Project overview
OpenViking is a context database for AI agents that unifies knowledge, memory, and skills. It organizes this content as a virtual filesystem that agents can browse, search, and read, while allowing users to inspect and edit what has been stored.
The project is written primarily in Python. The main project uses AGPLv3, while some components use other licenses. Consult the corresponding license files in the original repository for details.
Use cases
- Retaining user preferences and task experience across coding assistant sessions.
- Organizing project documents, code repositories, and web pages into searchable knowledge sources.
- Searching within a particular project or directory during research, then reading the relevant original material.
- Adding context management to an application through the Python, Go, or TypeScript SDK, or the HTTP API.
What it does and problems it solves
OpenViking places knowledge resources, user memories, and task skills in one directory structure, making it easier to inspect what an agent has stored and how that content is subsequently used.
Retrieval can be restricted to a project or memory subtree instead of searching the entire index each time. Content has three levels: a one-sentence abstract, an overview, and the full source. Agents can assess relevance before reading details. Committing a session can archive the conversation and extract Markdown memories that users can inspect, edit, and merge.
How to use
1. Start with a running OpenViking service. If you have not installed one, follow the next section. Users with an existing service can connect directly.
2. Run `ov status` in a terminal to check the service status. `ov` is the command-line tool included in the OpenViking package.
3. Follow the original repository's command-line example to import material with `ov add-resource`. The example includes a repository URL; obtain the corresponding address and complete usage instructions from the original repository below this page.
4. Record the returned `task_id`. Replace `TASK_ID` in `ov task status TASK_ID` with that value and repeat the check until the status is `completed`.
5. Try searching with `ov find "what is openviking"` and inspect the returned content identifiers. Follow the repository examples to browse directories with `ov ls` and `ov tree`, and find text within a specified directory with `ov grep`.
6. For cross-session memory, install the memory plugin using the repository's guide for your chosen tool and have the service address ready. If authentication is enabled, use a user key rather than a root key. Restart the agent after installation, ask it to remember a preference, and ask about that preference in a new session. Memories are processed in the background and may not be retrievable immediately after saving.
Installation
1. Before self-hosting, prepare uv, Python 3.10 or later, and a model provider offering an embedding model and a vision-language model. The former converts material into searchable representations; the latter interprets text and images. The supplied material does not explain how to install these prerequisites; consult the server configuration documentation in the original repository.
2. Run `uv tool install openviking --upgrade` in a terminal to install or update OpenViking.
3. Run `openviking-server init` and follow the setup wizard to configure the models. The wizard writes its configuration to `~/.openviking/ov.conf`. The README states that the service runs in the foreground, so keep that terminal open.
4. To install an agent memory plugin, obtain the installer entry point and complete command from the original repository below this page, then select the tools and service type when prompted. This installer requires macOS or Linux, Node.js 18 or later, and curl, without sudo. Windows users should consult the repository's beta desktop app entry. The desktop app lists support for macOS and Windows x64; complete installation steps are not included in the supplied material.
5. Before allowing devices beyond the local machine to access the service, configure authentication using the original repository's documentation. Consult its dedicated guides for production deployment, Docker deployment, and detailed integration steps for individual tools.
Source and usage notes
- Original repository: https://github.com/volcengine/OpenViking
- Source revision: 4ab22a4923452362b60aef2826c2083ce36168d2
This listing links to the upstream repository. It does not provide a verified download package, and the complete workflow has not been independently validated.
This description was organized and translated with AI from public upstream material. Refer to the original repository for capabilities, setup requirements, costs, and license terms. 
