Luma Uni-1 Edit Max
Integrer
luma/agent/uni-1/v1/max/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/luma/agent/uni-1/v1/max/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",
"image": "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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/luma/agent/uni-1/v1/max/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"image": "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/luma/agent/uni-1/v1/max/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/no/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": "luma/agent/uni-1/v1/max/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Kall Luma Uni-1 Edit Max-modellen (luma/agent/uni-1/v1/max/edit) gjennom Doitong API. Dokumentasjon for agenter: https://doitong.com/no/developers/models/luma/agent/uni-1/v1/max/edit.md
POST https://api.doitong.ru/v1/run/luma/agent/uni-1/v1/max/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",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Hvis responsstatusen er "queued" eller "running", send GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20-forespørsler til den er "succeeded"; filene ligger i outputs[].url. POST https://api.doitong.ru/v1/quote/luma/agent/uni-1/v1/max/edit med samme innhold returnerer den nøyaktige prisen før kjøringen.
Filer som eksempelet: 0,105 $ 105 API-kreditter · ≈ 11,30 ₽ filene dine måles før kjøring Kjør den på denne siden
Din nye API-nøkkel. Den vises bare nå og er allerede satt inn i koden og i API-nøkkelfeltet nedenfor. Hold den hemmelig: Legg den aldri i kode som kjører i en nettleser.
Det første resultatet ditt kommer her
Bygg en forespørsel nedenfor og kjør den med API-nøkkelen din. Utdata kopieres til lagringen vår, lagret for alltid eller 7 dager gratis.
Bygg en forespørsel
Kontrollene genereres fra modellskjemaet. Koden og prisen oppdateres når du endrer dem.
/run/luma/agent/uni-1/v1/max/edit?wait=20
pris → 0,105 $
# 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/luma/agent/uni-1/v1/max/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",
"image": "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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/luma/agent/uni-1/v1/max/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"image": "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/luma/agent/uni-1/v1/max/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": "luma/agent/uni-1/v1/max/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Kjør denne forespørselen
Nøkkelen din blir i denne nettleseren: Den sendes bare til Doitong API og lagres bare i localStorage hvis du krysser av for Husk. Hent en API-nøkkel
Om Luma Uni-1 Edit Max
Bruker en tekstbeskrevet redigering på opptil 6000 tegn på kildebildet i `image_url`, samtidig som strukturen bevares. Opptil 8 `reference_image_urls` kan styre endringen. `style` er auto eller manga, og resultatet er PNG eller JPEG. Velg denne fremfor standardmodellen når du ønsker det høyere nivået.
Parametere
Send enten det kanoniske navnet eller det opprinnelige navnet, ikke begge. Kanoniske navn
promptobligatorisk
image_urlobligatorisk
image
stylevalgfritt
output_formatvalgfritt
reference_image_urlsvalgfritt
images
enable_safety_checkervalgfritt
Filparametere tar imot en offentlig https:// URL, en data: URI på opptil 10 MB eller file_url fra en opplasting. Filer
Utdata
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "luma/agent/uni-1/v1/max/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": 105,
"usd": "0.105",
"charged": 105,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image_url": "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
}
]
},
"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"
}
}
Utdatafelt
- images
- array of object {url, content_type, file_name, file_size}Bilde eller bilder produsert ved generering.
Andre Luma Uni-1-varianter
Flere modeller: Bilderedigering
For AI-agenter: Denne siden som Markdown finnes på https://doitong.com/no/developers/models/luma/agent/uni-1/v1/max/edit.md. Alle modeller og veiledninger: https://doitong.com/developers/llms.txt






