Amazon Bedrock의 Claude Tool Use를 활용한 맞춤형 엔티티 인식 가속화

import boto3, json
import base64

def lambda_handler(event, context):
    bedrock = boto3.client("bedrock-runtime")
    s3 = boto3.client("s3")
    bucket = event["Records"][0]["s3"]["bucket"]["name"]
    key = event["Records"][0]["s3"]["object"]["key"]
    file = s3.get_object(Bucket=bucket, Key=key)

    # Convert image to base64
    image_data = file["Body"].read()
    base64_image = base64.b64encode(image_data).decode('utf-8')

    # Define tool schema
    tools = [{
        "name": "extract_license_fields",
        "input_schema": {
            "type": "object",
            "properties": {
                "first_name": { "type": "string" },
                "last_name": { "type": "string" },
                "issue_date": { "type": "string" },
                "license_number": { "type": "string" },
                "address": {
                    "type": "object",
                    "properties": {
                        "street": { "type": "string" },
                        "city": { "type": "string" },
                        "state": { "type": "string" },
                        "zip": { "type": "string" }
                    }
                }
            },
            "required": ["first_name", "last_name", "issue_date", "license_number", "address"]
        }
    }]

    payload = {
        "anthropic_version": "bedrock-2023-05-31",
        "max_tokens": 2048,
        "messages": [{
            "role": "user",
            "content": [
                { "type": "image", "source": { "type": "base64", "media_type": "image/jpeg", "data": base64_image } },
                { "type": "text", "text": "Extract the driver's license fields from this image." }
            ]
        }],
        "tools": tools
    }
    // ...(중략)