Re-added Tutorial App through PC->Apps. This fixes the issue where the Tutorial App is removed from the Onboarding project when Python Base is updated in AI Workbench.

.project/spec.yaml

@@ -23,8 +23,8 @@ layout:
 environment:
     base:
         registry: nvcr.io
-        image: nvidia/ai-workbench/python-basic:1.0.2
-        build_timestamp: "20241001182612"
+        image: nvidia/ai-workbench/python-basic:1.0.6
+        build_timestamp: "20250205043314"
         name: Python Basic
         supported_architectures: []
         cuda_version: ""
@@ -35,26 +35,6 @@ environment:
             - python3
             - jupyterlab
         apps:
-            - name: Tutorial
-              type: custom
-              class: webapp
-              start_command: |
-                cd /project/code/tutorial_app && \
-                export PROXY_PREFIX && \
-                streamlit run streamlit_app.py --server.baseUrlPath=$PROXY_PREFIX
-              health_check_command: curl -I http://localhost:8501
-              stop_command: |
-                pkill -f 'streamlit run streamlit_app.py'
-              user_msg: ""
-              logfile_path: ""
-              timeout_seconds: 30
-              icon_url: ""
-              webapp_options:
-                autolaunch: true
-                port: "8501"
-                proxy:
-                    trim_prefix: false
-                url: http://localhost:8501
             - name: jupyterlab
               type: jupyterlab
               class: webapp
@@ -74,7 +54,7 @@ environment:
         programming_languages:
             - python3
         icon_url: https://workbench.download.nvidia.com/static/img/ai-workbench-icon-rectangle.jpg
-        image_version: 1.0.5
+        image_version: 1.0.6
         os: linux
         os_distro: ubuntu
         os_distro_release: "22.04"
@@ -98,13 +78,32 @@ environment:
             - name: pip
               binary_path: /usr/bin/pip
               installed_packages:
-                - jupyterlab==4.2.4
+                - jupyterlab==4.2.5
         package_manager_environment:
             name: ""
             target: ""
     compose_file_path: ""
 execution:
-    apps: []
+    apps:
+        - name: Tutorial
+          type: custom
+          class: webapp
+          start_command: |
+            cd /project/code/tutorial_app && \
+                            export PROXY_PREFIX && \
+                            streamlit run streamlit_app.py --server.baseUrlPath=$PROXY_PREFIX
+          health_check_command: curl -I http://localhost:8501
+          stop_command: pkill -f 'streamlit run streamlit_app.py'
+          user_msg: ""
+          logfile_path: ""
+          timeout_seconds: 30
+          icon_url: ""
+          webapp_options:
+            autolaunch: true
+            port: "8501"
+            proxy:
+                trim_prefix: false
+            url: http://localhost:8501
     resources:
         gpu:
             requested: 0

code/tutorial_app/pages/basic_01.en_US.yaml

@@ -39,7 +39,7 @@ tasks:
     msg: |  
       ##### The Project Tab has a file browser to access, manage and edit files. 
 
-      * Click **File Browser** in the LHS menu.
+      * Click **File Browser** in the main menu bar on the left-side of **AI Workbench**.
       * Click **Create Folder**, and name it `my-first-folder`.
 
     response: |
@@ -60,7 +60,7 @@ tasks:
 
       > **Note:** On your local system, you could have done this in multiple ways without Workbench.     
       However, if the project were on a remote location, you would have had to transfer
-      the file via something like `scp`, or you could have used JupyterLab's file browser to upload the files.
+      the file through something like `scp`, or you could have used JupyterLab's file browser to upload the files.
 
     test: check_file_in_folder
 
@@ -76,10 +76,10 @@ tasks:
         * The `tutorial_app` folder. It has the code for this app.
         * The `example-file.txt` file.
         * The `delete-me.txt` file.      
-      * Click the option dots on the RHS of the `delete-me.txt` file and select `Delete`.
+      * Click the option dots on the right-side of the `delete-me.txt` file and select `Delete`.
 
     response: |
-      ##### Great. You deleted the `delete-me.txt` file.
+      ##### Awesome! You deleted the `delete-me.txt` file.
 
     test: check_file_deleted
 
@@ -90,11 +90,11 @@ tasks:
       For example, **Edit** lets you view and edit a text file without a full editor. It's not a 
       full-featured editor, but it's good for small edits.
 
-      * Click the option dots on the RHS of the `example-file.txt` file and select `Edit`.
+      * Click the option dots on the right-side of the `example-file.txt` file and select `Edit`.
       * A bare bones file editor will open. Add some text like `Hello, World!` and click **Save**.
 
     response: |
-      ##### Nice. You edited the file. 
+      ##### Congratulations!. You edited the file. 
 
       > **Note:** Again, you can do this multiple ways locally, but if the file were a remote location you would
       need to open up JupyterLab or jump through some hoops in a terminal.
@@ -106,7 +106,7 @@ tasks:
       ##### Workbench lets you manage packages without using the command line. 
 
       * Click **Environment > Project Container**
-      * Click **Packages** on the RHS to see installed packages. 
+      * Click **Packages** on the right-side menu to see installed packages. 
       * Click *Add* and select `apt`
       * Enter `jq` in the bar, click **Add** and then **Submit**
 
@@ -153,7 +153,10 @@ tasks:
       Seeing these differences on a file-by-file basis helps you decide whether to commit changes or stick with the current version of a file.
 
       * Go to **Git > Changes** to see the changes you made in this exercise.
-      * The left pane lists the files and the change type: `A` is *added*, `M` is *modified*, and `D` is *deleted*.
+      * The left pane lists the files and the change type: 
+         * `A` is *added*
+         * `M` is *modified*
+         * `D` is *deleted*
       * Clicking an individual file shows the line by line changes in the right pane.
       * You can resize the left and right panes by grabbing the divider between them and dragging it.
 

code/tutorial_app/pages/basic_02.en_US.yaml

@@ -68,7 +68,7 @@ tasks:
       ##### The most obvious way is the big green button that says **JupyterLab**. 
       However, let's do it the hard way to give you a more experience with the Status Bar.
 
-      * Click the `0 apps running` in the bottom RHS of the status bar.
+      * Click the `0 apps running` in the far right-side of the bottom status bar.
       * Click the toggle to start JupyterLab. It may take a second but will open in your browser.
 
       > **Note**: The Desktop App should be in the Project Tab  for `my-first-project`, **not** for `nvidia-ai-workbench-onboarding`.