Unlocking Enterprise AI with SAP Generative AI Hub Prompt Templating

Prompt templating in SAP Generative AI Hub is a practice of designing prompts with reusable structures and parameterized elements to unlock context-aware, high-quality responses. The lifecycle of prompt templating includes five steps: design a template with placeholders, fill placeholders with runtime values, send the finalized prompt to the LLM, capture and return the model response. Key principles of effective prompt templating are parameterizing inputs, following instructional patterns, and planning for error handling. The SAP Generative AI Hub SDK in Python can be used to implement prompt templating.

Prompt templating in SAP Generative AI Hub is a practice that involves designing prompts with reusable structures and parameterized elements to unlock context-aware, high-quality responses. This method is particularly useful in enterprise AI, where scaling prompt engineering across various business scenarios requires more than just creativity—it necessitates structure, governance, and reusability.

The lifecycle of prompt templating can be summarized in five simple steps: design a template with placeholders, fill placeholders with runtime values, send the finalized prompt to the LLM, capture and return the model response. For instance, a template might include placeholders like {{customer_name}} and {{invoice_number}}, which are dynamically replaced with actual input values at runtime.

Key principles of effective prompt templating include parameterizing inputs, following instructional patterns, and planning for error handling. Parameterizing inputs involves identifying which parts of the prompt will change and making them variables. This ensures that the template remains flexible and adaptable to different scenarios without requiring extensive rewrites. Following instructional patterns means that the LLM performs best when instructions are clear, explicit, and structured. Providing examples can further guide the model’s behavior. Lastly, planning for error handling ensures that the template anticipates edge cases and provides fallback instructions when necessary.

The SAP Generative AI Hub SDK in Python can be used to implement prompt templating. Before starting, ensure you have access to SAP AI Core, the SAP Generative AI Hub SDK installed, and a registered LLM deployment available in your AI Core tenant. The steps involve importing orchestration models, defining a template for the task, picking the LLM, configuring orchestration, and running inference by passing dynamic inputs to get structured, predictable outputs from the model.

In conclusion, prompt templating in SAP Generative AI Hub offers a structured approach to scaling prompt engineering across enterprise scenarios, enhancing the quality and consistency of AI-generated responses.

Reference List:
[1] https://community.sap.com/t5/technology-blog-posts-by-sap/getting-started-with-prompt-templating-in-sap-generative-ai-hub-principles/ba-p/14192547