SDK タスクポーリングとストリーミングレスポンス

import os, time
from acedatacloud import AceDataCloud

client = AceDataCloud(api_token=os.environ["ACEDATACLOUD_API_TOKEN"])

# wait=False ですぐに handle を取得
handle = client.images.generate(
    provider="midjourney",
    prompt="a cinematic photo of a banana wearing a tuxedo",
    wait=False,
)
print("task_id", handle.id)

t0 = time.time()
result = handle.wait(poll_interval=3.0, max_wait=180.0)
print("elapsed_s", round(time.time() - t0, 1))
print("status", result.get("response", result).get("status"))
print("images", [it.get("image_url") for it in (result.get("response", result).get("data") or [])])

import { AceDataCloud } from '@acedatacloud/sdk';

const client = new AceDataCloud();

// wait: false ですぐに handle を取得
const handle: any = await client.images.generate({
  provider: 'midjourney',
  prompt: 'a cinematic photo of a banana wearing a tuxedo',
  wait: false,
});
console.log('task_id', handle.id);

const t0 = Date.now();
const result: any = await handle.wait({ pollInterval: 3000, maxWait: 180_000 });
console.log('elapsed_s', ((Date.now() - t0) / 1000).toFixed(1));
const response = result.response ?? result;
console.log('status', response.status);
console.log('images', (response.data ?? []).map((it: any) => it.image_url));

# ✅ 推奨
res = client.images.generate(provider="nano-banana", prompt="...")
url = res["data"][0]["image_url"]

# ❌ 反例：SDK 内部が /nano-banana/tasks をポーリングすることを引き起こし、RTT を無駄にします
res = client.images.generate(provider="nano-banana", prompt="...", wait=True)

POST {API_BASE}/<provider>/tasks
Authorization: Bearer {token}
Content-Type: application/json

{"id": "<task_id>", "action": "retrieve"}

{
  "task_id": "...",
  "trace_id": "...",
  "response": {
    "status": "pending | running | succeeded | failed",
    "data": [...]
  }
}

import { AceDataCloud } from '@acedatacloud/sdk';

const client = new AceDataCloud();

const stream: any = await client.openai.chat.completions.create({
  model: 'gpt-4o-mini',
  messages: [{ role: 'user', content: '1から5までをスペースで区切って数えてください。数字だけ。' }],
  max_tokens: 30,
  temperature: 0,
  stream: true
});

let chunks = 0;
let collected = '';
for await (const chunk of stream) {
  chunks++;
  const delta = chunk?.choices?.[0]?.delta?.content;
  if (delta) collected += delta;
}
console.log('chunks', chunks);
console.log('collected', collected);

total_elapsed_ms 2616
first_chunk_ms 2481
chunks 13
collected 1 2 3 4 5

import os
from acedatacloud import AceDataCloud

client = AceDataCloud(api_token=os.environ["ACEDATACLOUD_API_TOKEN"])

chunks = 0
collected = []
for chunk in client.openai.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "1から5までをスペースで区切って数えてください。数字だけ。"}],
    max_tokens=30,
    temperature=0,
    stream=True,
):
    chunks += 1
    delta = (chunk.get("choices") or [{}])[0].get("delta", {}).get("content")
    if delta:
        collected.append(delta)
print("chunks", chunks)
print("collected", "".join(collected))

total_elapsed_ms 2111
first_chunk_ms 2104
chunks 12
collected 1 2 3 4 5

chunks, errs := client.OpenAI().Chat().Completions().CreateStream(ctx, adc.ChatCompletionRequest{
    Model:     "gpt-4o-mini",
    Messages:  []map[string]any{{"role": "user", "content": "1から5までをスペースで区切って数えてください。数字だけ。"}},
    MaxTokens: 30,
})
cnt := 0
collected := ""
for chunk := range chunks {
    cnt++
    if ch, ok := chunk["choices"].([]any); ok && len(ch) > 0 {
        if d, ok := ch[0].(map[string]any)["delta"].(map[string]any); ok {
            if s, ok := d["content"].(string); ok {
                collected += s
            }
        }
    }
}
if e, ok := <-errs; ok && e != nil {
    log.Println("stream_err", e)
}
fmt.Println("chunks", cnt, "collected", collected)

total_elapsed_ms 1816
first_chunk_ms 1633
chunks 13
collected 1 2 3 4 5

{
  "id": "chatcmpl-...",
  "object": "chat.completion.chunk",
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "delta": {
        "content": " 3"
      },
      "finish_reason": null
    }
  ]
}