Remove legacy Sphinx docs/ and finish the Mintlify cutover (#28964)
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@@ -17,7 +17,7 @@ Here we take the deployment of DeepSeek-R1 as an example.
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1. At least two Kubernetes nodes, each with two H20 systems and eight GPUs, are required.
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2. Make sure your K8S cluster has LWS correctly installed. If it hasn't been set up yet, please follow the [installation instructions](https://github.com/kubernetes-sigs/lws/blob/main/site/content/en/docs/installation/_index). **Note:** For LWS versions ≤0.5.x, you must use the Downward API to obtain `LWS_WORKER_INDEX`, as native support for this feature was introduced in v0.6.0.
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2. Make sure your K8S cluster has LWS correctly installed. If it hasn't been set up yet, please follow the [installation instructions](https://lws.sigs.k8s.io/docs/installation/). **Note:** For LWS versions ≤0.5.x, you must use the Downward API to obtain `LWS_WORKER_INDEX`, as native support for this feature was introduced in v0.6.0.
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## Basic example
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@@ -267,7 +267,7 @@ This should resolve most NCCL-related issues.
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#### RoCE scenario
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* Please make sure that RDMA devices are available in the cluster environment.
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* Please make sure that the nodes in the cluster have Mellanox NICs with RoCE. In this example, we use Mellanox ConnectX 5 model NICs, and the proper OFED driver has been installed. If not, please refer to the document [Install OFED Driver](https://docs.nvidia.com/networking/display/mlnxofedv461000/installing+mellanox+ofed) to install the driver.
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* Please make sure that the nodes in the cluster have Mellanox NICs with RoCE. In this example, we use Mellanox ConnectX 5 model NICs, and the proper OFED driver has been installed. If not, please refer to the document [Install OFED Driver](https://docs.nvidia.com/networking/display/mlnxofedv24102180lts/installing+the+driver) to install the driver.
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* Check your env:
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```shell Command
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@@ -1,14 +0,0 @@
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Multi-Node Deployment
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=====================
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.. toctree::
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:maxdepth: 1
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:caption: Multi-Node Deployment
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multi_node.md
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deploy_on_k8s.md
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lws_pd/lws_pd_deploy.md
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rbg_pd/deepseekv32_pd.md
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- `Deploying DeepSeek with PD Disaggregation and Large-Scale Expert Parallelism on 96 H100 GPUs <https://lmsys.org/blog/2025-05-05-large-scale-ep/>`_
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- `Deploying Kimi K2 with PD Disaggregation and Large-Scale Expert Parallelism on 128 H200 GPUs <https://lmsys.org/blog/2025-07-20-k2-large-scale-ep/>`_
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