Op den Inhalt sprangen

Isaac 0.1

Integréieren

Modell-ID perceptron/isaac-01
# 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/perceptron/isaac-01?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",
    "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"

Dës Ufro: ≈0,001 $ 1 API-Kredit Op dëser Säit ausféieren

API-Schlëssel kréien
Perceptron Visioun #multimodal#vision

Visioun-Sprooch-Modell, deen e Bild als Text, Këschten, Punkten oder Polygone beschreift

Perceptron · Text

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.

•obligatoresch

Prompt, deen op d'Bild applizéiert gouf.

•obligatoresch image_url
Fichier erofzéien, oder

URL, déi d'Bild fir d'Verschaffe identifizéiert.

Erweidert response_style
response_style Standard text

Wielt d'Format vun der Bildantwort: all Modi enthalen Text, woubäi box Begrenzungsboxen, point Punkten a polygon Polygone bäifüügt; text eleng gëtt nëmmen Text zréck. Benotzt polygon fir granular Segmentéierung oder box fir Lokaliséierung. Fir Beschreiwungen a Captioning benotzt text; fir vill Objeten ze zielen, benotzt point.

POST /run/perceptron/isaac-01?wait=20 Präis → 0,001 $
# 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/perceptron/isaac-01?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",
    "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"

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 Isaac 0.1

Hëlt en `image_url` an e `prompt` a gëtt eng Äntwert am Format zeréck, dat duerch `response_style` festgeluecht gëtt. Text eegent sech fir Ënnerschrëften a Beschreiwungen; box-, point- a polygon-Stiler fügen Lokalisatiounsausgab dobäi. D'Resultat enthält d'generéiert Ausgab, e Partial-Ausgab-Fändel, eng eventuell Fehlermeldung an Verbrauchsinformatioun.

Parameteren

Schéck entweder den kanoneschen Numm oder den natierlechen Numm, net béid. Kanonesch Nimm

NummTyp StandardErlaabt Beschreiwung
image_urlobligatoresch image
Typurl · image
URL, déi d'Bild fir d'Verschaffe identifizéiert.
promptobligatoresch
Typstring
Prompt, deen op d'Bild applizéiert gouf.
response_styleoptional
Typenum
Standardtext
textboxpointpolygon
Wielt d'Format vun der Bildantwort: all Modi enthalen Text, woubäi box Begrenzungsboxen, point Punkten a polygon Polygone bäifüügt; text eleng gëtt nëmmen Text zréck. Benotzt polygon fir granular Segmentéierung oder box fir Lokaliséierung. Fir Beschreiwungen a Captioning benotzt text; fir vill Objeten ze zielen, benotzt point.
obligatoresch Kanoneschen Numm, och akzeptéiert

Fichierparameter akzeptéieren eng ëffentlech https:// URL, eng data: URI bis zu 10 MB oder de file_url vun engem Upload. Fichieren

Output

GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "perceptron/isaac-01",
  "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": 1,
    "usd": "0.001",
    "charged": 1,
    "refunded": 0
  },
  "input": {
    "image_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": {
    "output": "To determine which car is trying to park into the garage, we need to carefully observe the positions and movements of the vehicles in the image.\n\n1. **Identify the Vehicles**: \n   - There are three vehicles visible: a green truck, an orange car, and a brown car.\n   - The green truck is positioned in front of the garage entrance.\n   - The orange car is parked to the left of the green truck.\n   - The brown car is parked to the right of the green truck.\n\n2. **Analyze the Positions**:\n   - The green truck is directly in front of the garage entrance, suggesting it is in the process of moving towards the entrance.\n   - The orange car is parked parallel to the garage but is not in the path of the green truck.\n   - The brown car is also parked parallel to the garage but is not in the path of the green truck.\n\n3. **Determine the Action**:\n   - Given the position of the green truck directly in front of the garage entrance, it is most likely that the green truck is trying to park into the garage.\n   - The orange and brown cars are already parked and do not appear to be in motion or attempting to park.\n\nTherefore, the car that is trying to park into the garage is the green truck.",
    "partial": false,
    "error": "string",
    "usage": {
      "completion_tokens": 1,
      "prompt_tokens": 1,
      "total_tokens": 1
    }
  },
  "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"
  }
}
Är Fichieren, Är WielAll outputs[].url ass eng Kopie an eiser Späicherung: fir ëmmer gespäichert (bezuelbar pro GB-Mount) oder 7 Deeg gratis, jee no Ärer Kontastellung oder ?storage=.
D'selwecht Struktur bei all Modelltype, url, content_type, width, height an duration, fir Biller, Video an Audio gläichermoossen. output ass dem Modell säin eegent Resultatobjet.
Output-Felder
output
stringResultat, dat vum Modell produzéiert gëtt.
partial
booleanGëtt un, ob den Output onvollstänneg ass.
error
string | nullMessage, deen e Feeler beschreift, wann een opgetrueden ass.
usage
object {completion_tokens, prompt_tokens, total_tokens} | nullDetailer zur Notzung.

Fir AI-Agenten: dës Säit als Markdown ass ënner https://doitong.com/lb/developers/models/perceptron/isaac-01.md. All Modeller a Guiden: https://doitong.com/developers/llms.txt