AWS Kit SDK

Utilisez le AWS SDK pour interagir directement avec AgentCore Memory pour un contrôle précis des opérations de mémoire. Les exemples suivants montrent comment accéder au AWS SDK avec le SDK pour Python (Boto3).

Installation des dépendances

pip install boto3

Ajouter de la mémoire à court terme

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'
            }
        }
    ]
)

Ajoutez de la mémoire à long terme grâce à des stratégies

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'
            }
        }
    ]
)

La référence complète de l'API Amazon Bedrock AgentCore AgentCore Memory du AWS SDK est disponible à l'adresse suivante :