Isaac 0.1
Integrasikan
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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/perceptron/isaac-01?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/perceptron/isaac-01", 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/id/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": "perceptron/isaac-01",
"input": {
"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"
}
}
Panggil model Isaac 0.1 (perceptron/isaac-01) melalui Doitong API. Dokumentasi untuk agen: https://doitong.com/id/developers/models/perceptron/isaac-01.md
POST https://api.doitong.com/v1/run/perceptron/isaac-01?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"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"
}
Jika status respons adalah "queued" atau "running", lakukan polling GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 hingga statusnya menjadi "succeeded"; file terdapat di outputs[].url. POST https://api.doitong.com/v1/quote/perceptron/isaac-01 dengan body yang sama mengembalikan harga pasti sebelum dijalankan.
Permintaan ini: ≈$0,001 1 kredit API Jalankan di halaman ini
Kunci API baru Anda. Ini hanya ditampilkan sekarang dan sudah dimasukkan ke dalam kode serta kolom kunci API di bawah. Simpan secara rahasia: jangan pernah menaruhnya di kode yang berjalan di browser.
Hasil pertama Anda akan muncul di sini
Buat permintaan di bawah ini dan jalankan dengan kunci API Anda. Output disalin ke penyimpanan kami, disimpan selamanya atau 7 hari gratis.
Buat permintaan
Kontrol dibuat dari skema model. Kode dan harga diperbarui saat Anda mengubahnya.
/run/perceptron/isaac-01?wait=20
estimasi harga → $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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/perceptron/isaac-01?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/perceptron/isaac-01", 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": "perceptron/isaac-01",
"input": {
"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"
},
"wait_seconds": 20
}
}
}
Jalankan permintaan ini
Key Anda tetap berada di browser ini: key hanya dikirim ke Doitong API dan disimpan (localStorage) hanya jika Anda mencentang Ingat. Dapatkan kunci API
Tentang Isaac 0.1
Menerima `image_url` dan `prompt`, lalu mengembalikan respons dalam format yang ditetapkan oleh `response_style`. Teks cocok untuk takarir dan deskripsi, sedangkan gaya box, point, dan polygon menambahkan output lokalisasi. Hasilnya mencakup output yang dibuat, flag output parsial, pesan error jika ada, dan informasi penggunaan.
Parameter
Kirim nama kanonis atau nama asli, bukan keduanya. Nama kanonis
image_urlwajib
image
promptwajib
response_styleopsional
Parameter file menerima URL publik https://, URI data: hingga 10 MB, atau file_url dari unggahan. File
Output
{
"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"
}
}
Field output
- output
- stringHasil yang dihasilkan model.
- partial
- booleanMenunjukkan apakah output tidak lengkap.
- error
- string | nullPesan yang menjelaskan error, jika terjadi.
- usage
- object {completion_tokens, prompt_tokens, total_tokens} | nullDetail penggunaan.
Model lainnya: Visi
Untuk agen AI: halaman ini dalam Markdown tersedia di https://doitong.com/id/developers/models/perceptron/isaac-01.md. Semua model dan panduan: https://doitong.com/developers/llms.txt