Feature/feres analysis

deployment/dev/.env.example

@@ -1,15 +1,20 @@
 # Versions
-EXAFLOW=1.1.0
-PLATFORM_BACKEND=9.3.0
-PLATFORM_UI=1.2.0
-MIP=9.1.0
+EXAFLOW=1.3.0
+PLATFORM_BACKEND=10.0.0_candidate
+PLATFORM_UI=2.0.0_candidate
+MIP=9.2.0
 
 # Toggle authentication
 AUTHENTICATION=0
 
 # Frontend base URL used for post-logout redirect.
 PLATFORM_UI_BASE_URL=http://localhost
 
+# JupyterLab (published on 127.0.0.1:8888 only).
+JUPYTER_TOKEN=dev
+# Keycloak access token for the notebook client; required when AUTHENTICATION=1.
+MIP_TOKEN=
+
 # External Keycloak
 KEYCLOAK_AUTH_URL=https://iam.ebrains.eu/auth/
 KEYCLOAK_REALM=MIP

deployment/dev/README.md

@@ -34,14 +34,17 @@
     ```
     ./start.sh
     ```
-    The script waits for `http://172.17.0.1:8080/services/data-models` and verifies 4 data models are loaded.
+    The script starts the MIP stack plus direct JupyterLab, then checks that the `dementia` data model is available.
 
-4. To test if the MIP stack is properly setup run the 'test.sh':
+    Open:
     ```
-    ./test.sh 
+    http://localhost
+    http://localhost:8888/lab/tree/workspace/examples/feres_analysis.ipynb?token=dev
     ```
-
-5. To stop the MIP stack run the 'stop.sh' script to stop all the containers:
+
+    JupyterLab uses the compose backend URL `http://platform-backend:8080/services` inside Docker. It is published on `127.0.0.1` only; change `JUPYTER_TOKEN` in `.env` if the host is shared. With `AUTHENTICATION=1`, set `MIP_TOKEN` in `.env` to a Keycloak access token so the notebook client can call the backend.
+
+4. To stop the MIP stack run the 'stop.sh' script to stop all the containers:
     ```
     ./stop.sh
     ```

deployment/dev/docker-compose.yml

@@ -160,7 +160,7 @@ services:
       ### Exaflow ###
       ALGORITHM_UPDATE_INTERVAL: 30     # seconds
       EXAFLOW_URL: http://exaflow_controller:5000
-      PLATFORM_UI_BASE_URL: "${PLATFORM_UI_BASE_URL}"
+      PLATFORM_UI_BASE_URL: "${PLATFORM_UI_BASE_URL:-http://localhost}"
       ### Keycloak (external) ###
       AUTHENTICATION: "${AUTHENTICATION}"
       KEYCLOAK_AUTH_URL: "${KEYCLOAK_AUTH_URL}"
@@ -185,6 +185,20 @@ services:
       - platform-backend
     restart: unless-stopped
 
+  mip_jupyter:
+    image: hbpmip/mip-jupyter:0.0.1_candidate
+    ports:
+      - "127.0.0.1:8888:8888"
+    environment:
+      PLATFORM_BACKEND_URL: http://platform-backend:8080/services
+      MIP_TOKEN: "${MIP_TOKEN:-}"
+      JUPYTER_TOKEN: "${JUPYTER_TOKEN:-dev}"
+      MIP_NOTEBOOK: workspace/examples/feres_analysis.ipynb
+      JUPYTER_ENABLE_LAB: "yes"
+    depends_on:
+      - platform-backend
+    restart: unless-stopped
+
 networks:
   default:
     ipam:

deployment/dev/start.sh

@@ -1,29 +1,20 @@
 #!/usr/bin/env bash
 set -euo pipefail
 
-set -a
-source ./.env
-set +a
-
 docker compose down -v
 docker compose up -d
 
 endpoint="http://172.17.0.1:8080/services/data-models"
-max_attempts=30
-
-for attempt in $(seq 1 "${max_attempts}"); do
+for _ in {1..30}; do
   response="$(curl -fsS --max-time 5 "${endpoint}" 2>/dev/null || true)"
-  if printf '%s' "${response}" | grep -q '"code"[[:space:]]*:[[:space:]]*"dementia_longitudinal"' \
-    && printf '%s' "${response}" | grep -q '"code"[[:space:]]*:[[:space:]]*"dementia"' \
-    && printf '%s' "${response}" | grep -q '"code"[[:space:]]*:[[:space:]]*"mentalhealth"' \
-    && printf '%s' "${response}" | grep -q '"code"[[:space:]]*:[[:space:]]*"tbi"'
-  then
-    echo "Data models check passed: expected codes are available."
-    echo "You can see the MIP at 172.17.0.1"
+  if printf "%s" "${response}" | grep -q "\"code\"[[:space:]]*:[[:space:]]*\"dementia\""; then
+    echo "Data model check passed: dementia is available."
+    echo "MIP UI: http://localhost"
+    echo "JupyterLab: http://localhost:8888/lab/tree/workspace/examples/feres_analysis.ipynb?token=<JUPYTER_TOKEN from .env, default dev>"
     exit 0
   fi
   sleep 2
 done
 
-echo "Error: expected data model codes were not found at ${endpoint}." >&2
+echo "Error: dementia data model was not found at ${endpoint}." >&2
 exit 1