For a more fully fledged example see examples/bedrock.py. This library also provides support for the Anthropic Vertex API if you install this library with the vertex extra, e.g. pip install -U anthropic[vertex]. You can then import and instantiate a separate AnthropicVertex/AsyncAnthropicVertex class, which has the same API as the base Anthropic/AsyncAnthropic class.

JavaScript is disabled in your browser · Please enable JavaScript to proceed · A required part of this site couldn’t load. This may be due to a browser extension, network issues, or browser settings. Please check your connection, disable any ad blockers, or try using a different browser

import { AnthropicBedrock } from '@anthropic-ai/bedrock-sdk'; // Note: this assumes you have configured AWS credentials in a way // that the AWS Node SDK will recognise, typicaly a shared `~/.aws/credentials` // file or `AWS_ACCESS_KEY_ID` & `AWS_SECRET_ACCESS_KEY` environment variables. // // https://docs.aws.amazon.com/sdk-for-javascript/v3/developer-guide/setting-credentials-node.html const client = new AnthropicBedrock(); async function main() { const message = await client.messages.create({ model: 'anthropic.claude-3-5-sonnet-20241022-v2:0', messages: [ { role: 'user', content: 'Hello!', }, ], max_tokens: 1024, }); console.log(message); } main();

* * To learn more about the Anthropic Messages API, go to: * https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html * * @param {string} prompt - The input text prompt for the model to complete. * @param {string} [modelId] - The ID of the model to use. Defaults to "anthropic.claude-3-haiku-20240307-v1:0". */ export const invokeModel = async ( prompt, modelId = "anthropic.claude-3-haiku-20240307-v1:0", ) => { // Create a new Bedrock Runtime client instance.

* * To learn more about the Anthropic Messages API, go to: * https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html * * @param {string} prompt - The input text prompt for the model to complete. * @param {string} [modelId] - The ID of the model to use. Defaults to "anthropic.claude-3-haiku-20240307-v1:0". */ export const invokeModel = async ( prompt, modelId = "anthropic.claude-3-haiku-20240307-v1:0", ) => { // Create a new Bedrock Runtime client instance.

Send a text message to Anthropic Claude, using Bedrock's Converse API. #[tokio::main] async fn main() -> Result<(), BedrockConverseError> { tracing_subscriber::fmt::init(); let sdk_config = aws_config::defaults(BehaviorVersion::latest()) .region(CLAUDE_REGION) .load() .await; let client = Client::new(&sdk_config); let response = client .converse() .model_id(MODEL_ID) .messages( Message::builder() .role(ConversationRole::User) .content(ContentBlock::Text(USER_MESSAGE.to_string())) .build() .map_err(|_| "failed to build message")?, ) .send() .await; match response { Ok(output) => { let text = ge

The Anthropic Python library provides ... definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. For the AWS Bedrock API, see ......

Contribute to anthropics/anthropic-bedrock-python development by creating an account on GitHub.

Additional configuration is needed to use Anthropic’s Client SDKs through a partner platform. If you are using Amazon Bedrock, see this guide; if you are using Google Cloud Vertex AI, see this guide; if you are using Microsoft Foundry, see this guide.

List methods in the Anthropic API are paginated. You can use the for await … of syntax to iterate through items across all pages: async function fetchAllMessageBatches(params) { const allMessageBatches = []; // Automatically fetches more pages as needed.

import Anthropic from "anthropic-bedrock"; const anthropic = new Anthropic({ access_key: process.env["AWS_ACCESS_KEY"], secret_key: process.env["AWS_SECRET_KEY"], }); async function main() { const completion = await anthropic.Completion.create( model: "anthropic.claude-v2", prompt: "In one sentence, what is good about the color blue?"

December 9, 2024 - From this pull request, my understanding is that you can switch the client to the Anthropic Bedrock client.

Required if using a model from AWS bedrock. To use this client, you must install the Anthropic extension: ... import asyncio from autogen_ext.models.anthropic import AnthropicBedrockChatCompletionClient, BedrockInfo from autogen_core.models import UserMessage, ModelInfo async def main(): anthropic_client = AnthropicBedrockChatCompletionClient( model="anthropic.claude-3-5-sonnet-20240620-v1:0", temperature=0.1, model_info=ModelInfo( vision=False, function_calling=True, json_output=False, family="unknown", structured_output=True ), bedrock_info=BedrockInfo( aws_access_key="<aws_access_key>", aws_secret_key="<aws_secret_key>", aws_session_token="<aws_session_token>", aws_region="<aws_region>", ), ) result = await anthropic_client.create([UserMessage(content="What is the capital of France?", source="user")]) # type: ignore print(result) if __name__ == "__main__": asyncio.run(main())

April 24, 2024 - import AnthropicBedrock from '@anthropic-ai/bedrock-sdk'; const client = new AnthropicBedrock(); async function main(prompt) { const message = await client.messages.create({ max_tokens: 1, stream: false, messages: [{role: 'user', content: prompt}], model: 'anthropic.claude-3-sonnet-20240229-v1:0', }); console.log('Response content: ', message.content); } await main('Explain quantum mechanics to a five year old'); // [] <-- ERROR await main('Translate Hello into French and Spanish'); // [ { type: 'text', text: 'Here' } ] dmellott ·

import instructor # Auto client with model specification client = instructor.from_provider("bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0") # The auto client automatically handles: # - AWS credential detection from environment # - Region configuration (defaults to us-east-1) # - Mode selection based on model (Claude models use BEDROCK_TOOLS) ... The _async argument to instructor.from_bedrock is deprecated.

The timeout period for inference calls to Anthropic Claude 3.7 Sonnet and Claude 4 models is 60 minutes. By default, AWS SDK clients timeout after 1 minute. We recommend that you increase the read timeout period of your AWS SDK client to at least 60 minutes.

Fast, reliable, and secure dependency management.

For a more fully fledged example see examples/bedrock.py. This library also provides support for the Anthropic Vertex API if you install this library with the vertex extra, e.g. pip install -U anthropic[vertex]. You can then import and instantiate a separate AnthropicVertex/AsyncAnthropicVertex class, which has the same API as the base Anthropic/AsyncAnthropic class.

We avoid blocking code execution by using asynchronous functions. Any questions on this? ... # example without a system message and debug flag on: response = bedrock.ChatCompletion.create( model="anthropic.claude-v2", messages=[ {"role": "user", "content": "Explain asynchronous programming in the style of the pirate Blackbeard."}, ] ) print(response['choices'][0]['message']['content'])