GPT Image 2.5 Edit
Integriruj
openai/gpt-image-2.5/flare/edit
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://vit.doitong.com/api/v1/run/openai/gpt-image-2.5/flare/edit?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://vit.doitong.com/api/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/openai/gpt-image-2.5/flare/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://vit.doitong.com/api/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
],
"quality": "medium",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/openai/gpt-image-2.5/flare/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/rom/developers/docs/mcp)
claude mcp add --transport http doitong-models https://vit.doitong.com/api/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "openai/gpt-image-2.5/flare/edit",
"input": {
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}
}
Kall o GPT Image 2.5 Edit modelo (openai/gpt-image-2.5/flare/edit) vas o Doitong API. Dokumentacia vaš agentura: https://doitong.com/rom/developers/models/openai/gpt-image-2.5/flare/edit.md
POST https://vit.doitong.com/api/v1/run/openai/gpt-image-2.5/flare/edit?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}
Te o response status si "queued" vaj "running", ker polling GET https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20 dži kaj te avel "succeeded"; e fajlo si andro outputs[].url. POST https://vit.doitong.com/api/v1/quote/openai/gpt-image-2.5/flare/edit sa jekhe body-esa del o precizno molipen angl-o phiripen.
Kava mangipen: ≈$0.12 120 API krediti Phir les kate
Tiro nevo API klidin. Dikhavel pes akana numa thaj si angleder ando kodo thaj ando API klidin kotor tele. Garav les: na thovel les ande kodo savo keren andre jekh browser.
Tiro prvo rezultato si kate
Ker tele jekh mangipen thaj phir les tire API klidinosa. E rezultatur si kopirime amare arakhipneste, vično vaj 7 dives bilačhes.
Ker jekh mangipen
O kontrolura kerde si katar e schemaske. O kodo thaj e cena menjinen sar tu len menjines.
/run/openai/gpt-image-2.5/flare/edit?wait=20
hesab → $0.12
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://vit.doitong.com/api/v1/run/openai/gpt-image-2.5/flare/edit?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://vit.doitong.com/api/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/openai/gpt-image-2.5/flare/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://vit.doitong.com/api/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
],
"quality": "medium",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/openai/gpt-image-2.5/flare/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": "openai/gpt-image-2.5/flare/edit",
"input": {
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
},
"wait_seconds": 20
}
}
}
Phandel kava mangipen
Tiro kluč ačhel kadale browsereste: bičhalel pes numa ko Doitong API thaj šuvav pes (localStorage) numa te tiknes Remember. Le jekh API ključ
Palal GPT Image 2.5 Edit
Editiripasko modo GPT Image 2.5: vaker keripe thaj bičhav dži 16 referencne kipo, opcionalno jekh maskasa savi limitirin kaj šaj te čhivel modelo. Podporinel transparentne pozadine, paň kvaliteto nivoja thaj dži des rezultato pala jekh mangipen.
Parametra
Bičhalav vaj e kanonikano nav vaj e native nav, na duj. Kanonikane nava
prompttrubul
image_urlstrubul
images
mask_urlopcionalno
mask
image_sizeopcionalno
backgroundopcionalno
qualityopcionalno
num_imagesopcionalno
num_outputs
output_formatopcionalno
output_compressionopcionalno
Fajloske parametra lel jekh publikano https:// URL, jekh data: URI dži 10 MB, vaj e file_url uploadoski. Fajlura
Rezultato
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "openai/gpt-image-2.5/flare/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": 120,
"usd": "0.12",
"charged": 120,
"refunded": 0
},
"input": {
"prompt": "Same sneaker, but on a snowy mountain trail in daylight",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
],
"quality": "medium"
},
"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
}
]
},
"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://vit.doitong.com/api/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://vit.doitong.com/api/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Outputoske fieldura
- images
- array of object {url, content_type, file_name, file_size, width, height}Kipo kerdine e modeloça.
Aver variantura e GPT Image 2.5
Bute modeli: Editime e kipesko
AI agentenge: kadija rig sar Markdown si kate https://doitong.com/rom/developers/models/openai/gpt-image-2.5/flare/edit.md. Sa e modelura thaj e gidura: https://doitong.com/developers/llms.txt










