Meta Muse Image Edit
Integréieren
meta/muse-image/edit
# 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/meta/muse-image/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/meta/muse-image/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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/meta/muse-image/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/lb/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": "meta/muse-image/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"
]
}
}
Rufft de Meta Muse Image Edit-Modell (meta/muse-image/edit) iwwer d'Doitong API op. Dokumentatioun fir Agenten: https://doitong.com/lb/developers/models/meta/muse-image/edit.md
POST https://api.doitong.com/v1/run/meta/muse-image/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"
]
}
Wann de Äntwertstatus "queued" oder "running" ass, frot GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 of, bis en "succeeded" ass; d'Dateie stinn an outputs[].url. POST https://api.doitong.com/v1/quote/meta/muse-image/edit mam selwechte Body gëtt de geneeë Präis virun der Ausféierung zréck.
Dës Ufro: 0,01 $ 10 API-Kreditter Op dëser Säit ausféieren
Ären neien API-Schlëssel. Si gëtt nëmmen elo ugewisen a steet schonn am Code an am API-Schlëssel-Feld hei drënner. Halt se geheim: Setz se ni an Code, deen an engem Browser leeft.
Äin éischt Resultat kënnt hei hin
Baut hei drënner eng Ufro a féiert se mat Ärem API-Schlëssel aus. Output gëtt an eis Späicherung kopéiert, fir ëmmer oder 7 Deeg gratis gespäichert.
Eng Ufro erstellen
D'Kontrolle ginn aus dem Modellschema generéiert. De Code an de Präis aktualiséiere sech, wann s du se ännerst.
/run/meta/muse-image/edit?wait=20
Präis → 0,01 $
# 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/meta/muse-image/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/meta/muse-image/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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/meta/muse-image/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": "meta/muse-image/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
}
}
}
Dës Ufro ausféieren
Äre Schlëssel bleift an dësem Browser: e gëtt nëmmen un d'Doitong API geschéckt an nëmme gespäichert (localStorage), wann s du „Erënneren“ aktivéiers. En API-Schlëssel kréien
Iwwer Meta Muse Image Edit
Bearbecht Biller no engem Text-`prompt` a benotzt tëscht 1 an 10 Referenzbiller a `image_urls`. `aspect_ratio` akzeptéiert all Breet:Héicht-Wäert tëscht 1:16 an 16:1, an `num_images` gëtt 1 bis 10 Resultater zeréck. `output_format` kann jpeg, png oder webp sinn (Standard webp). Geeegent fir gezielt Saachen z'änneren an de Rescht vum Bild ze behalen oder verschidde Referenzen ze kombinéieren.
Parameteren
Schéck entweder den kanoneschen Numm oder den natierlechen Numm, net béid. Kanonesch Nimm
promptobligatoresch
image_urlsobligatoresch
images
aspect_ratiooptional
num_imagesoptional
num_outputs
output_formatoptional
Fichierparameter akzeptéieren eng ëffentlech https:// URL, eng data: URI bis zu 10 MB oder de file_url vun engem Upload. Fichieren
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "meta/muse-image/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": 10,
"usd": "0.01",
"charged": 10,
"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
}
]
},
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Output-Felder
- images
- array of object {url, content_type, file_name, file_size, width, height}Biller, déi duerch Generatioun oder Bearbechtung produzéiert goufen.
Aner Meta Muse Image-Varianten
Méi Modeller: Bildbearbechtung
Fir AI-Agenten: dës Säit als Markdown ass ënner https://doitong.com/lb/developers/models/meta/muse-image/edit.md. All Modeller a Guiden: https://doitong.com/developers/llms.txt






