This article details the creation of a support-ticket agent using Google's Gemini model, focusing on a minimal, framework-free implementation. The core of the agent is a simple loop that calls the Gemini API, checks if the model requests a tool execution, and either runs the tool and continues the loop or returns the model's final answer. The system prompt is structured with six essential components: identity, goal, tool definitions, policy constraints, uncertainty handling, and a clear 'done' signal. AI
IMPACT Provides a practical, code-level example of building an LLM-powered agent with minimal dependencies, useful for developers.
RANK_REASON The article describes the implementation of an AI agent using existing tools and models, rather than a novel release or research.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
