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fix(trtllm): forward served model name to native workers - #495

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ishandhanani merged 2 commits into
NVIDIA:mainfrom
SemiAnalysisAI:codex/upstream-trt-native-served-model
Sep 22, 2026
Merged

ishandhanani merged 2 commits into
NVIDIA:mainfrom
SemiAnalysisAI:codex/upstream-trt-native-served-model

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@adibarra

@adibarra adibarra commented Sep 22, 2026 •

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An explicit engine.served_model_name reaches benchmark/eval clients but is omitted from native trtllm-serve worker commands. With locally mounted weights, clients can request org/model while the server exposes /model.

Forward the existing field as --served_model_name for native workers. Unset values preserve the current command and server default. This uses the existing TRT-LLM backend and configuration field, adds explicit/unset command-generation coverage, and updates the existing example and reference text. No schema, model-loading, precision, or performance settings change.

将显式配置的服务模型名传给原生 TRT-LLM worker,确保服务器与 benchmark/eval 客户端使用一致的 API 模型名。

Signed-off-by: adibarra <93070681+adibarra@users.noreply.github.com>
按现有测试风格只验证模型名参数的传递和省略,去掉无关命令细节及重复路径断言,并简化示例注释。

Signed-off-by: adibarra <93070681+adibarra@users.noreply.github.com>
@adibarra
adibarra marked this pull request as ready for review September 22, 2026 20:08
@adibarra adibarra changed the title fix(trtllm): forward served model name to native workers / 向原生 worker 传递服务模型名 fix(trtllm): forward served model name to native workers Sep 22, 2026
@ishandhanani
ishandhanani merged commit 48a028f into NVIDIA:main Sep 22, 2026
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ishandhanani added a commit to SemiAnalysisAI/srt-slurm that referenced this pull request Sep 23, 2026
Signed-off-by: Ishan Dhanani <idhanani@nvidia.com>

NVIDIA#431 landed on main as the squash 2917b06, so the AMD runtime commit on this branch is now also in main; the merge keeps one copy and the diff against main is only the MoRI-IO layer. Also picks up the TRT-LLM served-model-name forward (NVIDIA#495) and its VRNVL72 NUMA default (NVIDIA#493). docs/schema-reference.md was the only conflict and is regenerated.
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2 participants