docs: add quickstart compose file; condense README features section
Adds docker-compose.quickstart.yml that pulls the pre-built image from the registry so users can get started without a local build. Updates README Quick Start to use the new file as the default path. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@@ -4,30 +4,26 @@ A self-hosted second brain and project management application with integrated LL
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## Features
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## Features
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- **Notes** — Markdown editor (Tiptap), wikilinks, backlinks, tags, version history, AI writing assist
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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.
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- **Tasks** — Status, priority, due dates, sub-tasks, milestones, work logs
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- **Projects** — Kanban view, milestone progress, three-panel project workspace (tasks / chat / notes)
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- **AI Chat** — SSE streaming, RAG, tool calls (create/update content, search web, check weather, calendar)
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- **Daily Briefing** — Scheduled digest of tasks, calendar, weather, and RSS; interactive follow-up conversation
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- **Knowledge Graph** — D3 force-directed graph of all notes and tags
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- **Sharing** — Share projects and notes with users or groups at viewer/editor/admin permissions
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- **Fable MCP** — MCP server for Claude and other clients to read/write your data via API keys
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- **PWA** — Installable, push notifications, web and Android companion app
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## Quick Start
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## Quick Start
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**Prerequisites:** Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.
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**Prerequisites:** Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.
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Download [`docker-compose.quickstart.yml`](docker-compose.quickstart.yml) from this repo, then:
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```bash
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```bash
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git clone https://git.fabledsword.com/bvandeusen/FabledAssistant.git
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# Optional but recommended — set a secret key
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cd FabledAssistant
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export SECRET_KEY=your-random-secret-here
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cp .env.example .env # Edit .env to set SECRET_KEY
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docker compose up --build
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docker compose -f docker-compose.quickstart.yml up -d
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```
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```
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Open `http://localhost:5000`. The first user to register becomes admin.
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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.
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Go to **Settings → General** to pull an LLM model. `qwen3:8b` or `llama3.1:8b` are good starting points.
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> **GPU:** Ollama runs CPU-only by default. See the comments in `docker-compose.quickstart.yml` to enable NVIDIA GPU passthrough.
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> **Development:** To build from source, see [Development](docs/development.md).
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## Documentation
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## Documentation
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@@ -0,0 +1,82 @@
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# Fabled Assistant — Quick Start
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#
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# No build required. Pulls the latest pre-built image from the registry.
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#
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# Usage:
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# 1. Download this file
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# 2. docker compose -f docker-compose.quickstart.yml up -d
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# 3. Open http://localhost:5000 — the first account registered becomes admin
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# 4. Go to Settings → General to pull an LLM model (qwen3:8b or llama3.1:8b are good starting points)
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#
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# Set SECRET_KEY via environment variable or a .env file alongside this file:
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# SECRET_KEY=your-random-secret-here
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services:
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app:
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image: git.fabledsword.com/bvandeusen/fabledassistant:latest
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ports:
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- "5000:5000"
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environment:
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DATABASE_URL: "postgresql+asyncpg://fabled:fabled@db:5432/fabledassistant"
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SECRET_KEY: "${SECRET_KEY:-change-me-in-production}"
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OLLAMA_URL: "http://ollama:11434"
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OLLAMA_MODEL: "${OLLAMA_MODEL:-llama3.1:8b}"
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LOG_LEVEL: "${LOG_LEVEL:-INFO}"
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volumes:
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- app_data:/data
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depends_on:
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db:
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condition: service_healthy
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ollama:
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condition: service_healthy
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restart: unless-stopped
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healthcheck:
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test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:5000/api/health')"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 30s
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db:
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image: postgres:16-alpine
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volumes:
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- pgdata:/var/lib/postgresql/data
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environment:
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POSTGRES_USER: fabled
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POSTGRES_PASSWORD: fabled
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POSTGRES_DB: fabledassistant
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U fabled"]
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interval: 10s
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timeout: 5s
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retries: 5
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restart: unless-stopped
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ollama:
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image: ollama/ollama
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volumes:
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- ollama_models:/root/.ollama
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environment:
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OLLAMA_MAX_LOADED_MODELS: "2"
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OLLAMA_KEEP_ALIVE: "30m"
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OLLAMA_FLASH_ATTENTION: "1"
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healthcheck:
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test: ["CMD-SHELL", "ollama list > /dev/null 2>&1"]
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 15s
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restart: unless-stopped
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# Uncomment to enable NVIDIA GPU passthrough (requires nvidia-container-toolkit):
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# deploy:
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# resources:
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# reservations:
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# devices:
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# - driver: nvidia
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# count: all
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# capabilities: [gpu]
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volumes:
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app_data:
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pgdata:
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ollama_models:
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