Video Prompt Generator
Whakauru
video-prompt-generator
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/video-prompt-generator?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input_concept": "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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/video-prompt-generator?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"input_concept": "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/video-prompt-generator", 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.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "video-prompt-generator",
"input": {
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Karangahia te tauira Video Prompt Generator (video-prompt-generator) mā te Doitong API. Tuhinga mō ngā āpiha: https://doitong.com/mi/developers/models/video-prompt-generator.md
POST https://api.doitong.ru/v1/run/video-prompt-generator?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
Mēnā ko "queued" "running" rānei te tūnga whakautu, uiuitia GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 kia "succeeded"; kei outputs[].url ngā kōnae. Ko POST https://api.doitong.ru/v1/quote/video-prompt-generator me taua tinana anō ka whakahoki i te utu tika i mua i te whakahaere.
Tēnei tono: $ 0.001 1 whiwhinga API · ≈ ₽ 0.11 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/video-prompt-generator?wait=20
utu → $ 0.001
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/video-prompt-generator?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input_concept": "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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/video-prompt-generator?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"input_concept": "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/video-prompt-generator", 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": "video-prompt-generator",
"input": {
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"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 Video Prompt Generator
Ka tango i tētahi `input_concept` ka hanga aki mā te `style`, `camera_style`, `camera_direction`, `pacing` me `special_effects` kua kōwhiria. Ka taea te tāpiri `custom_elements`, `image_url` rānei, te kōwhiri i te tauira reo, me te tautuhi `prompt_length` ki Short, Medium, Long rānei. Ka whakahoki i te aki hei kuputuhi.
Ngā tawhā
Tukuna te ingoa tōmua, te ingoa taketake rānei, kaua e rua. Ngā ingoa tōmua
input_concepte hiahiatia ana
stylekōwhiringa
camera_stylekōwhiringa
+5 anō
Snorricam characterWhip pan dynamicsDutch angle tensionUnderwater housingPeriscope lenscamera_directionkōwhiringa
+2 anō
Vertical riseVertical descentpacingkōwhiringa
+4 anō
Ramping dynamicsMontage tempoContinuous flowEpisodic breaksspecial_effectskōwhiringa
+5 anō
Miniature integrationWeather simulationColor gradingMixed media compositeNeural style transfercustom_elementskōwhiringa
image_urlkōwhiringa
image
modelkōwhiringa
prompt_lengthkōwhiringa
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": "video-prompt-generator",
"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": {
"input_concept": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"prompt": "A futuristic city glows softly at dusk, captured with smooth gimbal movements and a slow burn pacing, enhanced by subtle holographic overlays."
},
"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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Ngā āpure o te putanga
- prompt
- stringTohutohu ataata i whakaputaina e te tauira.
Ētahi atu tauira: LLM
Mō ngā āpiha AI: kei te wātea tēnei whārangi hei Markdown ki https://doitong.com/mi/developers/models/video-prompt-generator.md. Ngā tauira me ngā aratohu katoa: https://doitong.com/developers/llms.txt