Merge pull request #562 from spencercjh/fix/docs-link-check-audit

fix(site): restore generated-site link checks

Author: hami-robot[bot]

.github/workflows/docs-health.yml

@@ -33,12 +33,9 @@ jobs:
         run: npm run format:check
 
       - name: Build Site
+        env:
+          DOCUSAURUS_SITE_URL: http://127.0.0.1:3000
         run: npm run build
 
       - name: Broken Internal Link Check
-        run: |
-          npx --yes linkinator ./build --recurse --skip "^https?://" --verbosity error 2>&1 | tee linkinator-output.txt
-          if grep -q "BROKEN" linkinator-output.txt; then
-            echo "::error::Broken internal links found"
-            exit 1
-          fi
+        run: bash scripts/check-links.sh

.gitignore

@@ -5,5 +5,6 @@ node_modules
 .hugo_build.lock
 .idea
 build
+.worktrees/
 .DS_Store
 changelog/source

blog/hami-at-kubecon-eu-2026/index.md

@@ -134,7 +134,7 @@ During the conference, the HAMi community will continue to curate and publish re
 Stay connected:
 
 - [HAMi GitHub Repository](https://github.com/Project-HAMi/HAMi)
-- [HAMi Community Website](https://project-hami.io)
+- [HAMi Community Website](/)
 
 If you'll be in Amsterdam, come find us at Project Pavilion.
 

blog/hami-cncf-incubating/index.md

@@ -16,7 +16,7 @@ Our sincere thanks to CNCF TOC Chair [Karena Angell](https://www.linkedin.com/fe
 
 HAMi is a heterogeneous compute virtualization and scheduling middleware for Kubernetes. Through container-level hard isolation, it finely partitions GPU memory and compute so that multiple workloads can safely share a single accelerator. Founded by maintainers [Xiao Zhang](https://github.com/wawa0210) and [Mengxuan Li](https://github.com/archlitchi), it is built by developers worldwide under CNCF governance.
 
-Today, HAMi is used by hundreds of organizations across a dozen-plus accelerators including NVIDIA, Ascend, Cambricon, Hygon, Moore Threads, Enflame, Kunlunxin, MetaX, AWS Neuron, and Vastai (see the [supported device list](https://project-hami.io/docs/userguide/device-supported)). [CNCF case studies](/case-studies) document production practices at China Merchants Bank, SNOW Corp., NIO, KE Holdings, DaoCloud, SF Technology, and PREP EDU, spanning finance, automotive, mobility, logistics, education, and cloud services. HAMi-core integrates with the Kubernetes default scheduler, [Volcano](https://github.com/volcano-sh/volcano/blob/master/docs/user-guide/how_to_use_gpu_sharing.md), [Kueue](https://github.com/kubernetes-sigs/kueue), [Koordinator](https://koordinator.sh/docs/user-manuals/device-scheduling-gpu-share-with-hami), and the [KAI Scheduler](/blog/hami-core-adopted-by-nvidia-kai-scheduler).
+Today, HAMi is used by hundreds of organizations across a dozen-plus accelerators including NVIDIA, Ascend, Cambricon, Hygon, Moore Threads, Enflame, Kunlunxin, MetaX, AWS Neuron, and Vastai (see the [supported device list](/docs/userguide/device-supported)). [CNCF case studies](/case-studies) document production practices at China Merchants Bank, SNOW Corp., NIO, KE Holdings, DaoCloud, SF Technology, and PREP EDU, spanning finance, automotive, mobility, logistics, education, and cloud services. HAMi-core integrates with the Kubernetes default scheduler, [Volcano](https://github.com/volcano-sh/volcano/blob/master/docs/user-guide/how_to_use_gpu_sharing.md), [Kueue](https://github.com/kubernetes-sigs/kueue), [Koordinator](https://koordinator.sh/docs/user-manuals/device-scheduling-gpu-share-with-hami), and the [KAI Scheduler](/blog/hami-core-adopted-by-nvidia-kai-scheduler).
 
 This milestone was made possible by a global community of nearly 500 contributors from dozens of countries. [Dynamia](https://www.dynamia.ai), [DaoCloud](https://www.daocloud.io), [4Paradigm](https://www.4paradigm.com), [NVIDIA](https://www.nvidia.com), and [Huawei Cloud](https://www.huawei.com), together with many individual developers, user enterprises, and ecosystem partners, have each made irreplaceable contributions.
 

blog/hami-core-adopted-by-nvidia-kai-scheduler/index.md

@@ -48,7 +48,7 @@ A simple way to understand HAMi's position:
 - **KAI Scheduler** decides "who uses which GPU, and when" (the scheduling layer).
 - **HAMi** ensures "once allocated, that is all you get, and you cannot take more" (the isolation layer).
 
-Only by combining the two do you get true production-grade GPU sharing. HAMi supports NVIDIA GPUs, Huawei Ascend NPUs, Cambricon MLUs, Hygon DCUs, Kunlun XPUs, and many other heterogeneous accelerators, making it the open source solution with the broadest coverage in cloud-native GPU virtualization. For the full list of supported accelerators, see the [HAMi documentation](https://project-hami.io/docs/userguide/device-supported).
+Only by combining the two do you get true production-grade GPU sharing. HAMi supports NVIDIA GPUs, Huawei Ascend NPUs, Cambricon MLUs, Hygon DCUs, Kunlun XPUs, and many other heterogeneous accelerators, making it the open source solution with the broadest coverage in cloud-native GPU virtualization. For the full list of supported accelerators, see the [HAMi documentation](/docs/userguide/device-supported).
 
 ## Integration architecture: how HAMi and KAI Scheduler work together
 

blog/hami-meetup-beijing-2025/index.md

@@ -3,7 +3,7 @@ title: "HAMi Meetup Beijing 2025 Recap"
 date: "2025-12-27"
 description: "HAMi Meetup Beijing was held on December 27, 2025. This article is available in Chinese only."
 authors: [hami_community]
-tags: ["Meetup"]
+tags: ["HAMi", "Meetup", "Heterogeneous Compute", "GPU Virtualization", "Cloud Native"]
 unlisted: true
 ---
 

blog/hami-meetup-shanghai-2025/index.md

@@ -3,7 +3,16 @@ title: "HAMi Meetup Shanghai 2025 Recap"
 date: "2025-11-30"
 description: "HAMi Meetup Shanghai was held on November 30, 2025. This article is available in Chinese only."
 authors: [hami_community]
-tags: ["Meetup"]
+tags:
+  [
+    "Meetup",
+    "Shanghai",
+    "Heterogeneous Compute Scheduling",
+    "GPU Virtualization",
+    "Kubernetes",
+    "Domestic Compute",
+    "AI Training and Inference Optimization",
+  ]
 unlisted: true
 ---
 

blog/hami-meetup-shenzhen-2026/index.md

@@ -3,7 +3,17 @@ title: "HAMi Meetup Shenzhen 2026 Recap"
 date: "2026-04-25"
 description: "HAMi Meetup Shenzhen was held on April 25, 2026. This article is available in Chinese only."
 authors: [hami_community]
-tags: ["Meetup"]
+tags:
+  [
+    "HAMi",
+    "Meetup",
+    "Shenzhen",
+    "GPU Virtualization",
+    "Heterogeneous Compute Scheduling",
+    "DRA",
+    "Cloud Native",
+    "AI Infrastructure",
+  ]
 unlisted: true
 ---
 

blog/hami-v2-9-0-release/index.md

@@ -206,7 +206,7 @@ helm repo update
 helm upgrade hami hami-charts/hami -n kube-system
 ```
 
-For complete installation documentation, refer to: [https://project-hami.io/docs/installation/online-installation](https://project-hami.io/docs/installation/online-installation)
+For complete installation documentation, refer to: [/docs/installation/online-installation](/docs/installation/online-installation)
 
 :::warning[Upgrade notes]
 
@@ -239,7 +239,7 @@ Since the v2.8.0 release, the HAMi website and documentation have undergone the
 
 Thanks to [@mesutoezdil](https://github.com/mesutoezdil) for contributions to optimizing HAMi official documentation.
 
-Website: [https://project-hami.io](https://project-hami.io)
+Website: [/](/)
 
 Website repository: [https://github.com/Project-HAMi/website](https://github.com/Project-HAMi/website)
 
@@ -266,6 +266,6 @@ We sincerely welcome more developers, users, and ecosystem partners to join the
 - GitHub Release: [https://github.com/Project-HAMi/HAMi/releases/tag/v2.9.0](https://github.com/Project-HAMi/HAMi/releases/tag/v2.9.0)
 - HAMi-DRA: [https://github.com/Project-HAMi/HAMi-DRA](https://github.com/Project-HAMi/HAMi-DRA)
 - Volcano vGPU Device Plugin: [https://github.com/Project-HAMi/volcano-vgpu-device-plugin](https://github.com/Project-HAMi/volcano-vgpu-device-plugin)
-- Documentation: [https://project-hami.io](https://project-hami.io)
+- Documentation: [/docs/](/docs/)
 - Community Discord (recommended): [https://discord.gg/Amhy7XmbNq](https://discord.gg/Amhy7XmbNq)
 - Community CNCF Slack: [https://cloud-native.slack.com/archives/C07T10BU4R2](https://cloud-native.slack.com/archives/C07T10BU4R2)

blog/kubecon-india-2026-recap/index.md

@@ -44,7 +44,7 @@ The demo illustrated how HAMi and vCluster together support practical multi-tena
 
 Throughout the Project Pavilion, visitors experienced two hands-on demonstrations highlighting real-world AI inference on Kubernetes.
 
-For readers who want to reproduce parts of the vLLM workflow, see the [HAMi vLLM lab](https://project-hami.io/tutorials/labs/hami-vllm).
+For readers who want to reproduce parts of the vLLM workflow, see the [HAMi vLLM lab](/tutorials/labs/hami-vllm).
 
 ### Demo 1: Production AI Inference with vLLM and SGLang