JavaScript examples for Amazon Nova and Amazon Nova Canvas

.doc_gen/metadata/bedrock-runtime_metadata.yaml

@@ -86,6 +86,14 @@ bedrock-runtime_Converse_AmazonNovaText:
             - description: Send a text message to Amazon Nova, using Bedrock's Converse API.
               snippet_tags:
                 - bedrock-runtime.java2.Converse_AmazonNovaText
+    JavaScript:
+      versions:
+        - sdk_version: 3
+          github: javascriptv3/example_code/bedrock-runtime
+          excerpts:
+            - description: Send a text message to Amazon Nova, using Bedrock's Converse API.
+              snippet_tags:
+                - javascript.v3.bedrock-runtime.Converse_AmazonTitanText
   services:
     bedrock-runtime: {Converse}
 
@@ -335,6 +343,14 @@ bedrock-runtime_ConverseStream_AmazonNovaText:
             - description: Send a text message to Amazon Nova using Bedrock's Converse API and process the response stream in real-time.
               snippet_tags:
                 - bedrock-runtime.java2.ConverseStream_AmazonNovaText
+    JavaScript:
+      versions:
+        - sdk_version: 3
+          github: javascriptv3/example_code/bedrock-runtime
+          excerpts:
+            - description: Send a text message to Amazon Nova using Bedrock's Converse API and process the response stream in real-time.
+              snippet_tags:
+                - javascript.v3.bedrock-runtime.Converse_Mistral
   services:
     bedrock-runtime: {ConverseStream}
 
@@ -1123,6 +1139,14 @@ bedrock-runtime_InvokeModel_AmazonNovaImageGeneration:
             - description: Create an image with Amazon Nova Canvas.
               snippet_tags:
                 - bedrock-runtime.java2.InvokeModel_AmazonNovaImageGeneration
+    JavaScript:
+      versions:
+        - sdk_version: 3
+          github: javascriptv3/example_code/bedrock-runtime
+          excerpts:
+            - description: Create an image with Amazon Nova Canvas.
+              snippet_tags:
+                - javascript.v3.bedrock-runtime.InvokeModel_AmazonNovaImageGeneration
   services:
     bedrock-runtime: {InvokeModel}
 

javascriptv3/example_code/bedrock-runtime/.gitignore

@@ -1 +1,2 @@
 /tempx/
+/output/

javascriptv3/example_code/bedrock-runtime/README.md

@@ -50,6 +50,15 @@ functions within the same service.
 - [Converse](models/ai21LabsJurassic2/converse.js#L4)
 - [InvokeModel](models/ai21LabsJurassic2/invoke_model.js)
 
+### Amazon Nova
+
+- [Converse](models/amazonTitanText/converse.js#L4)
+- [ConverseStream](models/mistral/converse.js#L4)
+
+### Amazon Nova Canvas
+
+- [InvokeModel](models/amazonNovaCanvas/invokeModel.js#L4)
+
 ### Amazon Titan Text
 
 - [Converse](models/amazonTitanText/converse.js#L4)

javascriptv3/example_code/bedrock-runtime/models/amazonNovaCanvas/invokeModel.js

@@ -0,0 +1,93 @@
+// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+// SPDX-License-Identifier: Apache-2.0
+
+// snippet-start:[javascript.v3.bedrock-runtime.InvokeModel_AmazonNovaImageGeneration]
+
+import {
+  BedrockRuntimeClient,
+  InvokeModelCommand,
+} from "@aws-sdk/client-bedrock-runtime";
+import { saveImage } from "../../utils/image-creation.js";
+import { fileURLToPath } from "node:url";
+
+/**
+ * This example demonstrates how to use Amazon Nova Canvas to generate images.
+ * It shows how to:
+ * - Set up the Amazon Bedrock runtime client
+ * - Configure the image generation parameters
+ * - Send a request to generate an image
+ * - Process the response and handle the generated image
+ *
+ * @returns {Promise<string>} Base64-encoded image data
+ */
+export const invokeModel = async () => {
+  // Step 1: Create the Amazon Bedrock runtime client
+  // Credentials will be automatically loaded from the environment
+  const client = new BedrockRuntimeClient({ region: "us-east-1" });
+
+  // Step 2: Specify which model to use
+  // For the latest available models, see:
+  // https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
+  const modelId = "amazon.nova-canvas-v1:0";
+
+  // Step 3: Configure the request payload
+  // First, set the main parameters:
+  // - prompt: Text description of the image to generate
+  // - seed: Random number for reproducible generation (0 to 858,993,459)
+  const prompt = "A stylized picture of a cute old steampunk robot";
+  const seed = Math.floor(Math.random() * 858993460);
+
+  // Then, create the payload using the following structure:
+  // - taskType: TEXT_IMAGE (specifies text-to-image generation)
+  // - textToImageParams: Contains the text prompt
+  // - imageGenerationConfig: Contains optional generation settings (seed, quality, etc.)
+  // For a list of available request parameters, see:
+  // https://docs.aws.amazon.com/nova/latest/userguide/image-gen-req-resp-structure.html
+  const payload = {
+    taskType: "TEXT_IMAGE",
+    textToImageParams: {
+      text: prompt,
+    },
+    imageGenerationConfig: {
+      seed,
+      quality: "standard",
+    },
+  };
+
+  // Step 4: Send and process the request
+  // - Embed the payload in a request object
+  // - Send the request to the model
+  // - Extract and return the generated image data from the response
+  try {
+    const request = {
+      modelId,
+      body: JSON.stringify(payload),
+    };
+    const response = await client.send(new InvokeModelCommand(request));
+
+    const decodedResponseBody = new TextDecoder().decode(response.body);
+    // The response includes an array of base64-encoded PNG images
+    /** @type {{images: string[]}} */
+    const responseBody = JSON.parse(decodedResponseBody);
+    return responseBody.images[0]; // Base64-encoded image data
+  } catch (error) {
+    console.error(`ERROR: Can't invoke '${modelId}'. Reason: ${error.message}`);
+    throw error;
+  }
+};
+
+// If run directly, execute the example and save the generated image
+if (process.argv[1] === fileURLToPath(import.meta.url)) {
+  console.log("Generating image. This may take a few seconds...");
+  invokeModel()
+    .then(async (imageData) => {
+      const imagePath = await saveImage(imageData, "nova-canvas");
+      // Example path: javascriptv3/example_code/bedrock-runtime/output/nova-canvas/image-01.png
+      console.log(`Image saved to: ${imagePath}`);
+    })
+    .catch((error) => {
+      console.error("Execution failed:", error);
+      process.exitCode = 1;
+    });
+}
+// snippet-end:[javascript.v3.bedrock-runtime.InvokeModel_AmazonNovaImageGeneration]

javascriptv3/example_code/bedrock-runtime/models/amazonNovaText/converse.js

@@ -0,0 +1,68 @@
+// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+// SPDX-License-Identifier: Apache-2.0
+
+// snippet-start:[javascript.v3.bedrock-runtime.Converse_AmazonNovaText]
+// This example demonstrates how to use the Amazon Nova foundation models to generate text.
+// It shows how to:
+// - Set up the Amazon Bedrock runtime client
+// - Create a message
+// - Configure and send a request
+// - Process the response
+
+import {
+  BedrockRuntimeClient,
+  ConversationRole,
+  ConverseCommand,
+} from "@aws-sdk/client-bedrock-runtime";
+
+// Step 1: Create the Amazon Bedrock runtime client
+// Credentials will be automatically loaded from the environment
+const client = new BedrockRuntimeClient({ region: "us-east-1" });
+
+// Step 2: Specify which model to use:
+// Available Amazon Nova models and their characteristics:
+// - Amazon Nova Micro: Text-only model optimized for lowest latency and cost
+// - Amazon Nova Lite:  Fast, low-cost multimodal model for image, video, and text
+// - Amazon Nova Pro:   Advanced multimodal model balancing accuracy, speed, and cost
+//
+// For the most current model IDs, see:
+// https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
+const modelId = "amazon.nova-lite-v1:0";
+
+// Step 3: Create the message
+// The message includes the text prompt and specifies that it comes from the user
+const inputText =
+  "Describe the purpose of a 'hello world' program in one line.";
+const message = {
+  content: [{ text: inputText }],
+  role: ConversationRole.USER,
+};
+
+// Step 4: Configure the request
+// Optional parameters to control the model's response:
+// - maxTokens: maximum number of tokens to generate
+// - temperature: randomness (max: 1.0, default: 0.7)
+//   OR
+// - topP: diversity of word choice (max: 1.0, default: 0.9)
+// Note: Use either temperature OR topP, but not both
+const request = {
+  modelId,
+  messages: [message],
+  inferenceConfig: {
+    maxTokens: 500, // The maximum response length
+    temperature: 0.5, // Using temperature for randomness control
+    //topP: 0.9,        // Alternative: use topP instead of temperature
+  },
+};
+
+// Step 5: Send and process the request
+// - Send the request to the model
+// - Extract and return the generated text from the response
+try {
+  const response = await client.send(new ConverseCommand(request));
+  console.log(response.output.message.content[0].text);
+} catch (error) {
+  console.error(`ERROR: Can't invoke '${modelId}'. Reason: ${error.message}`);
+  throw error;
+}
+// snippet-end:[javascript.v3.bedrock-runtime.Converse_AmazonNovaText]

javascriptv3/example_code/bedrock-runtime/models/amazonNovaText/converseStream.js

@@ -0,0 +1,75 @@
+// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+// SPDX-License-Identifier: Apache-2.0
+
+// snippet-start:[javascript.v3.bedrock-runtime.ConverseStream_AmazonNovaText]
+// This example demonstrates how to use the Amazon Nova foundation models
+// to generate streaming text responses.
+// It shows how to:
+// - Set up the Amazon Bedrock runtime client
+// - Create a message
+// - Configure a streaming request
+// - Process the streaming response
+
+import {
+  BedrockRuntimeClient,
+  ConversationRole,
+  ConverseStreamCommand,
+} from "@aws-sdk/client-bedrock-runtime";
+
+// Step 1: Create the Amazon Bedrock runtime client
+// Credentials will be automatically loaded from the environment
+const client = new BedrockRuntimeClient({ region: "us-east-1" });
+
+// Step 2: Specify which model to use
+// Available Amazon Nova models and their characteristics:
+// - Amazon Nova Micro: Text-only model optimized for lowest latency and cost
+// - Amazon Nova Lite:  Fast, low-cost multimodal model for image, video, and text
+// - Amazon Nova Pro:   Advanced multimodal model balancing accuracy, speed, and cost
+//
+// For the most current model IDs, see:
+// https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
+const modelId = "amazon.nova-lite-v1:0";
+
+// Step 3: Create the message
+// The message includes the text prompt and specifies that it comes from the user
+const inputText =
+  "Describe the purpose of a 'hello world' program in one paragraph";
+const message = {
+  content: [{ text: inputText }],
+  role: ConversationRole.USER,
+};
+
+// Step 4: Configure the streaming request
+// Optional parameters to control the model's response:
+// - maxTokens: maximum number of tokens to generate
+// - temperature: randomness (max: 1.0, default: 0.7)
+//   OR
+// - topP: diversity of word choice (max: 1.0, default: 0.9)
+// Note: Use either temperature OR topP, but not both
+const request = {
+  modelId,
+  messages: [message],
+  inferenceConfig: {
+    maxTokens: 500, // The maximum response length
+    temperature: 0.5, // Using temperature for randomness control
+    //topP: 0.9,        // Alternative: use topP instead of temperature
+  },
+};
+
+// Step 5: Send and process the streaming request
+// - Send the request to the model
+// - Process each chunk of the streaming response
+try {
+  const response = await client.send(new ConverseStreamCommand(request));
+
+  for await (const chunk of response.stream) {
+    if (chunk.contentBlockDelta) {
+      // Print each text chunk as it arrives
+      process.stdout.write(chunk.contentBlockDelta.delta?.text || "");
+    }
+  }
+} catch (error) {
+  console.error(`ERROR: Can't invoke '${modelId}'. Reason: ${error.message}`);
+  process.exitCode = 1;
+}
+// snippet-end:[javascript.v3.bedrock-runtime.ConverseStream_AmazonNovaText]

javascriptv3/example_code/bedrock-runtime/package.json

@@ -8,9 +8,9 @@
     "integration-test": "vitest run integration --reporter=junit --outputFile=test_results/bedrock-runtime-test-results.junit.xml"
   },
   "devDependencies": {
-    "vitest": "^1.6.0"
+    "vitest": "^1.6.1"
   },
   "dependencies": {
-    "@aws-sdk/client-bedrock-runtime": "^3.658.1"
+    "@aws-sdk/client-bedrock-runtime": "^3.751.0"
   }
 }

javascriptv3/example_code/bedrock-runtime/tests/converse.integration.test.js

@@ -8,18 +8,19 @@ describe("Converse with text generation models", () => {
   const baseDirectory = path.join(__dirname, "..", "models");
   const fileName = "converse.js";
 
-  const subdirectories = [
-    "ai21LabsJurassic2",
-    "amazonTitanText",
-    "anthropicClaude",
-    "cohereCommand",
-    "metaLlama",
-    "mistral",
-  ];
+  const models = {
+    ai21LabsJurassic2: "AI21 Labs Jurassic-2",
+    amazonNovaText: "Amazon Nova",
+    amazonTitanText: "Amazon Titan",
+    anthropicClaude: "Anthropic Claude",
+    cohereCommand: "Cohere Command",
+    metaLlama: "Meta Llama",
+    mistral: "Mistral",
+  };
 
-  test.each(subdirectories)(
-    "should invoke the model and return text",
-    async (subdirectory) => {
+  test.each(Object.entries(models).map(([sub, name]) => [name, sub]))(
+    "should invoke %s and return text",
+    async (_, subdirectory) => {
       const script = path.join(baseDirectory, subdirectory, fileName);
       const consoleLogSpy = vi.spyOn(console, "log");
 

javascriptv3/example_code/bedrock-runtime/tests/converse_stream.integration.test.js

@@ -9,17 +9,18 @@ describe("ConverseStream with text generation models", () => {
   const fileName = "converseStream.js";
   const baseDirectory = path.join(__dirname, "..", "models");
 
-  const subdirectories = [
-    "amazonTitanText",
-    "anthropicClaude",
-    "cohereCommand",
-    "metaLlama",
-    "mistral",
-  ];
+  const models = {
+    amazonNovaText: "Amazon Nova",
+    amazonTitanText: "Amazon Titan",
+    anthropicClaude: "Anthropic Claude",
+    cohereCommand: "Cohere Command",
+    metaLlama: "Meta Llama",
+    mistral: "Mistral",
+  };
 
-  test.each(subdirectories)(
-    "should invoke the model and return text",
-    async (subdirectory) => {
+  test.each(Object.entries(models).map(([sub, name]) => [name, sub]))(
+    "should invoke %s and return text",
+    async (_, subdirectory) => {
       let output = "";
       const outputStream = new Writable({
         write(/** @type string */ chunk, encoding, callback) {

javascriptv3/example_code/bedrock-runtime/tests/image_generation.integration.test.js

@@ -0,0 +1,13 @@
+// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+// SPDX-License-Identifier: Apache-2.0
+
+import { describe, it } from "vitest";
+import { invokeModel } from "../models/amazonNovaCanvas/invokeModel.js";
+import { expectToBeANonEmptyString } from "./test_tools.js";
+
+describe("Invoking Amazon Nova Canvas", () => {
+  it("should return a response", async () => {
+    const response = await invokeModel();
+    expectToBeANonEmptyString(response);
+  });
+});

javascriptv3/example_code/bedrock-runtime/tests/test_tools.js

@@ -10,5 +10,5 @@ import { expect } from "vitest";
  */
 export const expectToBeANonEmptyString = (string) => {
   expect(typeof string).toBe("string");
-  expect(string.length).not.toBe(0);
+  expect(string).not.toHaveLength(0);
 };