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Invoke AI21 Labs Jurassic-2 models on Amazon Bedrock using the Invoke Model API
The following code examples show how to send a text message to AI21 Labs Jurassic-2, using the Invoke Model API.
- .NET
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- AWS SDK for .NET
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
// Use the native inference API to send a text message to AI21 Labs Jurassic-2. using System; using System.IO; using System.Text.Json; using System.Text.Json.Nodes; using Amazon; using Amazon.BedrockRuntime; using Amazon.BedrockRuntime.Model; // Create a Bedrock Runtime client in the AWS Region you want to use. var client = new AmazonBedrockRuntimeClient(RegionEndpoint.USEast1); // Set the model ID, e.g., Jurassic-2 Mid. var modelId = "ai21.j2-mid-v1"; // Define the user message. var userMessage = "Describe the purpose of a 'hello world' program in one line."; //Format the request payload using the model's native structure. var nativeRequest = JsonSerializer.Serialize(new { prompt = userMessage, maxTokens = 512, temperature = 0.5 }); // Create a request with the model ID and the model's native request payload. var request = new InvokeModelRequest() { ModelId = modelId, Body = new MemoryStream(System.Text.Encoding.UTF8.GetBytes(nativeRequest)), ContentType = "application/json" }; try { // Send the request to the Bedrock Runtime and wait for the response. var response = await client.InvokeModelAsync(request); // Decode the response body. var modelResponse = await JsonNode.ParseAsync(response.Body); // Extract and print the response text. var responseText = modelResponse["completions"]?[0]?["data"]?["text"] ?? ""; Console.WriteLine(responseText); } catch (AmazonBedrockRuntimeException e) { Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}"); throw; }
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For API details, see InvokeModel in AWS SDK for .NET API Reference.
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- Go
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- SDK for Go V2
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
import ( "context" "encoding/json" "log" "strings" "github.com/aws/aws-sdk-go-v2/aws" "github.com/aws/aws-sdk-go-v2/service/bedrockruntime" ) // InvokeModelWrapper encapsulates Amazon Bedrock actions used in the examples. // It contains a Bedrock Runtime client that is used to invoke foundation models. type InvokeModelWrapper struct { BedrockRuntimeClient *bedrockruntime.Client } // Each model provider has their own individual request and response formats. // For the format, ranges, and default values for AI21 Labs Jurassic-2, refer to: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-jurassic2.html type Jurassic2Request struct { Prompt string `json:"prompt"` MaxTokens int `json:"maxTokens,omitempty"` Temperature float64 `json:"temperature,omitempty"` } type Jurassic2Response struct { Completions []Completion `json:"completions"` } type Completion struct { Data Data `json:"data"` } type Data struct { Text string `json:"text"` } // Invokes AI21 Labs Jurassic-2 on Amazon Bedrock to run an inference using the input // provided in the request body. func (wrapper InvokeModelWrapper) InvokeJurassic2(ctx context.Context, prompt string) (string, error) { modelId := "ai21.j2-mid-v1" body, err := json.Marshal(Jurassic2Request{ Prompt: prompt, MaxTokens: 200, Temperature: 0.5, }) if err != nil { log.Fatal("failed to marshal", err) } output, err := wrapper.BedrockRuntimeClient.InvokeModel(ctx, &bedrockruntime.InvokeModelInput{ ModelId: aws.String(modelId), ContentType: aws.String("application/json"), Body: body, }) if err != nil { ProcessError(err, modelId) } var response Jurassic2Response if err := json.Unmarshal(output.Body, &response); err != nil { log.Fatal("failed to unmarshal", err) } return response.Completions[0].Data.Text, nil }
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For API details, see InvokeModel
in AWS SDK for Go API Reference.
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- Java
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- SDK for Java 2.x
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
// Use the native inference API to send a text message to AI21 Labs Jurassic-2. import org.json.JSONObject; import org.json.JSONPointer; import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider; import software.amazon.awssdk.core.SdkBytes; import software.amazon.awssdk.core.exception.SdkClientException; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient; public class InvokeModel { public static String invokeModel() { // Create a Bedrock Runtime client in the AWS Region you want to use. // Replace the DefaultCredentialsProvider with your preferred credentials provider. var client = BedrockRuntimeClient.builder() .credentialsProvider(DefaultCredentialsProvider.create()) .region(Region.US_EAST_1) .build(); // Set the model ID, e.g., Jurassic-2 Mid. var modelId = "ai21.j2-mid-v1"; // The InvokeModel API uses the model's native payload. // Learn more about the available inference parameters and response fields at: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-jurassic2.html var nativeRequestTemplate = "{ \"prompt\": \"{{prompt}}\" }"; // Define the prompt for the model. var prompt = "Describe the purpose of a 'hello world' program in one line."; // Embed the prompt in the model's native request payload. String nativeRequest = nativeRequestTemplate.replace("{{prompt}}", prompt); try { // Encode and send the request to the Bedrock Runtime. var response = client.invokeModel(request -> request .body(SdkBytes.fromUtf8String(nativeRequest)) .modelId(modelId) ); // Decode the response body. var responseBody = new JSONObject(response.body().asUtf8String()); // Retrieve the generated text from the model's response. var text = new JSONPointer("/completions/0/data/text").queryFrom(responseBody).toString(); System.out.println(text); return text; } catch (SdkClientException e) { System.err.printf("ERROR: Can't invoke '%s'. Reason: %s", modelId, e.getMessage()); throw new RuntimeException(e); } } public static void main(String[] args) { invokeModel(); } }
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For API details, see InvokeModel in AWS SDK for Java 2.x API Reference.
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- JavaScript
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- SDK for JavaScript (v3)
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
import { fileURLToPath } from "node:url"; import { FoundationModels } from "../../config/foundation_models.js"; import { BedrockRuntimeClient, InvokeModelCommand, } from "@aws-sdk/client-bedrock-runtime"; /** * @typedef {Object} Data * @property {string} text * * @typedef {Object} Completion * @property {Data} data * * @typedef {Object} ResponseBody * @property {Completion[]} completions */ /** * Invokes an AI21 Labs Jurassic-2 model. * * @param {string} prompt - The input text prompt for the model to complete. * @param {string} [modelId] - The ID of the model to use. Defaults to "ai21.j2-mid-v1". */ export const invokeModel = async (prompt, modelId = "ai21.j2-mid-v1") => { // Create a new Bedrock Runtime client instance. const client = new BedrockRuntimeClient({ region: "us-east-1" }); // Prepare the payload for the model. const payload = { prompt, maxTokens: 500, temperature: 0.5, }; // Invoke the model with the payload and wait for the response. const command = new InvokeModelCommand({ contentType: "application/json", body: JSON.stringify(payload), modelId, }); const apiResponse = await client.send(command); // Decode and return the response(s). const decodedResponseBody = new TextDecoder().decode(apiResponse.body); /** @type {ResponseBody} */ const responseBody = JSON.parse(decodedResponseBody); return responseBody.completions[0].data.text; }; // Invoke the function if this file was run directly. if (process.argv[1] === fileURLToPath(import.meta.url)) { const prompt = 'Complete the following in one sentence: "Once upon a time..."'; const modelId = FoundationModels.JURASSIC2_MID.modelId; console.log(`Prompt: ${prompt}`); console.log(`Model ID: ${modelId}`); try { console.log("-".repeat(53)); const response = await invokeModel(prompt, modelId); console.log(response); } catch (err) { console.log(err); } }
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For API details, see InvokeModel in AWS SDK for JavaScript API Reference.
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- PHP
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- SDK for PHP
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
public function invokeJurassic2($prompt) { # The different model providers have individual request and response formats. # For the format, ranges, and default values for AI21 Labs Jurassic-2, refer to: # https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-jurassic2.html $completion = ""; try { $modelId = 'ai21.j2-mid-v1'; $body = [ 'prompt' => $prompt, 'temperature' => 0.5, 'maxTokens' => 200, ]; $result = $this->bedrockRuntimeClient->invokeModel([ 'contentType' => 'application/json', 'body' => json_encode($body), 'modelId' => $modelId, ]); $response_body = json_decode($result['body']); $completion = $response_body->completions[0]->data->text; } catch (Exception $e) { echo "Error: ({$e->getCode()}) - {$e->getMessage()}\n"; } return $completion; }
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For API details, see InvokeModel in AWS SDK for PHP API Reference.
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- Python
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- SDK for Python (Boto3)
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Use the Invoke Model API to send a text message.
# Use the native inference API to send a text message to AI21 Labs Jurassic-2. import boto3 import json from botocore.exceptions import ClientError # Create a Bedrock Runtime client in the AWS Region of your choice. client = boto3.client("bedrock-runtime", region_name="us-east-1") # Set the model ID, e.g., Jurassic-2 Mid. model_id = "ai21.j2-mid-v1" # Define the prompt for the model. prompt = "Describe the purpose of a 'hello world' program in one line." # Format the request payload using the model's native structure. native_request = { "prompt": prompt, "maxTokens": 512, "temperature": 0.5, } # Convert the native request to JSON. request = json.dumps(native_request) try: # Invoke the model with the request. response = client.invoke_model(modelId=model_id, body=request) except (ClientError, Exception) as e: print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}") exit(1) # Decode the response body. model_response = json.loads(response["body"].read()) # Extract and print the response text. response_text = model_response["completions"][0]["data"]["text"] print(response_text)
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For API details, see InvokeModel in AWS SDK for Python (Boto3) API Reference.
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