{"data":{"slug":"jaylfc-taos","name":"taOS","tagline":"Self-hosted AI agent OS with memory, chat, and multi-framework group chat support.","github_url":"https://github.com/jaylfc/taOS","owner":"jaylfc","repo":"taOS","owner_avatar_url":"https://avatars.githubusercontent.com/u/30096482?v=4","primary_language":"Python","stars":542,"forks":40,"topics":["agent-framework","ai-agents","ai-platform","apple-silicon","data-sovereignty","distributed-computing","kv-cache-quantization","llm","llm-inference","local-first","local-llm","offline-first","orange-pi","privacy","raspberry-pi","rockchip-npu","self-hosted","turboquant","vllm"],"archived":false,"github_pushed_at":"2026-09-20T01:37:19+00:00","maintenance_label":"Very active","stars_delta_30d":83,"url":"https://www.graphcanon.com/tools/jaylfc-taos","markdown_url":"https://www.graphcanon.com/tools/jaylfc-taos.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/jaylfc-taos","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=jaylfc-taos","description":"Self-hosted AI agent OS. Your memory, chat, agents, and files stay on hardware you own, offline by default, cloud by choice. Offline AI memory (taOSmd), self-hosted multi-framework group chat, a full web desktop + app store, and auto-clustering across the consumer hardware you already have (Orange/Raspberry Pi, Mac mini, gaming PC).","homepage_url":"https://taOS.my","license":"AGPL-3.0","open_issues":290,"watchers":6,"ai_summary":"taOS is a self-hosted operating system designed for AI agents, featuring offline AI memory, local-first functionality, full web desktop environment, and support for various hardware including Orange Pi, Raspberry Pi, and Apple Silicon. It offers auto-clustering capabilities for consumer hardware and integrates multiple AI frameworks.","readme_excerpt":"## Quick Start\n\n**Controller (server):**\n\n```bash\n\n---\n\n# Debian / Ubuntu / Fedora / Arch / Alpine / macOS, one-line install\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-server.sh | sudo sh\n```\n\n
Alpine / postmarketOS — install dependencies first\n\n```bash\nsudo apk add --no-cache bash python3 py3-pip git curl libtorrent-rasterbar sqlite nodejs npm sqlcipher-dev vulkan-tools\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-server.sh | sudo sh\n```\n
\n\n
Debian / Ubuntu — install dependencies first\n\n```bash\nsudo apt-get update && sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \\\n bash python3 python3-venv python3-pip git curl ca-certificates \\\n libtorrent-rasterbar-dev libboost-python-dev sqlite3 libsqlcipher-dev vulkan-tools\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-server.sh | sudo sh\n```\n
\n\n
Fedora — install dependencies first\n\n```bash\nsudo dnf install -y bash python3 python3-pip git curl \\\n rb_libtorrent-devel rb_libtorrent-python3 boost-python3 \\\n sqlite nodejs npm sqlcipher-devel vulkan-tools\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-server.sh | sudo sh\n```\n
\n\n
Arch — install dependencies first\n\n```bash\nsudo pacman -Sy --needed bash python python-pip git curl \\\n libtorrent-rasterbar boost sqlite nodejs npm sqlcipher vulkan-tools\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-server.sh | sudo sh\n```\n
\n\nNode 22 is installed by the script itself (NodeSource); it is not in these lists.\n\nRun without `sudo` to install as a user-mode systemd unit instead. The script is idempotent, safe to re-run on an existing install. Supports env-var overrides for install path, branch, and port.\n\n---\n\n# Linux / macOS, one-line worker install (auto-detects headless,\n\n---\n\n# service otherwise; works on a fresh Debian install or your existing box)\ncurl -fsSL https://raw.githubusercontent.com/jaylfc/taOS/master/scripts/install-worker.sh | sudo bash -s -- http://your-server:6969\n\n---\n\n# Windows 10/11, one-line worker install (PowerShell, mirrors the\n\n---\n\n### Agent Deployment\n5-step wizard: pick framework → choose model → configure → deploy into an isolated container (LXC on bare metal, Docker on VPS, auto-detected). Each agent gets its own memory system (taOSmd instance), its own file storage, and its own network identity. The framework runs inside the container but taOS manages everything around it: memory, channels, secrets, model access, scheduled tasks, and inter-agent communication. This means the framework is a swappable component, not a lock-in decision.\n\n> **Running taOS *inside* an LXC (e.g. Proxmox)?** Deploying an agent creates a *nested* container, which an **unprivileged** LXC cannot do -- the kernel can't remap the nested container's filesystem, so the deploy fails with an `idmapped storage / change ownership` error. Run the taOS LXC as **privileged with nesting enabled**. On Proxmox: untick *Unprivileged container* and set Options → Features → `nesting=1` (plus `keyctl=1`, `fuse=1`), then redeploy. Bare-metal and VM installs are unaffected. (taOS detects this and surfaces the fix in the deploy error.)\n\n

\n \"Agents\n

\n\n

The Agents app on mobile -- one tap from empty to your first deployed agent.

\n\n---\n\n## Supported Hardware\n\n| Category | Hardware | Notes |\n|----------|----------|-------|\n| **Apple Silicon** | Mac Mini, MacBook, Mac Studio, Mac Pro (M1-M5) | Ollama (Metal) or MLX backend, 8-192GB unified memory |\n| **ARM + Rockchip NPU** | Orange Pi 5/5 Plus, Rock 5B | 6 TOPS NPU, primary SBC target |\n| **Raspberry Pi** | Pi 4 (8GB), Pi 5 (8/16GB) | CPU-on","github_created_at":"2026-04-05T15:33:40+00:00","created_at":"2026-07-11T11:46:36.418665+00:00","updated_at":"2026-09-20T06:36:38.994406+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"agent-framework","name":"agent-framework"},{"slug":"ai-platform","name":"ai-platform"},{"slug":"data-sovereignty","name":"data-sovereignty"},{"slug":"distributed-computing","name":"distributed-computing"},{"slug":"llm-inference","name":"llm-inference"},{"slug":"local-first","name":"local-first"},{"slug":"offline-first","name":"offline-first"},{"slug":"privacy","name":"privacy"}],"trust":{"provenance":{"is_fork":false,"github_id":1202093119,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T03:46:26.915Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":30,"days_since_push":0,"last_release_at":"2026-09-16T11:39:02Z","stars_delta_30d":83,"open_issues_delta_30d":-18},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:46:37.649Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T03:46:28.441Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-09-20T03:46:28.441Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-20T03:46:28.441Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-09-20T03:46:28.441Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You require an AI agent OS that prioritizes your hardware ownership and offline capabilities, ensuring your data remains private without needing continuous internet access.","Your environment consists of diverse hardware like Orange Pi or Raspberry Pi, where you aim to deploy auto-clustering for more efficient resource utilization."],"when_not_to_use":["You prioritize cloud-based AI services with real-time data processing over self-hosted and offline solutions.","Your infrastructure is primarily composed of enterprise-grade servers that already support advanced clustering software, making taOS's auto-clustering less beneficial."],"source":"enrich:decision_facts","observed_at":"2026-07-12T01:11:20.255Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"taOS is a self-hosted AI operating system tailored for environments requiring data sovereignty and privacy. It offers unique offline-first capabilities along with multi-framework support on consumer hardware."}]}}