Getting started with AI app development in 20 minutes

Introduction

This tutorial is designed to help you get started with AI application development using the DevOpser Flask AMI integrated with OpenAI, AWS Secrets Manager, and Redis. In about 20 minutes, you will learn how to launch an AI application on AWS, configure your environment securely, and run a Flask application that leverages the power of OpenAI.

Step 1: Subscribe to the AMI

1. Create an AWS account if you don't have one (a credit card is required).
2. Navigate to the AWS Marketplace and search for the DevOpser Flask AMI.
3. Click on "Continue to Subscribe" and accept the user agreements.
4. Confirm your subscription.

Step 2: Configure and Launch the EC2 Instance

1. Select the AWS region closest to your users to reduce latency. For example, choose North Virginia.
2. Click on "Continue to Launch" and then select "Launch through EC2."
3. In the EC2 launch template:
   • Name your instance (e.g., "OpenAI Flask").
   • Select the AMI you just subscribed to.
   • Choose an appropriate instance type:
     • T3 Micro for low traffic or testing.
     • Medium or larger instances for production use.
4. If you don’t have an SSH key pair, create one and store it securely (consider using a password manager like 1Password).
5. Select a security group that allows access on ports 80443, 8000, and 22 (limiting access to your IP address for security).
6. Launch the instance and wait for it to initialize.

Step 3: Setup AWS Secrets Manager

1. In your AWS console, search for "AWS Secrets Manager."
2. Click "Store a new secret."
   • Select "Other type of secret" and choose "Plaintext."
   • Enter your OpenAI API key without any additional formatting.
3. Name your secret (e.g., "OpenAI_API_Key") and note it down for later use.
4. Create another secret for Flask with a randomly generated string.
5. Ensure that both secrets are created in the same region as your EC2 instance.

Step 4: Connect to Your EC2 Instance

1. Obtain the public IP address of your EC2 instance.
2. Configure your SSH access:
   • Install the Visual Studio Code Remote SSH extension.
   • Edit your SSH config file to include:

     Host openAI_flask
         HostName <Your_Public_IP>
         User ec2-user
         IdentityFile /path/to/your/key.pem
     

3. Use the extension to connect to your EC2 instance.

Step 5: Configure Python Environment

1. Ensure Python 3.11 is installed on your EC2 instance (the AMI should have it).
2. Create a virtual environment:

   python3.11 -m venv venv
   

3. Activate the virtual environment:

   source venv/bin/activate
   

4. Install necessary packages:

   pip install -r requirements.txt
   

Step 6: Configure Environment Variables

1. Copy the example environment file to a new file (e.g., .env).
2. Replace the placeholders in the environment file with your secret names from AWS Secrets Manager:

   OPENAI_API_KEY=Your_Secret_Name
   FLASK_SECRET_KEY=Your_Flask_Secret_Name
   AWS_REGION=Your_AWS_Region
   

3. Save the file.

Step 7: Launch the Flask Application

1. Start the Flask application using Gunicorn:

   gunicorn run:app
   

2. Wait approximately 30 seconds for the application to initialize.
3. Verify the initialization by checking the logs for the OpenAI API key and Flask secret key.

Step 8: Test Your Application

1. Open your browser and navigate to the public IP address of your EC2 instance.
2. Interact with the application and confirm that it responds appropriately (e.g., try asking it to tell a story).

Conclusion

You have successfully launched an AI application using the DevOpser Flask AMI, configured AWS Secrets Manager for secure API key storage, and set up a Python virtual environment for development. As you progress, consider implementing further security measures and exploring advanced configurations for production environments. Happy coding!