
文本转图像
从文本提示词创建 AI 图像
免费试用 Qwen Image Lora Edit API,用一张参考图和提示词完成 Alibaba 图像编辑、创意变体与 seed 可复现控制,适合产品图、视觉探索、营销素材和可扩展创意生产工作流。
立即体验 AI 图片生成
| 参数 | 价格 | 原价 | 折扣 |
|---|
Flaq AI 上的 Qwen Image Lora Edit API 为需要高质量提示词引导视觉转换的开发者和创意团队提供 Alibaba 图像编辑访问能力。这个 Qwen 图像编辑 API 集成可通过自然语言指令修改现有图像,并支持专业创意工作流、产品视觉、营销素材和设计迭代。它面向需要通过托管 API 路由获得稳定编辑输出的团队。
注意 请确保上传的图像和提示词符合 Alibaba 与 Flaq AI 安全要求。如果发生错误,请调整源图像或提示词后重试。
在浏览器中探索多种 AI 创作工具,用于快速图像和视频工作流,然后通过 Flaq AI 可用于生产的模型 API 扩展成功创意。Flaq AI 为所有模型提供统一 API 层,让你的工作流更容易使用和扩展。
// Step 1: Submit generation request
const response = await fetch('https://api.flaq.ai/api/v1/image/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'qwen-image-lora-edit',
prompt: 'Make the hair longer and more natural',
image_url_list: ['https://example.com/source-image.jpg'],
seed: 42
})
});
const { data } = await response.json();
const taskId = data.task_id;
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/image/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.images[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
# Step 1: Submit generation request
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/image/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'qwen-image-lora-edit',
'prompt': 'Make the hair longer and more natural',
'image_url_list': ['https://example.com/source-image.jpg'],
'seed': 42
}
)
result = response.json()
task_id = result['data']['task_id']
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/image/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['images'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
# Step 1: Submit generation request
curl -X POST https://api.flaq.ai/api/v1/image/task \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "qwen-image-lora-edit",
"prompt": "Make the hair longer and more natural",
"image_url_list": ["https://example.com/source-image.jpg"],
"seed": 42
}'
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/image/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"