Latent Consistency Models (v1.5/XL) · Inpainting
Integroi
fast-lcm-diffusion/inpainting
# 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/fast-lcm-diffusion/inpainting?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/fast-lcm-diffusion/inpainting?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/fast-lcm-diffusion/inpainting", 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/fi/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": "fast-lcm-diffusion/inpainting",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kutsu mallia Latent Consistency Models (v1.5/XL) · Inpainting (fast-lcm-diffusion/inpainting) Doitong API:n kautta. Dokumentaatio agenteille: https://doitong.com/fi/developers/models/fast-lcm-diffusion/inpainting.md
POST https://api.doitong.ru/v1/run/fast-lcm-diffusion/inpainting?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
Jos vastauksen tila on "queued" tai "running", kysy GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 uudelleen, kunnes tila on "succeeded"; tiedostot ovat kohteessa outputs[].url. POST https://api.doitong.ru/v1/quote/fast-lcm-diffusion/inpainting samalla rungolla palauttaa tarkan hinnan ennen suorittamista.
Tämä pyyntö: ≈0,014 $ 14 API-krediittiä · ≈ 1,49 ₽ Suorita tällä sivulla
Uusi API-avaimesi. Se näytetään vain nyt, ja se on jo koodissa ja alla olevassa API-avainkentässä. Pidä se salassa: älä koskaan lisää sitä selaimessa suoritettavaan koodiin.
Ensimmäinen tuloksesi tulee tähän
Muodosta pyyntö alla ja suorita se API-avaimellasi. Tulosteet kopioidaan tallennustilaamme, jossa ne säilytetään ikuisesti tai 7 päivää ilmaiseksi.
Muodosta pyyntö
Säätimet luodaan mallin skeemasta. Koodi ja hinta päivittyvät, kun muutat arvoja.
/run/fast-lcm-diffusion/inpainting?wait=20
hinta → 0,014 $
# 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/fast-lcm-diffusion/inpainting?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/fast-lcm-diffusion/inpainting?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/fast-lcm-diffusion/inpainting", 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": "fast-lcm-diffusion/inpainting",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Suorita tämä pyyntö
Avaimesi säilyy tässä selaimessa: se lähetetään vain Doitong APIlle ja tallennetaan localStorageen vain, jos valitset Muista. Hanki API-avain
Tietoja: Latent Consistency Models (v1.5/XL) · Inpainting
Tarvitsee `image_url`-, `mask_url`- ja `prompt`-arvot maskatun alueen uudelleenmaalaamiseen. `strength` vaihtelee välillä 0.01–1, ja `num_inference_steps`-oletus on 6 (enintään 32). Palauttaa 1–8 kuvaa sekä tukee `negative_prompt`-arvoa, `image_size`-esiasetuksia ja jpeg- tai png-tulostetta.
Parametrit
Lähetä joko kanoninen nimi tai natiivi nimi, älä molempia. Kanoniset nimet
image_urlpakollinen
image
mask_urlpakollinen
mask
promptpakollinen
negative_promptvalinnainen
image_sizevalinnainen
num_inference_stepsvalinnainen
guidance_scalevalinnainen
strengthvalinnainen
seedvalinnainen
num_imagesvalinnainen
num_outputs
enable_safety_checkervalinnainen
safety_checker_versionvalinnainen
expand_promptvalinnainen
formatvalinnainen
request_idvalinnainen
Tiedostoparametrit hyväksyvät julkisen https://-URL:n, enintään 10 MB:n data:-URI:n tai lähetyksen file_url-arvon. Tiedostot
Tulos
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "fast-lcm-diffusion/inpainting",
"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": 14,
"usd": "0.014",
"charged": 14,
"refunded": 0
},
"input": {
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"mask_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Tuloksen kentät
- images
- array of object {url, width, height, content_type}Generoitujen kuvien tiedostotiedot.
- timings
- object
- seed
- integerKuvageneroinnin siemen, mukaan lukien satunnaisesti valittu arvo, jos syötteessä ei annettu siementä; muuten annettu arvo toistetaan.
- has_nsfw_concepts
- array of booleanIlmaisee, esiintyykö generoiduissa kuvissa NSFW-sisältöä.
- prompt
- stringKuvan generoinnissa käytettävä kehote.
Muut Latent Consistency Models-muunnelmat
Lisää malleja: Kuvan muokkaus
Tekoälyagenteille: tämän sivun Markdown-muoto on osoitteessa https://doitong.com/fi/developers/models/fast-lcm-diffusion/inpainting.md. Kaikki mallit ja oppaat: https://doitong.com/developers/llms.txt






