Kling 3.0 Pro Image to Video
統合
kling-video/v3/pro/image-to-video
# 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/kling-video/v3/pro/image-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/image-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/kling-video/v3/pro/image-to-video", 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/ja/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": "kling-video/v3/pro/image-to-video",
"input": {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}
}
Doitong APIを通じてKling 3.0 Pro Image to Videoモデル(kling-video/v3/pro/image-to-video)を呼び出します。エージェント向けドキュメント: https://doitong.com/ja/developers/models/kling-video/v3/pro/image-to-video.md
POST https://api.doitong.ru/v1/run/kling-video/v3/pro/image-to-video?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}
レスポンスのステータスが"queued"または"running"の場合、"succeeded"になるまでGET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20をポーリングしてください。ファイルはoutputs[].urlにあります。同じボディでPOST https://api.doitong.ru/v1/quote/kling-video/v3/pro/image-to-videoを実行すると、実行前の正確な価格が返されます。
このリクエスト: $0.56 560 APIクレジット · ≈ ₽59.68 このページで実行
新しいAPIキーです。 これは今だけ表示され、コードと下記のAPIキー欄にすでに入力されています。秘密にしてください。ブラウザで実行されるコードに決して含めないでください。
例
リクエストを作成
コントロールはモデルスキーマから生成されます。値を変更するとコードと価格が更新されます。
/run/kling-video/v3/pro/image-to-video?wait=20
見積もり → $0.56
# 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/kling-video/v3/pro/image-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/image-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/kling-video/v3/pro/image-to-video", 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": "kling-video/v3/pro/image-to-video",
"input": {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
},
"wait_seconds": 20
}
}
}
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Kling 3.0 Pro Image to Videoについて
Kling の最上位画像から動画生成モデルです。開始画像の被写体を安定させながら、自然な動き、 カメラワーク、デフォルトで対応する音声と発話を追加します。終了画像を指定してショットの終点を制御し、 ショットごとのプロンプトで 1 回の生成を複数ショットに分割したり、 参照要素で繰り返し登場するキャラクターやオブジェクトを固定したりできます。フレーム形状は開始画像に従います。
パラメータ
正式名称またはネイティブ名のいずれか一方を送信してください。両方は送信しないでください。 正式名称
prompt任意
multi_prompt任意
multi_prompt[].prompt必須
multi_prompt[].duration任意
start_image_url必須
image
duration任意
generate_audio任意
end_image_url任意
end_image
elements任意
elements[].frontal_image_url任意
elements[].reference_image_urls任意
elements[].video_url任意
elements[].voice_id任意
shot_type任意
negative_prompt任意
cfg_scale任意
ファイルパラメータには、公開されたhttps:// URL、10 MBまでのdata: URI、またはアップロードしたファイルのfile_urlを指定します。 ファイル
出力
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "kling-video/v3/pro/image-to-video",
"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": 560,
"usd": "0.56",
"charged": 560,
"refunded": 0
},
"input": {
"prompt": "The banana manager turns to the camera, smiles and waves while coworkers keep typing, gentle handheld camera",
"image": "https://content.doitong.com/images/gp/image_20260610003801_541d9719_316882.png",
"duration": 5
},
"output": {
"video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_name": "0-output.mp4",
"file_size": 1843200
}
},
"outputs": [
{
"type": "video",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_size": 1843200,
"width": 1280,
"height": 720,
"duration": 5,
"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"
}
}
出力フィールド
- video
- object {url, content_type, file_name, file_size}モデルが生成した動画。
その他のKling v3バリアント
その他のモデル: 画像から動画
AIエージェント向け:このページのMarkdown版はこちらです: https://doitong.com/ja/developers/models/kling-video/v3/pro/image-to-video.md. すべてのモデルとガイド: https://doitong.com/developers/llms.txt