Qwen Image Edit 2509 Trainer
Integrasikan
qwen-image-edit-2509-trainer
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/qwen-image-edit-2509-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image_data_url": "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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/qwen-image-edit-2509-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image_data_url": "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/qwen-image-edit-2509-trainer", 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/ms/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "qwen-image-edit-2509-trainer",
"input": {
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Panggil model Qwen Image Edit 2509 Trainer (qwen-image-edit-2509-trainer) melalui Doitong API. Dokumentasi untuk ejen: https://doitong.com/ms/developers/models/qwen-image-edit-2509-trainer.md
POST https://api.doitong.com/v1/run/qwen-image-edit-2509-trainer?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Jika status respons ialah "queued" atau "running", tinjau GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 sehingga statusnya menjadi "succeeded"; fail berada dalam outputs[].url. POST https://api.doitong.com/v1/quote/qwen-image-edit-2509-trainer dengan badan yang sama mengembalikan harga tepat sebelum dijalankan.
Fail seperti contoh: $4.00 4,000 kredit API fail anda diukur sebelum dijalankan Jalankan pada halaman ini
Kunci API baharu anda. Ia hanya dipaparkan sekarang dan sudah dimasukkan dalam kod serta medan kunci API di bawah. Simpan secara rahsia: jangan sekali-kali letakkannya dalam kod yang berjalan dalam pelayar.
Hasil pertama anda akan muncul di sini
Bina permintaan di bawah dan jalankannya dengan kunci API anda. Output disalin ke storan kami, disimpan selama-lamanya atau 7 hari secara percuma.
Bina permintaan
Kawalan dijana daripada skema model. Kod dan harga dikemas kini apabila anda mengubahnya.
/run/qwen-image-edit-2509-trainer?wait=20
sebut harga → $4.00
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/qwen-image-edit-2509-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image_data_url": "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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/qwen-image-edit-2509-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image_data_url": "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/qwen-image-edit-2509-trainer", 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": "qwen-image-edit-2509-trainer",
"input": {
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Jalankan permintaan ini
Kunci anda kekal dalam pelayar ini: ia hanya dihantar kepada Doitong API dan disimpan (localStorage) hanya jika anda menanda Ingat. Dapatkan kunci API
Tentang Qwen Image Edit 2509 Trainer
Memadankan LoRA pada contoh sebelum/selepas anda sendiri. `image_data_url` menunjuk kepada zip pasangan imej bernama ROOT_start.EXT dan ROOT_end.EXT. Tetapkan `steps` (1 hingga 30000, lalai 1000) dan `learning_rate`, serta pilihan `default_caption` untuk pasangan tanpa fail kapsyen. Menghasilkan fail konfigurasi dan pemberat LoRA diffusers.
Parameter
image_data_urldiperlukan
learning_ratepilihan
stepspilihan
default_captionpilihan
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "qwen-image-edit-2509-trainer",
"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": 4000,
"usd": "4.00",
"charged": 4000,
"refunded": 0
},
"input": {
"image_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"output": {
"diffusers_lora_file": {
"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
},
"config_file": {
"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
}
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Medan output
- diffusers_lora_file
- object {url, content_type, file_name, file_size}URL yang menunjuk kepada pemberat LoRA terlatih dalam format diffusers.
- config_file
- object {url, content_type, file_name, file_size}URL yang menunjuk kepada fail konfigurasi model terlatih.
Lebih banyak model: Latihan
Untuk ejen AI: halaman ini dalam Markdown tersedia di https://doitong.com/ms/developers/models/qwen-image-edit-2509-trainer.md. Semua model dan panduan: https://doitong.com/developers/llms.txt