Configuring OpenAI, FastAPI as Layers for AWS Lambda

A Step-by-Step Guide to Seamlessly Integrate OpenAI APIs with AWS Lambda

Integrating OpenAI APIs with AWS Lambda can streamline your serverless AI applications, like Image Analysis, Automated replies and more. Here's a step-by-step guide to configuring OpenAI as a Lambda layer. These steps have been tested and verified for successful implementation

Step 1: Create an x86_64 EC2 Instance with Amazon Linux

To begin, set up an EC2 instance with the x86_64 architecture and Amazon Linux. This environment is required to compile dependencies compatible with AWS Lambda.

• Navigate to the AWS Management Console.

• Launch a new EC2 instance with the Amazon Linux AMI (Amazon Machine Image).

• Choose the x86_64 architecture for compatibility.

Step 2: Set Up AWS CLI in EC2

Once your EC2 instance is running, configure the AWS Command Line Interface (CLI):

1. Connect to your EC2 instance via SSH - https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/connect-linux-inst-ssh.html

2. Run the following command to install the AWS CLI:

    sudo yum install aws-cli -y
   

3. Configure your CLI environment variables. Refer to the AWS CLI documentation - https://docs.aws.amazon.com/cli/latest/reference/ec2/ for detailed instructions

Step 3: Create a Python Folder

Inside your EC2 instance, create a folder named python. This folder will serve as the root for your Lambda layer dependencies.

mkdir layer
cd layer
mkdir python

Step 4: Install OpenAI and Other Dependencies

Using the pip package manager, install the OpenAI library along with necessary dependencies. Run the following command:

pip install openai==0.28.1 fastapi[standard]==0.112.0 boto3 -t ./python --platform manylinux2014_x86_64 --only-binary=:all:

Notes:

• The --platform manylinux2014_x86_64 ensures compatibility with AWS Lambda’s runtime environment.

• The issue generally is with pydantic & pydantic-core versions, in this case, its - 2.10.4 & 2.27.2, respectively

• The -t ./python flag specifies the target directory for the installation

Step 5: Zip the Folder

Once the dependencies are installed, compress the python folder into a zip file.

zip -r python.zip ./python

This zip file will be uploaded as a Lambda layer.

Step 6: Upload to S3 and Configure Lambda

To make the layer accessible, upload the zip file to an S3 bucket and link it to your Lambda function:

1. Use the AWS CLI to upload the zip file:

    aws s3 cp python.zip s3://<your-s3-bucket-name>/
   

2. Navigate to the AWS Lambda Console.

3. Create a new Lambda layer or update an existing one.

4. Set the S3 path for the layer content, visible onces you click the zip file in s3.

5. Attach the layer to your Lambda function.