bvandeusen
ba0cb07c91
Qwen3:14b sometimes burns output tokens on tool-calling attempts whose emission doesn't parse into any field we read — eval_count > 0 but no thinking/content/tool_calls ever stream to the caller. Generation completes "successfully," the user sees an empty assistant bubble, and no error is logged. Seen in conv 220 today. Two safety rails: - stream_chat_with_tools now tracks whether it yielded anything; when Ollama's done frame reports eval_count > 0 with zero yields, log a warning including the last ~5 raw frames so the next occurrence leaves breadcrumbs for diagnosis. - run_generation checks the same post-condition after the tool loop exits and, if content is empty with no tool calls but output_tokens > 0, substitutes a visible fallback message and streams it as a chunk so the user gets something readable instead of a blank bubble. 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.