bvandeusen
ebc79b34f9
- Migration 0030: add conversations.rag_project_id (NULL=orphan-only, -1=all notes, positive=project), projects.auto_summary and projects.summary_updated_at - Three-value scope semantics thread from build_context() → semantic search and keyword fallback via orphan_only + effective_project_id - Project summarization background job (generate_project_summary, backfill_project_summaries) called via Ollama; triggered on project update and note saves (debounced 1h); runs at startup - New LLM tools: search_projects (SequenceMatcher scoring on title+description+auto_summary) and set_rag_scope (persists to DB, workspace-guarded, emits new_rag_scope in SSE done event) - execute_tool() accepts conv_id + workspace_project_id; generation_task passes both and captures scope changes for SSE done enrichment - Frontend: Conversation type gets rag_project_id; chat store adds ragProjectId computed + updateRagScope(); SSE done handler syncs scope - ChatView: replace sidebar ProjectSelector with a scope chip pill above the input bar, animated dropdown, pulse on model-driven scope change Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Fabled Assistant
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.