Claude Opus 5.5 现已在 AWS 上推出

英文标题：Claude Opus 5.5 is now available on AWS

Anthropic 面向 Agent 编程、知识工作和长时运行任务的 Claude Opus 5.5，现已登陆 Amazon Bedrock 和 Claude Platform on AWS。该模型据称可用更少 Token 完成更多工作，结合更低的单 Token 价格和显著降低的缓存读取费用，平均单任务成本低于 Claude Opus 5。Opus 5.5 默认启用自适应思考，并强化了任务过程中的沟通与可解释性；同时引入类似 Claude Fable 5.1 的生物学、网络安全和 AI 开发安全分类器，因此相较此前 Opus 版本会更频繁地拒绝请求。开发者可通过 Bedrock 控制台、Boto3、Converse API、Invoke API 或 Anthropic Messages API 调用该模型。

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import boto3
import json

# Create a Bedrock Runtime client
bedrock_runtime = boto3.client(
    service_name="bedrock-runtime",
    region_name="us-east-1"
)

# Invoke Claude Opus 5.5
response = bedrock_runtime.invoke_model(
    modelId="global.anthropic.claude-opus-5-5",
    contentType="application/json",
    accept="application/json",
    body=json.dumps({
        "anthropic_version": "bedrock-2023-05-31",
        "max_tokens": 4096,
        "messages": [
            {
                "role": "user",
                "content": "An S3 bucket serves 40 TB/month egress. Estimate the monthly egress cost at $0.09/GB, and state one architecture change to cut it. Show the calculation, keep it under 120 words."
            }
        ]
    })
)

result = json.loads(response["body"].read())
# Opus 5.5 is a reasoning model: the response may include a thinking block
# before the text block, so select the text block rather than a fixed index.
print(next(b["text"] for b in result["content"] if b["type"] == "text"))

import boto3

# Create a Bedrock Runtime client
bedrock_runtime = boto3.client(
    service_name="bedrock-runtime",
    region_name="us-east-1"
)

# Invoke Claude Opus 5.5
response = bedrock_runtime.converse(
    modelId="global.anthropic.claude-opus-5-5",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "text": "Can you explain the features of Amazon Bedrock?"
                }
            ]
        }
    ],
    inferenceConfig={
        "maxTokens": 4096
    }
)

if 'output' in response:
    blocks = response['output']['message']['content']
    print('\n'.join(b.get('text', '') for b in blocks if 'text' in b))

from anthropic import Anthropic
from aws_bedrock_token_generator import provide_token

token = provide_token(region="us-east-1")

client = Anthropic(
    base_url="https://bedrock-runtime.us-east-1.amazonaws.com/anthropic",
    api_key=token,
)

# Invoke Claude Opus 5.5
response = client.messages.create(
    model="global.anthropic.claude-opus-5-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}],
)
print(response)

import boto3
import json

# Create a Bedrock Runtime client
bedrock_runtime = boto3.client(
    service_name="bedrock-runtime",
    region_name="us-east-1"
)

# Invoke Claude Opus 5.5
response = bedrock_runtime.invoke_model(
    modelId="global.anthropic.claude-opus-5-5",
    contentType="application/json",
    accept="application/json",
    body=json.dumps({
        "anthropic_version": "bedrock-2023-05-31",
        "max_tokens": 4096,
        "messages": [
            {
                "role": "user",
                "content": "An S3 bucket serves 40 TB/month egress. Estimate the monthly egress cost at $0.09/GB, and state one architecture change to cut it. Show the calculation, keep it under 120 words."
            }
        ]
    })
)

result = json.loads(response["body"].read())
# Opus 5.5 is a reasoning model: the response may include a thinking block
# before the text block, so select the text block rather than a fixed index.
print(next(b["text"] for b in result["content"] if b["type"] == "text"))

import boto3

# Create a Bedrock Runtime client
bedrock_runtime = boto3.client(
    service_name="bedrock-runtime",
    region_name="us-east-1"
)

# Invoke Claude Opus 5.5
response = bedrock_runtime.converse(
    modelId="global.anthropic.claude-opus-5-5",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "text": "Can you explain the features of Amazon Bedrock?"
                }
            ]
        }
    ],
    inferenceConfig={
        "maxTokens": 4096
    }
)

if 'output' in response:
    blocks = response['output']['message']['content']
    print('\n'.join(b.get('text', '') for b in blocks if 'text' in b))

from anthropic import Anthropic
from aws_bedrock_token_generator import provide_token

token = provide_token(region="us-east-1")

client = Anthropic(
    base_url="https://bedrock-runtime.us-east-1.amazonaws.com/anthropic",
    api_key=token,
)

# Invoke Claude Opus 5.5
response = client.messages.create(
    model="global.anthropic.claude-opus-5-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}],
)
print(response)