# Task 3: Build a Serverless Backend
<a name="module-three"></a>


|  |  | 
| --- |--- |
| **Time to complete** | 10 minutes  | 
| **Requires** | A text editor. Here are a few free ones: [See the AWS documentation website for more details](http://docs.aws.amazon.com/hands-on/latest/build-serverless-web-app-lambda-amplify-bedrock-cognito-gen-ai/module-three.html) | 
| **Get help** | [Troubleshooting Lambda Functions](https://docs.amplify.aws/react/build-a-backend/functions/)  | 

## Overview
<a name="overview"></a>

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
<a name="what-you-will-accomplish"></a>

In this tutorial, you will: 
+ Add Amazon Bedrock as a data source 
+ Configure custom business logic handler code 

## Implementation
<a name="implementation"></a>

### Step 1: Create a Lambda function for handling requests
<a name="create-a-lambda-function-for-handling-requests"></a>

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**.   
![A file directory for the ai-recipe-generator project, showing folders amplify, auth, data, and files such as resource.ts, backend.ts, package.json. The file bedrock.js is highlighted in the data folder.](http://docs.aws.amazon.com/hands-on/latest/build-serverless-web-app-lambda-amplify-bedrock-cognito-gen-ai/images/file-directory-recipe-generator-project.png)

1. 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
<a name="add-amazon-bedrock-as-a-data-source"></a>
+ 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.   
![The 'ai-recipe-generator' project directory structure, highlighting the backend.ts file located in the amplify/auth folder.](http://docs.aws.amazon.com/hands-on/latest/build-serverless-web-app-lambda-amplify-bedrock-cognito-gen-ai/images/recipe-generator-project-directory.png)

## Conclusion
<a name="conclusion"></a>

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