File system memory for artificial intelligence agents
Developed by Volcengine, OpenViking offers a self-improving context database for AI agents. This system combines agent memory, information retrieval (RAG) processes and abilities under a single roof.
Updates
- September 9, 2026: Stars 36,004 → 36,182, latest release v0.4.19 (September 8, 2026).
- September 8, 2026: Stars 34,651 → 36,004, latest release v0.4.18 (September 8, 2026).
- August 31, 2026: Stars 33,757 → 34,651, latest release v0.4.17.1 (August 31, 2026).
- August 27, 2026: Stars 31,462 → 33,757, latest release v0.4.16 (August 21, 2026).
What you get
- Organizes information hierarchically like a file system.
- It reduces the cost of artificial intelligence with layered loading.
- Makes agent history traceable and debuggable.
Installation
pip install openviking --upgrade
openviking-server init # interactive wizard: providers, models, ov.conf
openviking-server doctor # validate setup
openviking-server # start (background: nohup openviking-server > openviking.log 2>&1 &)Running it
pip install "openviking[bot]"
openviking-server --with-bot
ov chat # in another terminalIf you don't write code
Construct context management for an artificial intelligence agent using the OpenViking database. It structures the information via the viking:// protocol by separating the information into L0 summary, L1 overview and L2 detail layers. By placing the agent's memory, resources, and capabilities in this virtual file system, it allows it to navigate directories during interrogation and create long-term memory by learning from past sessions.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-08-18: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. This page was machine-translated from the Turkish original · the Turkish version prevails.