Isaac 0.1
אינטעגרירן
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/yi/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"
}
}
רופֿט דעם Isaac 0.1 מאָדעל (perceptron/isaac-01) דורך דער Doitong API. דאָקומענטאַציע פֿאַר אַגענטס: https://doitong.com/yi/developers/models/perceptron/isaac-01.md
POST https://api.doitong.com/v1/run/perceptron/isaac-01?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
אויב דער ענטפֿער־סטאַטוס איז "queued" אָדער "running", פֿרעגט מיט GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 ביז ער איז "succeeded"; די פֿײַלן זענען אין outputs[].url. POST https://api.doitong.com/v1/quote/perceptron/isaac-01 מיט דעם זעלבן גוף גיט צוריק די גענויע פּרײַז איידערן לויפֿן.
דער דאָזיקער ריקוועסט: ≈$ 0.001 1 API־קרעדיט לויפֿן עס אויף דער דאָזיקער בלאַט
אײַער נײַער API שליסל. עס ווערט געוויזן בלויז איצט און איז שוין אין דעם קאָד און אין דעם API שליסל־פעלד אונטן. האַלט עס געהיים: לייג עס קיינמאָל נישט אַרײַן אין קאָד וואָס לויפֿט אין אַ בלעטערער.
דאָ קומט אײַער ערשטער רעזולטאַט
בויט אונטן אַ בקשה און לויפט זי מיט אײַער API שליסל. רעזולטאַטן ווערן קאַפּירט צו אונדזער סטאָרידזש, געהאַלטן אויף אייביק אָדער 7 טעג אומזיסט.
בויען אַ בעטן
קאָנטראָלן ווערן דזשענערירט פֿון דעם מאָדעל־סכעמע. דער קאָד און דער פּרײַז דערהײַנטיקן זיך ווען איר ענדערט זיי.
/run/perceptron/isaac-01?wait=20
פּרײַז → $ 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
}
}
}
לויפֿן דעם ריקוועסט
אײַער key בלײַבט אין דעם בלעטערער: זי ווערט געשיקט נאָר צום Doitong API און אָפּגעהיט (localStorage) נאָר אויב איר טיקט אָן געדענקען. באַקומען אַן API שליסל
וועגן Isaac 0.1
נעמט אַן `image_url` און אַ `prompt` און גיט צוריק אַן ענטפֿער אין דעם פֿאָרמאַט באַשטימט דורך `response_style`. טעקסט פּאַסט פֿאַר קאַפּשאַנז און באַשרײַבונגען, בשעת box, point און polygon סטילן לייגן צו לאָקאַליזאַציע־רעזולטאַטן. דער רעזולטאַט אַנטהאַלט דעם גענערירטן רעזולטאַט, אַ partial-output פֿאָן, אַן טעות־מעלדונג אויב ס׳איזאָ, און באַניץ־אינפֿאָרמאַציע.
פּאַראַמעטערס
שיקט אָדער דעם קאַנאָנישן נאָמען אָדער דעם נאַטיוון נאָמען, נישט ביידע. קאַנאָנישע נעמען
image_urlפארלאנגט
image
promptפארלאנגט
response_styleאָפּציאָנעל
טעקע־פּאַראַמעטערס נעמען אַן עפֿנטלעכע https:// URL, אַ data: URI ביז 10 MB, אָדער דעם file_url פֿון אַן אַרויפֿלאָד. טעקעס
אויסגאַבע
{
"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"
}
}
פֿעלדער פֿון דער אויסגאַבע
- output
- stringרעזולטאַט געשאַפֿן דורך דעם מאָדעל.
- partial
- booleanווײַזט צי דער רעזולטאַט איז נישט גאַנץ.
- error
- string | nullמעסעדזש וואָס באַשרײַבט אַן טעות, אויב איינער איז פֿאָרגעקומען.
- usage
- object {completion_tokens, prompt_tokens, total_tokens} | nullבאַניץ־דעטאַלן.
מער מאָדעלן: וויזיע
פֿאַר AI־אַגענטן: דער בלאַט ווי Markdown געפֿינט זיך בײַ https://doitong.com/yi/developers/models/perceptron/isaac-01.md. אַלע מאָדעלן און גוידעס: https://doitong.com/developers/llms.txt