Lyria3
Integréieren
lyria3
# 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/lyria3?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"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/lyria3?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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/lyria3", 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.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "lyria3",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Rufft de Lyria3-Modell (lyria3) iwwer d'Doitong API op. Dokumentatioun fir Agenten: https://doitong.com/lb/developers/models/lyria3.md
POST https://api.doitong.ru/v1/run/lyria3?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"
}
Wann de Äntwertstatus "queued" oder "running" ass, frot GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 of, bis en "succeeded" ass; d'Dateie stinn an outputs[].url. POST https://api.doitong.ru/v1/quote/lyria3 mam selwechte Body gëtt de geneeë Präis virun der Ausféierung zréck.
Dës Ufro: 0,04 $ 40 API-Kreditter · ≈ 4,22 ₽ 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/lyria3?wait=20
Präis → 0,04 $
# 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/lyria3?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"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/lyria3?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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/lyria3", 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": "lyria3",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"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 Lyria3
Komponéiert e Museksstéck aus engem Text-`prompt` mat bis zu 5000 Zeechen; Genre, Stëmmung, Instrumentéierung, Tempo a Vokalstil kënnen beschriwwe ginn. En optionalen `image_url` liwwert Inspiratioun fir Stëmmung an Thema. D'Resultat ass eng MP3-Audio-Datei plus e `lyrics`-Textfeld, wann zoutreffend. Negativ-Prompts ginn net ënnerstëtzt.
Parameteren
Schéck entweder den kanoneschen Numm oder den natierlechen Numm, net béid. Kanonesch Nimm
promptobligatoresch
negative_promptoptional
image_urloptional
image
enable_safety_checkeroptional
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": "lyria3",
"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": 40,
"usd": "0.04",
"charged": 40,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"audio": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_name": "0-output.mp3",
"file_size": 1843200
},
"lyrics": "Caption: This is a high-energy Progressive House anthem, a subgenre of EDM defined by its massive scale and uplifting melodic content, all polished with a clean, powerful, and wide stereo production aesthetic. The rhythmic foundation is a punchy, heavily compressed four-on-the-floor kick drum, modeled after a classic Roland TR-909, providing a relentless pulse at 128 BPM. Supporting the kick are crisp, bright open hi-hats on the off-beats and a thick clap/snare layer on beats 2 and 4. The harmonic and melodic core is built from multiple synth layers: vast, shimmering supersaw synth pads play a soaring major-key chord progression; a powerful, monophonic sawtooth bassline plays the root notes and is aggressively side-chained to the kick drum to create the genre's signature 'pumping' effect. Above it all, a soaring supersaw lead synth—composed of multiple detuned sawtooth waves to create a thick, wide sound—plays a memorable, uplifting arpeggiated melody. A powerful, clean female vocal delivers the catchy hook, processed with significant hall reverb and delay to make it feel enormous and seamlessly blend with the synths. The entire instrumental bed (pads, lead, bass) is also heavily side-chained to the kick, ensuring every element ducks in volume with each beat to maximize the kick's punch and drive the track forward.\nMosic: 4.5\nBPM: 128.0"
},
"outputs": [
{
"type": "audio",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_size": 1843200,
"duration": 12,
"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"
}
}
Output-Felder
- audio
- object {url, content_type, file_name, file_size}Musek-Output am MP3-Format.
- lyrics
- string | nullText vum Lidd, generéiert oder uginn, wann zoutreffend.
Aner Lyria3-Varianten
Méi Modeller: Text zu Musek
Fir AI-Agenten: dës Säit als Markdown ass ënner https://doitong.com/lb/developers/models/lyria3.md. All Modeller a Guiden: https://doitong.com/developers/llms.txt