Run AgentX

Setup

Resolve the endpoint URL, served model name, matching tokenizer, and requested concurrency from the task. Reuse the model checkpoint. If serving is needed, follow deployment to download missing weights and launch it. Enable prefix caching, streaming usage, and cached-token reporting. For vLLM, use --enable-prefix-caching --enable-prompt-tokens-details. Verify the context limit fits the traces with the model's tokenizer; never silently truncate requests.

Start each benchmark campaign with the latest harness and compatible serving-stack releases unless the user requests specific versions. Record and pin the resolved harness and other code revisions, dataset/model/tokenizer revisions, serving framework (e.g. vLLM), and client/server dependencies or container digests in the run artifacts. Keep them fixed across sweep points, cache formats, and repeats unless they are the variable under test. Record local patches; treat upgrades as a new comparison baseline.