bvandeusen
873e70c7ea
Restores a working browser surface for the journal feature, which was left UI-less when Stage F of the original plan was deferred. JournalView is a fresh write (not a rename of BriefingView) — drops the briefing- specific weather panel, news cards, RSS reactions, article-discuss button, and setup wizard, since none of those have journal-backend equivalents. What it does: - Fetches /api/journal/today on mount; shows today's daily-prep card (rendered from msg_metadata.kind === 'daily_prep' sections) - Day picker via /api/journal/days lets you switch to past days - Refresh-prep button hits /api/journal/trigger-prep - Center is the existing ChatPanel pinned to today's journal conversation (so the chat input + SSE + tool-call cards inherit unchanged) - Right sidebar keeps the upcoming-events list (uses the generic /api/events endpoint, not a briefing-specific one) Also: - Replace the dead Briefing API client functions with Journal equivalents (getJournalConfig, saveJournalConfig, getJournalToday, getJournalDay, getJournalDays, triggerJournalPrep, list/update/deleteJournalMoment). - Remove NewsView.vue — it was orphaned (no route, no nav) and depended on the deleted /api/briefing/* endpoints. If a standalone news surface is wanted later it'll need to be rebuilt against new endpoints. 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.