4 Commits

Author SHA1 Message Date
Cao Yi
6de207de88 [main][Docs] Fix typos across documentation (#6728)
## Summary

Fix typos and improve grammar consistency across 50 documentation files.
 
### Changes include:
- Spelling corrections (e.g., "Facotory" → "Factory", "certainty" →
"determinism")
- Grammar improvements (e.g., "multi-thread" → "multi-threaded",
"re-routed" → "re-run")
- Punctuation fixes (semicolon consistency in filter parameters)
- Code style fixes (correct flag name `--num-prompts` instead of
`--num-prompt`)
- Capitalization consistency (e.g., "python" → "Python", "ascend" →
"Ascend")
- vLLM version: v0.15.0
- vLLM main:
9562912cea

---------

Signed-off-by: SlightwindSec <slightwindsec@gmail.com>
2026-02-13 15:50:05 +08:00
SILONG ZENG
4811ba62e0 [Lint]Style: reformat markdown files via markdownlint (#5884)
### What this PR does / why we need it?
reformat markdown files via markdownlint

- vLLM version: v0.13.0
- vLLM main:
bde38c11df

---------

Signed-off-by: root <root@LAPTOP-VQKDDVMG.localdomain>
Signed-off-by: MrZ20 <2609716663@qq.com>
Co-authored-by: root <root@LAPTOP-VQKDDVMG.localdomain>
2026-01-15 09:06:01 +08:00
lty
295018ec0f [Refactor]Refactor of vllm_ascend/distributed module (#5719)
### What this PR does / why we need it?
Based on the RFC:https://github.com/vllm-project/vllm-ascend/issues/5604

This PR is a refactoring of vllm_ascend/distributed, moving all
kv_transfer realtaed codes into a dedicated folder, which has already
been done in vLLM

### Does this PR introduce _any_ user-facing change?
NA

### How was this patch tested?


- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

---------

Signed-off-by: lty <linhebiwen@gmail.com>
2026-01-15 08:57:40 +08:00
Tiger Xu / Zhonghu Xu
cb963c53a5 [Doc] Added deploying on k8s with kthena (#4674)
### What this PR does / why we need it?
[Kthena](https://github.com/volcano-sh/kthena) is a Kubernetes-native
LLM inference platform that transforms how organizations deploy and
manage Large Language Models in production. Built with declarative model
lifecycle management and intelligent request routing, it provides high
performance and enterprise-grade scalability for LLM inference
workloads.

The platform extends Kubernetes with purpose-built Custom Resource
Definitions (CRDs) for managing LLM workloads, supporting multiple
inference engines (vLLM, SGLang, Triton) and advanced serving patterns
like prefill-decode disaggregation.

This pr added a example on deloying llm on Ascend Kubernetes clusters.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: Zhonghu Xu <xuzhonghu@huawei.com>
2025-12-23 17:46:04 +08:00