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DeepSeek Harness (dsh) is an open-source agent harness from DeepSeek AI, built around a design in which major capabilities—including the model adapter, tools, session log, and agent loop—can be supplied as plugins. The project is in developer preview, so its official README warns: “DeepSeek Harness is in developer preview and iterating rapidly. THERE WILL BE COMPATIBILITY-BREAKING CHANGES.” The explanation below reflects the project’s official materials, not hands-on testing.
What is DeepSeek Harness?
DeepSeek Harness is software for assembling and running AI agents. It is powered by Cordis, and the project describes its approach as “everything is a plugin.” Rather than treating the model connection, tools, saved session history, and agent loop as fixed parts of one application, dsh makes them replaceable components. The project is open source; its official materials present it as usable through a desktop app or a web interface. DeepSeek Harness on GitHub
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That distinction matters: dsh is an agent framework and application, not a model in itself. The architecture provides ways to compose the pieces around an agent; it does not, by itself, establish which model or service a particular setup uses, what that service costs, or how its data is handled.
What does “everything is a plugin” mean?
The official architecture reference identifies four key plugin areas: the model adapter, tool registry, session log, and agent loop. In practical terms, these cover how the agent connects to a model, which tools it can use, how session activity is recorded, and how the agent proceeds through its work. The architecture is designed so these parts can be replaced through configuration. Official architecture reference
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A running instance combines a profile with an ordered set of bundles. Configuration patches can then change the resulting plugin tree. This gives users a way to assemble and adjust capabilities without assuming that every installation must use one unchangeable set of components. The details of what a particular configuration supports depend on its plugins and settings.
What does DeepSeek say you can do with it?
DeepSeek’s product page describes work including organizing files, analyzing data, drafting documents, creating slides, coding, research, background tasks, and building plugins. These are the developer’s stated use cases; the materials do not establish independent performance results for them. The page also links to desktop downloads for macOS Apple silicon and Windows 64-bit, alongside the web option. Check the official product page for current download availability, since preview packaging can change.
How do you start DeepSeek Harness?
The repository’s quick start calls for Node.js and documents launching the web interface with npx. For a local launch, the README says the interface starts at http://127.0.0.1:3080 by default and opens in a browser. These are the documented instructions, not independently tested steps. Official README and quick start
- Install Node.js if it is not already available.
- Run
npx @deepseek-ai/dsh web. - For the documented local launch, expect the web UI at
http://127.0.0.1:3080; the README says a browser opens automatically.
For a source-based setup, the README documents cloning the repository, installing packages with pnpm, building the project, and launching the web interface with pnpm dsh web. Follow the current README for the exact commands and any changes to prerequisites or setup. The project is evolving rapidly, so an instruction that worked for one version may not apply unchanged to another.
What should you know before relying on it?
Developer preview means dsh is still changing, and DeepSeek explicitly warns of compatibility-breaking changes. Treat plugins, configuration, APIs, and installation instructions as subject to change. If you plan to build an integration or depend on a particular setup, check the project documentation for the version you intend to use before committing to it.
The official materials summarized here do not establish full platform requirements, model or API costs, or detailed privacy and data-processing behavior. Do not infer those specifics from the plugin architecture or the quick-start commands; consult the relevant current documentation and service terms for your setup.
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