
- Shared editor-shared.css:
- btn-save: accent gradient → Moss (action-primary). Saving is
"operating the software", not a brand moment.
- btn-delete: --color-danger (Error terracotta) → Oxblood
(action-destructive). Layout updated for inline-flex so the
Trash2 icon at call sites lines up alongside the label.
- NoteEditorView, TaskEditorView: Delete buttons now contain a
Trash2 icon per Hybrid's "destructive paired with icon" rule.
- NoteViewerView, TaskViewerView:
- btn-edit (and TaskViewer's btn-advance): accent gradient → Moss.
Switching to edit / advancing status are workflow actions.
- btn-convert, btn-share: ghost-on-hover-to-accent → Bronze
action-secondary (alternate paths).
Two-weights-only
- Snapped every font-weight: 600/700 to 500 across editor-shared.css
and the five Knowledge-cluster views.
Out of scope for this PR (deliberate punt)
- Smaller utility buttons (.btn-suggest-tags, .btn-link-all,
.btn-add-subtask, the AI-assist generate/proofread/accept/reject
set, etc.) — currently ghost-styled, generally compliant. Will
revisit only if they read off in practice.
- Filter chip / sub-task list-row border audit — deferred since
current styles already lean on background tint for affordance.
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.