ReconViaGen 0.5
Whakauru
reconviagen-0.5
# 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/reconviagen-0.5?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/reconviagen-0.5?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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/reconviagen-0.5", 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/mi/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": "reconviagen-0.5",
"input": {
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
}
Karangahia te tauira ReconViaGen 0.5 (reconviagen-0.5) mā te Doitong API. Tuhinga mō ngā āpiha: https://doitong.com/mi/developers/models/reconviagen-0.5.md
POST https://api.doitong.com/v1/run/reconviagen-0.5?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}
Mēnā ko "queued" "running" rānei te tūnga whakautu, uiuitia GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 kia "succeeded"; kei outputs[].url ngā kōnae. Ko POST https://api.doitong.com/v1/quote/reconviagen-0.5 me taua tinana anō ka whakahoki i te utu tika i mua i te whakahaere.
Tēnei tono: $ 0.30 300 whiwhinga API Whakahaerehia ki tēnei whārangi
Tō kī API hou. Ka whakaaturia ināianei anake, ā, kua whakaurua kētia ki te waehere me te āpure kī API kei raro. Me huna: kaua rawa e waiho ki te waehere e whakahaere ana i roto i te pūtirotiro.
Kei konei tō hua tuatahi
Hangaia he tono ki raro nei, ka whakahaere mā tō kī API. Ka tāruatia ngā putanga ki tō mātou rokiroki, ka puritia mō ake tonu atu, mō rānei 7 rā mō te kore utu.
Hangaia he tono
Ka hangaia ngā mana whakahaere mai i te aronuinga o te tauira. Ka whakahoungia te waehere me te utu ina whakarerekē koe.
/run/reconviagen-0.5?wait=20
utu → $ 0.30
# 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/reconviagen-0.5?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/reconviagen-0.5?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"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/reconviagen-0.5", 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": "reconviagen-0.5",
"input": {
"images": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"wait_seconds": 20
}
}
}
Whakahaerehia tēnei tono
Ka noho tō kī ki tēnei pūtirotiro: ka tukuna ki te Doitong API anake, ā, ka tiakina ki te localStorage anake ina tohua e koe te Mahara. Tikina he kī API
Mō ReconViaGen 0.5
Ka hanga i tētahi tauira 3D mai i `image_urls`, e tango ana i te 1 ki te 16 tirohanga o taua mea; ka pai ake te hanga anō ina nui ake ngā tirohanga. Ka whakahoki i tētahi kōnae GLB me ngā rauemi PBR. Ka taea `resolution` te 512, 1024, 1536 rānei, `texture_size` te 1024, 2048, 4096 rānei, ā, mā `decimation_target` e whakarite te tatau pito mātiti mai i te 5,000 ki te 2,000,000. Mā `ss_source` me `multi_image_strategy` e kōwhiri te hanumi o te hanganga me ngā tirohanga, me ngā mana arataki me te tīpako mō ia wāhanga.
Ngā tawhā
Tukuna te ingoa tōmua, te ingoa taketake rānei, kaua e rua. Ngā ingoa tōmua
seedkōwhiringa
resolutionkōwhiringa
ss_sourcekōwhiringa
ss_guidance_strengthkōwhiringa
ss_guidance_rescalekōwhiringa
ss_sampling_stepskōwhiringa
ss_rescale_tkōwhiringa
slat_guidance_strengthkōwhiringa
slat_guidance_rescalekōwhiringa
slat_sampling_stepskōwhiringa
slat_rescale_tkōwhiringa
shape_slat_guidance_strengthkōwhiringa
shape_slat_guidance_rescalekōwhiringa
shape_slat_sampling_stepskōwhiringa
shape_slat_rescale_tkōwhiringa
tex_slat_guidance_strengthkōwhiringa
tex_slat_guidance_rescalekōwhiringa
tex_slat_sampling_stepskōwhiringa
tex_slat_rescale_tkōwhiringa
decimation_targetkōwhiringa
texture_sizekōwhiringa
image_urlse hiahiatia ana
images
multi_image_strategykōwhiringa
enable_safety_checkerkōwhiringa
Mō ngā tawhā kōnae, whakamahia he URL tūmatanui https://, he URI data: tae atu ki te 10 MB, he file_url rānei o tētahi tukuake. Ngā kōnae
Putanga
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "reconviagen-0.5",
"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": 300,
"usd": "0.30",
"charged": 300,
"refunded": 0
},
"input": {
"image_urls": [
"https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
]
},
"output": {
"model_glb": {
"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
},
"seed": 42
},
"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"
}
}
Ngā āpure o te putanga
- model_glb
- object {url, content_type, file_name, file_size}GLB kua whakaputaina kei roto he tauira 3D me ngā rauemi PBR.
- seed
- integerKākano i whakamahia i te whakaputanga.
Ētahi atu tauira: Atahanga ki te 3D
Mō ngā āpiha AI: kei te wātea tēnei whārangi hei Markdown ki https://doitong.com/mi/developers/models/reconviagen-0.5.md. Ngā tauira me ngā aratohu katoa: https://doitong.com/developers/llms.txt