Prompt Templates and the Super Agent in h2oGPTe
- Agentic AI
- Enterprise h2oGPTe
This lesson shows how Enterprise h2oGPTe's centralized prompt library, a managed catalog of shareable templates, connects to a predictive model built earlier to identify at risk customers. It walks through editing a template's system prompt, testing the response, and collecting thumbs up or down feedback from users, then moves to a more advanced version where the Super Agent takes a user's natural language request, calls the model's scoring API, and returns a personalized response. It also covers multilingual support, showing the same retention prompt configured with language specific examples for English, Spanish, or Mandarin.
Key takeaways
- How Enterprise h2oGPTe's prompt library lets teams create, clone, and share prompt templates across an organization
- What a system prompt controls in a template: the AI's role, behavior, key decisions, and output format
- How the Super Agent connects a user's natural language request to a predictive model's scoring API and returns a tailored response
- Why thumbs up or down feedback on a template's response helps refine a prompt based on real user reactions
- How multilingual templates let the same prompt run with language specific examples for markets like Spanish or Mandarin
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