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README fix (#2171)
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health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/helm/README.md

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@@ -60,7 +60,9 @@ Healthy services will show:
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## Access the Frontend UI
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Check Ingress resource:
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### 1. Check the Ingress Resource
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Run the following command to view the ingress configuration:
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```bash
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kubectl get ingress -n multi-modal-patient-monitoring
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NAME HOSTS PATHS ADDRESS PORTS
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multi-modal-patient-monitoring multi-modal-patient-monitoring.local / xx.xx.xx.xx 80
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```
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### 2. If an IP Address Appears in ADDRESS
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Add an entry on your Linux host (replace <IP> with the one you found):
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Add the hostname mapping to your local machine:
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```bash
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echo "<IP> multi-modal-patient-monitoring.local" | sudo tee -a /etc/hosts
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```
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Replace <IP> with the value shown in the ADDRESS column.
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### 3. If the ADDRESS Field is Empty (Common in Minikube)
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Some local Kubernetes environments (such as Minikube) do not automatically populate the ingress IP.
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Retrieve the Minikube cluster IP:
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```bash
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minikube ip
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```
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Then map the hostname to the IP:
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```bash
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echo "$(minikube ip) multi-modal-patient-monitoring.local" | sudo tee -a /etc/hosts
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```
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Open your browser and go to:
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### 4. Enable Ingress in Minikube (if not already enabled)
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```bash
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minikube addons enable ingress
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```
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Wait a few moments for the ingress controller to start.
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### 5.Open the Application
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Open your browser and navigate to:
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```bash
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http://<host-or-ip>/
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```
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Example:
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```bash
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http://multi-modal-patient-monitoring.local/
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```
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If using Minikube, you may need to enable the ingress addon:
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```bash
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minikube addons enable ingress
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```
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This will open the Health AI Suite frontend dashboard.
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From here you can access:

health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/helm/multi_modal_patient_monitoring/templates/ai-ecg-deployment.yaml

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@@ -12,6 +12,20 @@ spec:
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labels:
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app: ai-ecg
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spec:
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initContainers:
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- name: wait-for-ecg-model
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image: busybox:1.36
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command:
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- sh
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- -c
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- >-
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until [ -f /models/ai-ecg/hubert_ecg_small_fp16.xml ]; do
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echo "Waiting for HuBERT-ECG model asset...";
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sleep 5;
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done
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volumeMounts:
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- name: models
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mountPath: /models
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containers:
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- name: ai-ecg
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image: "{{ .Values.aiEcg.image.repository }}/{{ .Values.aiEcg.image.name }}:{{ .Values.aiEcg.image.tag }}"
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envFrom:
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- configMapRef:
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name: device-config
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startupProbe:
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tcpSocket:
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port: 8000
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periodSeconds: 5
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failureThreshold: 24
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readinessProbe:
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httpGet:
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path: /health
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port: 8000
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initialDelaySeconds: 5
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periodSeconds: 5
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failureThreshold: 6
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livenessProbe:
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httpGet:
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path: /health
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port: 8000
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initialDelaySeconds: 15
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periodSeconds: 15
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failureThreshold: 3
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ports:
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- containerPort: 8000
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volumeMounts:

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