gh-secondsky-sap-skills-skills-sap-ai-core/references/ai-launchpad-guide.md

SAP AI Launchpad Complete Guide

Comprehensive reference for SAP AI Launchpad features and operations.

Documentation Source: https://github.com/SAP-docs/sap-artificial-intelligence/tree/main/docs/sap-ai-launchpad

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Table of Contents

1. Overview
2. Initial Setup
3. Workspaces and Connections
4. User Roles
5. Generative AI Hub
6. Prompt Editor
7. Orchestration Workflows
8. ML Operations
9. Configurations
10. Deployments
11. Executions and Runs
12. Schedules
13. Datasets and Artifacts
14. Model Comparison
15. Applications
16. Meta API and Custom Runtime Capabilities

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Overview

SAP AI Launchpad is a multitenant SaaS application on SAP BTP that provides:

• Management UI for AI runtimes (SAP AI Core)
• Generative AI Hub for prompt experimentation
• ML Operations for model lifecycle management
• Analytics and monitoring dashboards

Two User Types

Type	Description
AI Scenario Producer	Engineers developing and productizing AI scenarios
AI Scenario Consumer	Business analysts subscribing to and using AI scenarios

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Initial Setup

Prerequisites

1. SAP BTP enterprise account
2. Subaccount with Cloud Foundry enabled
3. SAP AI Launchpad subscription
4. SAP AI Core instance (for runtime connection)

Setup Steps

1. Create Subaccount with Cloud Foundry environment
2. Subscribe to SAP AI Launchpad in Service Marketplace
3. Create Service Instance of SAP AI Core (if needed)
4. Assign Role Collections to users
5. Add Connection to SAP AI Core runtime

Service Plans

Plan	Cost	Support	GenAI Hub
Free	Free	Community only, no SLA	No
Standard	Monthly fixed price	Full SAP support	Yes

Note: Free → Standard upgrade preserves data; downgrade not supported.

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Workspaces and Connections

Adding a Connection

1. Navigate to Administration → Connections
2. Click Add
3. Enter connection details:
   • Name
   • Service Key (from SAP AI Core)
4. Test connection
5. Save

Managing Connections

Operation	Description
Edit	Modify connection settings
Delete	Remove connection
Test	Verify connectivity
Set Default	Make primary connection

Assigning Connection to Workspace

1. Navigate to Workspaces
2. Select workspace
3. Click Assign Connection
4. Select connection from dropdown
5. Confirm

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User Roles

Administrative Roles

Role	Capabilities
ailaunchpad_admin	Full administrative access
ailaunchpad_connections_editor	Manage connections
ailaunchpad_aicore_admin	SAP AI Core integration management

ML Operations Roles

Role	Capabilities
ailaunchpad_mloperations_viewer	View ML operations
ailaunchpad_mloperations_editor	Full ML operations access

Generative AI Hub Roles

Role	Capabilities
genai_manager	Full GenAI hub access, save prompts
genai_experimenter	Prompt experimentation only
prompt_manager	Manage saved prompts
prompt_experimenter	Use saved prompts

Functions Explorer Roles

Role	Capabilities
ailaunchpad_functions_explorer_editor_v2	Edit functions explorer
ailaunchpad_functions_explorer_viewer_v2	View functions explorer

Note: Role names prompt_media_executor and orchestration_executor may be deprecated. Verify current role names in SAP documentation.

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Generative AI Hub

Access Path

Workspaces → Select workspace → Generative AI Hub

Features

Feature	Description
Prompt Editor	Interactive prompt testing
Model Library	Browse available models
Grounding Management	Manage document pipelines
Orchestration	Build workflow configurations
Chat	Direct model interaction
Saved Prompts	Prompt management

Model Library

View model specifications including:

• Capabilities (chat, embeddings, vision)
• Context window sizes
• Performance benchmarks
• Cost per token
• Deprecation dates

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Prompt Editor

Access

Generative AI Hub → Prompt Editor

Interface Elements

Element	Description
Name	Prompt identifier (manager roles only)
Collection	Organize prompts (manager roles only)
Messages	Configure message blocks with roles
Variables	Define input placeholders
Model Selection	Choose model and version
Parameters	Adjust model parameters
Metadata	Tags and notes (manager roles only)

Message Roles

• System: Instructions for the model
• User: User input
• Assistant: Previous assistant responses

Variable Syntax

Use {{variable_name}} for placeholders with definitions section.

Running Prompts

1. Configure messages and variables
2. Select model (optional - uses default)
3. Adjust parameters
4. Click Run
5. View response (streaming available)

Image Inputs

• Supported for select models (GPT-4o, Gemini, Llama Vision)
• Maximum 5MB across all inputs
• Requires prompt_media_executor role

Saving Prompts

• Click Save (manager roles only)
• Assign to collection
• Add tags and notes
• Version automatically managed

Prompt Types

Type	Description
Question Answering	Q&A interactions
Summarization	Extract key points
Inferencing	Sentiment, entity extraction
Transformations	Translation, format conversion
Expansions	Content generation

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Orchestration Workflows

Access

Generative AI Hub → Orchestration → Create

Workflow Modules

Order	Module	Required
1	Grounding	Optional
2	Templating	Mandatory
3	Input Translation	Optional
4	Data Masking	Optional
5	Input Filtering	Optional
6	Model Configuration	Mandatory
7	Output Filtering	Optional
8	Output Translation	Optional

Required Modules Explained:

• Templating: Constructs the actual prompt/messages sent to the LLM using input variables and context
• Model Configuration: Specifies which LLM model to use and its parameters (temperature, max_tokens, etc.)

Building Workflows

1. Click Create to start new workflow
2. Configure required modules (Templating, Model)
3. Enable optional modules via Edit
4. Configure each enabled module
5. Click Test to run workflow
6. Click Save to store configuration

JSON Upload

• Maximum file size: 200 KB
• Format: JSON with module_configurations
• Note: Workflows with images can be downloaded but not uploaded

Saving Workflows

• Save as configuration for reuse
• Assign name and description
• Link to deployments

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ML Operations

Access

Workspaces → Select workspace → ML Operations

Components

Component	Purpose
Configurations	Parameter and artifact settings
Executions	Training jobs
Deployments	Model serving
Schedules	Automated executions
Datasets	Training data
Models	Trained models
Result Sets	Inference outputs
Other Artifacts	Miscellaneous artifacts

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Configurations

Creating Configuration

1. Navigate to ML Operations → Configurations
2. Click Create
3. Enter details:
   • Name
   • Scenario
   • Executable
   • Parameters
   • Input artifacts
4. Save

Configuration Contents

Field	Description
Name	Configuration identifier
Scenario	AI scenario reference
Executable	Workflow or serving template
Parameter Bindings	Key-value parameters
Artifact Bindings	Input artifact references

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Deployments

Creating Deployment

1. Navigate to ML Operations → Deployments
2. Click Create
3. Select configuration
4. Set duration (optional TTL)
5. Click Create

Deployment Details

Field	Description
ID	Unique identifier
Status	Current state
URL	Inference endpoint
Configuration	Associated config
Created	Timestamp
Duration	TTL if set

Deployment Statuses

Status	Description	Actions
Pending	Starting	Stop
Running	Active	Stop
Stopping	Shutting down	Wait
Stopped	Inactive	Delete
Dead	Failed	Delete
Unknown	Initial	Delete

Operations

Operation	Description
View	See deployment details
View Logs	Access pipeline logs
Update	Change configuration
Stop	Halt deployment
Delete	Remove deployment

Bulk Operations

• Stop multiple deployments
• Delete multiple deployments (up to 100)

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Executions and Runs

Creating Execution

1. Navigate to ML Operations → Executions
2. Click Create
3. Select configuration
4. Click Create

Execution Statuses

Status	Description
Pending	Queued
Running	Executing
Completed	Finished successfully
Dead	Failed
Stopped	Manually stopped

Viewing Execution Details

• Parameters and artifacts
• Status and timing
• Logs from pipeline
• Output artifacts
• Metrics

Comparing Executions

1. Select multiple executions
2. Click Compare
3. View side-by-side:
   • Parameters
   • Metrics
   • Durations
4. Create charts for visualization

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Schedules

Creating Schedule

1. Navigate to ML Operations → Schedules
2. Click Create
3. Select configuration
4. Set cron expression
5. Define start/end dates
6. Save

Cron Expression Format

┌───────── minute (0-59)
│ ┌─────── hour (0-23)
│ │ ┌───── day of month (1-31)
│ │ │ ┌─── month (1-12)
│ │ │ │ ┌─ day of week (0-6)
│ │ │ │ │
* * * * *

Schedule Operations

Operation	Description
View	See schedule details
Edit	Modify schedule
Stop	Pause schedule
Resume	Restart schedule
Delete	Remove schedule

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Datasets and Artifacts

Dataset Registration

1. Navigate to ML Operations → Datasets
2. Click Register
3. Enter details:
   • Name
   • URL (ai://secret-name/path)
   • Scenario
   • Description
4. Save

Artifact Types

Type	Description
Dataset	Training/validation data
Model	Trained model
Result Set	Inference results
Other	Miscellaneous

Finding Artifacts

• Filter by scenario
• Search by name
• Sort by date
• View details

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Model Comparison

Comparing Models

1. Navigate to ML Operations → Models
2. Select multiple models
3. Click Compare
4. View:
   • Configuration differences
   • Metric comparisons
   • Performance charts

Creating Comparison Charts

1. Select metrics to compare
2. Choose chart type
3. Configure axes
4. Generate visualization

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Applications

Managing Applications

Access: Administration → Applications

Operations

Operation	Description
Create	Add new application
View	See application details
Edit	Modify settings
Delete	Remove application
Create Disclaimer	Add usage disclaimer

Chat Application

Create chat interfaces using deployed models:

1. Create application
2. Configure model deployment
3. Set disclaimer (optional)
4. Share application URL

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Meta API and Custom Runtime Capabilities

The Meta API identifies which capabilities apply to a given AI runtime, allowing SAP AI Launchpad to display only relevant features.

Purpose

Function	Description
Capability Management	Enable/disable capabilities based on AI use case
UI Streamlining	Hide unnecessary features to reduce confusion
API Decoupling	Reduce impact of backend API changes

Supported Capabilities

Capability	Description
userDeployments	Allows users to create custom deployments
userExecutions	Enables execution functionality
staticDeployments	System-managed deployments
timeToLiveDeployments	TTL-based deployment limits
bulkUpdates	Bulk operations support
executionSchedules	Scheduling functionality
analytics	Analytics dashboard

Metadata Refresh

• Automatic: Refreshed periodically on schedule
• On-demand: Users can trigger manual refresh
• Administration: SAP Runtime team manages active capabilities

Custom Runtime Usage

Custom runtimes can selectively implement only necessary capabilities, creating a tailored experience:

AI Runtime → Meta API Query → Capability List → Filtered UI

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Accessibility Features

SAP AI Launchpad provides:

• Keyboard navigation
• Screen reader support
• High contrast themes
• Accessible UI components

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Language Settings

Change interface language:

1. Navigate to user settings
2. Select language preference
3. Save changes

Supported languages vary by region and deployment.

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Documentation Links

• What is AI Launchpad: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/what-is-sap-ai-launchpad-760889a.md
• Initial Setup: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/initial-setup-5d8adb6.md
• Service Plans: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/service-plans-ec1717d.md
• ML Operations: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/ml-operations-df78271.md
• Generative AI Hub: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/generative-ai-hub-b0b935b.md
• Prompt Experimentation: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/prompt-experimentation-384cc0c.md
• Orchestration: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/build-your-orchestration-workflow-b7dc8b4.md
• Deployments: https://github.com/SAP-docs/sap-artificial-intelligence/blob/main/docs/sap-ai-launchpad/deployments-0543c2c.md