Krea 3 Edit
集成
模型 id
krea/v3/edit
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/krea/v3/edit?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/krea/v3/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/krea/v3/edit", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/zh/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "krea/v3/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
}
通过 Doitong API 调用 Krea 3 Edit 模型(krea/v3/edit)。智能体文档:https://doitong.com/zh/developers/models/krea/v3/edit.md
POST https://api.doitong.ru/v1/run/krea/v3/edit?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
如果响应状态为 "queued" 或 "running",请轮询 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到状态变为 "succeeded";文件位于 outputs[].url。使用相同请求体 POST https://api.doitong.ru/v1/quote/krea/v3/edit,可在运行前返回确切价格。
此请求: ≈$0.026 26 API 积分 · ≈ ₽2.74 在此页面运行
你的新 API 密钥。 它仅在此时显示,并且已填入下方的代码和 API 密钥字段中。请妥善保密:切勿将其放入在浏览器中运行的代码。
构建请求
控件根据模型架构生成。更改控件时,代码和价格会同步更新。
POST
/run/krea/v3/edit?wait=20
报价 → $0.026
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/krea/v3/edit?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/krea/v3/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/krea/v3/edit", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "krea/v3/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"wait_seconds": 20
}
}
}
关于 Krea 3 Edit
根据最长 5000 个字符的 `prompt` 编辑或合并 `image_urls` 中的一到八张图像。`model` 选择 berry(质量)或 jam(速度)。`reasoning_level` 范围为 low 到 ultra,`image_size` 接受预设或 auto,最多 4,220,160 像素。`negative_prompt` 仅适用于 berry。
参数
发送规范名称或原生名称之一,不要同时发送两者。 规范名称
名称类型
默认值允许值
描述
prompt必填
类型string
≤ 5,000 个字符
所需输出图像的描述。
image_urls必填
images
类型url[] · image
≤ 8 个项目
按顺序排列的 1–8 个图像集合,用于编辑或组合;位置会分配 <image-N> 标签。
model可选
类型enum
默认值berry
berryjam
模型变体选择:berry 优先考虑质量,jam 优先考虑速度。
image_size可选
类型object
默认值auto
square_hdsquareportrait_4_3portrait_16_9landscape_4_3landscape_16_9auto
输出尺寸;也可使用 `auto`,让提示词扩展器选择约为 2048×2048 的比例。尺寸会向上取整为 16 的倍数,并受 4,220,160 像素总上限(1680×2512)限制。
reasoning_level可选
类型enum
默认值medium
lowmediumhighultra
编辑任务在 harness 中的推理强度:较高设置会延长生成时间,但提供更多推理。
negative_prompt可选
类型string
默认值
≤ 1,024 个字符
要从图像中排除的内容;只有 berry 使用此输入。
seed可选
类型integer | null
为之前生成的输出执行后续编辑时,为每次编辑选择新的潜空间噪声种子。
output_format可选
类型enum
默认值png
pngjpeg
结果图像的格式。
enable_safety_checker可选
类型boolean
默认值true
输出图像的不安全内容筛查。禁用此功能需要账户授权。
必填
规范名称,也可接受
文件参数接受公开的 https:// URL、最大 10 MB 的 data: URI,或上传文件的 file_url。 文件
输出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "krea/v3/edit",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 26,
"usd": "0.026",
"charged": 26,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image_urls": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"output": {
"images": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768
}
],
"seed": 42,
"prompt": "string",
"timings": {},
"has_nsfw_concepts": [
false
]
},
"outputs": [
{
"type": "image",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
你的文件,由你选择每个 outputs[].url 都是存储中的副本:可永久保存(按 GB-月付费),也可免费保存 7 天,由账户设置或 ?storage= 决定。
每个模型的结构相同图像、视频和音频均包含 type、url、content_type、width、height 和 duration。output 是模型自身的结果对象。
输出字段
- images
- array of object {url, content_type, file_name, file_size, width, height}生成得到的图像。
- seed
- integer生成期间提供潜空间噪声的种子。
- prompt
- string用于生成输出的扩展提示词。
- timings
- object以秒计的各阶段生成耗时,包括 `inference` 下的 GPU 采样总时间。
- has_nsfw_concepts
- array of boolean每个图像的安全评估。
其他 Krea 3 变体
更多模型:图像编辑
对于 AI 代理:此页面的 Markdown 版本位于 https://doitong.com/zh/developers/models/krea/v3/edit.md. 所有模型和指南: https://doitong.com/developers/llms.txt






