Zum Hauptinhalt springen
POST
/
v1
/
videos
/
generations
curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'
import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "kling-video-o1",
  prompt: "Make the person in <<<image_1>>> wave at the camera",
  image_urls: ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/videos/generations"

    payload := map[string]interface{}{
        "model":        "kling-video-o1",
        "prompt":       "Make the person in <<<image_1>>> wave at the camera",
        "image_urls":   []string{"https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"},
        "mode":         "std",
        "duration":     5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/videos/generations";

        String payload = """
        {
          "model": "kling-video-o1",
          "prompt": "Make the person in <<<image_1>>> wave at the camera",
          "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
          "mode": "std",
          "duration": 5,
          "aspect_ratio": "16:9"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}
<?php

$url = "https://api.apimart.ai/v1/videos/generations";

$payload = [
    "model" => "kling-video-o1",
    "prompt" => "Make the person in <<<image_1>>> wave at the camera",
    "image_urls" => ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode" => "std",
    "duration" => 5,
    "aspect_ratio" => "16:9"
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>
require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/videos/generations")

payload = {
  model: "kling-video-o1",
  prompt: "Make the person in <<<image_1>>> wave at the camera",
  image_urls: ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
}

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

response = http.request(request)
puts response.body
import Foundation

let url = URL(string: "https://api.apimart.ai/v1/videos/generations")!

let payload: [String: Any] = [
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/videos/generations";

        var payload = @"{
            ""model"": ""kling-video-o1"",
            ""prompt"": ""Make the person in <<<image_1>>> wave at the camera"",
            ""image_urls"": [""https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp""],
            ""mode"": ""std"",
            ""duration"": 5,
            ""aspect_ratio"": ""16:9""
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}
{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_xxxxxxxxxx"
    }
  ]
}
{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": 401,
    "message": "Invalid authentication credentials",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": 402,
    "message": "Insufficient balance. Please top up your account",
    "type": "payment_required"
  }
}
{
  "error": {
    "code": 429,
    "message": "Rate limit exceeded. Please try again later",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": 500,
    "message": "Internal server error. Please try again later",
    "type": "server_error"
  }
}
curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'
import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "kling-video-o1",
  prompt: "Make the person in <<<image_1>>> wave at the camera",
  image_urls: ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/videos/generations"

    payload := map[string]interface{}{
        "model":        "kling-video-o1",
        "prompt":       "Make the person in <<<image_1>>> wave at the camera",
        "image_urls":   []string{"https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"},
        "mode":         "std",
        "duration":     5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/videos/generations";

        String payload = """
        {
          "model": "kling-video-o1",
          "prompt": "Make the person in <<<image_1>>> wave at the camera",
          "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
          "mode": "std",
          "duration": 5,
          "aspect_ratio": "16:9"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}
<?php

$url = "https://api.apimart.ai/v1/videos/generations";

$payload = [
    "model" => "kling-video-o1",
    "prompt" => "Make the person in <<<image_1>>> wave at the camera",
    "image_urls" => ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode" => "std",
    "duration" => 5,
    "aspect_ratio" => "16:9"
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>
require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/videos/generations")

payload = {
  model: "kling-video-o1",
  prompt: "Make the person in <<<image_1>>> wave at the camera",
  image_urls: ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
}

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

response = http.request(request)
puts response.body
import Foundation

let url = URL(string: "https://api.apimart.ai/v1/videos/generations")!

let payload: [String: Any] = [
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/videos/generations";

        var payload = @"{
            ""model"": ""kling-video-o1"",
            ""prompt"": ""Make the person in <<<image_1>>> wave at the camera"",
            ""image_urls"": [""https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp""],
            ""mode"": ""std"",
            ""duration"": 5,
            ""aspect_ratio"": ""16:9""
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}
{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_xxxxxxxxxx"
    }
  ]
}
{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": 401,
    "message": "Invalid authentication credentials",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": 402,
    "message": "Insufficient balance. Please top up your account",
    "type": "payment_required"
  }
}
{
  "error": {
    "code": 429,
    "message": "Rate limit exceeded. Please try again later",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": 500,
    "message": "Internal server error. Please try again later",
    "type": "server_error"
  }
}

Autorisierung

Authorization
string
erforderlich
Alle API-Endpunkte erfordern eine Authentifizierung per Bearer TokenAPI-Schlüssel abrufen:Besuchen Sie die Seite zur API-Schlüsselverwaltung, um Ihren API-Schlüssel zu erhaltenFügen Sie ihn dem Anfrage-Header hinzu:
Authorization: Bearer YOUR_API_KEY

Anfrageparameter

model
string
erforderlich
Name des VideogenerierungsmodellsUnterstützte Modelle:
  • kling-video-o1 — Kling Video O1 (Reasoning-erweitert, höchste Qualität)
prompt
string
erforderlich
Positiver TextpromptUnterstützt das Referenzieren von Bildern aus image_urls mit der Syntax <<<image_N>>>, wobei N bei 1 beginnt.Beispiel: "Make the person in <<<image_1>>> wave at the camera"
Wenn Bilder bereitgestellt werden, der Prompt aber keine <<<image_N>>>-Referenz enthält, fügt das System automatisch <<<image_1>>> an den Anfang des Prompts an.
mode
string
Standard:"std"
GenerierungsmodusOptionen:
  • std — Standardmodus (720P)
  • pro — Profimodus (1080P)
Standard: std
duration
integer
Standard:"5"
Videodauer (Sekunden)Optionen: 5 oder 10Standard: 5
aspect_ratio
string
Standard:"16:9"
Seitenverhältnis des VideosOptionen:
  • 16:9 — Querformat
  • 9:16 — Hochformat
  • 1:1 — Quadrat
Standard: 16:9
image_urls
array<url>
Array mit Bild-URLs für BildreferenzenReferenzieren Sie die entsprechenden Bilder im Prompt mit der Syntax <<<image_N>>> (N beginnt bei 1)Beispiel: ["https://example.png"]
  • Bild-URLs müssen öffentlich zugänglich sein, ohne Hotlink-Schutz
  • Im Image-to-Video-Modus kann aspect_ratio durch das tatsächliche Seitenverhältnis des Bildes überschrieben werden
  • Bis zu zwei Bilder. Das erste Element im Array ist das Startbild, das zweite das Endbild
image_with_roles
array<object>
Rollenbasiertes Bild-Array, empfohlen für Image-to-Video.Format jedes Elements: { "url": "...", "role": "..." }
  • first_frame: erstes Bild
  • last_frame: letztes Bild
  • reference: Referenzbild
  • image_urls und image_with_roles schließen sich gegenseitig aus, übergeben Sie nicht beide gleichzeitig.
  • Bei mehr als 2 Bildern wird das Festlegen von Start- und Endbild nicht unterstützt.
video_list
array
Liste der Referenzvideos (URL-basiert), bis zu 1 Video.Verwenden Sie refer_type, um Typen zu unterscheiden:
  • base: zu bearbeitendes Video (Standard)
  • feature: Feature-Referenzvideo
Verwenden Sie keep_original_sound, um zu steuern, ob der Originalton beibehalten wird:
  • no: nicht behalten (Standard)
  • yes: Originalton behalten
Anfrageformat:
"video_list":[
  { "video_url": "video_url", "refer_type": "base", "keep_original_sound": "no" }
]
  • video_url darf nicht leer sein, und die Video-URL muss zugänglich sein
  • Bei refer_type=base:
    • Erste/letzte Bilder können nicht definiert werden
    • Das Referenzvideo muss 3–10 Sekunden lang sein
    • Die Dauer des erzeugten Videos richtet sich nach dem hochgeladenen Video
  • Bei refer_type=feature und nicht leerer video_url:
    • image_urls darf nur ein Bild für das erste Bild enthalten
  • Video-Anforderungen: Nur MP4/MOV; mindestens 3 Sekunden Dauer; Auflösung 720–2160 px; Bildrate 24–60 fps (Ausgabe ist 24 fps); maximal 200 MB Größe

Bildreferenz-Syntax

Das Video-O1-Modell verwendet die Syntax <<<image_N>>>, um Bilder in Prompts zu referenzieren, und bietet so ein einheitliches Text-to-Video- / Image-to-Video-Erlebnis:
SyntaxBeschreibung
<<<image_1>>>Verweist auf das 1. Bild im Array image_urls
<<<image_2>>>Verweist auf das 2. Bild im Array image_urls
Automatische Referenz: Wenn image_urls bereitgestellt wird, der Prompt aber keine <<<image_N>>>-Referenz enthält, fügt das System automatisch <<<image_1>>> an den Anfang des Prompts an.

Antwort

code
integer
Statuscode der Antwort, 200 bei Erfolg
data
array
Datenarray der Antwort

Anwendungsfälle

Fall 1: Text-zu-Video (höchste Qualität)

{
  "model": "kling-video-o1",
  "prompt": "A cinematic shot of a city skyline at golden hour",
  "mode": "pro",
  "duration": 5,
  "aspect_ratio": "16:9"
}

Fall 2: Bildreferenz (einzelnes Bild)

{
  "model": "kling-video-o1",
  "prompt": "Make the person in <<<image_1>>> wave at the camera",
  "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  "mode": "pro",
  "duration": 5
}

Fall 3: Mehrere Bildreferenzen

{
  "model": "kling-video-o1",
  "prompt": "The character in <<<image_1>>> walks toward the scene in <<<image_2>>>",
  "image_urls": [
    "https://example.com/character.jpg",
    "https://example.com/scene.jpg"
  ],
  "mode": "pro",
  "duration": 5
}

Fall 4: Bild ohne explizite Referenz bereitgestellt (automatisch hinzugefügt)

{
  "model": "kling-video-o1",
  "prompt": "The person slowly turns and smiles",
  "image_urls": ["https://upload.apimart.ai/f/models/9998230426123070-e9d6af04-cb5e-4731-8ae7-abf144cb0d29-9998230586368386-29641169-f698-4ab9-9b6d-380899e6521e-9998230593110693-c1741a3a-.webp"],
  "mode": "std",
  "duration": 5
}
Das System fügt <<<image_1>>> automatisch am Anfang des Prompts hinzu, was "<<<image_1>>>The person slowly turns and smiles" entspricht.
Aufgabenergebnisse abfragenDie Videogenerierung ist eine asynchrone Aufgabe, die bei der Einreichung eine task_id zurückgibt. Verwenden Sie den Endpunkt Aufgabenstatus abrufen, um Fortschritt und Ergebnis abzufragen.