Tripo P2 Text to 3D
Integrieren
tripo3d/p2/text-to-3d
# 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/tripo3d/p2/text-to-3d?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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/tripo3d/p2/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/tripo3d/p2/text-to-3d", 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/de/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": "tripo3d/p2/text-to-3d",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Rufe das Modell Tripo P2 Text to 3D (tripo3d/p2/text-to-3d) über die Doitong API auf. Dokumentation für Agenten: https://doitong.com/de/developers/models/tripo3d/p2/text-to-3d.md
POST https://api.doitong.com/v1/run/tripo3d/p2/text-to-3d?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"
}
Wenn der Antwortstatus "queued" oder "running" lautet, frage GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 ab, bis er "succeeded" lautet; die Dateien befinden sich in outputs[].url. POST https://api.doitong.com/v1/quote/tripo3d/p2/text-to-3d mit demselben Body gibt den exakten Preis vor der Ausführung zurück.
Dateien wie das Beispiel: 1,10 $ 1.100 API-Credits Deine Dateien werden vor der Ausführung gemessen Auf dieser Seite ausführen
Dein neuer API-Schlüssel. Sie wird nur jetzt angezeigt und befindet sich bereits im Code und im untenstehenden API-Schlüssel-Feld. Halten Sie sie geheim: Fügen Sie sie niemals in Code ein, der in einem Browser ausgeführt wird.
Dein erstes Ergebnis erscheint hier
Erstelle unten eine Anfrage und führe sie mit deinem API-Schlüssel aus. Ausgaben werden in unseren Speicher kopiert und dauerhaft oder 7 Tage kostenlos aufbewahrt.
Anfrage erstellen
Die Steuerelemente werden aus dem Modellschema generiert. Code und Preis werden aktualisiert, während du sie änderst.
/run/tripo3d/p2/text-to-3d?wait=20
Preis → 1,10 $
# 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/tripo3d/p2/text-to-3d?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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/tripo3d/p2/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/tripo3d/p2/text-to-3d", 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": "tripo3d/p2/text-to-3d",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Diese Anfrage ausführen
Dein Schlüssel bleibt in diesem Browser: Er wird nur an die Doitong API gesendet und nur gespeichert (localStorage), wenn du „Merken“ aktivierst. API-Schlüssel abrufen
Über Tripo P2 Text to 3D
Erzeugt aus einem Prompt mit bis zu 1024 Zeichen ein 3D-Modell, mit einem `negative_prompt` von bis zu 255 Zeichen. Meshes umfassen bis zu 50,000 Flächen oder 25,000 bei aktiviertem `quad`. Die Texturqualität reicht von fast bis extreme, mit auswählbarer `texture_version`, optionalem PBR, De-Lighting und UV-Export. Seeds sind für den Bildschritt, die Geometrie und Texturen verfügbar.
Parameter
prompterforderlich
negative_promptoptional
image_seedoptional
model_seedoptional
face_limitoptional
textureoptional
pbroptional
texture_seedoptional
texture_qualityoptional
texture_versionoptional
delightoptional
auto_sizeoptional
export_uvoptional
export_orientationoptional
quadoptional
enable_safety_checkeroptional
Ausgabe
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "tripo3d/p2/text-to-3d",
"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": 1100,
"usd": "1.10",
"charged": 1100,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"model_mesh": {
"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
},
"model_urls": {
"glb": {
"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
},
"fbx": {
"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
},
"base_model": {
"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
},
"pbr_model": {
"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
}
},
"rendered_image": {
"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
},
"task_id": "string"
},
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Ausgabefelder
- model_mesh
- object {url, content_type, file_name, file_size}GLB- oder FBX-Datei mit dem generierten 3D-Modell; das Format wird durch die Ausgabe von Tripo bestimmt.
- model_urls
- object {glb, fbx, base_model, pbr_model}URLs, die auf alternative Versionen des 3D-Modells verweisen.
- rendered_image
- object {url, content_type, file_name, file_size} | nullGerenderte Vorschau des generierten 3D-Modells.
- task_id
- string | nullWiederverwendbare Tripo-Aufgaben-ID zur Identifizierung des generierten Modells für rig oder rig-check; diese Vorgänge sind dadurch ohne erneutes Hochladen eines Modells möglich.
Weitere Tripo P2-Varianten
Weitere Modelle: Text zu 3D
Für KI-Agenten: Diese Seite ist als Markdown verfügbar unter https://doitong.com/de/developers/models/tripo3d/p2/text-to-3d.md. Alle Modelle und Anleitungen: https://doitong.com/developers/llms.txt