Isaac 0.1
ਇੰਟੀਗ੍ਰੇਟ ਕਰੋ
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/pa/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"
}
}
Doitong API ਰਾਹੀਂ Isaac 0.1 ਮਾਡਲ (perceptron/isaac-01) ਨੂੰ ਕਾਲ ਕਰੋ। ਏਜੰਟਾਂ ਲਈ ਦਸਤਾਵੇਜ਼: https://doitong.com/pa/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"
}
ਜੇ ਜਵਾਬ ਦੀ ਸਥਿਤੀ "queued" ਜਾਂ "running" ਹੈ, ਤਾਂ GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 ਨੂੰ ਉਦੋਂ ਤੱਕ ਪੋਲ ਕਰੋ ਜਦੋਂ ਤੱਕ ਇਹ "succeeded" ਨਾ ਹੋ ਜਾਵੇ; ਫ਼ਾਈਲਾਂ outputs[].url ਵਿੱਚ ਹਨ। ਉਸੇ ਬਾਡੀ ਨਾਲ POST https://api.doitong.com/v1/quote/perceptron/isaac-01 ਚਲਾਉਣ ’ਤੇ ਰਨ ਤੋਂ ਪਹਿਲਾਂ ਸਹੀ ਕੀਮਤ ਮਿਲ ਜਾਂਦੀ ਹੈ।
ਇਹ ਬੇਨਤੀ: ≈$0.001 1 API ਕ੍ਰੈਡਿਟ ਇਸ ਪੰਨੇ ’ਤੇ ਚਲਾਓ
ਤੁਹਾਡੀ ਨਵੀਂ API ਕੁੰਜੀ। ਇਹ ਸਿਰਫ਼ ਹੁਣ ਦਿਖਾਈ ਜਾਂਦੀ ਹੈ ਅਤੇ ਪਹਿਲਾਂ ਹੀ ਕੋਡ ਅਤੇ ਹੇਠਾਂ ਦਿੱਤੇ API ਕੁੰਜੀ ਖੇਤਰ ਵਿੱਚ ਮੌਜੂਦ ਹੈ। ਇਸਨੂੰ ਗੁਪਤ ਰੱਖੋ: ਇਸਨੂੰ ਕਦੇ ਵੀ ਬ੍ਰਾਊਜ਼ਰ ਵਿੱਚ ਚੱਲਣ ਵਾਲੇ ਕੋਡ ਵਿੱਚ ਨਾ ਰੱਖੋ।
ਤੁਹਾਡਾ ਪਹਿਲਾ ਨਤੀਜਾ ਇੱਥੇ ਹੋਵੇਗਾ
ਹੇਠਾਂ ਬੇਨਤੀ ਬਣਾਓ ਅਤੇ ਆਪਣੀ API ਕੁੰਜੀ ਨਾਲ ਚਲਾਓ। ਆਉਟਪੁੱਟ ਸਾਡੇ ਸਟੋਰੇਜ ਵਿੱਚ ਕਾਪੀ ਕੀਤੇ ਜਾਂਦੇ ਹਨ ਅਤੇ ਹਮੇਸ਼ਾ ਲਈ ਜਾਂ ਮੁਫ਼ਤ ਵਿੱਚ 7 ਦਿਨ ਤੱਕ ਰੱਖੇ ਜਾਂਦੇ ਹਨ।
ਰਿਕਵੈਸਟ ਬਣਾਓ
ਕੰਟਰੋਲ ਮਾਡਲ ਸਕੀਮਾ ਤੋਂ ਤਿਆਰ ਹੁੰਦੇ ਹਨ। ਤੁਸੀਂ ਬਦਲਾਅ ਕਰਦੇ ਹੀ ਕੋਡ ਅਤੇ ਕੀਮਤ ਅੱਪਡੇਟ ਹੋ ਜਾਂਦੇ ਹਨ।
/run/perceptron/isaac-01?wait=20
ਕੋਟ → $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
}
}
}
ਇਹ ਬੇਨਤੀ ਚਲਾਓ
ਤੁਹਾਡੀ key ਇਸ ਬ੍ਰਾਊਜ਼ਰ ਵਿੱਚ ਰਹਿੰਦੀ ਹੈ: ਇਹ ਸਿਰਫ਼ Doitong API ਨੂੰ ਭੇਜੀ ਜਾਂਦੀ ਹੈ ਅਤੇ ਸਿਰਫ਼ ਤਾਂ ਹੀ (localStorage) ਵਿੱਚ ਸੁਰੱਖਿਅਤ ਹੁੰਦੀ ਹੈ ਜੇ ਤੁਸੀਂ Remember ਚੁਣੋ। API ਕੁੰਜੀ ਪ੍ਰਾਪਤ ਕਰੋ
Isaac 0.1 ਬਾਰੇ
`image_url` ਅਤੇ `prompt` ਲੈ ਕੇ `response_style` ਦੁਆਰਾ ਨਿਰਧਾਰਤ ਫਾਰਮੈਟ ਵਿੱਚ ਜਵਾਬ ਵਾਪਸ ਕਰਦਾ ਹੈ। ਟੈਕਸਟ ਕੈਪਸ਼ਨਾਂ ਅਤੇ ਵਰਣਨਾਂ ਲਈ ਢੁਕਵਾਂ ਹੈ, ਜਦਕਿ ਬਾਕਸ, ਬਿੰਦੂ ਅਤੇ ਪੌਲੀਗਨ ਸਟਾਈਲ ਸਥਾਨ-ਨਿਰਧਾਰਣ ਆਉਟਪੁੱਟ ਜੋੜਦੇ ਹਨ। ਨਤੀਜੇ ਵਿੱਚ ਤਿਆਰ ਕੀਤੀ ਆਉਟਪੁੱਟ, ਅੰਸ਼ਕ-ਆਉਟਪੁੱਟ ਫਲੈਗ, ਹੋਣ 'ਤੇ ਗਲਤੀ ਸੁਨੇਹਾ ਅਤੇ ਵਰਤੋਂ ਦੀ ਜਾਣਕਾਰੀ ਸ਼ਾਮਲ ਹੁੰਦੀ ਹੈ।
ਪੈਰਾਮੀਟਰ
ਕੈਨੋਨਿਕਲ ਨਾਮ ਜਾਂ ਨੇਟਿਵ ਨਾਮ ਵਿੱਚੋਂ ਕੋਈ ਇੱਕ ਭੇਜੋ, ਦੋਵੇਂ ਨਹੀਂ। ਕੈਨੋਨਿਕਲ ਨਾਮ
image_urlਲੋੜੀਂਦਾ
image
promptਲੋੜੀਂਦਾ
response_styleਵਿਕਲਪਿਕ
ਫ਼ਾਈਲ ਪੈਰਾਮੀਟਰ ਜਨਤਕ https:// URL, 10 MB ਤੱਕ ਦਾ data: URI, ਜਾਂ ਅੱਪਲੋਡ ਦੇ file_url ਨੂੰ ਸਵੀਕਾਰਦੇ ਹਨ। ਫ਼ਾਈਲਾਂ
ਆਉਟਪੁੱਟ
{
"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"
}
}
ਆਉਟਪੁੱਟ ਦੇ ਫ਼ੀਲਡ
- output
- stringਮਾਡਲ ਵੱਲੋਂ ਤਿਆਰ ਕੀਤਾ ਨਤੀਜਾ।
- partial
- booleanਦੱਸਦਾ ਹੈ ਕਿ ਆਉਟਪੁੱਟ ਅਧੂਰਾ ਹੈ ਜਾਂ ਨਹੀਂ।
- error
- string | nullਜੇ ਕੋਈ ਗਲਤੀ ਹੋਈ ਹੋਵੇ ਤਾਂ ਉਸਦਾ ਵੇਰਵਾ ਦੇਣ ਵਾਲਾ ਸੁਨੇਹਾ।
- usage
- object {completion_tokens, prompt_tokens, total_tokens} | nullਵਰਤੋਂ ਦੇ ਵੇਰਵੇ।
ਹੋਰ ਮਾਡਲ: ਵਿਜ਼ਨ
AI ਏਜੰਟਾਂ ਲਈ: ਇਹ ਪੰਨਾ Markdown ਵਜੋਂ ਇੱਥੇ ਹੈ https://doitong.com/pa/developers/models/perceptron/isaac-01.md. ਸਾਰੇ ਮਾਡਲ ਅਤੇ ਗਾਈਡ: https://doitong.com/developers/llms.txt