Amazon Rekognition, Neptune, Bedrock을 활용한 지능형 사진 검색 시스템 구축

config = {
    "people": [
        {"name": "alice", "gender": "woman", "role": "mother"},
        {"name": "jane", "gender": "girl", "role": "daughter"}
    ],
    "relationships": [
        {"from": "alice", "to": "jane", "type": "parent_of", "subtype": "mother_of"},
        {"from": "jane", "to": "david", "type": "sibling_of", "bidirectional": True}
    ]
}

for rel in relationships_data:
    g.V().has('name', rel["from"]).addE(rel["type"]).to(
        __.V().has('name', rel["to"])
    ).property('type', rel["subtype"]).next()

response = rekognition.detect_labels(
    Image={'Bytes': image_bytes},
    MaxLabels=20,
    MinConfidence=70
)

for label in response.get('Labels', []):
    label_name = label['Name']
    categories = [cat['Name'] for cat in label.get('Categories', [])]
    # Neptune에 belongs_to 관계 생성 로직 실행