kwaivgi/kling-video-o3-std/text-to-video

texte-vers-vidéo

Kling Video O3 Std Text-to-Video API by Kuaishou

kwaivgi/kling-video-o3-std/text-to-video

Text-to-video

Kling Omni Video O3 (Standard) is Kuaishou's advanced unified multi-modal video model with MVL (Multi-modal Visual Language) technology. Generates high-quality videos from text prompts with natural motion and audio generation support.

Entrée

Prompt

Tapez @ pour référencer un sujet.

Multi-plan

Sujets

MAX: 6

Format d'Image

Durée

Son

Sortie

Inactif

Les vidéos générées apparaîtront ici

Configurez vos paramètres et cliquez sur exécuter pour commencer

Votre requête coûtera $0.071 par exécution. Avec $10, vous pouvez exécuter ce modèle environ 140 fois.

Vous pouvez continuer avec :

Seedance 2.0 Kling v3 Vidu Wan2.7

Paramètres

Exemple de code
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "kwaivgi/kling-video-o3-std/text-to-video",  # Required. model name. default: "kwaivgi/kling-video-o3-std/text-to-video-test"
    "aspect_ratio": "16:9",  # The aspect ratio of the generated video. options: 16:9 | 9:16 | 1:1
    "duration": 5,  # The duration of the generated media in seconds (3-15)
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # The positive prompt for the generation
    "sound": True,  # Whether to generate audio for the video
    "multi_shot": False,  # Whether to enable multi-shot generation
    "shot_type": "example_value",  # Multi-shot mode. options: customize | intelligence
    "multi_prompt": [
        {
            "prompt": "example_prompt",
            "duration": 1
        }
    ],  # Per-shot storyboards
    "elements": [
        {
            "reference_type": "image_refer",
            "frontal_image": "example_frontal_image",
            "refer_images": [
                "https://example.com/image1.jpg"
            ],
            "refer_videos": [
                "https://example.com/image1.jpg"
            ],
            "element_name": "example_element_name",
            "element_description": "example_element_description",
            "element_id": 0
        }
    ],  # Subject references (Atlas naming; maps to Kling 'element_list')
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

Installer

Installez le package requis pour votre langage.

pip install requests

Authentification

Toutes les requêtes API nécessitent une authentification via une clé API. Vous pouvez obtenir votre clé API depuis le tableau de bord Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

En-têtes HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Protégez votre clé API

N'exposez jamais votre clé API dans du code côté client ou dans des dépôts publics. Utilisez plutôt des variables d'environnement ou un proxy backend.

Soumettre une requête

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Soumettre une requête

Soumettez une requête de génération asynchrone. L'API renvoie un identifiant de prédiction que vous pouvez utiliser pour vérifier le statut et récupérer le résultat.

POST/api/v1/model/generateVideo

Corps de la requête

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "kwaivgi/kling-video-o3-std/text-to-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Réponse

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Vérifier le statut

Interrogez le point de terminaison de prédiction pour vérifier le statut actuel de votre requête.

GET/api/v1/model/prediction/{prediction_id}

Exemple d'interrogation

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Valeurs de statut

processingLa requête est encore en cours de traitement.

completedLa génération est terminée. Les résultats sont disponibles.

succeededLa génération a réussi. Les résultats sont disponibles.

failedLa génération a échoué. Vérifiez le champ d'erreur.

Réponse terminée

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Téléverser des fichiers

Téléversez des fichiers vers le stockage Atlas Cloud et obtenez une URL utilisable dans vos requêtes API. Utilisez multipart/form-data pour le téléversement.

POST/api/v1/model/uploadMedia

Exemple de téléversement

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Réponse

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Schema d'entrée

Les paramètres suivants sont acceptés dans le corps de la requête.

Total: 9Requis: 1Optionnel: 8

modelstringrequired

model name

Default: "kwaivgi/kling-video-o3-std/text-to-video-test"

aspect_ratiostring

The aspect ratio of the generated video.

Default: "16:9"

16:99:161:1

durationinteger

The duration of the generated media in seconds (3-15).

Default: 5

3456789101112131415

promptstring

The positive prompt for the generation.

soundboolean

Whether to generate audio for the video.

Default: true

multi_shotboolean

Whether to enable multi-shot generation.

Default: false

shot_typestring

Multi-shot mode. customize = caller provides per-shot prompts; intelligence = model auto-splits the top-level prompt into shots. Required when multi_shot=true.

customizeintelligence

multi_promptarray[object]

Per-shot storyboards. Required when multi_shot=true and shot_type=customize. Sum of each shot's duration must equal the top-level duration; each shot duration must be >= 1.

Min items: 1Max items: 6

promptstringrequired

Prompt for this shot. Supports subject mentions like <<<element_1>>>.

durationintegerrequired

Duration of this shot in seconds (string, '1'~'15'). Sum of all shots must equal the top-level duration. Each shot duration >= 1.

Min: 1

elementsarray[object]

Subject references (Atlas naming; maps to Kling 'element_list'). Each item either references an existing subject by element_id, or creates a new one inline with element_name + reference_type + frontal_image / refer_images / refer_videos (Atlas wrapper feature — backend creates the element via Kling's element API, then injects the resulting element_id). Mention subjects in prompt with <<<element_N>>> (1-based, matches array position). For kling-v3-omni: up to 3 elements.

Max items: 6

reference_typestring

Reference media type for the new subject (Atlas wrapper).

Default: "image_refer"

image_refervideo_refer

frontal_imagestring

Frontal image URL of the new subject (required when reference_type=image_refer).

refer_imagesarray[string]

Reference image URLs of the new subject (used with reference_type=image_refer).

Max items: 4

refer_videosarray[string]

Reference video URLs of the new subject (used with reference_type=video_refer).

Max items: 4

element_namestring

Name of the new subject to create inline (Atlas wrapper). Mutually exclusive with element_id.

element_descriptionstring

Optional description of the new subject (Atlas wrapper).

element_idinteger

ID of an existing subject from the Kling element library (long / 64-bit integer). Mutually exclusive with element_name.

Exemple de corps de requête

{
  "model": "kwaivgi/kling-video-o3-std/text-to-video",
  "aspect_ratio": "16:9",
  "duration": 5,
  "sound": true,
  "multi_shot": false
}

Schema de sortie

L'API renvoie une réponse de prédiction avec les URL des résultats générés.

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction, the ID of the prediction to get.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty when status is not completed).

statusstring

Status of the task: created, processing, completed, or failed.

Exemple de réponse

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills intègre plus de 400 modèles d'IA directement dans votre assistant de codage IA. Une seule commande pour installer, puis utilisez le langage naturel pour générer des images, des vidéos et discuter avec des LLM.

Clients pris en charge

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clients pris en charge

Installer

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurer la clé API

Obtenez votre clé API depuis le tableau de bord Atlas Cloud et définissez-la comme variable d'environnement.

export ATLASCLOUD_API_KEY="your-api-key-here"

Fonctionnalités

Une fois installé, vous pouvez utiliser le langage naturel dans votre assistant IA pour accéder à tous les modèles Atlas Cloud.

Génération d'imagesGénérez des images avec des modèles comme Nano Banana 2, Z-Image, et plus encore.

Création de vidéosCréez des vidéos à partir de texte ou d'images avec Kling, Vidu, Veo, etc.

Chat LLMDiscutez avec Qwen, DeepSeek et d'autres grands modèles de langage.

Téléversement de médiasTéléversez des fichiers locaux pour l'édition d'images et les workflows image-vers-vidéo.

En savoir plus

github.com/AtlasCloudAI/atlas-cloud-skills

Serveur MCP

Le serveur MCP Atlas Cloud connecte votre IDE avec plus de 400 modèles d'IA via le Model Context Protocol. Compatible avec tout client compatible MCP.

Clients pris en charge

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clients pris en charge

Installer

npx -y atlascloud-mcp

Configuration

Ajoutez la configuration suivante au fichier de paramètres MCP de votre IDE.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Outils disponibles

atlas_generate_imageGénérez des images à partir de prompts textuels.

atlas_generate_videoCréez des vidéos à partir de texte ou d'images.

atlas_chatDiscutez avec de grands modèles de langage.

atlas_list_modelsParcourez plus de 400 modèles d'IA disponibles.

atlas_quick_generateCréation de contenu en une étape avec sélection automatique du modèle.

atlas_upload_mediaTéléversez des fichiers locaux pour les workflows API.

En savoir plus

github.com/AtlasCloudAI/mcp-server

Schéma API

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "kwaivgi/kling-video-o3-std/text-to-video-test"
          },
          "aspect_ratio": {
            "default": "16:9",
            "description": "The aspect ratio of the generated video.",
            "enum": [
              "16:9",
              "9:16",
              "1:1"
            ],
            "type": "string"
          },
          "duration": {
            "default": 5,
            "description": "The duration of the generated media in seconds (3-15).",
            "enum": [
              3,
              4,
              5,
              6,
              7,
              8,
              9,
              10,
              11,
              12,
              13,
              14,
              15
            ],
            "type": "integer",
            "x-ui-component": "select"
          },
          "prompt": {
            "description": "The positive prompt for the generation.",
            "type": "string"
          },
          "sound": {
            "default": true,
            "description": "Whether to generate audio for the video.",
            "type": "boolean"
          },
          "multi_shot": {
            "type": "boolean",
            "description": "Whether to enable multi-shot generation.",
            "default": false
          },
          "shot_type": {
            "type": "string",
            "description": "Multi-shot mode. customize = caller provides per-shot prompts; intelligence = model auto-splits the top-level prompt into shots. Required when multi_shot=true.",
            "enum": [
              "customize",
              "intelligence"
            ],
            "x-ui-component": "select"
          },
          "multi_prompt": {
            "type": "array",
            "description": "Per-shot storyboards. Required when multi_shot=true and shot_type=customize. Sum of each shot's duration must equal the top-level duration; each shot duration must be >= 1.",
            "minItems": 1,
            "maxItems": 6,
            "items": {
              "type": "object",
              "required": [
                "prompt",
                "duration"
              ],
              "properties": {
                "prompt": {
                  "type": "string",
                  "description": "Prompt for this shot. Supports subject mentions like <<<element_1>>>.",
                  "maxLength": 512
                },
                "duration": {
                  "type": "integer",
                  "description": "Duration of this shot in seconds (string, '1'~'15'). Sum of all shots must equal the top-level duration. Each shot duration >= 1.",
                  "minimum": 1
                }
              }
            }
          },
          "elements": {
            "type": "array",
            "description": "Subject references (Atlas naming; maps to Kling 'element_list'). Each item either references an existing subject by element_id, or creates a new one inline with element_name + reference_type + frontal_image / refer_images / refer_videos (Atlas wrapper feature — backend creates the element via Kling's element API, then injects the resulting element_id). Mention subjects in prompt with <<<element_N>>> (1-based, matches array position). For kling-v3-omni: up to 3 elements.",
            "maxItems": 6,
            "items": {
              "type": "object",
              "properties": {
                "reference_type": {
                  "type": "string",
                  "description": "Reference media type for the new subject (Atlas wrapper).",
                  "enum": [
                    "image_refer",
                    "video_refer"
                  ],
                  "default": "image_refer"
                },
                "frontal_image": {
                  "type": "string",
                  "description": "Frontal image URL of the new subject (required when reference_type=image_refer)."
                },
                "refer_images": {
                  "type": "array",
                  "description": "Reference image URLs of the new subject (used with reference_type=image_refer).",
                  "items": {
                    "type": "string"
                  },
                  "maxItems": 4
                },
                "refer_videos": {
                  "type": "array",
                  "description": "Reference video URLs of the new subject (used with reference_type=video_refer).",
                  "items": {
                    "type": "string"
                  },
                  "maxItems": 4
                },
                "element_name": {
                  "type": "string",
                  "description": "Name of the new subject to create inline (Atlas wrapper). Mutually exclusive with element_id."
                },
                "element_description": {
                  "type": "string",
                  "description": "Optional description of the new subject (Atlas wrapper).",
                  "x-hidden": true
                },
                "element_id": {
                  "type": "integer",
                  "description": "ID of an existing subject from the Kling element library (long / 64-bit integer). Mutually exclusive with element_name.",
                  "x-hidden": true
                }
              },
              "allOf": [
                {
                  "if": {
                    "properties": {
                      "reference_type": {
                        "const": "video_refer"
                      }
                    },
                    "required": [
                      "reference_type"
                    ]
                  },
                  "then": {
                    "required": [
                      "refer_videos"
                    ],
                    "properties": {
                      "frontal_image": {
                        "x-hidden": true
                      },
                      "refer_images": {
                        "x-hidden": true
                      },
                      "refer_videos": {
                        "minItems": 1
                      }
                    }
                  },
                  "else": {
                    "required": [
                      "frontal_image",
                      "refer_images"
                    ],
                    "properties": {
                      "refer_videos": {
                        "x-hidden": true
                      },
                      "refer_images": {
                        "minItems": 1
                      }
                    }
                  }
                }
              ]
            }
          }
        },
        "allOf": [
          {
            "if": {
              "properties": {
                "multi_shot": {
                  "const": true
                }
              },
              "required": [
                "multi_shot"
              ]
            },
            "then": {
              "required": [
                "shot_type"
              ]
            },
            "else": {
              "required": [
                "prompt"
              ],
              "properties": {
                "shot_type": {
                  "x-hidden": true
                },
                "multi_prompt": {
                  "x-hidden": true
                }
              }
            }
          },
          {
            "if": {
              "properties": {
                "shot_type": {
                  "const": "customize"
                }
              },
              "required": [
                "shot_type"
              ]
            },
            "then": {
              "required": [
                "multi_prompt"
              ],
              "properties": {
                "prompt": {
                  "x-hidden": true,
                  "x-hidden-hint": "Customize mode uses the per-shot prompts below. Your prompt is saved and reappears when you leave Customize mode."
                }
              }
            }
          },
          {
            "if": {
              "properties": {
                "shot_type": {
                  "const": "intelligence"
                }
              },
              "required": [
                "shot_type"
              ]
            },
            "then": {
              "required": [
                "prompt"
              ],
              "properties": {
                "multi_prompt": {
                  "x-hidden": true
                }
              }
            }
          }
        ],
        "required": [
          "model"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "multi_shot",
          "shot_type",
          "multi_prompt",
          "elements",
          "aspect_ratio",
          "duration",
          "sound"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction, the ID of the prediction to get.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/result/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "model": "kwaivgi/kling-video-o3-std/text-to-video"
}

Template de Prompt pour LLM

# kwaivgi/kling-video-o3-std/text-to-video

> Kling Omni Video O3 (Standard) is Kuaishou's advanced unified multi-modal video model with MVL (Multi-modal Visual Language) technology. Generates high-quality videos from text prompts with natural motion and audio generation support.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `kwaivgi/kling-video-o3-std/text-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"kwaivgi/kling-video-o3-std/text-to-video-test"`

- **`prompt`** (`string`, _optional_):
  The positive prompt for the generation.

- **`multi_shot`** (`boolean`, _optional_):
  Whether to enable multi-shot generation.
  - Default: `false`

- **`shot_type`** (`string`, _optional_):
  Multi-shot mode. customize = caller provides per-shot prompts; intelligence = model auto-splits the top-level prompt into shots. Required when multi_shot=true.
  - Options: "customize", "intelligence"

- **`multi_prompt`** (`array[object]`, _optional_):
  Per-shot storyboards. Required when multi_shot=true and shot_type=customize. Sum of each shot's duration must equal the top-level duration; each shot duration must be >= 1.
  - Min items: 1
  - Max items: 6
  - Item properties:
    - **`prompt`** (`string`, _required_):
      Prompt for this shot. Supports subject mentions like <<<element_1>>>.

    - **`duration`** (`integer`, _required_):
      Duration of this shot in seconds (string, '1'~'15'). Sum of all shots must equal the top-level duration. Each shot duration >= 1.
      - Min: 1


- **`elements`** (`array[object]`, _optional_):
  Subject references (Atlas naming; maps to Kling 'element_list'). Each item either references an existing subject by element_id, or creates a new one inline with element_name + reference_type + frontal_image / refer_images / refer_videos (Atlas wrapper feature — backend creates the element via Kling's element API, then injects the resulting element_id). Mention subjects in prompt with <<<element_N>>> (1-based, matches array position). For kling-v3-omni: up to 3 elements.
  - Max items: 6
  - Item properties:
    - **`reference_type`** (`string`, _optional_):
      Reference media type for the new subject (Atlas wrapper).
      - Default: `"image_refer"`
      - Options: "image_refer", "video_refer"

    - **`frontal_image`** (`string`, _optional_):
      Frontal image URL of the new subject (required when reference_type=image_refer).

    - **`refer_images`** (`array[string]`, _optional_):
      Reference image URLs of the new subject (used with reference_type=image_refer).
      - Max items: 4

    - **`refer_videos`** (`array[string]`, _optional_):
      Reference video URLs of the new subject (used with reference_type=video_refer).
      - Max items: 4

    - **`element_name`** (`string`, _optional_):
      Name of the new subject to create inline (Atlas wrapper). Mutually exclusive with element_id.

    - **`element_description`** (`string`, _optional_):
      Optional description of the new subject (Atlas wrapper).

    - **`element_id`** (`integer`, _optional_):
      ID of an existing subject from the Kling element library (long / 64-bit integer). Mutually exclusive with element_name.


- **`aspect_ratio`** (`string`, _optional_):
  The aspect ratio of the generated video.
  - Default: `"16:9"`
  - Options: "16:9", "9:16", "1:1"

- **`duration`** (`integer`, _optional_):
  The duration of the generated media in seconds (3-15).
  - Default: `5`
  - Options: 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15

- **`sound`** (`boolean`, _optional_):
  Whether to generate audio for the video.
  - Default: `true`



**Required Parameters Example**:

```json
{
  "model": "kwaivgi/kling-video-o3-std/text-to-video"
}
```


**Full Example**:

```json
{
  "model": "kwaivgi/kling-video-o3-std/text-to-video",
  "prompt": "",
  "multi_shot": false,
  "shot_type": "customize",
  "multi_prompt": [
    {
      "prompt": "",
      "duration": 1
    }
  ],
  "elements": [
    {
      "reference_type": "image_refer",
      "frontal_image": "",
      "refer_images": [
        ""
      ],
      "refer_videos": [
        ""
      ],
      "element_name": "",
      "element_description": "",
      "element_id": 0
    }
  ],
  "aspect_ratio": "16:9",
  "duration": 5,
  "sound": true
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "kwaivgi/kling-video-o3-std/text-to-video",
  "prompt": "",
  "multi_shot": false,
  "shot_type": "customize",
  "multi_prompt": [
    {
      "prompt": "",
      "duration": 1
    }
  ],
  "elements": [
    {
      "reference_type": "image_refer",
      "frontal_image": "",
      "refer_images": [
        ""
      ],
      "refer_videos": [
        ""
      ],
      "element_name": "",
      "element_description": "",
      "element_id": 0
    }
  ],
  "aspect_ratio": "16:9",
  "duration": 5,
  "sound": true
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/kwaivgi/kling-video-o3-std/text-to-video)

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Kling Video O3 Standard Text-to-Video

Kling Video O3 Standard is Kuaishou's advanced text-to-video model in the O3 family, delivering high-quality cinematic video from text descriptions. With optional synchronized sound generation, multiple aspect ratios, and flexible duration from 3 to 15 seconds, it offers a strong balance of quality and cost.

Why Choose This?

O3-level quality Advanced visual fidelity and motion realism beyond V3.0 models.

Sound generation Optional synchronized sound effects generated alongside the video.

Flexible duration Generate videos from 3 to 15 seconds — any length you need.

Multiple aspect ratios Support for 16:9, 9:16, and 1:1 to fit any platform.

Prompt Enhancer Built-in tool to automatically improve your video descriptions.

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the video scene and motion
aspect_ratio	No	Output ratio: 16:9 (default), 9:16, 1:1
duration	No	Video length: 3-15 seconds (default: 5)
sound	No	Generate synchronized sound (default: disabled)

How to Use

Run — submit and download your video.
Enable sound (optional) — generate synchronized audio with the video.
Set duration — choose any length from 3 to 15 seconds.
Select aspect ratio — match your target platform.
Write your prompt — describe the scene, characters, motion, and style in detail.

Best Use Cases

Long-Form Scenes — Up to 15 seconds for extended scene development.
Concept Visualization — Bring creative ideas to life from text.
Marketing Videos — Produce promotional content with optional sound.
Social Media — Create engaging videos for TikTok, Reels, and Stories.
Professional Content — High-quality videos at a more accessible price than O3 Pro.

Pro Tips

Use O3 Standard for regular production; upgrade to O3 Pro for maximum quality.
Use shorter durations (3-5s) for testing, longer (10-15s) for final production.
Be specific about camera movements, lighting, and atmosphere for best results.
Enable sound for a complete video experience with synchronized audio.
Match aspect ratio to your platform: 16:9 for YouTube, 9:16 for TikTok/Reels, 1:1 for Instagram.
Use the Prompt Enhancer to refine your descriptions automatically.

Notes

Duration supports any value from 3 to 15 seconds.
Only prompt is required; other parameters have defaults.

Kling V3.0 Pro Text-to-Video — V3.0 Pro quality text-to-video.
Kling V3.0 Standard Text-to-Video — V3.0 Standard at lower cost.
Kling Video O3 Pro Image-to-Video — O3 Pro quality image-to-video.

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Kling Video O3 Pro Video-Edit

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Kling Video O3 Std Text-to-Video API by Kuaishou

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