
No hay coincidencias. Prueba con «video», «FLUX» o «webhooks».
Cargando modelos…
flux/dev
# 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/flux/dev?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A lighthouse keeper'\''s cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux/dev?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux/dev", 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/es-ES/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": "flux/dev",
"input": {
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}
}
Llama al modelo FLUX.1 [dev] (flux/dev) a través de Doitong API. Documentación para agentes: https://doitong.com/es-ES/developers/models/flux/dev.md
POST https://api.doitong.com/v1/run/flux/dev?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}
Si el estado de la respuesta es "queued" o "running", consulta GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 hasta que sea "succeeded"; los archivos están en outputs[].url. POST https://api.doitong.com/v1/quote/flux/dev con el mismo cuerpo devuelve el precio exacto antes de la ejecución.
Esta solicitud: 0,025 $ 25 créditos de API Ejecutar en esta página
Tu nueva clave de API. Solo se muestra ahora y ya está incluida en el código y en el campo de clave de API de abajo. Mantenla en secreto: nunca la incluyas en código que se ejecute en un navegador.
Los controles se generan a partir del esquema del modelo. El código y el precio se actualizan al modificarlos.
/run/flux/dev?wait=20
presupuesto → 0,025 $
# 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/flux/dev?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A lighthouse keeper'\''s cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux/dev?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux/dev", 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": "flux/dev",
"input": {
"prompt": "A lighthouse keeper's cottage on a windswept cliff at blue hour, warm light glowing from small square windows, waves breaking far below, long-exposure sea mist, moody cinematic landscape photograph, 35mm, rich detail.",
"num_outputs": 1
},
"wait_seconds": 20
}
}
}
Tu clave permanece en este navegador: solo se envía a la Doitong API y solo se guarda en localStorage si marcas Recordar. Obtener una clave de API
Trabajos públicos creados con FLUX.1 por la comunidad de Doitong. Reutiliza un prompt con un solo clic.
Close-up portrait seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Close-up portrait seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Prompt Details Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi wajahnya. Ia memeluk...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam, celana riding fit, dan sepatu motor. Ia sedang melakukan aksi freestyle ekstrem dengan motor sport 500cc...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam dan celana riding fit. Ia sedang bersiap melakukan freestyle menggunakan motor sport 500cc berwarna merah,...
El modelo FLUX de 12.000 millones de parámetros destilado para guía, con un programa completo de muestreo (28 pasos de forma predeterminada, ajustable de 1 a 50) y una escala de guía configurable. Sigue prompts detallados y renderiza manos, rostros y texto corto notablemente mejor que la variante schnell, a un precio superior. Tamaños predefinidos o personalizados, hasta cuatro imágenes por solicitud y salida JPEG o PNG.
Envía el nombre canónico o el nombre nativo, pero no ambos. Nombres canónicos
promptobligatorio
image_sizeopcional
num_inference_stepsopcional
seedopcional
guidance_scaleopcional
num_imagesopcional
num_outputs
output_formatopcional
accelerationopcional
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "flux/dev",
"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": 25,
"usd": "0.025",
"charged": 25,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field, telephoto lens",
"image_size": "landscape_4_3",
"num_outputs": 1
},
"output": {
"images": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"width": 1024,
"height": 768,
"content_type": "image/jpeg"
}
],
"timings": {},
"seed": 42,
"has_nsfw_concepts": [
false
],
"prompt": "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"
}
}
Para agentes de IA: esta página en Markdown está en https://doitong.com/es-ES/developers/models/flux/dev.md. Todos los modelos y guías: https://doitong.com/developers/llms.txt