Krea 2 Trainer
Integrere
krea-2-trainer
# 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/krea-2-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"images_data_url": "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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/krea-2-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"images_data_url": "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/krea-2-trainer", 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/se/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": "krea-2-trainer",
"input": {
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Riŋge Krea 2 Trainer-modeallii (krea-2-trainer) Doitong API bokte. Dokumentašuvdna ageanttaide: https://doitong.com/se/developers/models/krea-2-trainer.md
POST https://api.doitong.ru/v1/run/krea-2-trainer?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Jus vástádusa status lea "queued" dahje "running", jeara GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 dassážii go dat lea "succeeded"; fiillat leat outputs[].url:s. POST https://api.doitong.ru/v1/quote/krea-2-trainer seamma boduin máksá dárkilis haddái ovdal vuodjámis.
Fiillat nugo ovdamearka: 0,30 $ 300 API-kreditta · ≈ 31,64 ₽ du fiillat mihtiduvvojit ovdal vuodjámis Vuodje dán siiddu alde
Du ođđa API-čoavdda. Dat čájehuvvo dušše dál ja lea juo koden ja API-čoavdda giettis dás vuolábealde. Bisso dan čihkosis: ale goassige bidde dan kodaide mat vuđđojuvvojit fierpmádatrávnnji.
Dát lea du vuosttaš bohtos
Daga jearaldaga vuolábealde ja vuodje dan iežat API-čoavddain. Boađusat kopierejuvvojit min vurkemii, bisuhuvvojit álo dahje 7 beaivvi nuvttá.
Ráhkat jearaldaga
Kontrollat ráhkaduvvojit modealla skeama vuođul. Koda ja haddi ođasmahttojuvvojit go rievddadat daid.
/run/krea-2-trainer?wait=20
haddemearrádus → 0,30 $
# 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/krea-2-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"images_data_url": "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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/krea-2-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"images_data_url": "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/krea-2-trainer", 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": "krea-2-trainer",
"input": {
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Geavat dán ohcamuša
Du key báhcá dán fierpmádatlogan: dat sáddejuvvo dušše Doitong API:ii ja vurkejuvvo (localStorage) dušše jos válljet Remember. Viečča API-keya
Dát lea Krea 2 Trainer birra
Dárkilis heiveha LoRA:a .zip-fiillas, mas leat govvagovat `images_data_url`:s, eaktodáhtolaš seamma-nama .txt-govvateavsttaiguin ja `trigger_phrase`:in. `auto_captioning`-modusat leat Off, Object/Character, Style ja Custom. `steps` lea 50–10000 (standárda 100), `resolution` lea 768 dahje 1024. Boađusin leat LoRA-deattut ja konfigurašuvdnafiila.
Parametterat
images_data_urlgáibiduvvo
trigger_phraseeaktodáhtolaš
auto_captioningeaktodáhtolaš
stepseaktodáhtolaš
learning_rateeaktodáhtolaš
resolutioneaktodáhtolaš
debug_dataseteaktodáhtolaš
Boađus
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "krea-2-trainer",
"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": 300,
"usd": "0.30",
"charged": 300,
"refunded": 0
},
"input": {
"images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"output": {
"lora_file": {
"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
},
"config_file": {
"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
},
"prompt_enhancement_system_prompt": "string",
"debug_dataset": {
"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": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"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"
}
}
Outputa giettit
- lora_file
- object {url, content_type, file_name, file_size}Download URL for trained Krea-2 LoRA weights in safetensors format.
- config_file
- object {url, content_type, file_name, file_size}Liŋka JSON-fiilii, mas lea hárjehallan-/LoRA-heivehus.
- prompt_enhancement_system_prompt
- string | nullVuogádatbivdda, mii máhcahuvvo go `auto_captioning` lea jođus, veahkkin čállit dahje buoridit inferensabivdagiid seamma govvateakstavuogi mielde go automáhtalaččat govvateavsttaiguin merkejuvvon hárjehallandáhtat.
- debug_dataset
- object {url, content_type, file_name, file_size} | nullTraining-data download provided when `debug_dataset` is enabled: an archive containing the prepared dataset and its automatically generated captions.
Eará Krea 2-variánttat
Eanet modeallat: Oahpahus
AI-agenttaide: dán siidu Markdowna lea dáppe https://doitong.com/se/developers/models/krea-2-trainer.md. Buot modeallat ja ráđit: https://doitong.com/developers/llms.txt