DeepSeek Harness plugin

dsh-plugin-llmtr

LLMTR AI gateway provider for the DeepSeek Harness LLM seam: 170+ chat models and Türkiye-hosted LLMs behind one OpenAI-compatible key

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Source facts

Repository
knowhycodata/dsh-plugin-llmtr
Latest update
Aug 15, 2026
Category
Models & Providers
GitHub stars
0
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

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GitHub: https://github.com/knowhycodata/dsh-plugin-llmtr
Plugin: dsh-plugin-llmtr
Author: knowhycodata

Check the source files

Read the README and other files from this plugin directory before installing.

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README.mdSource · read only
README language

dsh-plugin-llmtr

English | Türkçe

An LLMTR provider route for DeepSeek Harness (dsh).

LLMTR is an OpenAI-compatible AI gateway. One API key reaches 170+ chat models from OpenAI, Anthropic, Google, Qwen, Mistral, xAI and others — plus the models LLMTR runs on its own infrastructure in Türkiye, for deployments that need their prompts to stay in-country.

This plugin registers those models as the llmtr provider route on ctx.llm, so they appear in the harness model picker and can be selected per session, per agent, and per subagent like any other route.

Install

dsh plugin add dsh-plugin-llmtr

The package ships a bundle patch, so plugin add inserts the row for you. Then open Settings → Models, find the LLMTR card, paste a key from llmtr.com, and save. The key is stored in $DSH_HOME/.credentials.yaml; settings retain only its reference.

The model picker fills itself from the gateway's live listing — nothing to type, and models LLMTR adds later appear without an upgrade.

Without the plugin CLI

Add the row to your own cordis.yml or --patch overlay:

- insert:
    - id: llm-llmtr
      name: dsh-plugin-llmtr

and export the key instead of storing it:

export LLMTR_API_KEY=llmtr-...

Model ids

Model ids are the gateway's own, owner/model, and are sent verbatim:

openai/gpt-5.4          anthropic/claude-...      google/gemini-3.7-flash
qwen/qwen3-8-...        mistral/...               deepseek/deepseek-v4-...
llmtr/muse-glimmer-30b-tr   llmtr/trendyol-asure-12b   llmtr/gemma-4

Ids starting with llmtr/ are the ones LLMTR hosts in Türkiye; the picker labels them "Hosted in Türkiye on LLMTR infrastructure". Everything else is routed to its upstream provider and processed under that provider's own terms — the plugin does not claim otherwise for them.

Data residency

To offer only the in-country models, narrow the catalog scope:

llm-llmtr:
  catalogScope: turkey-hosted

The picker then lists nothing else, so a session cannot be started on a model whose prompts leave the country.

Configuration

Every field is optional and lives in the llm-llmtr section of $DSH_HOME/settings.yaml (or in the plugin row's config). Changes reach the next request without a restart; an in-flight stream keeps the values it started with.

FieldDefaultWhat it decides
apiKeyEnvLLMTR_API_KEYCredential reference resolved per request
baseURLhttps://llmtr.com/v1Endpoint; $LLMTR_BASE_URL from a trusted launch layer overrides the default
headers{}Extra request headers; authentication and attribution names always win
catalogScopechatchat, turkey-hosted, or all
catalogTtlMs900000How long a fetched listing is reused
models[]A pinned list; non-empty replaces the live listing entirely
modelOverrides{}Per-model corrections applied over the live listing
reasoningEfforts[]Effort ids the gateway accepts for your models
maxTokens32768Default per-request output cap
defaultContextWindow131072Capacity assumed for a model you have not sized
streamIdleTimeoutMs300000Idle ceiling while a stream read is outstanding
retryPolicyharness defaultProvider-owned retry policy

Context windows

The LLMTR listing publishes ids and operations, not capacities, so every model is sized at defaultContextWindow until you say otherwise. Correct the ones you actually use:

llm-llmtr:
  modelOverrides:
    openai/gpt-5.4:
      contextWindow: 400000
    llmtr/muse-glimmer-30b-tr:
      contextWindow: 32768
      maxTokens: 8192

Reasoning effort

Reasoning output works out of the box: the adapter reads both reasoning_content and reasoning deltas, so a reasoning model's thinking shows up in the transcript with no configuration.

Selecting an effort level is opt-in, because the gateway fans requests out to upstreams that reject reasoning_effort on non-reasoning models. Declare what your models accept and the harness offers exactly those:

llm-llmtr:
  reasoningEfforts: [low, medium, high]

With the list empty, no selector is shown and nothing reaches the wire. A request carrying an undeclared effort is refused by name rather than silently dropped.

Pinning a model list

A deployment that must fix exactly which models its users can reach replaces the listing instead of filtering it:

llm-llmtr:
  models:
    - id: llmtr/muse-glimmer-30b-tr
      name: Muse Glimmer 30B
      contextWindow: 32768
    - id: llmtr/trendyol-asure-12b

With models non-empty the gateway listing is never fetched.

Scope

  • Chat completions only. Requests go to /v1/chat/completions with streaming and usage reporting on. LLMTR's embeddings, image, video, rerank, and realtime models are listed by catalogScope: all but cannot be routed by this adapter, which is why chat is the default.
  • Text in, text out. Image content is refused before it is sent, naming the model, rather than being flattened away.
  • One attempt per call. Retries belong to the harness retry policy, so a failure is visible once rather than hidden inside the adapter.

Privacy

The plugin sends the harness's standard User-Agent, an x-llmtr-client header naming this package and version, and your API key. No session id, prompt text, file path, or user identifier is added to any header.

Development

npm install
npm test          # 80 unit tests, no network and no key required
npm run typecheck
npm run build

tests/mock-server.ts stands in for the gateway, so the suite runs offline.

License

[MIT](LICENSE). Portions derive from DeepSeek Harness — see [NOTICE](NOTICE).