Crafting Bespoke Output Formats with Gemini API
Abstract
The Gemini API unlocks potential for diverse applications but requires consistent output formatting. This report proposes a method using question phrasing and API calls to craft a bespoke output, enabling seamless integration with user applications. Examples include data categorization and obtaining multiple response options.
Introduction
With the release of the LLM model Gemini as an API on Vertex AI and Google AI Studio, a world of possibilities has opened up. Ref The Gemini API significantly expands the potential of various scripting languages and paves the way for diverse applications. However, leveraging the Gemini API smoothly requires consistent output formatting, which can be tricky due to its dependence on the specific question asked.