dsh-model-retry
Run the following command in DeepSeek Harness:
dsh plugin install 502399493zjw-lgtm/dsh-model-retry
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install 502399493zjw-lgtm/dsh-model-retry in a terminal to install the plugin; source code is published at https://github.com/502399493zjw-lgtm/dsh-model-retry — restart DSH Web after installation.
About this plugin
In DSH rc.8, model-retry policy was pushed down into individual provider profiles, so tuning how many times a request is retried meant digging through each provider config with no single entry point. dsh-model-retry adds one non-negative integer row to Settings → General and, with a single revision-fenced settings.mutate call, writes retryPolicy.maxRetries across all active configurable providers at once. Existing backoff and retryable-code fields are preserved, and always policies remain unlimited.
The plugin ships as a standalone external Cordis package and does not patch DSH core. Actual retry execution, backoff timing, and retryable-status-code logic are still owned by the DSH engine; the plugin only manages the shared retry-budget setting. It accepts finite non-negative integers including 0, and discovers the current normal/default policies through llm.providers before writing, so locked or removed entries are left untouched.
Best for developers working across multiple inference providers who want a unified retry budget without hand-editing each profile, or who prefer to adjust maxRetries in bulk during local mock testing and CI pipelines.
Screenshots
Use Cases
- Uniformly tune retry count across multiple inference providers
- Batch-update maxRetries in CI without editing each provider profile
- Quickly switch retry budget during local mock-driven testing
Best For
- Developers managing multiple inference provider configurations
- Engineers adjusting model retry parameters in bulk within CI/CD pipelines
- Users who prefer UI-driven settings over hand-editing provider profile JSON
Related Plugins
A unified suite combining hot runtime injection, task-aware thinking-mode routing, and a graded session protocol with red-team gates to sustain model diligence across long-horizon inference.
ModLens is a vision plugin for DeepSeek Harness that gives text-only models sight by reading images pasted directly into chat, with zero-config setup and multiple vision engines.
On-demand vision for text-only DeepSeek Harness agents: built-in free keyless vision chain and 14 vision tools, routing image turns as tool calls to vision models with pixel fidelity, no Python needed, one-command install.
Give text-only models in DeepSeek Harness eyes, enabling image Q&A, long-screenshot OCR, UI restoration, and GUI visual tasks.