bvandeusen
0becc1439b
Three related fixes uncovered while benchmarking qwen3:14b against 8b: - pick_num_ctx was only counting message content, missing the ~15K tokens of tool schemas. num_ctx=8192 was being selected while actual prompt_tokens hit 14K+, causing silent prompt truncation on every tool-using request. Now includes json.dumps(tools) in the estimate. KV cache priming in app.py and routes/settings.py also fetches tools so the primed num_ctx matches what real chat requests will use. - _should_think's heuristic classifier was overriding explicit think=true requests from the frontend toggle and MCP, gating on message length and regex patterns. Now a pass-through — the caller is the source of truth. quick_capture hardcodes think=False since it's a fast classification path that was relying on the old gating. - delete_note description only mentioned "note or task", so the model refused to call it for entries created by save_person / save_place / create_list. Description now explicitly lists all five note_types it handles. Co-Authored-By: Claude Opus 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.