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dsh-h-v1

Model Inference Updated 2026.09.15

Run the following command in DeepSeek Harness:

dsh plugin install marcosmmjr2023/dsh-h-v1

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install marcosmmjr2023/dsh-h-v1 in DeepSeek Harness to install this plugin; the full source is at https://github.com/marcosmmjr2023/dsh-h-v1 .

About this plugin

Running DeepSeek Harness on a single model provider day in, day out means two things: a monthly inference bill that keeps climbing, and a workflow that breaks the moment that provider hits rate limits, ships an API change, or pulls a free tier. FreeDSH, the community distribution layer on top of DeepSeek Harness, places FreeLLMAPI, OpenRouter :free, OpenCode free/zen and other configured free or low-cost providers ahead of any paid fallback, so routine calls stay at zero or near-zero cost.

The core capabilities orbit one goal: keep every workday moving. A task-aware router reads auto, eco, and ultra profiles to pick the right model tier for each workload; when a provider times out or goes dark, the router silently shifts to the next configured option without anyone watching terminal logs. Core updates are no longer overwrite-and-pray: a new kernel is validated in a parallel instance first, and local snapshots backed by git history make rollback a single command. An integrated status panel surface provider health, routing rules, recent files, and model controls directly inside the Harness UI, replacing the old habit of hunting through config files. The interface ships in Brazilian Portuguese, English, and Chinese, and interactive one-line installers cover both Windows and Linux.

FreeDSH fits two audiences. The first is developers already running DeepSeek Harness who want to cut their monthly inference costs without being chained to any single API. The second is users with a stable setup who only want to layer on smart routing, a status panel, and safe updates without touching core configuration; the DSH bundle install registers plugins only and never touches keys, providers, or existing settings. Licensed under MIT, the project explicitly respects every provider's terms of service and falls back to paid options when free tiers run out, putting reliability first.

Screenshots

Use Cases

  • Route daily inference calls through free providers first to cut monthly cost
  • Automatically fail over to a backup provider when one times out or drops
  • Validate core updates in a parallel instance before touching the live environment

Best For

  • Developers already running DeepSeek Harness who want to trim inference spend
  • Multi-provider users who refuse to be locked into a single API
  • Harness maintainers who need a safe update pipeline and practical rollback