Amazon Bedrock API

pip install anthropic-bedrock

npm install @anthropic-ai/bedrock-sdk

pip install boto3>=1.28.59

aws bedrock list-foundation-models --by-provider anthropic --query "modelSummaries[*].modelId"

import boto3

bedrock = boto3.client(service_name="bedrock")
response = bedrock.list_foundation_models(byProvider="anthropic")

for summary in response["modelSummaries"]:
    print(summary["modelId"])

import anthropic_bedrock
from anthropic_bedrock import AnthropicBedrock

client = AnthropicBedrock(
    # Authenticate by either providing the keys below or use the default AWS credential providers, such as
    # using ~/.aws/credentials or the "AWS_SECRET_ACCESS_KEY" and "AWS_ACCESS_KEY_ID" environment variables.
    aws_access_key="<access key>",
    aws_secret_key="<secret key>",
    # Temporary credentials can be used with aws_session_token.
    # Read more at https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp.html.
    aws_session_token="<session_token>",
    # aws_region changes the aws region to which the request is made. By default, we read AWS_REGION,
    # and if that's not present, we default to us-east-1. Note that we do not read ~/.aws/config for the region.
    aws_region="us-east-2",
)

completion = client.completions.create(
    model="anthropic.claude-v2:1",
    max_tokens_to_sample=256,
    prompt=f"{anthropic_bedrock.HUMAN_PROMPT} Tell me a funny joke about outer space! {anthropic_bedrock.AI_PROMPT}",
)
print(completion.completion)

import AnthropicBedrock from '@anthropic-ai/bedrock-sdk';

const client = new AnthropicBedrock({
  // Authenticate by either providing the keys below or use the default AWS credential providers, such as
  // using ~/.aws/credentials or the "AWS_SECRET_ACCESS_KEY" and "AWS_ACCESS_KEY_ID" environment variables.
  awsAccessKey: '<access key>',
  awsSecretKey: '<secret key>',

  // Temporary credentials can be used with awsSessionToken.
  // Read more at https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp.html.
  awsSessionToken: '<session_token>',

  // awsRegion changes the aws region to which the request is made. By default, we read AWS_REGION,
  // and if that's not present, we default to us-east-1. Note that we do not read ~/.aws/config for the region.
  awsRegion: 'us-east-2',
});

async function main() {
  const completion = await client.completions.create({
    model: 'anthropic.claude-v2:1',
    max_tokens_to_sample: 256,
    prompt: `${AnthropicBedrock.HUMAN_PROMPT} Tell me a funny joke about outer space! ${AnthropicBedrock.AI_PROMPT}`,
  });
}
main().catch(console.error);

aws bedrock-runtime invoke-model \
  --model-id anthropic.claude-v2:1 \
  --cli-binary-format raw-in-base64-out \
  --body '{"prompt": "Human: Tell me a funny joke about outer space!\n\nAssistant:", "max_tokens_to_sample": 50, "anthropic_version": "bedrock-2023-05-31"}'  \
  /dev/stdout

import boto3
import json

bedrock = boto3.client(service_name="bedrock-runtime")
body = json.dumps(
    {
        "prompt": "\n\nHuman: Tell me a funny joke about outer space\n\nAssistant:",
        "max_tokens_to_sample": 100,
        "anthropic_version": "bedrock-2023-05-31"
    }
)

response = bedrock.invoke_model(body=body, modelId="anthropic.claude-v2:1")

response_body = json.loads(response.get("body").read())
print(response_body.get("completion"))

from anthropic_bedrock import AnthropicBedrock, HUMAN_PROMPT, AI_PROMPT

client = AnthropicBedrock()

stream = client.completions.create(
    prompt=f"{HUMAN_PROMPT} Write a very short essay about space travel to Mars{AI_PROMPT}",
    max_tokens_to_sample=300,
    model="anthropic.claude-v2:1",
    stream=True,
)
for completion in stream:
    print(completion.completion, end="", flush=True)

import AnthropicBedrock from '@anthropic-ai/bedrock-sdk';

const client = new AnthropicBedrock();

const stream = await client.completions.create({
  prompt: `${AnthropicBedrock.HUMAN_PROMPT} Write a very short essay about space travel to Mars${AnthropicBedrock.AI_PROMPT}`,
  model: 'anthropic.claude-v2:1',
  stream: true,
  max_tokens_to_sample: 300,
});
for await (const completion of stream) {
  console.log(completion.completion);
}

import boto3
import json

bedrock = boto3.client(service_name="bedrock-runtime")
body = json.dumps(
    {
        "prompt": "\n\nHuman: Write a very short essay about space travel to Mars\n\nAssistant:",
        "max_tokens_to_sample": 200,
        "anthropic_version": "bedrock-2023-05-31"
    }
)
response = bedrock.invoke_model_with_response_stream(
    modelId="anthropic.claude-v2:1", body=body
)

stream = response.get("body")

if stream:
    for event in stream:
        chunk = event.get("chunk")
        if chunk:
            print(json.loads(chunk.get("bytes").decode()))