Large language models (LLMs) offer vast potential for interactive and educational applications, but ensuring their safe usage—especially when handling sensitive information—requires careful implementation of safeguards. Guardrails for Amazon Bedrock provides a powerful platform for controlling and refining the outputs of LLMs so that content stays appropriate, secure, and reliable. This makes it an ideal solution for creating restricted environments where language models can be used securely.
In this Cloud Lab, you’ll learn how to build a single-page application using Python3 that allows users to safely interact with LLMs by applying word and phrase filters. You will implement these safeguards using Amazon Bedrock Guardrails, ensuring inappropriate or harmful content is filtered before it reaches users. While the Cloud Lab focuses on applying basic word and phrase filters, you will also gain insight into extending this approach to incorporate more advanced techniques, such as topic denial, PII (personally identifiable information) protection, and more.
After completing this Cloud Lab, you’ll be well-equipped to create, configure, and manage Guardrails for Amazon Bedrock, IAM roles, and policies for LLM usage. You will deploy a secure, interactive website for users on an EC2 instance. Additionally, you’ll understand how to enhance these safeguards further, allowing you to build more sophisticated protection mechanisms as needed.
The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
