Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP...
SAP AI Core is a service on SAP Business Technology Platform (BTP) that manages AI asset execution in a standardized, scalable, hyperscaler-agnostic manner. SAP AI Launchpad provides the management UI for AI runtimes including the Generative AI Hub.
| Capability | Description |
|---|---|
| Generative AI Hub | Access to LLMs from multiple providers with unified API |
| Orchestration | Modular pipeline for templating, filtering, grounding, masking |
| ML Training | Argo Workflows-based batch pipelines for model training |
| Inference Serving | Deploy models as HTTPS endpoints for predictions |
| Grounding/RAG | Vector database integration for contextual AI |
# Set environment variables from service key
export AI_API_URL="<your-ai-api-url>"
export AUTH_URL="<your-auth-url>"
export CLIENT_ID="<your-client-id>"
export CLIENT_SECRET="<your-client-secret>"
# Get OAuth token
AUTH_TOKEN=$(curl -s -X POST "$AUTH_URL/oauth/token" \
-H "Content-Type: application/x-www-form-urlencoded" \
-d "grant_type=client_credentials&client_id=$CLIENT_ID&client_secret=$CLIENT_SECRET" \
| jq -r '.access_token')
# Check for existing orchestration deployment
curl -X GET "$AI_API_URL/v2/lm/deployments" \
-H "Authorization: Bearer $AUTH_TOKEN" \
-H "AI-Resource-Group: default" \
-H "Content-Type: application/json"
# Create orchestration deployment if needed
curl -X POST "$AI_API_URL/v2/lm/deployments" \
-H "Authorization: Bearer $AUTH_TOKEN" \
-H "AI-Resource-Group: default" \
-H "Content-Type: application/json" \
-d '{
"configurationId": "<orchestration-config-id>"
}'
ORCHESTRATION_URL="<deployment-url>"
curl -X POST "$ORCHESTRATION_URL/v2/completion" \
-H "Authorization: Bearer $AUTH_TOKEN" \
-H "AI-Resource-Group: default" \
-H "Content-Type: application/json" \
-d '{
"config": {
"module_configurations": {
"llm_module_config": {
"model_name": "gpt-4o",
"model_version": "latest",
"model_params": {
"max_tokens": 1000,
"temperature": 0.7
}
},
"templating_module_config": {
"template": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "{{?user_query}}"}
]
}
}
},
"input_params": {
"user_query": "What is SAP AI Core?"
}
}'
| Plan | Cost | GenAI Hub | Support | Resource Groups |
|---|---|---|---|---|
| Free | Free | No | Community only | Default only |
| Standard | Per resource + baseline | No | Full SLA | Multiple |
| Extended | Per resource + tokens | Yes | Full SLA | Multiple |
Key Restrictions:
SAP AI Core provides access to models from six providers:
For detailed provider configurations and model lists, see references/model-providers.md.
The orchestration service provides unified access to multiple models through a modular pipeline with 8 execution stages:
For complete orchestration module configurations, examples, and advanced patterns, see references/orchestration-modules.md.
Azure Content Safety: Filters content across 4 categories (Hate, Violence, Sexual, SelfHarm) with severity levels 0-6. Azure OpenAI blocks severity 4+ automatically. Additional features include PromptShield and Protected Material detection.
Llama Guard 3: Covers 14 categories including violent crimes, privacy violations, and code interpreter abuse.
Two PII protection methods:
MASKED_ENTITY (non-reversible)MASKED_ENTITY_ID (reversible)Supported entities (25 total): Personal data, IDs, financial information, SAP-specific IDs, and sensitive attributes. For complete entity list and implementation details, see references/orchestration-modules.md.
Integrate external data from SharePoint, S3, SFTP, SAP Build Work Zone, and DMS. Supports PDF, HTML, DOCX, images, and more. Limit: 2,000 documents per pipeline with daily refresh. For detailed setup, see references/grounding-rag.md.
Enable LLMs to execute functions through a 5-step workflow: define tools → receive tool_calls → execute functions → return results → LLM incorporates responses. Templates available in templates/tool-definition.json.
Force model responses to match JSON schemas using strict validation. Useful for structured data extraction and API responses.
Generate semantic embeddings for RAG and similarity search via /v2/embeddings endpoint. Supports document, query, and text input types.
Uses Argo Workflows for training pipelines. Key requirements: create default object store secret, define workflow template, create configuration with parameters, and execute training. For complete workflow patterns, see references/ml-operations.md.
Deploy models via two-step process: create configuration (with model binding), then create deployment with TTL. Statuses: Pending → Running → Stopping → Stopped/Dead. Templates in templates/deployment-config.json.
Web-based UI with 4 key applications:
Required roles include genai_manager, genai_experimenter, prompt_manager, orchestration_executor, and mloperations_editor. For complete guide, see references/ai-launchpad-guide.md.
Key endpoints: /v2/lm/scenarios, /v2/lm/configurations, /v2/lm/deployments, /v2/lm/executions, /lm/meta. For complete API reference with examples, see references/api-reference.md.
Simple Chat: Basic model invocation with templating module
RAG with Grounding: Combine vector search with LLM for context-aware responses
Secure Enterprise Chat: Filtering + masking + grounding for PII protection
Templates available in templates/orchestration-workflow.json.
"masking_providers": [{
Common Issues:
default object store secretRequest quota increases via support ticket (Component: CA-ML-AIC).
references/orchestration-modules.md - All orchestration modules in detailreferences/generative-ai-hub.md - Complete GenAI hub documentationreferences/model-providers.md - Model providers and configurationsreferences/api-reference.md - Complete API endpoint referencereferences/grounding-rag.md - Grounding and RAG implementationreferences/ml-operations.md - ML operations and trainingreferences/advanced-features.md - Chat, applications, security, auditingreferences/ai-launchpad-guide.md - Complete SAP AI Launchpad UI guidetemplates/deployment-config.json - Deployment configuration templatetemplates/orchestration-workflow.json - Orchestration workflow templatetemplates/tool-definition.json - Tool calling definition template
