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Prompt-Optimization-LLM

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.

  • agent - code for the agent's action group's Lambda function, requirements and Dockerfile.
  • data - chat data used for the demonstraton
  • openapi_schema - OpenAPI Schema for Agent usage.
  • test - example user questions for demonstration
  • template.yaml - A template that defines the application's AWS resources.

The application uses several AWS resources, including Lambda functions and IAM roles/policies that are required to deploy an Amazon Bedrock Agent. 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.

After the deployment is complete please make sure to follow the instructions [https://docs.aws.amazon.com/bedrock/latest/userguide/agents-create.html] on AWS console to create the Bedrock Agent. Use the provided agent instruction (agent_instruction.txt) when creating the agent on the console.

Additionally it includes the "function_calling" folder containing code for using Anthropic Claude’s function calling capability via Amazon Bedrock.

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.

You may need the following for local testing.

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

sam build
sam validate
sam deploy --guided

The first command will build a docker image from a Dockerfile and then copy the source of your application inside the Docker image. 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.

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.

test

To test the agent with the prompt optiomization functionality, use the example user questions provided in the test folder.

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 "prompt-optimize"

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