10. 참고: 배치 API 활용하여 비용 절감하기¶
대량의 문서를 벡터 데이터로 변환하는 작업은 그만큼 비용도 많이 들어갑니다. 실시간으로 벡터 데이터를 처리하지 않고 최대 24시간의 여유를 가지고 변환을 해도 된다면 배치 API를 활용하여 비용을 50% 절감할 수 있습니다. 대개 24시간보다 더 빠르게 완료됩니다. 임베딩 모델을 포함한 모든 모델 요청에 대해서 배치 API를 활용할 수 있습니다.
OpenAI Batch API를 활용하시거나, 아래와 같이 웹 대시보드의 Batches 페이지를 통해서도 배치 요청을 할 수 있습니다.
10.1. 웹 대시보드 활용 예시¶
OpenAI 웹 대시보드 Batches 페이지를 통해서 5만건의 임베딩 배치 처리를 하는 예시를 살펴보겠습니다.
+ Create 버튼을 클릭하시면 아래와 같은 배치 생성 폼이 뜨고, 3개의 입력 필드가 있습니다.
Input file : 임베딩 요청 데이터를 단일 파일로 작성한 파일을 업로드합니다.
jsonl형식만 가능합니다.Completion window : 배치 요청이 완료되어야할 마감시간을 설정합니다.
24 hours고정입니다.Endpoint : 배치 내 모든 요청에서 사용하는 엔드포인트를 지정합니다.
/v1/chat/completions/v1/embeddings: 임베딩 요청/v1/completions
10.1.1. 입력 jsonl 파일 예시¶
배치 요청을 위한 입력 파일은 jsonl (json + line) 형식이어야 합니다.
각 줄마다 완전한 json 형식어야 합니다.
각 줄은 하나의 요청을 나타내며, 각 요청은 아래와 같은 필드를 포함해야 합니다.
custom_id: 요청을 식별하기 위한 고유 ID로서, 파일 내에서 유일한 값이어야 합니다. 중복된 값이 있을 경우 배치 처리하기 전에 유효성 검사 단계에서 오류가 발생합니다.예:
"24f588995d774780967e1a12afbf0005"
method: API 요청 메서드예:
"POST"
url: 요청할 API 엔드포인트예:
"/v1/embeddings"
body: API 요청 본문. 일반 API 요청과 동일한 형식임베딩 요청의 경우,
model필드와input필드를 가집니다.
아래와 같이 줄 단위로 json 포맷으로 요청 내역을 만들어야 합니다.
input.jsonl¶{"custom_id": "24f588995d774780967e1a12afbf0005", "method": "POST", "url": "/v1/embeddings", "body": {"model": "text-embedding-3-large", "input": "임베딩 텍스트 #1"}}
{"custom_id": "4f73b4c3544d486fa0eaa52b905a9216", "method": "POST", "url": "/v1/embeddings", "body": {"model": "text-embedding-3-large", "input": "임베딩 텍스트 #2"}}
{"custom_id": "bb932da5563148cba424ff4a786f3c4d", "method": "POST", "url": "/v1/embeddings", "body": {"model": "text-embedding-3-large", "input": "임베딩 텍스트 #3"}}
10.1.2. 배치 요청¶
50,000건의 임베딩 배치 요청을 하고, 현재 처리 중인 모습입니다. 각 임베딩 요청의 문자열은 토큰 수 제한에 맞춰져 있습니다.
50,000건의 임베딩 요청이 실패없이 완료된 모습입니다. 총 2시간 30분이 소요되었습니다.
10.1.3. 생성된 jsonl 파일 예시¶
배치 요청이 끝나고 나서, Output 링크에서 생성된 jsonl 파일을 다운받으실 수 있습니다.
각 줄은 json 포맷으로서 id, custom_id, response, error 필드를 가지며,
response 필드는 일반 API 응답 본문과 동일합니다.
output.jsonl¶{"id": "batch_req_67a06e9184508190a1a65020d302a991", "custom_id": "24f588995d774780967e1a12afbf0005", "response": {"status_code": 200, "request_id": "ca2d4bdd4a714a6205ff860cf20766ae", "body": {"object": "list", "data": [{"object": "embedding", "index": 0, "embedding": [0.0066079637, -0.013486774, -0.0068197795, 0.011653351, 0.027362457, 0.023723388, -0.027112443, 0.01650081, -0.022237204, 0.013722897, 0.011299167, -0.021445498, 0.018195339, -0.006625326, -0.005257203, -0.014750725, -0.039585277, 0.015695216, -0.0017865462, -0.019792639, 0.014625719, 0.013215927, 0.013792344, -0.020903805, -0.012396443, 0.016348027, -0.0064621232, 0.015320198, -0.025154015, 0.01751475, -0.0422243, 0.007173964, -0.013625669, -0.021348272, -0.0046252273, -0.0077295466, -0.0016242118, 0.05358597, -0.013056197, -0.00045661966, -0.023501156, 0.0042189574, -0.051585868, 0.016306357, -0.013299265, -0.011924197, 0.006882283, -0.0298348, -0.036557354, -0.0018264786, 0.0044203564, 0.007924001, 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// 생략 ...