This lab is currently in Beta, content may be updated as we refine the material
LABINTERMEDIATE

Implement Guardrails System

Build production guardrails for AI safety including input validation, prompt injection detection, and output filtering.

60 minutes
ai-infrastructure/safety
Implement Guardrails System - Platform Engineering Hands-On Lab Icon

Lab Overview

🛠 Lab from the AI Platform Engineering Bootcamp. Used in Week 7. Bootcamp landing page: https://academy.tekanaid.com/bootcamps/ai-platform-engineering-bootcamp Parent course(s):

  • Week 7: AI Observability and LLMOps (slug: ai-observability-107)

🟡 Beta bootcamp lab. Hands-on instructions, check scripts, and solve scripts are in place. Lab is part of the running Platform Assistant capstone arc that grows across all 8 weeks of the bootcamp.

This hands-on lab teaches you to build production guardrails for AI safety.

You'll learn to:

  • Implement input validation guardrails for length and content
  • Create prompt injection detection patterns
  • Build output filtering for sensitive content
  • Test guardrails against attack patterns

What You'll Learn

Implement input validation guardrails for length and content

Create prompt injection detection patterns

Build output filtering for sensitive content

Test guardrails against attack patterns

Prerequisites

Python programming fundamentals

Understanding of LLM APIs

Basic security concepts

Technologies Covered

guardrailssecurityvalidationllmsafetypythonmlops

Part of a Course

This lab is part of the AI Safety and Guardrails course

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