dsh-provider-hub
Run the following command in DeepSeek Harness:
dsh plugin install tappat225/dsh-provider-hub
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install tappat225/dsh-provider-hub in your terminal to install the plugin into DeepSeek Harness; the full source repository is https://github.com/tappat225/dsh-provider-hub . After installation, restart DSH and find the Provider Hub entry above the settings button on the left sidebar.
About this plugin
Every time a DSH user adds a new LLM gateway, they have to hand-edit llm-pi-ai.providers in settings.yaml, filling in protocol, endpoint, model list, and reasoning tiers, and a misconfiguration means a restart. With multiple gateways that YAML quickly turns into an entangled block of text. dsh-provider-hub lifts the entire workflow into the Provider Hub panel on the left sidebar: a card-style console where you add gateways one by one, expand a segmented editor covering basic fields, request headers, model table, and raw JSON, and save to hot-swap routes, no YAML required.
The panel ships a built-in catalog spanning GLM, Claude, GPT, Qwen, DeepSeek, Kimi, Gemini, and more. Typing a model name triggers prefix-aware autocomplete that carries contextWindow, maxTokens, input modality, and reasoning-effort parameters; a one-click discovery call fetches the full upstream /models list, or you can hand-write every parameter in the JSON view, with list and JSON staying bidirectionally in sync. Each gateway independently configures protocol, Base URL, a fully custom User-Agent, API key, and extra headers. For gateways that whitelist by UA, the plugin sends the exact UA you set on that gateway, bypassing the default DSH attribution header. The adapter classifies every upstream failure into a canonical code; transient errors are automatically retried with exponential backoff and jitter, while deterministic failures are reported as-is without wasting turns.
Built for DSH users who run two or more LLM gateways simultaneously, need per-gateway UA or header differentiation, and would rather not keep wrestling with provider YAML.
Use Cases
- Running multiple OpenAI / Anthropic-compatible gateways with per-gateway protocol, UA, key, and model catalog
- Gateways that whitelist by User-Agent require a fully custom UA per gateway to bypass the default attribution header
- Configuring model parameters and request headers through a card-style panel instead of hand-writing settings.yaml
Best For
- DSH users running two or more LLM gateways simultaneously
- Developers who need per-gateway UA or header differentiation
- Users who prefer panel-based configuration over repeated YAML edits
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