流式输出

传入 stream: true 即可让响应以 Server-Sent Events 流的形式逐 token 推送，适合实时打字机效果。

请求

bash

curl https://onegate.club/v1/chat/completions \
  -H "Authorization: Bearer $ONEGATE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "messages": [{"role": "user", "content": "Write a haiku."}],
    "stream": true
  }'

事件流

每个事件以 data: 开头，承载一个增量 delta。流末尾发送 data: [DONE]。

text

data: {"id":"chatcmpl-...","choices":[{"index":0,"delta":{"role":"assistant","content":""}}]}

data: {"id":"chatcmpl-...","choices":[{"index":0,"delta":{"content":"Soft"}}]}

data: {"id":"chatcmpl-...","choices":[{"index":0,"delta":{"content":" cherry"}}]}

data: {"id":"chatcmpl-...","choices":[{"index":0,"delta":{"content":" blossoms..."}}]}

data: [DONE]

Python 客户端

python

stream = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Tell a short story."}],
    stream=True,
)

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

Node.js 客户端

javascript

const stream = await client.chat.completions.create({
  model: "gpt-5.1",
  messages: [{ role: "user", content: "Tell a short story." }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0].delta.content ?? "");
}

流式响应也计入 token 用量。stream_options.include_usage = true 可让最后一条事件包含完整 usage 字段。

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