move one.demo.redhat.com info to a less visible location (#127)

* move one.demo.redhat.com info to a less visible location

* typos and wordlist update

.github/.wordlist.txt

@@ -23,9 +23,12 @@ bugfix
 CarImage
 cd
 centric
+cephfs
 Chase
+ChatGPT
 ChatOps
 Chris
+claimdb
 CLI
 cls
 CMD
@@ -49,6 +52,7 @@ dotenv
 drawio
 ds
 DS
+DSP
 dvh
 eCommerce
 elyra
@@ -68,6 +72,7 @@ formatter
 fromarray
 frontend
 Frontend
+GiB
 gitea
 Gitea
 GITEA
@@ -134,6 +139,7 @@ nav
 Nodejs
 npm
 oc
+ocs
 ods
 ojsonpath
 ok
@@ -143,17 +149,21 @@ OpenCV
 openshift
 OpenShift
 openShiftOAuth
+OpenSift
 opentlc
 OpenVINO
 patternfly
 Patternfly
 PatternFly
+PersistantStorageClaims
+PersistentVolumeClaim
 pipelineserver
 Pipfile
 pn
 png
 Podman
 podname
+Postgres
 PostgreSql
 Prasanth
 pre
@@ -162,6 +172,7 @@ productname
 proj
 proto
 PRs
+pvc
 py
 pytorch
 Pytorch
@@ -186,10 +197,13 @@ Roboflow
 RoboFlow
 rollout
 runtime
+RWX
 selfHeal
 Serverless
 src
 sso
+StorageClass
+storagecluster
 stylePaths
 stylesheet
 subfolder
@@ -228,4 +242,5 @@ YAML
 yolo
 YOLO
 yolov
+YOLOv
 YOLOV

README.md

@@ -104,3 +104,11 @@ done
 
 
 </details>
+
+
+
+<details>
+  <summary>Links for RH1 event environment assignment</summary>
+* URL for all labs: https://one.demo.redhat.com/[https://one.demo.redhat.com/,window=_blank]
+* Search for `insurance`
+</details>

content/modules/ROOT/pages/04-01-over-approach.adoc

@@ -4,7 +4,7 @@ include::_attributes.adoc[]
 As part of this prototype, we investigated the use of the YOLOv8 model.
 This model can be found online at https://www.yolov8.com[yolov8,window=_blank] and downloaded.
 
-We will first review its out-of-the-box capabilities. We will then fine-tune it to allow it to do more specialized work for us. Once we have a new, customized version of the model, we will deploy it in OpenSift AI Model Serving. Once that is done, we will send queries to it.
+We will first review its out-of-the-box capabilities. We will then fine-tune it to allow it to do more specialized work for us. Once we have a new, customized version of the model, we will deploy it in OpenShift AI Model Serving. Once that is done, we will send queries to it.
 
 Let's start by looking at a YOLOv8 model and explore how it works on static car images.
 

content/modules/ROOT/pages/05-05-process-claims.adoc

@@ -6,7 +6,7 @@ Now that we have the web app deployed, we need some way to process the claims in
 This pipeline is also a good starting point for creating an ArgoCD or Tekton pipeline which can be automatically triggered.
 
 == What's inside the pipeline?
-If you naviage to `lab-materials/05/05-05/` you can see a variety of files. +
+If you navigate to `lab-materials/05/05-05/` you can see a variety of files. +
 Just like before, we have both an Elyra version and a yaml version of the pipeline. This time, we will use the yaml file of the pipeline, which has been slightly customized to be able to run independently of Elyra. +
 Here are the main files of the pipeline and what they do:
 

content/modules/ROOT/pages/index.adoc

@@ -1,11 +1,6 @@
 = {lab_name}
 include::_attributes.adoc[]
 
-During RH1:
-
-* URL for all labs: https://one.demo.redhat.com/[https://one.demo.redhat.com/,window=_blank]
-* Search for `insurance`
-
 == Lab Overview
 
 This lab will illustrate how the use of various AI/ML technologies can be combined to produce a valuable solution to a business problem.