Hunyuan Image · v3 · Instruct · Edit
इंटीग्रेट करें
hunyuan-image/v3/instruct/edit
# 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/hunyuan-image/v3/instruct/edit?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",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/hunyuan-image/v3/instruct/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/hunyuan-image/v3/instruct/edit", 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/hi/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": "hunyuan-image/v3/instruct/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
}
Hunyuan Image · v3 · Instruct · Edit मॉडल (hunyuan-image/v3/instruct/edit) को Doitong API के ज़रिए कॉल करें। एजेंट के लिए दस्तावेज़: https://doitong.com/hi/developers/models/hunyuan-image/v3/instruct/edit.md
POST https://api.doitong.com/v1/run/hunyuan-image/v3/instruct/edit?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",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
यदि रिस्पॉन्स स्टेटस "queued" या "running" है, तो GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 को तब तक पोल करें जब तक यह "succeeded" न हो जाए; फ़ाइलें outputs[].url में हैं। उसी बॉडी के साथ POST https://api.doitong.com/v1/quote/hunyuan-image/v3/instruct/edit चलाने से रन से पहले सटीक कीमत मिलती है।
यह अनुरोध: ≈$0.174 174 API क्रेडिट इसे इस पेज पर चलाएँ
आपकी नई API कुंजी। यह केवल अभी दिखाया गया है और कोड तथा नीचे दिए गए API कुंजी फ़ील्ड में पहले से मौजूद है। इसे गुप्त रखें: इसे कभी भी ब्राउज़र में चलने वाले कोड में न डालें।
आपका पहला परिणाम यहाँ आएगा
नीचे एक अनुरोध बनाएँ और उसे अपनी API कुंजी से चलाएँ। आउटपुट हमारे स्टोरेज में कॉपी किए जाते हैं और हमेशा के लिए या 7 दिन तक मुफ़्त में रखे जाते हैं।
अनुरोध बनाएँ
कंट्रोल मॉडल स्कीमा से जनरेट होते हैं। इन्हें बदलने पर कोड और कीमत अपडेट होती है।
/run/hunyuan-image/v3/instruct/edit?wait=20
कोटेशन → $0.174
# 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/hunyuan-image/v3/instruct/edit?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",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/hunyuan-image/v3/instruct/edit?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/hunyuan-image/v3/instruct/edit", 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": "hunyuan-image/v3/instruct/edit",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"wait_seconds": 20
}
}
}
यह अनुरोध चलाएँ
आपकी key इसी ब्राउज़र में रहती है: इसे केवल Doitong API को भेजा जाता है और केवल तभी (localStorage) में सेव किया जाता है जब आप Remember चुनते हैं। API कुंजी प्राप्त करें
Hunyuan Image · v3 · Instruct · Edit के बारे में
`prompt` के अनुसार इमेज संपादित करता है और `image_urls` में एक से तीन संदर्भ इमेज का उपयोग करता है। `image_size` का डिफ़ॉल्ट auto है, इसलिए मॉडल आउटपुट आकार चुनता है। अधिकतम 4 इमेज लौटाई जा सकती हैं, `guidance_scale` 1 से 20 तक होता है, और प्रॉम्प्ट विस्तार डिफ़ॉल्ट रूप से चालू है। आउटपुट png या jpeg होता है।
पैरामीटर
कैनोनिकल नाम या नेटिव नाम में से कोई एक भेजें, दोनों नहीं। कैनोनिकल नाम
promptआवश्यक
image_sizeवैकल्पिक
num_imagesवैकल्पिक
num_outputs
guidance_scaleवैकल्पिक
enable_prompt_expansionवैकल्पिक
seedवैकल्पिक
enable_safety_checkerवैकल्पिक
output_formatवैकल्पिक
image_urlsआवश्यक
images
फ़ाइल पैरामीटर में सार्वजनिक https:// URL, 10 MB तक का data: URI, या अपलोड का file_url लिया जाता है। फ़ाइलें
आउटपुट
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "hunyuan-image/v3/instruct/edit",
"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": 174,
"usd": "0.174",
"charged": 174,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image_urls": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"output": {
"images": [
{
"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,
"width": 1024,
"height": 768
}
],
"seed": 42
},
"outputs": [
{
"type": "image",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768,
"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"
}
}
आउटपुट के फ़ील्ड
- images
- array of object {url, content_type, file_name, file_size, width, height}निर्मित इमेज वाली सूची।
- seed
- integerनिर्माण के दौरान उपयोग किया गया आधार seed।
अन्य Hunyuan Image वेरिएंट
और मॉडल: इमेज एडिटिंग
AI एजेंट के लिए: इस पेज का Markdown यहाँ है https://doitong.com/hi/developers/models/hunyuan-image/v3/instruct/edit.md. सभी मॉडल और गाइड: https://doitong.com/developers/llms.txt






