Gemini 3 Pro Image Preview · Edit
Integrar
gemini-3-pro-image-preview/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/gemini-3-pro-image-preview/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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/gemini-3-pro-image-preview/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/gemini-3-pro-image-preview/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/rm/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": "gemini-3-pro-image-preview/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"
]
}
}
Cloma il model Gemini 3 Pro Image Preview · Edit (gemini-3-pro-image-preview/edit) tras la Doitong API. Documentaziun per agents: https://doitong.com/rm/developers/models/gemini-3-pro-image-preview/edit.md
POST https://api.doitong.com/v1/run/gemini-3-pro-image-preview/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"
]
}
Sche il status da la resposta è "queued" u "running", fa polling GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 fin ch'el è "succeeded"; las datotecas èn en outputs[].url. POST https://api.doitong.com/v1/quote/gemini-3-pro-image-preview/edit cun il medem body returna il pretsch exact avant l'execuziun.
Questa dumonda: $0,15 150 credits API Lantschar sin questa pagina
Tia nova clav API. Quest vegn mussada mo ussa ed è gia en il code ed en il champ da la clav API sutvart. Mantegna ella secreta: na la metta mai en code che vegn exequì en in navigatur.
Fatg sin Doitong
Ovras publicas fatgas cun Gemini 3 Pro Image Preview da la communitad Doitong. Reutilisescha in prompt cun in clic.
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Art style: 3D Pixar, highly detailed, vibrant colors, expr.... 3D Pixar style. A dark, snowy city street at night. The banana man looks incredibly guilty and sad as he places the two tiny baby grapes into a metal trash can. Heavy snow is falling. Somber atmosphere....
Art style: 3D Pixar. Young man Dmitry looking exhausted, split image: left side dull grayscale park walk, right side vibrant exploding phone screen and glowing overloaded dopamine receptors in brain overlay. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FINAL STYLE ENFORCEMENT (this is the authoritative...
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[Lighting: cinematic] Art style: Кинематографический, фотореалистичный. рука парня, решительно тянется к экрану монитора своего компьютера и нажимает кнопку 'Включить SILA VPN' на экране. В момент клика вся комната заливается мощным, чистым синим светом. Амогусы с ножами в ужасе отлетают от окон...
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Construir ina dumonda
Ils controls vegnan generads dal schema dal model. Il code e il pretsch s'actualiseschan durant che ti als midas.
/run/gemini-3-pro-image-preview/edit?wait=20
calculaziun → $0,15
# 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/gemini-3-pro-image-preview/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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/gemini-3-pro-image-preview/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/gemini-3-pro-image-preview/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": "gemini-3-pro-image-preview/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
}
}
}
Executar questa dumonda
Tia clav resta en quest browser: ella vegn tramessa mo al Doitong API e memorisada (localStorage) mo sch'ella scheccas Tiar a memoria. Obtegnair ina clav API
Davart Gemini 3 Pro Image Preview · Edit
Modifitgescha u ricumbinescha maletgs da `image_urls` (obligatoric) tenor in `prompt`. `aspect_ratio` è auto per default, `resolution` po esser 1K, 2K u 4K, e `system_prompt` e la tschertga web pon vegnir activads. Returna 1 to 4 maletgs modifitgadas en PNG, JPEG u WebP.
Parameters
Invia u il num canonic u il num nativ, betg omaduas. Nums canonics
promptobligatori
num_imagesopziunal
num_outputs
seedopziunal
aspect_ratioopziunal
output_formatopziunal
safety_toleranceopziunal
image_urlsobligatori
images
system_promptopziunal
resolutionopziunal
limit_generationsopziunal
enable_web_searchopziunal
Ils parameters da datotecas acceptan ina URL publica https://, ina URI data: fin a 10 MB u il file_url d'ina chargiada. Datotecas
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "gemini-3-pro-image-preview/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": 150,
"usd": "0.15",
"charged": 150,
"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
}
],
"description": "string"
},
"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"
}
}
Champs da l'output
- images
- array of object {url, content_type, file_name, file_size, width, height}Maletgs resultants da l'ediziun.
- description
- stringDescripziun che accumpogna ils maletgs generads.
Autras variantes Gemini 3 Pro Image Preview
Dapli models: Modificaziun da maletgs
Per agents AI: questa pagina sco Markdown è disponibla sut https://doitong.com/rm/developers/models/gemini-3-pro-image-preview/edit.md. Tut ils models e las guidas: https://doitong.com/developers/llms.txt






