Add bounded LLM worker cancellation

[seyeong-han]

Summary

Add bounded cancellation for the existing process-isolated LLM worker protocol.

• Negotiate supports_cancel and pass monotonically increasing request IDs over JSONL.
• Deliver cancellation out of band through an inherited POSIX pipe, so stop() never waits behind the blocking request/response lock.
• Cooperatively call LLMSession::stop() once at the next decode boundary. Cancelled sessions are marked dirty and reset before reuse.
• If cooperative cancellation misses its grace period, terminate/kill/reap the worker, fail queued and future work, and report /health as unavailable. Model reload remains the supervisor's responsibility.
• Keep older and non-POSIX workers compatible; they do not advertise cancellation and use the bounded process-termination fallback.

Review guide:

1. Python transport and process lifecycle: examples/llm_server/python/worker_client.py.
2. Async cancellation, escalation, and health: examples/llm_server/python/session_runtime.py, serving_chat.py, and server.py.
3. Native request controller and dirty-on-cancel semantics: examples/llm_server/cpp/worker_loop.h.
4. MuseGlimmer custom-loop integration: examples/models/muse-glimmer/runtime/runners/muse_glimmer_worker.cpp.
5. The remaining changes are focused tests, documentation, and thread linkage for worker targets that include the shared controller.

Cancellation remains token-boundary cooperative: it cannot interrupt active prefill, vision preparation, or an in-progress backend invocation. The process fallback provides the bound in those cases.

Test plan

• pytest -q examples/llm_server/python/tests (229 passed, 6 skipped)
• Built and ran test_worker_loop and test_worker_prefill_plan (2/2 CTests passed)
• Built and linked the MLX muse_glimmer_worker, qwen3_5_moe_worker, and gemma4_31b_worker targets
• Ran the real loopback Uvicorn/socket disconnect test five consecutive times
• Ran exact-file Python, C++, CMake, and documentation linters

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/22070

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

✅ No Failures

As of commit ca6c74a with merge base cff6f4d ():
💚 Looks good so far! There are no failures yet. 💚

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.