Task 3: Build a Serverless Backend

Time to complete	10 minutes
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Get help	Troubleshooting Lambda Functions

Overview

In this task, you will configure a serverless function using AWS Amplify and AWS Lambda. This function takes an input parameter i.e. ingredients to generate a prompt. It then sends this prompt to Amazon Bedrock via an HTTP POST request to the Claude 3 Sonnet model. The body of the request includes the prompt string within a messages array.

What you will accomplish

In this tutorial, you will:

• Add Amazon Bedrock as a data source

• Configure custom business logic handler code

Implementation

Step 1: Create a Lambda function for handling requests

1. Create a Lambda function

   On your local machine, navigate to the ai-recipe-generator/amplify/data folder, and create a file named bedrock.js.

   

2. Add the function code

   Then, update the file with the following code:

   export function request(ctx) {
       const { ingredients = [] } = ctx.args;
     
       // Construct the prompt with the provided ingredients
       const prompt = `Suggest a recipe idea using these ingredients: ${ingredients.join(", ")}.`;
     
       // Return the request configuration
       return {
         resourcePath: `/model/anthropic.claude-3-sonnet-20240229-v1:0/invoke`,
         method: "POST",
         params: {
           headers: {
             "Content-Type": "application/json",
           },
           body: JSON.stringify({
             anthropic_version: "bedrock-2023-05-31",
             max_tokens: 1000,
             messages: [
               {
                 role: "user",
                 content: [
                   {
                     type: "text",
                     text: `\n\nHuman: ${prompt}\n\nAssistant:`,
                   },
                 ],
               },
             ],
           }),
         },
       };
     }
     
     export function response(ctx) {
       // Parse the response body
       const parsedBody = JSON.parse(ctx.result.body);
       // Extract the text content from the response
       const res = {
         body: parsedBody.content[0].text,
       };
       // Return the response
       return res;
     }

   This code defines a request function that constructs the HTTP request to invoke the Claude 3 Sonnet foundation model in Amazon Bedrock. The response function parses the response and returns the generated recipe.

Step 2: Add Amazon Bedrock as a data source

• Update the backend file

  Update the amplify/backend.ts file with the following code. Then, save the file.

  import { defineBackend } from "@aws-amplify/backend";
  import { data } from "./data/resource";
  import { PolicyStatement } from "aws-cdk-lib/aws-iam";
  import { auth } from "./auth/resource";
  
  const backend = defineBackend({
    auth,
    data,
  });
  
  const bedrockDataSource = backend.data.resources.graphqlApi.addHttpDataSource(
    "bedrockDS",
    "https://bedrock-runtime.us-east-1.amazonaws.com",
    {
      authorizationConfig: {
        signingRegion: "us-east-1",
        signingServiceName: "bedrock",
      },
    }
  );
  
  bedrockDataSource.grantPrincipal.addToPrincipalPolicy(
    new PolicyStatement({
      resources: [
        "arn:aws:bedrock:us-east-1::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0",
      ],
      actions: ["bedrock:InvokeModel"],
      
    })
  );

  • The code adds an HTTP data source for Amazon Bedrock to your API and grant it permissions to invoke the Claude model.

  

Conclusion

You have defined a Lambda function using Amplify, and added Amazon Bedrock as an HTTP data source.