응답 스트리밍(SSE)

왜 스트리밍할까요

서버 전송 이벤트(SSE)

OpenAI로 스트리밍하기

stream = client.chat.completions.create(
    model='gpt-4o-mini',
    messages=messages,
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end='', flush=True)

전체 응답 수집

buf = []
for chunk in stream:
    delta = chunk.choices[0].delta.content or ''
    buf.append(delta)
    print(delta, end='', flush=True)

full_text = ''.join(buf)
messages.append({'role': 'assistant', 'content': full_text})

Anthropic으로 스트리밍하기

with client.messages.stream(
    model='claude-sonnet-4-5',
    max_tokens=1024,
    messages=messages,
) as stream:
    for text in stream.text_stream:
        print(text, end='', flush=True)

    final = stream.get_final_message()
    print('\ndone, tokens:', final.usage.output_tokens)

도구 호출 스트리밍

for chunk in stream:
    delta = chunk.choices[0].delta
    if delta.tool_calls:
        for tc in delta.tool_calls:
            # tc.function.name and tc.function.arguments arrive as partial strings
            pass

역압과 취소

try:
    for chunk in stream:
        if request_was_cancelled():
            stream.close()
            break
finally:
    stream.close()

웹 서버를 통한 스트리밍

from fastapi.responses import StreamingResponse

def token_generator():
    for chunk in stream:
        delta = chunk.choices[0].delta.content or ''
        yield f'data: {delta}\n\n'

return StreamingResponse(token_generator(), media_type='text/event-stream')

문장 단위 버퍼링

buf = ''
for chunk in stream:
    buf += chunk.choices[0].delta.content or ''
    while '. ' in buf:
        sentence, buf = buf.split('. ', 1)
        speak(sentence + '.')

스트리밍된 JSON 구문 분석

지연 시간 지표: TTFT와 TPS

왜 스트리밍할까요

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