openbrain 0.1.0

A package to interact with generative AI and build specialized generative AI workflows

ai-infra

Simple project holding central infrastructure that is shared across projects. Other projects can learn dynamic names for these resources by querying the outputs of this stack.

To build and deploy run the following in your shell:

pipenv run build

Alternatively, you can run the following to build and deploy:

sam build 
sam deploy --guided

The first command will build the source of your application. The second command will package and deploy your application to AWS with the default samconfig.toml in the project. Alternatively, you can run sam deploy --guided to deploy with a series of prompts:

• Stack Name: The name of the stack to deploy to CloudFormation. This should be unique to your account and region, and a good starting point would be something matching your project name.
• AWS Region: The AWS region you want to deploy your app to.
• Confirm changes before deploy: If set to yes, any change sets will be shown to you before execution for manual review. If set to no, the AWS SAM CLI will automatically deploy application changes.
• Allow SAM CLI IAM role creation: Many AWS SAM templates, including this example, create AWS IAM roles required for the AWS Lambda function(s) included to access AWS services. By default, these are scoped down to minimum required permissions. To deploy an AWS CloudFormation stack which creates or modifies IAM roles, the CAPABILITY_IAM value for capabilities must be provided. If permission isn't provided through this prompt, to deploy this example you must explicitly pass --capabilities CAPABILITY_IAM to the sam deploy command.
• Save arguments to samconfig.toml: If set to yes, your choices will be saved to a configuration file inside the project, so that in the future you can just re-run sam deploy without parameters to deploy changes to your application.

You can find your API Gateway Endpoint URL in the output values displayed after deployment.

Add a resource to your application

The application template uses AWS Serverless Application Model (AWS SAM) to define application resources. AWS SAM is an extension of AWS CloudFormation with a simpler syntax for configuring common serverless application resources such as functions, triggers, and APIs. For resources not included in the SAM specification, you can use standard AWS CloudFormation resource types.

Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

ai-infra$ sam logs -n HelloWorldFunction --stack-name ai-infra --tail

You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.

Tests

Tests are defined alongside your lambda function code in the rust_app/src folder.

cargo test

Cleanup

To delete the sample application that you created, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:

sam delete

Resources

See the AWS SAM developer guide for an introduction to SAM specification, the SAM CLI, and serverless application concepts.

Next, you can use AWS Serverless Application Repository to deploy ready-to-use apps that go beyond hello world samples and learn how authors developed their applications: AWS Serverless Application Repository main page.

ai-infra