Build an LLM-Powered Prompt Router for Intent Classification

Background
Most real-world AI applications don't use a single, monolithic prompt. They use a collection of specialized prompts, each tuned for a different task—a coding assistant, a writing coach, a data analyst, and so on. The core challenge is determining which prompt to use based on the user's input. This process is called prompt routing, and it is one of the most practical and powerful patterns in production AI systems.

The naive approach involves writing one giant system prompt that attempts to handle every possible task. This often produces mediocre, generic results. A far better approach is to first detect the user's intent and then delegate the request to a focused 'expert' persona that is specifically designed for that task.

How It Works
Your system will implement a two-step process: Classify, then Respond. First, a lightweight, inexpensive LLM call classifies the user's intent. Second, the system uses that intent to select a highly specialized prompt and makes a second, more detailed LLM call to generate the final response.

github url:https://github.com/Satyanagapraveen/-LLM-Powered-Prompt-Router-for-Intent-Classification

Видео Build an LLM-Powered Prompt Router for Intent Classification канала Praveen Namburi