bench: run one server at a time, match thinking mode, fix tools package

Refinements from end-to-end bring-up on the GPU host:

- Run each system start→suites→stop in sequence. Two BF16 8B models don't
  co-reside on one 32GB GPU, and a resident idle engine would distort the
  other's latency/throughput.
- Match generation mode: xserv hardcodes Qwen3 thinking off, so send
  chat_template_kwargs={enable_thinking:false} to llama.cpp via a per-endpoint
  extra_body. --enable-thinking opts back into thinking mode.
- Add tools/__init__.py so `python3 -m tools.bench.runner` resolves our package
  instead of a site-packages `tools` (nvfuser ships one that shadowed it).
- Document offline-GPU-host workflow, thinking-match, and the xserv 8192 OOM
  finding that the bench surfaced.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tools/bench/config.py

@@ -24,6 +24,12 @@ class SystemEndpoint:
     base_url: str                  # http://host:port  (OpenAI-compatible root, no /v1)
     model_id: str                  # what to put in the request body's "model" field
     api_key: str | None = None     # llama-server doesn't need one; xserv ignores it
+    # Extra fields merged into every request body for this system. Used to keep
+    # the two engines in the SAME generation mode — xserv hardcodes Qwen3
+    # thinking OFF (empty <think></think> in its prompt builder), so we disable
+    # thinking on llama-server via chat_template_kwargs to match. Both engines
+    # ignore unknown fields, so this is safe.
+    extra_body: dict | None = None
     # Process supervision is optional — if base_url is already serving, we skip launch.
     launch_cmd: list[str] | None = None
     launch_env: dict[str, str] = field(default_factory=dict)