467c815db6
- Replace minimal label rules with a comprehensive keyword-based issue
labeler taxonomy.
- Add grouped labels for core features and advanced capabilities to
improve issue routing.
- Expand model-related matching for LLM, multimodal generation,
multimodal understanding, audio, and omni scenarios.
- Add/normalize regex patterns for common model families (DeepSeek,
Kimi, GLM, Qwen, 310p, etc.) to increase auto-label coverage and
consistency.
### What this PR does / why we need it?
- Expands `.github/issue-labeler.yml` from a minimal set of rules to a
richer keyword-based labeling configuration.
- Adds grouped label dimensions for:
- Core features (e.g., PD disaggregation, KV cache pool, ACLGraph, async
scheduler, CPU binding, quantization)
- Advanced features (e.g., long sequence, DPC/PCP, MTP/speculative
decode)
- Model categories (LLM, multimodal generation, multimodal
understanding, audio, omni, etc.)
- Specific model families (e.g., DeepSeek, Kimi, GLM, Qwen, 310p)
- Improves automatic issue triage accuracy and reduces manual label
maintenance effort.
- Makes issue categorization more consistent for maintainers and
contributors.
Why needed:
- Existing labeler rules were too limited and could not adequately cover
current feature/model issue distribution.
- Broader and more structured matching helps faster routing,
prioritization, and ownership assignment.
Fixes #N/A
### Does this PR introduce _any_ user-facing change?
- No runtime/API user-facing changes.
- This PR only updates GitHub issue automation rules.
### How was this patch tested?
- Performed static validation and review of `.github/issue-labeler.yml`
structure and regex entries.
- Verified that rule groups and label keys are correctly formatted for
GitHub issue labeler consumption.
- Confirmed that legacy minimal rules were replaced by expanded taxonomy
without syntax-breaking YAML changes.
- No unit/e2e tests were added because this is repository automation
configuration (GitHub labeling rules) rather than application runtime
logic.
- vLLM version: v0.17.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: drizzlezyk <drizzlezyk@163.com>
75 lines
1.8 KiB
YAML
75 lines
1.8 KiB
YAML
core-features:
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- '/((pd|(prefill[- ]?decode))\s+disaggregation|kv cache pool|aclgraph|async scheduler|cpu binding|quantization)/i'
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pd-disaggregation:
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- '/((pd|(prefill[- ]?decode))\s+disaggregation)/i'
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kv-cache-pool:
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- '/(kv cache pool)/i'
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aclgraph:
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- '/(aclgraph)/i'
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async-scheduler:
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- '/(async scheduler)/i'
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cpu-binding:
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- '/(cpu binding)/i'
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quantization:
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- '/(quantization)/i'
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advanced_features:
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- '/(long sequence|dpc|pcp|mtp|speculative decode)/i'
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long-seq:
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- '/(long sequence|dpc|pcp)/i'
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mtp/speculative-decode:
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- '/(mtp|speculative decode)/i'
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eplb:
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- '/(eplb)/i'
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llm-model:
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- '/(deepseek[- ]*(r1|v3(\.2)?)\S*|(kimi k2|kimik2|kimi-k2)(?!\.5)|glm5|qwen3-(?:235b|480b)\S*|Qwen3-(?:32B|8B|30B)\S*|qwen3 next|glm\s*4\.(?![^v\s]*v)\S*)/i'
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deepseek:
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- '/(deepseek[- ]*(r1|v3(\.2)?)\S*)/i'
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kimi-k2:
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- '/((kimi k2|kimik2|kimi-k2)(?!\.5))/i'
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kimi-k2.5:
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- '/((kimi k2\.5|kimik2\.5|kimi-k2\.5))/i'
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glm5:
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- '/(glm5)/i'
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qwen3-moe:
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- '/(Qwen3-(?:235B|480B)\S*)/i'
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qwen3-dense:
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- '/(Qwen3-(?:32B|8B|30B)\S*)/i'
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qwen3-next:
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- '/(qwen3-next)/i'
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glm-4:
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- '/(glm\s*4\.(?![^v\s]*v)\S*)/i'
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multi-modality-generate:
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- '/(seedance\S*|seedream\S*|wan\S*|hunyuan\S*|fLux\S*|kimi k2\.5|kimi-k2\.5|kimik2\.5|minimax\S*|qwen-image\S*)/i'
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seedance:
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- '/(seedance\S*)/i'
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seedream:
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- '/(seedream\S*)/i'
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wan:
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- '/(wan\S*)/i'
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hunyuan:
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- '/(hunyuan\S*)/i'
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fLux:
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- '/(fLux\S*)/i'
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qwen-image:
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- '/(qwen-image\S*)/i'
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minimax:
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- '/(minimax\S*)/i'
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multimodal_understanding:
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- '/(glm-?4\.\S*v\b|qwen3\.5\S*|deepseek-ocr\S*)/i'
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glm-4v:
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- '/(glm-?4\.\S*v\b)/i'
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qwen-3.5:
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- '/(qwen3\.5\S*)/i'
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deepseek-ocr:
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- '/(deepseek-ocr\S*)/i'
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audio-model:
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- '/(qwen3-tts\S*)/i'
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omni-model:
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- '/(qwen3-Omni\S*)/i'
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multimodal-unified-autoregress:
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- '/(hunyuan\S*|emu\S*)/i'
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paddle:
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- '/(paddle\S*)/i'
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310p:
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- '/(310p\S*)/i'
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