Nitpicky items in the docs (#18)

* Nitpicky items in the docs Signed-off-by: Mike McKiernan <[email protected]> * Clarify registry reqs I tried to imitate the phrasing I found when I accessed the following address in an incognito window: https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.1-8b-instruct/tags This is the text: This page requires an active subscription to an NVIDIA AI Enterprise product Because the repository has a developer audience, I included the address for signing up. Signed-off-by: Mike McKiernan <[email protected]> --------- Signed-off-by: Mike McKiernan <[email protected]>
NVIDIA · Aug 5, 2024 · e707787 · e707787
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diff --git a/docs/install.md b/docs/install.md
@@ -1,3 +1,8 @@
+<!--
+  SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+  SPDX-License-Identifier: Apache-2.0
+-->
+
 # Installing NIM Operator for Kubernetes using Helm
 
 ### Pre-requisites

diff --git a/docs/nimcache.md b/docs/nimcache.md
@@ -1,22 +1,31 @@
-# Caching NIM models
-Follow these steps to cache NIM models into a persistent storage (PVC)
+<!--
+  SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+  SPDX-License-Identifier: Apache-2.0
+-->
 
-### Pre-requisites
+# Caching NIM Models
 
-* NVIDIA GPU Operator have to be installed
-* NVIDIA NIM Operator for K8s have to be installed
-* Access to following NGC repositories required
-  - nvcr.io/nvstaging/cloud-native
-  - nvcr.io/nvidian/nim-llm-dev
-* Local Path Provisioner for creating a Persistent Volume (PV)
+Follow these steps to cache NIM models in a persistent volume.
 
-### 1. Create a Namespace for running NIM services
+## Prerequisites
+
+* NVIDIA GPU Operator is installed.
+* NVIDIA NIM Operator is installed.
+* You must have an active subscription to an NVIDIA AI Enterprise product or be an NVIDIA Developer Program
+  [member](https://build.nvidia.com/explore/discover?integrate_nim=true&developer_enroll=true&self_hosted_api=true&signin=true).
+  Access to the containers and models for NVIDIA NIM microservices is restricted.
+
+* A persistent volume provisioner is installed.
+
+  The Local Path Provisioner from Rancher is acceptable for development on a single-node cluster.
+
+## 1. Create a Namespace for Running NIM Microservices
 
 ```sh
 kubectl create ns nim-service
 ```
 
-### 2. Create an Image Pull Secret for the NIM container
+### 2. Create an Image Pull Secret for the NIM Container
 
 Replace <ngc-cli-api-key> with your NGC CLI API key.
 
@@ -27,12 +36,13 @@ kubectl create secret -n nim-service docker-registry ngc-secret \
     --docker-password=<ngc-cli-api-key>
 ```
 
-### 3. Create the `NIMCache` instance with auto-selection of models enabled
+## 3. Create the NIM Cache Instance and Enable Model Auto-Detection
+
 Update the `NIMCache` custom resource (CR) with appropriate values for model selection.
 These include `model.precision`, `model.engine`, `model.qosProfile`, `model.gpu.product` and `model.gpu.ids`.
-With these, the NIM operator will extract supported profiles and use that for caching.
+With these, the NIM Operator can extract the supported profiles and use that for caching.
 
-Alternatively if `model.profiles` are specified, then that particular model profile will be downloaded.
+Alternatively, if you specify `model.profiles`, then the model puller downloads and caches that particular model profile.
 
 ```yaml
 apiVersion: apps.nvidia.com/v1alpha1
@@ -73,23 +83,26 @@ spec:
 kubectl create -f nimcache.yaml -n nim-service
 ```
 
-### 5. Verify the progress of NIM model caching
+### 5. Verify the Progress of NIM Model Caching
+
 Verify that the NIM Operator has initiated the caching job and track status via the CR.
 
 ```sh
 kubectl get nimcache -n nim-service -o wide
 ```
 
-```console
+```output
 NAME                             STATUS   PVC                                  AGE
 meta-llama3-8b-instruct   ready    meta-llama3-8b-instruct-pvc   2024-07-04T23:22:13Z
 ```
 
+Get the NIM cache so you can view the status:
+
 ```sh
 kubectl get nimcache -n nim-service -o yaml
 ```
 
-```console
+```output
 apiVersion: apps.nvidia.com/v1alpha1
 kind: NIMCache
 metadata:
@@ -164,4 +177,4 @@ status:
         tp: "2"
   pvc: meta-llama3-8b-instruct-pvc
   state: ready
-```
+```
diff --git a/docs/nimservice.md b/docs/nimservice.md
@@ -1,13 +1,17 @@
+<!--
+  SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+  SPDX-License-Identifier: Apache-2.0
+-->
+
 # Create a NIM Service
 
-### Pre-requisites
+## Prerequisites
 
-* Create a namespace e.g. `nim-service`
-* Create a `NIMCache` instance in the namespace `nim-service` following the guide [here](https://gitlab-master.nvidia.com/dl/container-dev/k8s-nim-operator/-/blob/51e9727929b16982a2dba6d7fccbd0474f566bf8/docs/nimcache.md).
+* A `NIMCache` instance in the namespace `nim-service`.
 
-### 1. Create the CR for NIMService
+## 1. Create the NIM Service Instance
 
-nimservice.yaml:
+Create a file, such as `nimservice.yaml`, with contents like the following example:
 
 ```yaml
 apiVersion: apps.nvidia.com/v1alpha1
@@ -39,42 +43,43 @@ spec:
       openaiPort: 8000
 ```
 
+Apply the manifest:
+
 ```sh
 kubectl create -f nimservice.yaml -n nim-service
 ```
 
-### 2. Check the status of NIMService deployment
+### 2. Check the Status of NIM Service Deployment
 
 ```sh
 kubectl get nimservice -n nim-service
 ```
 
-```console
-kubectl get nimservice -n nim-service
-NAME                             STATUS   AGE
-meta-llama3-8b-instruct-latest   ready    115m
+```output
+NAME                      STATUS   AGE
+meta-llama3-8b-instruct   Ready    115m
 ```
 
 ```sh
 kubectl get pods -n nim-service
 ```
 
-```console
-NAME                                              READY   STATUS      RESTARTS   AGE
-meta-llama3-8b-instruct-latest-db9d899fd-mfmq2    1/1     Running     0          108m
-meta-llama3-8b-instruct-latest-job-xktnk          0/1     Completed   0          4m38s
+```output
+NAME                                       READY   STATUS      RESTARTS   AGE
+meta-llama3-8b-instruct-db9d899fd-mfmq2    1/1     Running     0          108m
+meta-llama3-8b-instruct-job-xktnk          0/1     Completed   0          4m38s
 ```
 
-### 3. Verify with a sample pod
+### 3. Verify the Microservice is Running
 
-test-pod.yaml:
+Create a file, `verify-pod.yaml`, with contents like the following example:
 
 ```yaml
 ---
 apiVersion: v1
 kind: Pod
 metadata:
-  name: test-streaming-chat
+  name: verify-streaming-chat
 spec:
   containers:
     - name: curl
@@ -118,10 +123,14 @@ spec:
   restartPolicy: Never
 ```
 
+Apply the manifest:
+
 ```sh
 kubectl create -f test-pod.yaml -n nim-service
 ```
 
+Confirm the verification pod ran to completion:
+
 ```sh
 kubectl get pods -n nim-service
 ```
@@ -130,6 +139,6 @@ kubectl get pods -n nim-service
 NAME                                              READY   STATUS      RESTARTS   AGE
 meta-llama3-8b-instruct-latest-db9d899fd-mfmq2    1/1     Running     0          112m
 meta-llama3-8b-instruct-latest-job-xktnk          0/1     Completed   0          8m8s
-test-streaming-chat                               0/1     Completed   0          99m
+verify-streaming-chat                             0/1     Completed   0          99m
 ```