AWS SDK

Gunakan AWS SDK untuk berinteraksi langsung dengan kontrol berbutir halus AgentCore Memori atas operasi memori. Contoh berikut menunjukkan cara mengakses AWS SDK dengan SDK for Python (Boto3).

Instal dependensi

pip install boto3

Tambahkan memori jangka pendek

import boto3
from datetime import datetime

# Initialize boto3 clients
control_client = boto3.client('bedrock-agentcore-control', region_name='us-east-1')
data_client = boto3.client('bedrock-agentcore', region_name='us-east-1')

# Create short-term memory
memory_response = control_client.create_memory(
    name="BasicMemory",
    description="Basic memory for short-term event storage",
    eventExpiryDuration=90
)

memory_id = memory_response['memory']['id']
actor_id = f"actor_{datetime.now().strftime('%Y%m%d%H%M%S')}"
session_id = f"session_{datetime.now().strftime('%Y%m%d%H%M%S')}"

# Create event with multiple conversation turns
event = data_client.create_event(
    memoryId=memory_id,
    actorId=actor_id,
    sessionId=session_id,
    eventTimestamp=datetime.now(),
    payload=[
        {
            'conversational': {
                'content': {'text': 'I like sushi with tuna'},
                'role': 'USER'
            }
        },
        {
            'conversational': {
                'content': {'text': 'That sounds delicious! Tuna sushi is a great choice.'},
                'role': 'ASSISTANT'
            }
        },
        {
            'conversational': {
                'content': {'text': 'I also like pizza'},
                'role': 'USER'
            }
        },
        {
            'conversational': {
                'content': {'text': 'Pizza is another excellent choice! You have great taste in food.'},
                'role': 'ASSISTANT'
            }
        }
    ]
)

Tambahkan memori jangka panjang dengan strategi

import boto3
import time
from datetime import datetime

# Initialize boto3 clients
control_client = boto3.client('bedrock-agentcore-control', region_name='us-east-1')
data_client = boto3.client('bedrock-agentcore', region_name='us-east-1')

# Create long-term memory
memory_response = control_client.create_memory(
    name=f"ComprehensiveMemory",
    description="Memory with strategies for long-term memory extraction",
    eventExpiryDuration=90,
    memoryStrategies=[
        {
            'summaryMemoryStrategy': {
                'name': 'SessionSummarizer',
                'namespaceTemplates': ['/summaries/{actorId}/{sessionId}/']
            }
        },
        {
            'userPreferenceMemoryStrategy': {
                'name': 'PreferenceLearner',
                'namespaceTemplates': ['/preferences/{actorId}/']
            }
        },
        {
            'semanticMemoryStrategy': {
                'name': 'FactExtractor',
                'namespaceTemplates': ['/facts/{actorId}/']
            }
        }
    ]
)

memory_id = memory_response['memory']['id']
actor_id = f"actor_{datetime.now().strftime('%Y%m%d%H%M%S')}"
session_id = f"session_{datetime.now().strftime('%Y%m%d%H%M%S')}"

########## Wait for long-term memory to become active ##########

while True:
    mem_status_response = control_client.get_memory(memoryId=memory_id)
    status = mem_status_response.get('memory', {}).get('status')
    if status == 'ACTIVE':
        print("Memory resource is now ACTIVE.")
        break
    elif status == 'FAILED':
        raise Exception("Memory resource creation FAILED.")
    print("Waiting for memory to become active...")
    time.sleep(10)

# Create single event with all conversation turns
event = data_client.create_event(
    memoryId=memory_id,
    actorId=actor_id,
    sessionId=session_id,
    eventTimestamp=datetime.now(),
    payload=[
        {
            'conversational': {
                'content': {'text': 'I like sushi with tuna'},
                'role': 'USER'
            }
        },
        {
            'conversational': {
                'content': {'text': 'That sounds delicious! Tuna sushi is a great choice.'},
                'role': 'ASSISTANT'
            }
        },
        {
            'conversational': {
                'content': {'text': 'I also like pizza'},
                'role': 'USER'
            }
        },
        {
            'conversational': {
                'content': {'text': 'Pizza is another excellent choice! You have great taste in food.'},
                'role': 'ASSISTANT'
            }
        }
    ]
)

Referensi API AgentCore AgentCore Memori Amazon Bedrock AWS SDK lengkap dapat ditemukan di: