Task 4: Deploy the Backend API

Overview

In this task, you will configure a custom query that will reference the data source and the resolver you defined the previous model to produce a recipe based on a list of ingredients. This query will use a custom type to structure the response from Amazon Bedrock. 

What you will accomplish

In this tutorial, you will:

• Define a GraphQL Query that takes an array of strings

• Define a custom type to be used to structure the response from the query

Implementation

Time to complete	5 minutes
Get help	Troubleshooting Amplify Learn about Data

Step 1: Set up Amplify Data

1. Update the resource.ts file

   On your local machine, navigate to the ai-recipe-generator/amplify/data/resource.ts file, and update it with the following code. Then, save the file.

   • The following code defines the askBedrock query that takes an array of strings called ingredients and returns a BedrockResponse. The .handler(a.handler.custom({ entry: "./bedrock.js", dataSource: "bedrockDS" })) line sets up a custom handler for this query, defined in bedrock.js, using bedrockDS as its data source.

   import { type ClientSchema, a, defineData } from "@aws-amplify/backend";
   
   const schema = a.schema({
     BedrockResponse: a.customType({
       body: a.string(),
       error: a.string(),
     }),
     askBedrock: a
       .query()
       .arguments({ ingredients: a.string().array() })
       .returns(a.ref("BedrockResponse"))
       .authorization((allow) => [allow.authenticated()])
       .handler(
         a.handler.custom({
           entry: "./bedrock.js",
           dataSource: "bedrockDS"
         })
       ),
   });
   
   export type Schema = ClientSchema<typeof schema>;
   
   export const data = defineData({
     schema,
     authorizationModes: {
       defaultAuthorizationMode: "apiKey",
       apiKeyAuthorizationMode: {
         expiresInDays: 30,
       },
     },
   });

   

2. Deploy resources

   Open a new terminal window, navigate to your apps project folder (ai-recipe-generator), and run the following command to deploy cloud resources into an isolated development space so you can iterate fast.

   npx ampx sandbox

   

3. View confirmation message

   After the cloud sandbox has been fully deployed, your terminal will display a confirmation message.

   

4. Verify outputs file creation

   Verify that the amplify_outputs.json file was generated and added to your project.

   

Conclusion

You have configured a GraphQL API to define a custom query to connect to Amazon Bedrock and generate recipes based on a list of ingredients.