Update documentation for ADO project initialization (#84)

.azuredevops/initialise-project.yml

@@ -1,40 +1,50 @@
 trigger: none
 
 parameters:
-- name: adoProjectName
-  displayName: ADO project name
-  type: string
+  - name: adoProjectName
+    displayName: Azure DevOps ProjectName
+    type: string
 
-- name: repoName
-  displayName: Repo name
-  type: string
+  - name: repoName
+    displayName: New Project Repository Name
+    type: string
 
-- name: mlOpsProjectTemplateAdoProjectName
-  displayName: MLOps Project Template's ADO project name
-  type: string
-  # default: [good idea to put your default here]
+  #- name: mlOpsProjectTemplateAdoProjectName
+  #  displayName: MLOps Project Template's ADO project name
+  #  type: string
+  #  # default: [good idea to put your default here]
 
-- name: mlOpsProjectRepoName
-  displayName: MLOps Project Template's repo
-  type: string  
-  default: mlops-project-template
+  - name: mlOpsProjectRepoName
+    displayName: MLOps Project Template's repo
+    type: string
+    default: mlops-project-template
 
-- name: projectType
-  displayName: ML project type
-  type: string
-  default: classical
-  values:
-  - classical
-  - cv
-  - nlp
-  
-- name: mlopsVersion
-  displayName: MLOps version
-  type: string
-  default: aml-cli-v2
-  values:
-  - python-sdk
-  - aml-cli-v2
+  - name: projectType
+    displayName: ML Project Type
+    type: string
+    default: classical
+    values:
+      - classical
+      - cv
+      - nlp
+
+  - name: mlopsVersion
+    displayName: MLOps Interface
+    type: string
+    default: aml-cli-v2
+    values:
+      - aml-cli-v2
+      - python-sdk-v1
+      - python-sdk-v2
+      - rai-aml-cli-v2
+
+  - name: infrastructure_version
+    displayName: Infrastructure Provider
+    type: string
+    default: bicep
+    values:
+      - bicep
+      - terraform
 
 stages:
   - stage: InitialiseProject
@@ -45,7 +55,9 @@ stages:
         steps:
           - checkout: self
             persistCredentials: false
-          - checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
+          #- checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
+          #  persistCredentials: false
+          - checkout: git://${{ parameters.adoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
             persistCredentials: false
           - checkout: git://${{ parameters.adoProjectName }}/${{ parameters.repoName }}
             persistCredentials: true
@@ -53,20 +65,19 @@ stages:
           - task: Bash@3
             displayName: Run script to initialise your repo
             inputs:
-              targetType: 'filePath'
+              targetType: "filePath"
               filePath: mlops-v2/.azuredevops/scripts/initialise_repo.sh
               arguments: >
-                ${{ parameters.repoName }}
-                ${{ parameters.projectType }}
-                ${{ parameters.mlopsVersion }}
+                ${{ parameters.repoName }} ${{ parameters.projectType }} ${{ parameters.mlopsVersion }} ${{ parameters.infrastructure_version}}
+
 
           - task: Bash@3
             displayName: Run script to create pipelines in ADO
             inputs:
-              targetType: 'filePath'
+              targetType: "filePath"
               filePath: mlops-v2/.azuredevops/scripts/create_ado_pipelines.sh
               arguments: >
-                ${{ parameters.repoName }}
-                ${{ parameters.adoProjectName }}
+                ${{ parameters.repoName }} ${{ parameters.adoProjectName }}
+
             env:
               AZURE_DEVOPS_EXT_PAT: $(System.AccessToken)

.azuredevops/scripts/initialise_repo.sh

@@ -1,7 +1,8 @@
 repo_name=$1
 project_type=$2
 mlops_version=$3
-infrastructure_version=bicep #options: terraform / bicep 
+#infrastructure_version=bicep #options: terraform / bicep 
+infrastructure_version=$4 #options: terraform / bicep 
 
 git config --global user.email "hosted.agent@dev.azure.com"
 git config --global user.name "Azure Pipeline"

documentation/deployguides/deployguide_ado.md

@@ -184,18 +184,21 @@ This document will guide you through deploying the MLOps V2 project generator an
 
    ![image](./images/ado-parameters-sparepipeline.png)
 
-   - **ADO project name** : This is the name of the Azure DevOps project you created
-   - **Project repo name**: This is the name of the mlops-v2 accelerator project you imported from GitHub (Default is **mlops-v2** unless you changed it during import)
-   - **MLOps Project Template name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
-   - ML Project type: 
+   - **Azure DevOps Project Name** : This is the name of the Azure DevOps project you are running the pipeline from.
+   - **New Project Repository Name**: The name of your new project repository created in 3.5.1.
+   - **MLOps Project Template Repo Name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
+   - **ML Project type**:
      - Choose **classical** for a regression or classification project.
      - Choose **cv** for a computer vision project
      - Choose **nlp** for natural language  projects
-   - MLOps version
-     - choose **python-sdk** to use the python SDK for training and deployment of your model
-     - Choose **aml-cli-v2** to yse the cli tools for training and deployment of your model
-   - Infrastructure Version: 
-     - Choose **Bicep** to deploy using Azure ARM based templates
+   - **MLOps Interface**: Select the interface to the ML platform, either CLI or SDK.
+     - Choose **aml-cli-v2** for the Azure ML CLI v2 interface. This is supported for all ML project types.
+     - Choose **python-sdk-v1** to use the Azure ML python SDK v1 for training and deployment of your model. This is supported for Classical and CV project types.
+     - Choose **python-sdk-v1** to use the Azure ML python SDK v2 for training and deployment of your model. This is supported for Classical and NLP project types.
+     - Choose **rai-aml-cli-v2** to use the Responsible AI cli tools for training and deployment of your model. This is supported only for Classical project types at this time.
+
+   - **Infrastructure Provider**: Choose the provider to use to deploy Azure infrastructure for your project.
+     - Choose **Bicep** to deploy using Azure ARM-based templates
      - Choose **terraform** to use terraform based templates. 
 
    3.8.1 The first run of the pipeline will require you to grant access to the repositories you created. Click **View**