Update send data scripts, installation instructions

1-Installation/README.md

@@ -36,20 +36,25 @@ your cluster management UI (for example, on console.redhat.com)
 ## ODH v2.x
 If the provided ODH version in your cluster's OperatorHub is version 2.x, use the following steps:
 
+### Prerequisties
+1) Install the community Authorino Operator. At the time of writing, Authorino 0.11.1 is verified to be compatible.
+
 ### Install ODH (ODH v2.x)
 1) Navigate to your `opendatahub` project
 2) From "Installed Operators", select "Open Data Hub Operator".
-3) Navigate to the "Data Science Cluster" tab and hit "Create DataScienceCluster"
-4) In the YAML view Make sure `trustyai` is set to `Managed`:
+3) Navigate to the "DSC Initialization" tab and hit "Create DSCInitialization", then install the default DSCI.
+4) Navigate to the "Data Science Cluster" tab and hit "Create DataScienceCluster"
+5) In the YAML view Make sure `trustyai` is set to `Managed`:
 ![ODH V2 YAML](images/odh_V2.png)
-5) Hit the "Create" button
-6) Within the "Pods" menu, you should begin to see various ODH components being created, including the `trustyai-service-operator-controller-manager-xxx`
+6) Hit the "Create" button
+7) Within the "Pods" menu, you should begin to see various ODH components being created, including the `trustyai-service-operator-controller-manager-xxx`
 
 ### Install TrustyAI (ODH v2.x)
 1) Navigate to your `model-namespace` project: `oc project model-namespace`
 2) Run `oc apply -f resources/trustyai_crd.yaml`. This will install the TrustyAI Service
 into your `model-namespace` project, which will then provide TrustyAI features to all subsequent models deployed into that project, such as explainability, fairness monitoring, and data drift monitoring, 
 
+# Legacy Installation Steps
 ## ODH v1.x (legacy)
 If the provided ODH version in your cluster's OperatorHub is version 1.x, use the following steps:
 ### Install ODH (ODH v1.x)

2-BiasMonitoring/README.md

@@ -25,7 +25,7 @@ use the following information about the applicant to make their prediction:
 * Length of Employment (in days)
 
 What we want to verify is that neither of our models are not biased over the gender field of `Is Male-Identifying?`. To do this,
-we will monitor our models with *Statistical Parity Difference (SPD)* metric, which will tell us how the difference betweem how often
+we will monitor our models with *Statistical Parity Difference (SPD)* metric, which will tell us how the difference between how often
 male-identifying and non-male-identifying applicants are given favorable predictions (i.e., they are predicted
 to pay back their loans). Ideally, the SPD value would be 0, indicating that both groups have equal likelihood of getting a good outcome. However, an SPD value between -0.1 and 0.1 is also indicative of reasonable fairness,
 indicating that the two groups' rates of getting good outcomes only varies by +/-10%.
@@ -38,7 +38,7 @@ an instance of the TrustyAI Service.
 
 > ✏️ TrustyAI endpoints are authenticated via a Bearer token. To obtain this token, run the following command:
 > ```shell
->export TOKEN=$(oc whoami -t)
+> export TOKEN=$(oc whoami -t)
 > ```
 
 ## Deploy Models

2-BiasMonitoring/scripts/send_data_batch

@@ -10,20 +10,21 @@ MODEL_ALPHA=demo-loan-nn-onnx-alpha
 MODEL_BETA=demo-loan-nn-onnx-beta
 
 ODHPROJECT=opendatahub
-MM_NAMESPACE=model-namespace
+MM_NAMESPACE=opendatahub-model
 
 oc project $MM_NAMESPACE 2>&1 1>/dev/null
 TRUSTY_POD=$(oc get pods -o name | grep trustyai-service)
+TRUSTY_ROUTE=https://$(oc get route/trustyai-service --template={{.spec.host}})
 
 INFER_ROUTE_ALPHA=$(oc get route demo-loan-nn-onnx-alpha --template={{.spec.host}}{{.spec.path}})
 INFER_ROUTE_BETA=$(oc get route demo-loan-nn-onnx-beta --template={{.spec.host}}{{.spec.path}})
 
-function curl_trustyai_token() {
-    TOKEN=$(oc create token user-one -n ${MM_NAMESPACE}) || eval "$FAILURE_HANDLING"
+TOKEN=$(oc whoami -t)
+
+function curl_token() {
     curl -s -H "Authorization: Bearer ${TOKEN}"  "$@"
 }
 
-
 function check_for_reception () {
   CHECKS=0
   THRESHOLD=${3:-950}
@@ -47,11 +48,11 @@ function check_for_reception () {
 }
 
 function get_counter () {
-  FILE_PRESENT=$(curl_trustyai_token $TRUSTY_ROUTE/info | grep $1 || echo '')
+  FILE_PRESENT=$(curl_token $TRUSTY_ROUTE/info | grep $1 || echo '')
   if [[ -z $FILE_PRESENT ]]; then
     echo 0
   else
-    echo $(curl_trustyai_token $TRUSTY_ROUTE/info | jq ".[].data | select(.modelId==\"$1\")" | jq .observations)
+    echo $(curl_token $TRUSTY_ROUTE/info | jq ".[].data | select(.modelId==\"$1\")" | jq .observations)
   fi
 }
 
@@ -76,12 +77,12 @@ while [ "$SUCCESS_ALPHA" != true ] || [ "$SUCCESS_BETA" != true ]; do
   fi
 
   if [ "$SUCCESS_ALPHA" != true ]; then
-    curl_trustyai_token https://$INFER_ROUTE_ALPHA/infer -d @$1 > /dev/null 2>&1
+    curl_token https://$INFER_ROUTE_ALPHA/infer -d @$1 > /dev/null 2>&1
     ( check_for_reception $(( $(jq '.inputs[0].data | length' $1) + $START_OBS_ALPHA )) $MODEL_ALPHA; ) && SUCCESS_ALPHA=true
   fi;
 
   if [ "$SUCCESS_BETA" != true ]; then
-    curl_trustyai_token https://$INFER_ROUTE_BETA/infer -d @$1 > /dev/null 2>&1
+    curl_token https://$INFER_ROUTE_BETA/infer -d @$1 > /dev/null 2>&1
     ( check_for_reception $(( $(jq '.inputs[0].data | length' $1) + $START_OBS_BETA )) $MODEL_BETA; ) && SUCCESS_BETA=true
   fi;