Gerencie exemplos de conjuntos de dados

Para adicionar exemplos com a AgentCore CLI, anexe novos cenários ao seu arquivo JSONL local e reimplante:

# Edit agentcore/datasets/my_eval_dataset.jsonl — add new lines
agentcore deploy

A implantação detecta novos cenários em seu arquivo JSONL e os adiciona ao serviço. Somente a diferença é aplicada — os exemplos existentes não são recarregados.

from bedrock_agentcore.evaluation import DatasetClient

client = DatasetClient(region_name="us-west-2")

ds = client.add_examples_and_wait(
    datasetId="my-dataset-id",
    source={
        "inlineExamples": {
            "examples": [
                {
                    "scenario_id": "TC-02",
                    "turns": [{"input": "Transfer $100", "expected_response": "Transfer complete."}],
                }
            ]
        }
    },
)
print(f"Example count: {ds['exampleCount']}")

import boto3
import time

client = boto3.client('bedrock-agentcore-control')

resp = client.add_dataset_examples(
    datasetId='my-dataset-id',
    source={'inlineExamples': {'examples': [
        {'scenario_id': 'TC-02', 'turns': [{'input': 'Transfer $100', 'expected_response': 'Transfer complete.'}]}
    ]}}
)
print(f"Added example IDs: {resp['exampleIds']}")

# Poll until ACTIVE
while True:
    ds = client.get_dataset(datasetId='my-dataset-id')
    if ds['status'] == 'ACTIVE':
        break
    time.sleep(2)

aws bedrock-agentcore-control add-dataset-examples \
    --dataset-id my-dataset-id \
    --source '{"inlineExamples": {"examples": [{"scenario_id": "TC-02", "turns": [{"input": "Transfer $100", "expected_response": "Transfer complete."}]}]}}'

Para atualizar exemplos com a AgentCore CLI, modifique os cenários existentes em seu arquivo JSONL local e reimplante:

# Edit agentcore/datasets/my_eval_dataset.jsonl — modify existing lines
agentcore deploy

A implantação diferencia seu arquivo local com o serviço e atualiza os exemplos alterados. Cada linha deve mantê-la exampleId para que o serviço a reconheça como uma atualização em vez de um novo exemplo.

from bedrock_agentcore.evaluation import DatasetClient

client = DatasetClient(region_name="us-west-2")

ds = client.update_examples_and_wait(
    datasetId="my-dataset-id",
    examples=[
        {
            "exampleId": "example-id-from-list",
            "scenario_id": "TC-02-updated",
            "turns": [{"input": "Transfer $200", "expected_response": "Transfer complete."}],
        }
    ],
)

import boto3
import time

client = boto3.client('bedrock-agentcore-control')

client.update_dataset_examples(
    datasetId='my-dataset-id',
    examples=[
        {
            'exampleId': 'example-id-from-list',
            'scenario_id': 'TC-02-updated',
            'turns': [{'input': 'Transfer $200', 'expected_response': 'Transfer complete.'}],
        }
    ]
)

# Poll until ACTIVE
while True:
    ds = client.get_dataset(datasetId='my-dataset-id')
    if ds['status'] == 'ACTIVE':
        break
    time.sleep(2)

aws bedrock-agentcore-control update-dataset-examples \
    --dataset-id my-dataset-id \
    --cli-input-json file://update-examples.json

Para excluir exemplos com a AgentCore CLI, remova as linhas correspondentes do arquivo JSONL local e reimplante:

# Edit agentcore/datasets/my_eval_dataset.jsonl — remove lines
agentcore deploy

A implantação detecta cenários removidos e os exclui do serviço.

from bedrock_agentcore.evaluation import DatasetClient

client = DatasetClient(region_name="us-west-2")

ds = client.delete_examples_and_wait(
    datasetId="my-dataset-id",
    exampleIds=["example-id-1", "example-id-2"],
)

import boto3
import time

client = boto3.client('bedrock-agentcore-control')

client.delete_dataset_examples(
    datasetId='my-dataset-id',
    exampleIds=['example-id-1', 'example-id-2']
)

# Poll until ACTIVE
while True:
    ds = client.get_dataset(datasetId='my-dataset-id')
    if ds['status'] == 'ACTIVE':
        break
    time.sleep(2)

aws bedrock-agentcore-control delete-dataset-examples \
    --dataset-id my-dataset-id \
    --example-ids '["example-id-1", "example-id-2"]'

# Download examples to your local JSONL file (default: Draft)
agentcore dataset download --name my_eval_dataset

# Download examples from a published version
agentcore dataset download --name my_eval_dataset --version 1

from bedrock_agentcore.evaluation import DatasetClient

client = DatasetClient(region_name="us-west-2")

# List examples from Draft
resp = client.list_dataset_examples(datasetId="my-dataset-id")
for example in resp["examples"]:
    print(f"  {example['exampleId']}: {example['scenario_id']}")

# List examples from a published version
resp = client.list_dataset_examples(datasetId="my-dataset-id", datasetVersion="1")

import boto3

client = boto3.client('bedrock-agentcore-control')

resp = client.list_dataset_examples(datasetId='my-dataset-id')
for example in resp['examples']:
    print(f"  {example['exampleId']}: {example.get('scenario_id')}")

# List examples from a published version
resp = client.list_dataset_examples(datasetId='my-dataset-id', datasetVersion='1')

# List examples from Draft
aws bedrock-agentcore-control list-dataset-examples \
    --dataset-id my-dataset-id

# List examples from a published version
aws bedrock-agentcore-control list-dataset-examples \
    --dataset-id my-dataset-id \
    --dataset-version 1