volcengine/OpenViking
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
安装Install
dsh plugin --profile web add github:volcengine/OpenViking把 volcengine/OpenViking 加入你的 DSH 配置（web profile）即可启用。
READMEREADME
OpenViking: The Context Database for AI Agents
Website · Live Demo · GitHub · Issues · Docs
👋 Join our Community
📱 Lark Group · WeChat · Discord · X
What is OpenViking
OpenViking is an open-source context database for AI agents. It stores memories, resources, and skills as one virtual filesystem under the viking:// protocol, so an agent browses its own context with ls, tree, and find instead of querying a black-box vector store. Content is processed into three tiers — L0 abstract, L1 overview, L2 details — and loaded on demand. Every retrieval leaves a trajectory you can watch and debug. Full introduction: Getting started.
The OpenViking Studio playground — a live demo you can open in the browser, no installation required.
Why OpenViking
- One filesystem for all context. Memories, resources, and skills each get a
viking://URI. Agents locate and manipulate context deterministically, like a developer working with files. → Viking URI · Context types - Tiered loading cuts token spend. Every entry is processed into L0 (abstract), L1 (overview), and L2 (details) on write, then loaded only as deep as the task requires. → Context layers
- Directory recursive retrieval. Vector search first locates the highest-scoring directory, then drills down layer by layer, so results arrive with their surrounding context intact. → Retrieval
- Observable retrieval. Each query preserves its directory-browsing trajectory. When a result looks wrong, you can see exactly which path produced it. → Retrieval
- Sessions become memory. After a session commits, OpenViking asynchronously extracts user preferences and agent experience into long-term memory. → Session
How the pieces fit together: Architecture. The thinking behind the design: The Database Paradigm for Context Engineering.
viking://
├── resources/ # Resources: project docs, repos, web pages, etc.
│ └── my_project/
│ ├── docs/
│ │ ├── api/
│ │ └── tutorials/
│ └── src/
└── user/
└── {user_id}/
├── memories/
│ └── preferences/
│ ├── writing_style
│ └── coding_habits
├── resources/
│ └── private_project/
├── skills/
│ ├── search_code
│ └── analyze_data
└── peers/
└── web-visitor-alice/
The three loading tiers:
- L0 (Abstract): a one-sentence summary for quick relevance checks.
- L1 (Overview): core information and usage scenarios for planning.
- L2 (Details): the full original data, read only when needed.
Each directory carries its own L0/L1 layers, so relevance can be judged before any full file is read:
viking://resources/my_project/
├── .abstract # L0: ~100 tokens - quick relevance check
├── .overview # L1: ~2k tokens - structure and key points
└── docs/
├── .abstract
├── .overview
└── api/
├── auth.md # L2: full content, loaded on demand
└── endpoints.md
Proof it works
OpenViking 0.3.22 has been evaluated on long-conversation user memory (LoCoMo) and multi-turn agent tasks (tau2-bench). Full results and setup details, including knowledge-base QA, are in the benchmark report; reproduction scripts live in ./benchmark.
The memory evaluation used Doubao 2.0 Pro as the VLM and Doubao-embedding-vision-251215 as the embedding model.
- User memory (LoCoMo): with OpenViking, all three agent integrations land at 80–83% accuracy — up from 24–57% on their native memory — while input tokens drop by 34.3–91.0% and query latency by 58.45–66.10%.
- Agent experience (tau2-bench): experience memory lifts task success by +6.87pp (retail) and +11.87pp (airline) over the same LLM without memory.
Quick start
💡 Want to see it in action first? Try OpenViking Studio — a live hosted instance with a context playground, semantic search, and a multi-agent hub. No installation required.
Requires Python 3.10 or higher.
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 &)
init walks you through provider setup and writes ~/.openviking/ov.conf. It supports Volcengine, OpenAI, Codex OAuth, Kimi, GLM, and local Ollama — for Ollama it can detect and install the runtime and pull models suited to your hardware. doctor checks the config file, Python version, provider connectivity, and disk space without a running server. Manual ov.conf templates, per-provider examples, environment variables, and Windows setup: Configuration guide · Quick start docs.
The install already includes the ov client CLI. With the server running:
ov status
ov add-resource https://github.com/volcengine/OpenViking # --wait
ov ls viking://resources/
ov tree viking://resources/volcengine -L 2
# wait some time for semantic processing if not --wait
ov find "what is openviking"
ov grep "openviking" --uri viking://resources/volcengine/OpenViking/docs/en
Next steps:
- Client configuration (
ov config), standalone CLI installs (npm / cargo), and advanced usage such as index rebuilding: CLI setup - Docker and production deployment: Deployment guide
Use it with your agent
Integrations inject OpenViking recall into your agent's context and auto-commit session memory:
- Claude Code
- Codex
- OpenClaw
- Hermes
- Cursor
- TRAE / TRAE CN / TraeCode CLI 2.0
- OpenCode
- pi
- Agent Plugins 1.0
- MCP clients
- LangChain / LangGraph
Setup instructions for each agent: Agent integrations overview.
OpenViking Helper (Beta)
OpenViking Helper is a desktop console, currently in beta for macOS and Windows x64:
- Visual local agent setup: detects OpenViking CLI, Claude Code, Codex, Cursor, Trae, and OpenCode, then configures supported plugin, MCP, Hook, and CLI integrations.
- Session trace inspection: parses Claude Code, Codex, and Trae sessions to show OpenViking recall, prompt injection, MCP calls, capture, and commit events.
- Local memory and skill management: views local memory / rule files and
SKILL.mdskills, then syncs them to OpenViking.
Download:
VikingBot
VikingBot is an AI agent framework built on top of OpenViking:
pip install "openviking[bot]"
openviking-server --with-bot
ov chat # in another terminal
The official Docker image bundles VikingBot and starts it by default alongside the server and console UI. Details: VikingBot guide.
Deploy in production
For production, run OpenViking as a standalone HTTP service — see Server deployment and the Deployment guide.
Commercial editions
The open-source edition is not crippled. OpenViking in this repo is fully open source under AGPLv3: no feature gates, no account required, no activation key. Follow Deploy in production above and run it in production yourself — and that will stay true.
The two editions below answer "who operates it and where it runs", not "can I use it".
 ☁️ Managed SaaSOfficially hosted on Volcano Engine. Nothing to set up, nothing to operate.
Existing open-source users can move over with the migration tool. → Volcano Engine product page · Documentation Global hosting for regions outside China is coming to BytePlus. |
 🏢 Self-ManagedRuns inside your own environment. Data never leaves it.
Adds distributed deployment and official support on top of the open-source edition, activated by license key. |
Just want to run the open-source edition? Go ahead — you don't need to contact anyone. Head to Quick start.
Research
OpenViking open-sources a subset of the core capabilities described in the VikingMem paper:
VikingMem: A Memory Base Management System for Stateful LLM-based Applications Jiajie Fu, Junwen Chen, Mengzhao Wang, Aoxiang He, Maojia Sheng, Xiangyu Ke, Yifan Zhu, and Yunjun Gao. arXiv:2605.29640, 2026. Accepted by VLDB 2026. 📄 Read the paper on arXiv
Partner Projects
OpenViking welcomes collaboration with other open-source projects to build the context data ecosystem. Our confirmed partners include:
- deer-flow - Open-source long-horizon SuperAgent harness
- NoKV - AI native distributed file system
- loopx - Lightweight loop engineering state kernel
- Hermes Agent - The agent that grows with you
Interested in joining our partner list? Please submit an issue to our community to apply.
Community & contributing
OpenViking is still in its early stages, and there is plenty left to build.
- Docs: docs.openviking.ai · FAQ
- Blog: blog.openviking.ai
- Team: About us
- Chat: 📱 Lark Group · 💬 WeChat · 🎮 Discord · 🐦 X
- Contribute: bug fixes and new features are both welcome — see CONTRIBUTING.md
Security and privacy
This project takes security seriously. For vulnerability reporting and supported versions, see SECURITY.md
License
The OpenViking project uses different licenses for different components:
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