upgrade-vllm

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Aktualisiert17. Juli 2026 um 20:24

Bump the pinned vLLM version in `pyproject.toml`, re-sync the upstream test plugin, and triage the breakages that the bump exposes. Use whenever a user asks to upgrade/bump/update vLLM, pull up the lower bound, or chase a specific upstream commit. Most failures after a bump are not in our code — they are upstream API churn (worker `load_model` wrappers, platform `is_*()` predicates, KV-cache layout flips, new constructor kwargs) that our `_enum = PlatformEnum.OOT` platform doesn't get the CPU/GPU short-circuits for.

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torch-spyre

torch-spyre/spyre-inference

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SKILL.md

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name	upgrade-vllm
description	Bump the pinned vLLM version in `pyproject.toml`, re-sync the upstream test plugin, and triage the breakages that the bump exposes. Use whenever a user asks to upgrade/bump/update vLLM, pull up the lower bound, or chase a specific upstream commit. Most failures after a bump are not in our code — they are upstream API churn (worker `load_model` wrappers, platform `is_*()` predicates, KV-cache layout flips, new constructor kwargs) that our `_enum = PlatformEnum.OOT` platform doesn't get the CPU/GPU short-circuits for.
argument-hint	<target-vllm-version e.g. 0.23.0>

Upgrade spyre-inference to vLLM $ARGUMENTS.

If $ARGUMENTS is empty, ask the user which target version before doing anything else.

Follow the complete procedure in docs/contributing/vllm-upgrade-procedure.md.

When you see {VERSION} in that document, replace it with $ARGUMENTS (the version provided by the user or requested from them).

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Bump the pinned `torch-spyre` git rev in `pyproject.toml` and update `spyre-rpms.lock` to match artifactory, binary-search to the latest commit that actually compiles against this host's `ibm-*` RPMs, clear the stale inductor cache, run a smoke test, and write a reviewer-ready PR description. Use whenever the user asks to "bump", "upgrade", "update", or "pull up" torch-spyre — typically after new `ibm-deeptools` / `ibm-flex` / `ibm-senlib` packages land that unblock previously-failing torch-spyre commits. Encodes that build failures are the expected signal that supporting libs need a matching bump, that the torchinductor cache must be wiped after the bump to avoid `TypeError: ...__init__() got an unexpected keyword argument ...` red herrings, and the curated PR-description shape (notable upstream PRs + bisect table + installed `ibm-*` RPM versions).

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Reconcile monthly labels (April2026, May2026, June2026, …) on the torch-spyre vLLM project board (project 2, view 7, repo torch-spyre/spyre-inference) at the end of each month. Use whenever the user asks to "clean up the board", "do the monthly label cleanup", "do the May/June/July cleanup", or otherwise refresh which monthly bucket each issue lives in. The skill enforces three rules — May-closed → MayYYYY, open MayYYYY → JuneYYYY swap, and Q2-relevant unlabeled issues → current month — while flagging anomalies for the user instead of guessing.

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debug-spyre

torch-spyre/spyre-inference

Debug numerical, compilation, or correctness failures anywhere the Spyre backend is involved — custom ops, attention, model runner, end-to-end vLLM runs. Use whenever a user reports failing Spyre tests, accuracy/tolerance mismatches against a CPU reference, torch.compile errors on `spyre` device, silent CPU fallbacks, or generally "something on Spyre is broken." Most bugs here are not in our code — they are torch-spyre op gaps or dtype/layout limitations, so debugging requires tracing into the torch-spyre site-packages, not just reading `spyre_inference/`. For attention-specific hints (cache-seeding, KV alignment, MHA/MQA, broadcast diagnosis), see `attention-notes.md` next to this file.

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