Bedrock Agentcore

# Install SDK and CLI
pip install bedrock-agentcore strands-agents bedrock-agentcore-starter-toolkit

# Verify installation
agentcore --help

import boto3

# Data plane operations
client = boto3.client('bedrock-agentcore')

# Control plane operations
control = boto3.client('bedrock-agentcore-control')

# Using starter toolkit
# agentcore configure -e main.py -n my-agent
# agentcore deploy

# Using boto3 control plane
response = control.create_agent_runtime(
    name='my-production-agent',
    description='Customer service agent',
    agentRuntimeArtifact={
        's3': {
            'uri': 's3://my-bucket/agent-package.zip'
        }
    },
    roleArn='arn:aws:iam::123456789012:role/AgentCoreExecutionRole',
    pythonRuntime='PYTHON_3_13',
    entryPoint=['main.py']
)
agent_runtime_arn = response['agentRuntimeArn']

# Invoke deployed agent
response = client.invoke_agent_runtime(
    agentRuntimeArn='arn:aws:bedrock-agentcore:us-east-1:123456789012:agent-runtime/xxx',
    runtimeSessionId='session-123',
    payload={
        'prompt': 'What is my order status?',
        'context': {'user_id': 'user-456'}
    }
)

result = response['payload']
print(result)

from bedrock_agentcore import BedrockAgentCoreApp
from strands import Agent

app = BedrockAgentCoreApp(debug=True)
agent = Agent()

@app.entrypoint
def invoke(payload):
    """Main agent entry point"""
    user_message = payload.get("prompt", "Hello!")
    app.logger.info(f"Processing: {user_message}")

    result = agent(user_message)
    return {"result": result.message}

if __name__ == "__main__":
    app.run()

response = control.create_gateway(
    name='customer-service-gateway',
    description='Gateway for customer service tools',
    protocolType='REST'
)
gateway_arn = response['gatewayArn']

# Add an existing Lambda as a tool
response = control.create_gateway_target(
    gatewayId='gateway-xxx',
    name='GetOrderStatus',
    description='Retrieves order status by order ID',
    targetConfiguration={
        'lambdaTarget': {
            'lambdaArn': 'arn:aws:lambda:us-east-1:123456789012:function:GetOrder'
        }
    },
    toolSchema={
        'name': 'get_order_status',
        'description': 'Get the current status of a customer order',
        'inputSchema': {
            'type': 'object',
            'properties': {
                'order_id': {
                    'type': 'string',
                    'description': 'The unique order identifier'
                }
            },
            'required': ['order_id']
        }
    }
)

# Sync gateway tools for discovery
control.synchronize_gateway_targets(
    gatewayId='gateway-xxx'
)

response = client.start_browser_session(
    browserId='browser-xxx',
    sessionConfiguration={
        'timeout': 300,
        'viewport': {'width': 1920, 'height': 1080}
    }
)
session_id = response['browserSessionId']

# Navigate and interact
response = client.update_browser_stream(
    browserSessionId=session_id,
    action={
        'navigate': {'url': 'https://example.com'},
        'click': {'selector': '#submit-button'},
        'type': {'selector': '#search', 'text': 'query'}
    }
)

response = client.start_code_interpreter_session(
    codeInterpreterId='interpreter-xxx'
)
session_id = response['codeInterpreterSessionId']

response = client.invoke_code_interpreter(
    codeInterpreterSessionId=session_id,
    code='''
import pandas as pd
import matplotlib.pyplot as plt

# Analyze data
df = pd.DataFrame({'x': [1,2,3,4,5], 'y': [2,4,6,8,10]})
plt.plot(df['x'], df['y'])
plt.savefig('output.png')
print(df.describe())
''',
    language='PYTHON'
)

output = response['output']
files = response['files']  # Generated files