Video Prompt Generator
ᠵᡠᠸᡝᠪᡠᠮᠪᡳ
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/mnc/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"
}
}
Video Prompt Generator ᠮᠣᠳᡝᠯ (video-prompt-generator) ᠪᡝ Doitong API ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ. ᠠᡤᡝᠨᡨᡳ ᡩᠠᡳᠯᠠᠨ: https://doitong.com/mnc/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"
}
ᡝᡵᡝᠮᡝ ᠪᡠᠮᡝᠨᡳ ᠠᠨᠠᠮᡝ "queued" ᡳᠨᡠ "running" ᠪᡝ, GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 ᠪᡝ ᠠᠨᠠᠮᡝ "succeeded" ᠪᡝᠴᡳ ᠠᠰᡠᠮᠪᡳ; ᡶᡳᠯᡝ ᠪᡝ outputs[].url ᠪᡝᠴᡳ ᠣᠨᡩᠣᠮᡝ. POST https://api.doitong.ru/v1/quote/video-prompt-generator ᠪᡝ ᡝᠮᡠ ᠪᡠᠶᡝᠮᡝ ᠪᡝ ᠠᠰᡠᠮᠪᡳᡩᡝ ᠵᠠᠯᡤᠠᠨ ᠪᡝ ᠶᠠᠪᡠᠮᠪᡳ ᠰᡳᠨᡳ ᠠᠮᡤᠠ ᠠᠰᡠᠮᠪᡳ ᠣᠯᡥᠣᠮᡝ.
ᡝᠨᡳ ᠵᠠᠯᡳᠨ: $0.001 1 API ᠺᠷᡝᡩᡳᠲ · ≈ ₽0.11 ᡝᡵᡝ ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ
ᠰᡳᠨᡳ ᠵᠠᠮᡠᠰᡳᠨ API ᠵᡳᡵᡤᠠ. ᡝᠯᡝ ᡝᠨᡩᡝ ᡳᠯᡤᠠᠮᠪᡳ ᡝᡵᡝ ᠮᡠᠨᡩᡝ ᡴᠣᡩᡝ ᡩᠠᠮᡠ ᠮᡝᠨᡩᡝᡵᡝ ᠪᠠᡩᡝᠯᡝᠨ ᠠᠮᡪᡳ ᡳᠨᡠ API ᠵᡳᡵᡤᠠ ᡩᡝᠪᡨᡝᡵᡝ ᡩᡝ ᠠᡴᡠ᠉ ᡳᠨᡠ ᡝᡵᡝᠩᡤᡝ ᠠᠮᠪᠠᠨ ᠮᡠᠨᡩᡝ ᠪᡝ ᠠᠰᡠᡵᠠᠮᠪᡳ: ᠮᡠᡵᡝ ᡩᠠᠮᡠ ᠪᡠᠶᡝᡵᡝ ᠪᠠᡩᡝᠯᡝᠨ ᡩᡝ ᠰᡳᠨᡩᡝᠮᡝ ᠠᠪᡠᠮᡝ ᠰᠠᠮᡪᡳ᠉
ᡳᠨᡝ ᡝᠮᡠᠨᡳᠩᡤᡝ ᡝᡵᡝᠮᡝ ᡩᡝ
ᡝᡵᡝ ᠵᡠᠯᡝᠨ ᡩᡝ ᡤᡝᡪᡳᠯᡝᠨ ᠪᠠᠶᠠᠨᠠᠮᡝ ᠠᠮᡪᠠᠯᠠ ᡶᡳᠯᡝᠮᡝ ᠪᡝᠶᡝᠮᡝ᠃ API ᠵᡳᡵᡤᠠᡳ ᡤᠠᡳᡥᠠᡩᡝ ᡤᡝᡪᡳᠯᡝᠨ ᠵᠠᠯᠠᠨᠠᠮᡝ ᠪᡠᠶᡝᠮᡝ ᠮᡠᠰᡝᡳ ᠰᡠᠯᡠᠨᡩᡝ ᠪᠠᠶᠠᠨᠠᠮᡝ᠂ ᠮᡤᡳ ᠮᡠᠰᡝ ᠠᠶᠠᠨ 7 ᡥᠠᠨ ᠰᠠᡳᠨᠠᠮᡝ᠃
ᡤᡳᠰᡠᠨ ᠪᡠᠶᡝᠮᡝ
ᠵᠠᡴᡠᠨᡳ ᠵᡠᠯᡝ ᡩᡝᡵᡤᡳ ᡩᡝᠪᡝᠰᡠᠮᡝ ᠵᡠᠯᡤᡝ ᠪᡠᠶᡝᠮᡝ᠈ ᡳᠨᡳ ᡤᡳᠰᡠᠨ ᠪᠠᡳ ᡝᠨᡝᠩᡤᡳ ᠠᠮᠪᡳ
/run/video-prompt-generator?wait=20
ᠵᠠᠯᡳᠨ → $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
}
}
}
ᡝᠨᡳ ᠵᠠᠯᡳᠨ ᠪᡝ ᠵᠠᠯᠠᠨᠠᠮᡝ
ᡳᠨᡝ ᠵᠠᠯᠠᠨ ᡝᡵᡝ ᠪᡠᡵᡝᠪᡝᡵᡳ ᡩᡝ ᠪᡳᠮᡝ᠈ Doitong API ᡩᡝ ᠵᡝᠯᡤᡳ ᡩᠠᡵᠠᠮᡝ᠈ Remember ᠵᡠᠯᡝᠮᡝ ᡤᡳᠯᠠᠮᡝ localStorage ᡩᡝ ᠰᡠᠯᡝᠮᡝ ᠪᡳᠮᡝ API ᠵᠠᠯᠠᠨ ᠠᠪᠠᠮᡝ
Video Prompt Generator ᡠᡵᡝᠮᡝ
`input_concept` ᡳ ᠪᡝᠶᡝᠨ ᡩᡝᠨ ᠪᡝ ᠠᠪᡠᠮᡝ᠂ ᠰᠣᠩᡤᠣᡥᠠ `style`᠂ `camera_style`᠂ `camera_direction`᠂ `pacing` ᠣᠴᡳ `special_effects` ᡳ ᠵᠠᠯᡤᠠᠨ ᡩᡝ ᠵᠠᠰᠠᡥᠠ ᠵᠠᠯᡤᠠᠨ ᠪᡝ ᠪᡠᠮᠪᡳ。 `custom_elements` ᠣᠴᡳ `image_url` ᠪᡝ ᠠᠪᡠᠮᡝ ᠵᠠᠯᡤᠠᠨ ᡩᡝ ᠯᡝᡳᠯᡝᠮᡝ ᠪᡠᠮᠪᡳ,ᠵᠠᠯᡤᠠᠨ ᡳ ᠵᡠᠯᡤᡝᠨ ᠪᡝ ᠰᠣᠩᡤᠣᠮᡝ᠂ `prompt_length` ᠪᡝ Short᠂ Medium ᠣᠴᡳ Long ᠵᠠᠰᠠᠮᡝ ᠪᡠᠮᠪᡳ。 ᠮᡠᡵᡝᠨ ᠪᡝ ᠵᠠᠯᡤᠠᠨ ᡳ ᠵᡠᠯᡤᡝᠨ ᡩᡝ ᠪᡠᠮᠪᡳ。
ᠵᠠᡴᡠᠨ
ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ ᠵᡝᠯᡤᡳ ᠠᠪᠠᠮᠪᡳ᠈ ᠨᡝᠮᡝ ᠮᡠᠰᡝ ᡠᠯᠠᠮᠪᡳ ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ
input_conceptᡴᠠᠷᠠᡴᡡ
styleᠵᡠᠯᡝ
camera_styleᠵᡠᠯᡝ
+5 ᡝᠨᡝ
Snorricam characterWhip pan dynamicsDutch angle tensionUnderwater housingPeriscope lenscamera_directionᠵᡠᠯᡝ
+2 ᡝᠨᡝ
Vertical riseVertical descentpacingᠵᡠᠯᡝ
+4 ᡝᠨᡝ
Ramping dynamicsMontage tempoContinuous flowEpisodic breaksspecial_effectsᠵᡠᠯᡝ
+5 ᡝᠨᡝ
Miniature integrationWeather simulationColor gradingMixed media compositeNeural style transfercustom_elementsᠵᡠᠯᡝ
image_urlᠵᡠᠯᡝ
image
modelᠵᡠᠯᡝ
prompt_lengthᠵᡠᠯᡝ
ᠪᡠᠮᠪᡳᠯᡝᠰᡝ ᡝᠮᡠ ᡤᡝᠮᡠᠨᡳ https:// URL᠈ 10 MB ᡩᡝ ᡩᡝᠷᡤᡳ data: URI ᠵᡝᡵᡤᡳ ᡝᠮᡝ᠈ ᡳᠨᡝ ᠪᡠᠮᠪᡳᠯᡝᠰᡝᠨᡳ file_url ᠠᠪᠠᠮᠪᡳ ᠪᡠᠮᠪᡳ
ᠪᡠᠶᡝᠮᡝ
{
"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"
}
}
ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᡳᠰᡠᠨ
- prompt
- stringᠮᠣᡩᡝᠯ ᡳ ᠪᡠᠶᡝᠮᡝᠩᡤᡝ ᠰᡠᠨᡤᠠ ᡳ ᡥᡡᠯᠠᠨ᠉
ᡝᠯᡤᡳ ᡩᠠᠯᡳᠨ: LLM
AI ᠠᡤᡝᠨᡨᡳ ᡠᠴᡠᠷᡳ᠈ ᡝᡵᡝ ᡩᡝᠪᡝᡵᡳ Markdown ᠰᡳᠨᡩᠠᡵᡳ https://doitong.com/mnc/developers/models/video-prompt-generator.md. ᡝᡵᡝ ᠮᠣᡩᡝᠯ ᠵᠠᡴᡠᠨ ᠰᡠᠯᡠᠮᡝ https://doitong.com/developers/llms.txt