weaviate-bedrock-example

Congratulations, you have just created a Serverless "Hello World" application using the AWS Serverless Application Model (AWS SAM) for the python3.12 runtime, and options to bootstrap it with AWS Lambda Powertools for Python (Lambda Powertools) utilities for Logging, Tracing and Metrics.

Powertools is a developer toolkit to implement Serverless best practices and increase developer velocity.

Powertools features

Powertools provides three core utilities:

• Tracing - Decorators and utilities to trace Lambda function handlers, and both synchronous and asynchronous functions
• Logging - Structured logging made easier, and decorator to enrich structured logging with key Lambda context details
• Metrics - Custom Metrics created asynchronously via CloudWatch Embedded Metric Format (EMF)

Find the complete project's documentation here.

Installing AWS Lambda Powertools for Python

With pip installed, run:

pip install aws-lambda-powertools

Powertools Examples

• Tutorial
• Serverless Shopping cart
• Serverless Airline
• Serverless E-commerce platform
• Serverless GraphQL Nanny Booking Api

Working with this project

This project contains source code and supporting files for a serverless application that you can deploy with the SAM CLI. It includes the following files and folders.

• hello_world - Code for the application's Lambda function.
• events - Invocation events that you can use to invoke the function.
• tests - Unit tests for the application code.
• template.yaml - A template that defines the application's AWS resources.

The application uses several AWS resources, including Lambda functions and an API Gateway API. These resources are defined in the template.yaml file in this project. You can update the template to add AWS resources through the same deployment process that updates your application code.

If you prefer to use an integrated development environment (IDE) to build and test your application, you can use the AWS Toolkit.
The AWS Toolkit is an open source plug-in for popular IDEs that uses the SAM CLI to build and deploy serverless applications on AWS. The AWS Toolkit also adds a simplified step-through debugging experience for Lambda function code. See the following links to get started.

• CLion
• GoLand
• IntelliJ
• WebStorm
• Rider
• PhpStorm
• PyCharm
• RubyMine
• DataGrip
• VS Code
• Visual Studio

Deploy the sample application

The Serverless Application Model Command Line Interface (SAM CLI) is an extension of the AWS CLI that adds functionality for building and testing Lambda applications. It uses Docker to run your functions in an Amazon Linux environment that matches Lambda. It can also emulate your application's build environment and API.

To use the SAM CLI, you need the following tools.

• SAM CLI - Install the SAM CLI
• Python 3 installed
• Docker - Install Docker community edition

To build and deploy your application for the first time, run the following in your shell:

sam build --use-container
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 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.

Use the SAM CLI to build and test locally

Build your application with the sam build --use-container command.

weaviate-bedrock-example$ sam build --use-container

The SAM CLI installs dependencies defined in hello_world/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.

Test a single function by invoking it directly with a test event. An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.

Run functions locally and invoke them with the sam local invoke command.

weaviate-bedrock-example$ sam local invoke HelloWorldFunction --event events/event.json

The SAM CLI can also emulate your application's API. Use the sam local start-api to run the API locally on port 3000.

weaviate-bedrock-example$ sam local start-api
weaviate-bedrock-example$ curl http://localhost:3000/

The SAM CLI reads the application template to determine the API's routes and the functions that they invoke. The Events property on each function's definition includes the route and method for each path.

Events:
  HelloWorld:
    Type: Api
    Properties:
      Path: /hello
      Method: get

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.

weaviate-bedrock-example$ sam logs -n HelloWorldFunction --stack-name weaviate-bedrock-example --tail

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

Tests

Tests are defined in the tests folder in this project. Use PIP to install the test dependencies and run tests.

weaviate-bedrock-example$ pip install -r tests/requirements.txt --user
# unit test
weaviate-bedrock-example$ python -m pytest tests/unit -v
# integration test, requiring deploying the stack first.
# Create the env variable AWS_SAM_STACK_NAME with the name of the stack we are testing
weaviate-bedrock-example$ AWS_SAM_STACK_NAME="weaviate-bedrock-example" python -m pytest tests/integration -v

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 --stack-name "weaviate-bedrock-example"

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