VEO 3.1 Official 图生视频 API 参考

{/* OpenAI 官方 SDK 没有 videos.create 方法，/v1/videos 是自定义路径，需用底层 client.post() */}
from openai import OpenAI
import time, mimetypes

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apiyi.com/v1"
)

# 第 1 步：multipart 上传（OpenAI SDK 底层 client.post 自动处理 multipart 边界）
with open("./lighthouse.png", "rb") as f:
    resp = client.post(
        "/videos",
        body=None,
        files={
            "input_reference": ("lighthouse.png", f, "image/png")
        },
        extra_body={
            "model": "veo-3.1-fast-generate-preview",
            "prompt": "镜头从灯塔基座缓慢上升至塔顶，黄昏光线，海浪声",
            "duration": "8",  # ⚠️ 必须字符串
            "size": "1280x720",
            "resolution": "720p",
            "aspectRatio": "16:9"
        },
        cast_to=dict
    )
task_id = resp["task_id"]
print(f"Task ID: {task_id}, status: {resp['status']}")

# 第 2 步：轮询（最长等 3 分钟）
deadline = time.time() + 180
while time.time() < deadline:
    status_resp = client.get(f"/videos/{task_id}", cast_to=dict)
    print(f"Status: {status_resp['status']}, progress: {status_resp.get('progress', 0)}%")
    if status_resp["status"] == "completed":
        break
    if status_resp["status"] == "failed":
        raise RuntimeError(f"Generation failed: {status_resp}")
    time.sleep(8)

# 第 3 步：下载（带重试兜底）
import urllib.request, urllib.error
time.sleep(4)
for i in range(5):
    try:
        req = urllib.request.Request(
            f"https://api.apiyi.com/v1/videos/{task_id}/content",
            headers={"Authorization": "Bearer sk-your-api-key"}
        )
        with urllib.request.urlopen(req, timeout=180) as r, open("output.mp4", "wb") as f:
            while chunk := r.read(1 << 16):
                f.write(chunk)
        break
    except urllib.error.HTTPError as e:
        if i == 4:
            raise
        time.sleep(4)
print("Saved: output.mp4")

import requests
import time

API_KEY = "sk-your-api-key"
BASE_URL = "https://api.apiyi.com/v1"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# 第 1 步：multipart 上传参考图 + 表单字段
with open("./lighthouse.png", "rb") as f:
    resp = requests.post(
        f"{BASE_URL}/videos",
        headers=HEADERS,  # 不要手动加 Content-Type，requests 会自动处理 multipart 边界
        data={
            "model": "veo-3.1-fast-generate-preview",
            "prompt": "镜头从灯塔基座缓慢上升至塔顶，黄昏光线，海浪轻拍礁石的声音",
            "duration": "8",  # ⚠️ 字符串，不是数字
            "size": "1280x720",
            "resolution": "720p",
            "aspectRatio": "16:9",
            "seed": "20260521"
        },
        files={
            "input_reference": ("lighthouse.png", f, "image/png")
        },
        timeout=60  # multipart 上传大图可能慢，超时建议 60 秒
    ).json()
task_id = resp["task_id"]
print(f"Task ID: {task_id}")

# 第 2 步：轮询
deadline = time.time() + 180
while time.time() < deadline:
    s = requests.get(f"{BASE_URL}/videos/{task_id}", headers=HEADERS).json()
    print(f"Status: {s['status']}, progress: {s.get('progress', 0)}%")
    if s["status"] == "completed":
        break
    if s["status"] == "failed":
        raise RuntimeError(s)
    time.sleep(8)

# 第 3 步：下载（带 3 次重试）
time.sleep(4)
for i in range(5):
    try:
        with requests.get(
            f"{BASE_URL}/videos/{task_id}/content",
            headers=HEADERS, stream=True, timeout=180
        ) as r:
            r.raise_for_status()
            with open("output.mp4", "wb") as f:
                for chunk in r.iter_content(chunk_size=8192):
                    f.write(chunk)
        break
    except requests.HTTPError:
        if i == 4:
            raise
        time.sleep(4)
print("Saved: output.mp4")

{/* 第 1 步：multipart 上传（注意 -F 字段顺序，input_reference 用 @ 引用本地文件）*/}
RESP=$(curl -sS -X POST "https://api.apiyi.com/v1/videos" \
  -H "Authorization: Bearer sk-your-api-key" \
  -F "model=veo-3.1-fast-generate-preview" \
  -F "prompt=镜头从灯塔基座缓慢上升至塔顶，黄昏光线" \
  -F "duration=8" \
  -F "size=1280x720" \
  -F "resolution=720p" \
  -F "aspectRatio=16:9" \
  -F "input_reference=@./lighthouse.png;type=image/png")
TASK_ID=$(echo "$RESP" | python3 -c 'import sys,json;print(json.load(sys.stdin)["task_id"])')
echo "task_id=$TASK_ID"

{/* 第 2 步：轮询状态 */}
while :; do
  S=$(curl -sS -H "Authorization: Bearer sk-your-api-key" "https://api.apiyi.com/v1/videos/$TASK_ID")
  ST=$(echo "$S" | python3 -c 'import sys,json;print(json.load(sys.stdin)["status"])')
  echo "status=$ST"
  [ "$ST" = "completed" ] && break
  [ "$ST" = "failed" ] && { echo "$S"; exit 1; }
  sleep 8
done

{/* 第 3 步：下载（--retry 兜底 status=completed 后的偶发 400）*/}
sleep 4
curl -sSL --retry 3 --retry-delay 4 \
  -H "Authorization: Bearer sk-your-api-key" \
  "https://api.apiyi.com/v1/videos/$TASK_ID/content" \
  -o output.mp4
ls -lh output.mp4

import fs from 'node:fs';
import { FormData, File } from 'undici';

const API_KEY = 'sk-your-api-key';
const BASE_URL = 'https://api.apiyi.com/v1';

// 第 1 步：multipart 上传
const buffer = fs.readFileSync('./lighthouse.png');
const form = new FormData();
form.append('model', 'veo-3.1-fast-generate-preview');
form.append('prompt', '镜头从灯塔基座缓慢上升至塔顶，黄昏光线');
form.append('duration', '8');  // ⚠️ 字符串
form.append('size', '1280x720');
form.append('resolution', '720p');
form.append('aspectRatio', '16:9');
form.append('input_reference', new File([buffer], 'lighthouse.png', { type: 'image/png' }));

const submitResp = await fetch(`${BASE_URL}/videos`, {
    method: 'POST',
    headers: { 'Authorization': `Bearer ${API_KEY}` },  // 不要手动加 Content-Type
    body: form
});
const { task_id } = await submitResp.json();
console.log(`Task ID: ${task_id}`);

// 第 2 步：轮询
let status = 'queued';
while (status !== 'completed' && status !== 'failed') {
    await new Promise(r => setTimeout(r, 8000));
    const s = await (await fetch(`${BASE_URL}/videos/${task_id}`, {
        headers: { 'Authorization': `Bearer ${API_KEY}` }
    })).json();
    status = s.status;
    console.log(`Status: ${status}, progress: ${s.progress ?? 0}%`);
}

if (status === 'failed') throw new Error('Generation failed');

// 第 3 步：下载（带重试）
await new Promise(r => setTimeout(r, 4000));
let videoBuffer;
for (let i = 0; i < 4; i++) {
    try {
        const resp = await fetch(`${BASE_URL}/videos/${task_id}/content`, {
            headers: { 'Authorization': `Bearer ${API_KEY}` }
        });
        if (!resp.ok) throw new Error(`HTTP ${resp.status}`);
        videoBuffer = Buffer.from(await resp.arrayBuffer());
        break;
    } catch (e) {
        if (i === 3) throw e;
        await new Promise(r => setTimeout(r, 4000));
    }
}
fs.writeFileSync('output.mp4', videoBuffer);
console.log('Saved: output.mp4');

{/* 仅作演示，生产请走后端代理避免 Key 泄露；视频文件较大也不适合直接在浏览器下载 */}
const fileInput = document.querySelector('input[type=file]');
const file = fileInput.files[0];

const form = new FormData();
form.append('model', 'veo-3.1-fast-generate-preview');
form.append('prompt', '让这张静态画面动起来，缓慢推镜，自然环境音');
form.append('duration', '4');
form.append('size', '720x1280');
form.append('resolution', '720p');
form.append('aspectRatio', '9:16');
form.append('input_reference', file);

const submitResp = await fetch('https://api.apiyi.com/v1/videos', {
    method: 'POST',
    headers: { 'Authorization': 'Bearer sk-your-api-key' },
    body: form
});
const { task_id } = await submitResp.json();
console.log('Task ID:', task_id);

{/* 轮询完成后，把 /content 端点交给后端代理下载，再回流给前端展示 */}

{
  "id": "task_xxxxxxxxxxxxxxxx",
  "task_id": "task_xxxxxxxxxxxxxxxx",
  "object": "video",
  "model": "veo-3.1-fast-generate-preview",
  "status": "queued",
  "progress": 0,
  "created_at": 1775025000
}