## Developing Hallucination Guardrails
A guardrail is a set of rules and checks designed to ensure that the outputs of an LLM are accurate, appropriate, and aligned with user expectations. For more additional information on developing guardrails, you can refer to this [guide on developing guardrails](https://cookbook.openai.com/examples/how_to_use_guardrails).
In this notebook, we'll walk through the process of developing an output guardrail that specifically checks model outputs for hallucinations.
This notebook will focus on:
1. Building out a strong eval set
2. Identifying specific criteria to measure hallucinations
3. Improving the accuracy of our guardrail with few-shot prompting