如何通过 EvoLink 使用 Midjourney V8.1 API：代码示例、轮询与 Callback

curl --request POST \
  --url https://api.evolink.ai/v1/images/generations \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "mj-v8.1",
    "prompt": "a premium product photo of a matte black espresso machine on a marble counter --ar 16:9 --s 250",
    "quality": "standard",
    "model_params": {
      "speed": "fast"
    },
    "callback_url": "https://your-domain.com/webhooks/evolink-image-task"
  }'

curl --request GET \
  --url https://api.evolink.ai/v1/tasks/<task_id> \
  --header 'Authorization: Bearer YOUR_API_KEY'

Authorization: Bearer YOUR_API_KEY

用户在你的产品中发起生成
  -> 你的后端 API route
  -> EvoLink 图像生成接口
  -> 保存 task_id
  -> 轮询或接收 callback
  -> 保存结果到你自己的存储
  -> 在产品中展示最终图片

POST https://api.evolink.ai/v1/images/generations

{
  "model": "mj-v8.1"
}

curl --request POST \
  --url https://api.evolink.ai/v1/images/generations \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "mj-v8.1",
    "prompt": "a cinematic product photo of a titanium travel mug on wet black stone, soft studio reflection, premium outdoor brand style --ar 16:9 --s 250 --chaos 8",
    "quality": "standard",
    "model_params": {
      "speed": "fast"
    }
  }'

{
  "created": 1757156493,
  "id": "task-unified-1757156493-xkd8mv2r",
  "model": "mj-v8.1",
  "object": "image.generation.task",
  "progress": 0,
  "status": "pending",
  "task_info": {
    "can_cancel": true,
    "estimated_time": 120
  },
  "type": "image",
  "usage": {
    "billing_rule": "per_call",
    "credits_reserved": 6.0,
    "user_group": "default"
  }
}

curl --request POST \
  --url https://api.evolink.ai/v1/images/generations \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "mj-v8.1",
    "prompt": "https://your-cdn.example.com/reference-sofa.jpg a luxury living room campaign image, keep the sofa shape and fabric feel, warm morning light --ar 4:3 --iw 1.2 --s 200",
    "quality": "standard",
    "model_params": {
      "speed": "fast"
    }
  }'

{
  "model": "mj-v8.1",
  "prompt": "a premium skincare bottle on a clean studio set, soft shadows, commercial beauty lighting --ar 1:1 --sref https://your-cdn.example.com/brand-style.jpg --sw 180 --oref https://your-cdn.example.com/product-object.jpg --ow 250",
  "quality": "standard",
  "model_params": {
    "speed": "fast"
  }
}

curl --request GET \
  --url https://api.evolink.ai/v1/tasks/task-unified-1757156493-xkd8mv2r \
  --header 'Authorization: Bearer YOUR_API_KEY'

{
  "created": 1756817821,
  "id": "task-unified-1756817821-4x3rx6ny",
  "model": "mj-v8.1",
  "object": "image.generation.task",
  "progress": 100,
  "results": [
    "https://cdn.evolink.ai/images/generated-image-abc123.jpg"
  ],
  "status": "completed",
  "task_info": {
    "can_cancel": false
  },
  "type": "image"
}

{
  "model": "mj-v8.1",
  "prompt": "a clean hero image for a travel booking app, modern airport lounge, premium editorial photo style --ar 16:9",
  "quality": "standard",
  "model_params": {
    "speed": "fast"
  },
  "callback_url": "https://your-domain.com/webhooks/evolink-image-task"
}

{
  "model": "mj-v8.1",
  "prompt": "a premium product photo of a ceramic desk lamp on a walnut table, soft window light, editorial interior design style --ar 4:3 --s 180",
  "quality": "standard",
  "model_params": {
    "speed": "fast"
  }
}

{
  "model": "mj-v8.1",
  "prompt": "a luxury resort terrace overlooking a futuristic skyline at golden hour, cinematic commercial photography, elegant travel campaign mood --ar 16:9 --s 300 --chaos 6",
  "quality": "hd",
  "model_params": {
    "speed": "fast"
  },
  "callback_url": "https://your-domain.com/webhooks/evolink-image-task"
}

{
  "model": "mj-v8.1",
  "prompt": "https://your-cdn.example.com/reference-chair.jpg a modern ecommerce lifestyle photo, keep the chair silhouette, add a bright Scandinavian apartment setting --ar 3:2 --iw 1.4 --s 150",
  "quality": "standard",
  "model_params": {
    "speed": "fast"
  }
}

{
  "model": "mj-v8.1",
  "prompt": "a set of premium coffee packaging on a clean studio background --ar 1:1 --sref https://your-cdn.example.com/brand-moodboard.jpg --sw 220 --s 200",
  "quality": "standard",
  "model_params": {
    "speed": "fast"
  }
}

const API_KEY = process.env.EVOLINK_API_KEY;
const BASE_URL = "https://api.evolink.ai/v1";

async function createMidjourneyTask() {
  const response = await fetch(`${BASE_URL}/images/generations`, {
    method: "POST",
    headers: {
      Authorization: `Bearer ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      model: "mj-v8.1",
      prompt: "a premium product photo of a smart speaker on a stone plinth --ar 16:9 --s 250",
      quality: "standard",
      model_params: {
        speed: "fast"
      }
    })
  });

  if (!response.ok) {
    throw new Error(`EvoLink task create failed: ${response.status}`);
  }

  return response.json();
}

async function getTask(taskId) {
  const response = await fetch(`${BASE_URL}/tasks/${taskId}`, {
    headers: {
      Authorization: `Bearer ${API_KEY}`
    }
  });

  if (!response.ok) {
    throw new Error(`EvoLink task query failed: ${response.status}`);
  }

  return response.json();
}

async function waitForTask(taskId) {
  for (let attempt = 0; attempt < 60; attempt += 1) {
    const task = await getTask(taskId);

    if (task.status === "completed") return task;
    if (task.status === "failed") throw new Error(`Task failed: ${task.id}`);

    await new Promise((resolve) => setTimeout(resolve, 5000));
  }

  throw new Error(`Task timeout: ${taskId}`);
}

import os
import time
import requests

API_KEY = os.environ["EVOLINK_API_KEY"]
BASE_URL = "https://api.evolink.ai/v1"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json",
}

payload = {
    "model": "mj-v8.1",
    "prompt": "a premium product photo of a minimalist wristwatch on dark slate --ar 16:9 --s 220",
    "quality": "standard",
    "model_params": {
        "speed": "fast",
    },
}

create_response = requests.post(
    f"{BASE_URL}/images/generations",
    headers=headers,
    json=payload,
    timeout=30,
)
create_response.raise_for_status()
task = create_response.json()
task_id = task["id"]

for _ in range(60):
    status_response = requests.get(
        f"{BASE_URL}/tasks/{task_id}",
        headers={"Authorization": f"Bearer {API_KEY}"},
        timeout=30,
    )
    status_response.raise_for_status()
    current = status_response.json()

    if current["status"] == "completed":
        print(current.get("results", []))
        break

    if current["status"] == "failed":
        raise RuntimeError(f"Task failed: {task_id}")

    time.sleep(5)
else:
    raise TimeoutError(f"Task timeout: {task_id}")