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dsh-llm-gate

Model Inference Updated 2026.08.29

Run the following command in DeepSeek Harness:

dsh plugin install d3vmeh/dsh-llm-gate

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

Run dsh plugin install d3vmeh/dsh-llm-gate in your terminal to install the plugin; the project repository is available at https://github.com/d3vmeh/dsh-llm-gate .

About this plugin

Local LLM backends like llama-server often accept only one or two concurrent requests. When the main agent, a subagent, and a compaction job in DeepSeek Harness overlap, the surplus requests are silently parked by the server. The client cannot tell "waiting for a slot" from "dead", and the Node HTTP layer times out after 300 seconds with a terminated error, killing the entire turn. dsh-llm-gate intercepts those surplus requests inside dsh before any HTTP call is made: they sit in a FIFO queue with no timeout clock running, and are dispatched as soon as a slot frees up. You configure maxConcurrent, maxQueued, and queueTimeoutMs per provider, so an overfull queue fails fast with QUEUE_FULL or QUEUE_TIMEOUT instead of hanging forever. The plugin hooks into the llm/stream waterfall, so it covers every model request in the host—agents, subagents, compaction, and title generation—without any per-site code changes. It is built for developers who plug local or low-concurrency LLM providers into DeepSeek Harness and want to eliminate timeout cascades caused by concurrent overflow, without hand-rolling semaphores or retry loops in their own code.

Use Cases

  • Main agent and subagent hit a local llama-server simultaneously; the low-concurrency backend cannot absorb both, and the HTTP layer times out at 300 s.
  • A compaction job overlaps an active conversation; surplus model calls are silently parked by the server, indistinguishable from a dead connection.
  • Per-provider slots are tuned to the actual --parallel value; excess requests wait in an internal FIFO queue and dispatch automatically once a slot frees up.

Best For

  • Developers plugging local or low-concurrency LLM backends into DeepSeek Harness.
  • Users running llama.cpp or llama-server with a small --parallel value who want to eliminate overflow-induced timeouts.
  • Harness users who prefer a minimal-intrusion concurrency gate over hand-rolled semaphores or retry loops in application code.