Build an event-driven knowledge graph with machine-learning

August 6, 2024 ยท View on GitHub

This sample-code demonstrates how to build an event-driven knowledge graph with machine-learning using Amazon SageMaker and Amazon Neptune.

Start by deploying the architecture with CDK (see instructions below) then run through the steps in the sample Jupyter notebook by:

  • navigating to the Amazon SageMaker console
  • expanding the "Applications and IDEs" section on the left hand side.
  • Clicking notebook instances
  • Finding the notebook deployed by the CDK. It should start with workbenchgraphnotebookinstance. If you don't see any, check to ensure you are in the correct region and the CDK has finished deploying.
  • Clicking open JupyterLab
  • Running through build-an-event-driven-knowledge-graph-with-machine-learning.ipynb

Sample code notes

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources.

Pre-requisites

Before installing this sample, make sure you have following installed:

  1. AWS CLI
  2. Docker
  3. NodeJS
  4. AWS CDK v2
  5. Configure your AWS CLI
  6. Bootstrap AWS CDK in your target account

Bootstrap your account

This repo uses the AWS Cloud Development Kit (AWS CDK) v2. AWS CDK requires you to bootstrap your AWS account before deploying with CDK (see Bootstrapping in the AWS CDK documentation). Either follow the steps described in the manual our run make bootstrap-cdk to boostrap your AWS account.

Quick start

After completing the prerequisites clone this repo and run

cdk deploy --all

Cost and Cleanup

Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the AWS Pricing page for details.

For example, resources created by this sample include:

Delete resources created by the Jupyter notebooks by using the 'clean-up' section.

Run cdk destroy to clean-up all related resources in your account.

  • Verify that all resources have been removed by checking the AWS console. This ensures no resources are accidentally left running, which would lead to unexpected charges.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

Contributing

Refer to CONTRIBUTING for more details on how to contribute to this project.

Security

See CONTRIBUTING for more information.