AI Agents
EverOS
One portable, local-first memory layer for every AI agent - Markdown-native, user-owned and self-evolving.
★ 13.4k starsApache-2.0
View guide →A self-evolving context database unifying agent memory, RAG, and skills.
OpenViking is an open-source ai agents project by volcengine (volcengine/OpenViking on GitHub). It has 39,398 GitHub stars and 3,109 forks, is released under the AGPL-3.0 license, and was last updated on GitHub on 8 October 2026.
Start with one concrete task rather than a grand architecture.
Clone the repo and check the examples folder for a quickstart.
Install packages, set environment variables, and point it at your model.
Execute the demo workflow, then adapt it to your own data.
Memory, RAG, and skills in one database.
The store adapts as the agent operates.
Fits Python agent stacks.
dsh-plugin topic hints at harness integration.
Nearly 40k stars shortly after launch.
AGPL-3.0 - check the terms before SaaS use.
Download the source and move into the project folder.
git clone https://github.com/volcengine/OpenViking.git
cd OpenVikingCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pyvolcengine/OpenViking is its home on GitHub, with 3109 forks so far. The contributors tab and recent commits show how actively it is maintained.
It is AGPL-3.0 licensed: free to use, but if you run a modified version as a service you must share the source.
It depends on your setup - self-hosted storage can be free, while hosted tiers or embedding APIs may cost money. Check the README for options.
mem0 is a focused drop-in memory layer; OpenViking is a broader context database that also covers RAG and skills with a self-evolving design. Choose by scope: memory-only versus unified context.
Follow the README quickstart, then browse the examples directory for patterns that match what you want to build.
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