Bedrockの新機能 Structured Outputs (構造化出力)でJSON出力を厳格化してみた

FROM python:3.12-slim

WORKDIR /app

# キャッシュを使わず最新版をインストール
RUN pip install --no-cache-dir boto3 --upgrade

COPY . .

# バージョン確認と実行
CMD pip show boto3 | grep Version && python structured_outputs_demo.py

# ビルド
docker build -t bedrock-structured-demo .

# 実行（クレデンシャルを渡す）
docker run --rm \
  -e AWS_ACCESS_KEY_ID \
  -e AWS_SECRET_ACCESS_KEY \
  -e AWS_SESSION_TOKEN \
  -e AWS_DEFAULT_REGION=ap-northeast-1 \
  bedrock-structured-demo

Version: 1.42.42

import boto3
import json
import os

bedrock = boto3.client("bedrock-runtime", region_name="ap-northeast-1")
MODEL_ID = "global.anthropic.claude-sonnet-4-5-20250929-v1:0"

# 入力データ
csv_input = """date,product,quantity,price,region
2026-01-15,ノートPC,5,89800,東京
2026-01-15,マウス,20,2980,大阪
2026-01-16,キーボード,8,12800,東京
2026-01-16,モニター,3,45000,福岡"""

# JSON Schema定義
schema = {
    "type": "object",
    "properties": {
        "total_sales": {"type": "integer", "description": "総売上金額"},
        "total_items": {"type": "integer", "description": "総販売数"},
        "by_region": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "region": {"type": "string"},
                    "sales": {"type": "integer"}
                },
                "required": ["region", "sales"],
                "additionalProperties": False
            }
        },
        "top_product": {"type": "string", "description": "最も売上が高い商品"}
    },
    "required": ["total_sales", "total_items", "by_region", "top_product"],
    "additionalProperties": False
}

# リクエスト実行
try:
    response = bedrock.invoke_model(
        modelId=MODEL_ID,
        body=json.dumps({
            "anthropic_version": "bedrock-2023-05-31",
            "max_tokens": 1024,
            "messages": [{"role": "user", "content": f"以下のCSVデータを集計してください:\n\n{csv_input}"}],
            # ここでStructured Outputsを指定
            "output_config": {"format": {"type": "json_schema", "schema": schema}}
        }),
    )

    result = json.loads(response["body"].read())
    output_text = result["content"][0]["text"]

    # JSONとしてパースできるか確認
    output_json = json.loads(output_text)
    print(json.dumps(output_json, indent=2, ensure_ascii=False))

except Exception as e:
    print(f"Error: {e}")

{
  "total_sales": 743600,
  "total_items": 36,
  "by_region": [
    {
      "region": "東京",
      "sales": 551400
    },
    {
      "region": "大阪",
      "sales": 59600
    },
    {
      "region": "福岡",
      "sales": 135000
    }
  ],
  "top_product": "ノートPC"
}

# スキーマ定義（enumを使用）
schema_sentiment = {
    "type": "object",
    "properties": {
        "sentiment": {"type": "string", "enum": ["positive", "negative", "neutral"]}
    },
    "required": ["sentiment"],
    "additionalProperties": False
}

response = bedrock.converse(
    modelId=MODEL_ID,
    messages=[{"role": "user", "content": [{"text": "このサービスは本当に素晴らしい！使いやすくて感動しました。"}]}],
    outputConfig={
        "textFormat": {
            "type": "json_schema",
            "structure": {
                "jsonSchema": {
                    "schema": json.dumps(schema_sentiment), # 文字列として渡す必要あり
                    "name": "sentiment_analysis",          # 必須
                    "description": "感情分析結果"
                }
            }
        }
    },
)

output = json.loads(response["output"]["message"]["content"][0]["text"])
print(json.dumps(output, indent=2, ensure_ascii=False))

{
  "sentiment": "positive"
}

tool_config = {
    "tools": [{
        "toolSpec": {
            "name": "search_products",
            "description": "商品を検索する",
            "inputSchema": {
                "json": {
                    "type": "object",
                    "properties": {
                        "category": {"type": "string", "enum": ["electronics", "books"]},
                        "price_limit": {"type": "integer"}
                    },
                    "required": ["category", "price_limit"],
                    "additionalProperties": False
                }
            }
        }
    }],
    "toolChoice": {"auto": {}}, 
}