The practice of constraining LLM responses to a predefined format, schema, or template to ensure consistency, reliability, and integration into downstream automation workflows.
Core Techniques & Workflows
- Prompt Transformation: Converting “messy” or vague natural language inputs into clean, standardized, and consistent outputs.
- Automated Optimization: Utilizing a notebooklm and gemini workflow to automate the structural refinement of prompts, potentially reducing the need for manual prompt-engineering.
- New Workflow: NotebookLM + Gemini can optimize [[concepts/ai-templ
Multimodal Decision Services
- OpenAI Decisions API: A service designed to evaluate text and images to generate structured decisions for applications, expanding structured output beyond text-only contexts.
- Comparison with Jev: Evaluations compare OpenAI’s Decisions API against Jev, an open-source alternative, focusing on multimodal capabilities and cost efficiency.
- Analysis: See OpenAI Decisions API and Jev: Multimodal Decision-Making and Cost Comparison for detailed metrics on performance and pricing.