How to Install DeepSeek Harness in 10 Minutes (And Point It at Any Model You Want)

DeepSeek Harness is a free, MIT-licensed developer-preview tool for running coding agents through a local web interface, but it includes no model, credentials, or default provider, so installation with `npx @deepseek-ai/dsh web` is only the first step and requires Node.js 22.19.0 or later on supported release lines. Users must connect an OpenAI-compatible provider such as DeepSeek’s API, a gateway, or local Ollama, configure a permanent provider ID, API key, endpoint, and model ID, and address common setup failures including occupied ports, invalid credentials, unavailable model indexes, and incorrect reasoning-format detection. The guide emphasizes that custom DeepSeek-compatible gateways may require explicitly setting the thinking format to DeepSeek and increasing manually declared model context windows from the 262,144-token default to V4’s 1,048,576-token capacity. It demonstrates the agent workflow with a small Python FizzBuzz bug, where the harness reads files, runs tests, makes a minimal fix, reruns the suite, and records all actions in append-only session logs that can be replayed or forked. Harness also supports a headless profile for scripts and CI, source installation for contributors, and a local Ollama option for private or offline work, though local models may be slower or weaker at tool use. While the software itself is free, API-backed usage incurs provider token charges, credentials are stored locally in plain text unless otherwise managed, code is sent to the selected endpoint, and users are advised to pin tested versions because the project warns of compatibility-breaking changes.

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