Learn how to build a GPT 4 enabled microservice using AWS lambda, OpenAI GPT4, and serverless express
Table of Contents
Introduction
Prerequisites
Understanding AWS CDK and its Benefits
Setting Up Your Development Environment
Building the AWS Lambda Function
Setting up Serverless Express
Integrating with OpenAI's GPT-4 Endpoint
Deploying with AWS CDK
Conclusion
1. Introduction to GPT and AWS CDK
Deploying applications and services to the cloud can often be a tedious process. Fortunately, the AWS Cloud Development Kit (AWS CDK) offers a high-level, declarative approach for defining cloud resources using familiar programming languages. In this guide, we will walk through building and deploying a GPT-4 endpoint using AWS CDK, AWS Lambda, Serverless Express, and OpenAI's GPT-4.
2. Prerequisites
An AWS account.
Familiarity with AWS services, particularly AWS Lambda and AWS CDK.
Node.js installed.
OpenAI API key for GPT-4 access.
3. Understanding AWS CDK and its Benefits
AWS CDK allows developers to define cloud resources in code and provision them using AWS CloudFormation. Here's why it stands out:
Flexibility: Craft resources using familiar programming languages.
Reusable Components: Develop and reuse high-level components.
Integrated with AWS: Seamless integration with AWS services and best practices.
From my own experience, transitioning to AWS CDK made cloud deployments smoother and more intuitive.
4. GPT 4 Chat Route Handler
Serverless Express allows you to run Express.js applications on AWS Lambda.
Below, an example route handler for a basic GPT request/response using the OpenAI SDK
5. Fetching OpenAI GPT API Key with Secret Manager
AWS Secrets Manager is used to securely retrieve and utilize secrets, specifically the OpenAI API key. This integration provides a higher level of security by ensuring the API key is never hard-coded or directly stored in the function. Let's break down the code and see how it all comes together.
8. Deploying GPT with AWS CDK
After building out the application, we need to deploy our application to AWS. Below, we'll create a stack that will create a CI/CD pipeline and deploy the AWS Lambda application.
9. Conclusion
Creating a robust and scalable GPT-4 endpoint on AWS has never been easier, thanks to tools like AWS CDK and Serverless Express. Not only have we automated the deployment process, but we've also built an endpoint that leverages the power of GPT-4 using the OpenAI API. Now, developers can seamlessly interact with GPT-4, expanding the horizons of what's possible in the realm of AI-driven applications.
If you're looking to deploy a GPT powered app without having to do this process manually, check out https://dev-kit.io/deploy