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dsh-llm-api-pool

Client Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install bainianlaoyao/dsh-llm-api-pool

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

Run dsh plugin install bainianlaoyao/dsh-llm-api-pool in the DeepSeek Harness terminal to install this plugin; source code is available at https://github.com/bainianlaoyao/dsh-llm-api-pool .

About this plugin

Juggling several opencode go subscriptions by hand means constantly checking balances, swapping keys one at a time, and eating 429 errors at the worst possible moment. dsh-llm-api-pool collects multiple {baseUrl, apiKey} entries into a single pool, calls the official /usage endpoint to pull exact 5-hour, weekly, and monthly quota percentages with precise reset timestamps, and renders each key as a progress bar with a dollar conversion so the whole pool is visible at a glance.

Routing is driven entirely by official usage pressure: before every model request the plugin automatically selects the subscription with the largest remaining quota. When any key returns a 429, a 5xx error, or times out, it is cooled down for 60 seconds and the next key takes over with zero human intervention. On load the plugin also self-registers as a native DSH provider, making every probed model in the pool immediately selectable with a reasoning-effort picker, and it exposes an OpenAI-compatible endpoint so any SDK can simply point its baseURL at the pool and inherit load-balanced, failover-ready inference.

Built for developers holding multiple opencode go subscriptions who want to eliminate manual key rotation and balance anxiety, and for teams that need to unify several LLM endpoints under one load-balancing and failover layer inside the DSH ecosystem.

Use Cases

  • Managing multiple opencode go subscriptions without manual key rotation
  • Auto-routing requests to the key with the largest remaining quota under load
  • Pointing existing OpenAI SDKs at a pool endpoint for transparent failover

Best For

  • Solo developers juggling several LLM API keys
  • Engineering teams unifying multiple endpoints inside the DSH stack
  • Integrators who want an OpenAI-compatible facade over pooled subscriptions