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Rose22 Debuts Openlumara A Lean Ai Agent For Life Organization

Translucent geometric AI assistant core of intricate nodes and lines forming a faceted crystalline sphere.

OpenLumara is a new open-source AI agent framework built from the ground up in Python, designed to run locally and keep token counts low. It serves as a private, modular assistant that you can talk to through a web interface, command line, or chat apps like Telegram and Discord. The system prompt can be trimmed down to just 4,000 tokens, making it ideal for users who want to avoid wasting tokens on cloud APIs or on limited local hardware.

Rose22 created OpenLumara as a personal tool for life management, tracking todos, notes, and routines and later shared it with the community. Parts of the codebase were written by hand, while other sections were AI-generated and then manually reviewed and edited. The developer specifically notes that the framework helps people with executive dysfunction, such as ADHD or autism, by organizing daily tasks.

Local-first design with swappable modules

Key features at a glance
  • Connects to any OpenAI-compatible local or cloud API.
  • Fully self-hosted and private if you choose.
  • Toggle any module on or off at will.
  • Scheduler for setting timed tasks and reminders.
  • Sandboxed shell in a Docker container for safety.
  • Switch between AI models on the fly.
  • Optional character system replaces other chat apps.
  • Memory system saves important details in messagepack format.

If you run local AI models on your own hardware and want an agent that won’t eat up your context window, OpenLumara fits neatly into that workflow. People managing daily tasks, notes, or morning routines will find the built-in scheduling and memory features especially helpful. It’s also a solid pick for anyone who values keeping conversations and data completely off the cloud.

Hand-coded core with AI-assisted polish

Rose22 stresses that the core framework was written by hand, with AI used only for suggestions and bug fixes after the fact. A plugin downloading system is planned for a future update, which will make it even easier to expand. The project is not based on any existing agent framework, including OpenClaw, and instead strips everything down to the bare essentials for speed and low token use.

"The system prompt can be extremely small, as little as around 4000 tokens with normal use." — Source: GitHub