bvandeusen
70cea78c2f
Non-streaming generate_completion was the only LLM entry point that didn't default num_ctx — stream_chat and stream_chat_with_tools both fall back to Config.OLLAMA_NUM_CTX (16384). When a caller omitted the argument, Ollama silently used the model's default window (~4k on qwen3) and truncated the prompt. That footgun was masked by fallback paths in the research pipeline: _generate_outline's prompt carries ~12 sources × 2000 chars (~6k tokens) of source material plus a system prompt, so the prompt got chopped, the model never saw the sources, JSON parsing failed twice, and run_research_pipeline dropped into the single-note "monolith" fallback (research.py:251). The user reported chat 215 producing such a monolith note for a multi-source research topic. Two-layer fix: - Default num_ctx to Config.OLLAMA_NUM_CTX inside generate_completion, matching the streaming entry points. Any current or future caller that forgets the argument stops silently losing input. - Pin num_ctx=16384 explicitly in _generate_outline and _generate_executive_summary with comments pointing at the failure mode, so a refactor of the generate_completion default can't silently regress the research pipeline. 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.