SAP Cloud SDK for AI

Generative AI development on SAP BTP — LLM orchestration, prompt management, RAG.

Python SDK

from gen_ai_hub.orchestration import OrchestrationService

# Orchestration with templating and grounding
service = OrchestrationService(
    api_url="https://api.ai.core.prod.<region>.aws.cloud.sap/v2",
    client_id="...", client_secret="..."
)

# Define a prompt template
template = '''
System: You are an SAP procurement expert. Answer using only provided context.

Context: {{?grounding_context}}

User: {{?user_input}}
'''

result = service.invoke(
    template=template,
    grounding={"type": "document", "source": "sap-procurement-docs"},
    model={"name": "gpt-4"},
    input={"user_input": "How do I create a purchase order?"}
)
print(result.content)

Document Grounding

# Upload SAP documents for RAG
service.upload_document(
    name="sap-procurement-docs",
    content=open("procurement_guide.pdf", "rb"),
    metadata={"category": "SAP_MM", "language": "EN"}
)

# Query with grounding
response = service.query_with_grounding(
    question="What BAPI creates a purchase order?",
    document_names=["sap-procurement-docs"],
    top_k=3
)

Model Selection

Multi-Step Orchestration

# Chain: classify → route → generate → validate
orchestrator = OrchestrationService()

steps = [
    {"name": "classify", "template": classify_template, "model": "gpt-4o-mini"},
    {"name": "generate", "template": generate_template, "model": "gpt-4"},
    {"name": "validate", "template": validate_template, "model": "gpt-4o-mini"}
]

result = orchestrator.run_pipeline(steps=steps, input={"question": user_input})

Gotchas

• GenAI Hub requires AI Core entitlement on BTP subaccount
• Rate limits vary by model provider (OpenAI vs Anthropic vs Meta)
• Document grounding documents must be in supported format (PDF, TXT, MD)
• Always validate LLM output — hallucination risk with SAP technical content