kwaivgi/kling-effects

Bild-zu-Video

Kling Effects API by Kuaishou

kwaivgi/kling-effects

Kling-effects

Adds post-processing and stylistic motion effects, expanding creative editing within Kling’s video suite.

Eingabe

Effect scene *

Bild *

Sie können Dateien hier ablegen oder zum Hochladen klicken

MAX:1

Ausgabe

Inaktiv

Ihre generierten Videos erscheinen hier

Konfigurieren Sie Parameter und klicken Sie auf Ausführen, um mit der Generierung zu beginnen

Jede Ausführung kostet $0.212. Für $10 können Sie ca. 47 Mal ausführen.

Sie können fortfahren mit:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameter

Codebeispiel
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-effects",  # Required. model name
    "effect_scene": "example_value",  # Required. Effect scene
    "image": "example_value",  # Required. Image URL or Base64 encoding, in the format of data:image/png;base64,
}

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()

Installieren

Installieren Sie das erforderliche Paket für Ihre Programmiersprache.

pip install requests

Authentifizierung

Alle API-Anfragen erfordern eine Authentifizierung über einen API-Schlüssel. Sie können Ihren API-Schlüssel über das Atlas Cloud Dashboard erhalten.

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

HTTP-Header

import os

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

Schützen Sie Ihren API-Schlüssel

Geben Sie Ihren API-Schlüssel niemals in clientseitigem Code oder öffentlichen Repositories preis. Verwenden Sie stattdessen Umgebungsvariablen oder einen Backend-Proxy.

Anfrage senden

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())

Anfrage senden

Senden Sie eine asynchrone Generierungsanfrage. Die API gibt eine Vorhersage-ID zurück, mit der Sie den Status prüfen und das Ergebnis abrufen können.

POST/api/v1/model/generateVideo

Anfragekörper

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-effects",
    "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']}")

Antwort

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

Status prüfen

Fragen Sie den Vorhersage-Endpunkt ab, um den aktuellen Status Ihrer Anfrage zu überprüfen.

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

Abfrage-Beispiel

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)

Statuswerte

processingDie Anfrage wird noch verarbeitet.

completedDie Generierung ist abgeschlossen. Ergebnisse sind verfügbar.

succeededDie Generierung war erfolgreich. Ergebnisse sind verfügbar.

failedDie Generierung ist fehlgeschlagen. Überprüfen Sie das Fehlerfeld.

Abgeschlossene Antwort

{
  "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"
  }
}

Dateien hochladen

Laden Sie Dateien in den Atlas Cloud Speicher hoch und erhalten Sie eine URL, die Sie in Ihren API-Anfragen verwenden können. Verwenden Sie multipart/form-data zum Hochladen.

POST/api/v1/model/uploadMedia

Upload-Beispiel

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}")

Antwort

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

Eingabe-Schema

Die folgenden Parameter werden im Anfragekörper akzeptiert.

Gesamt: 3Erforderlich: 3Optional: 0

modelstringrequired

model name

Default: "kwaivgi/kling-effects"

effect_scenestringrequired

Effect scene

firework_2026glamour_photo_shootbox_of_joyfirst_toast_of_the_yearmy_santa_picsanta_giftsteampunk_christmassnowglobeornament_crashsanta_expressinstant_christmasparticle_santa_surroundcoronation_of_frostbuilding_sweaterspark_in_the_snowscarlet_and_snowcozy_toon_wrapbullet_time_litemagic_cloakballoon_paradejumping_ginger_joybullet_timec4d_cartoon_propure_white_wingsblack_wingsgolden_wingpink_pink_wingsvenomous_spiderthrone_of_kingluminous_elfwoodland_elfjapanese_anime_1american_comicsguardian_spiritswish_swishsnowboardingwitch_transformvampire_transformpumpkin_head_transformdemon_transformmummy_transformzombie_transformcute_pumpkin_transformcute_ghost_transformknock_knock_halloweenhalloween_escapebaseballinner_voicea_list_lookmemory_alivetrampolinetrampoline_nightpucker_upguess_whatfeed_mooncakerampage_apeflyerdishwasherpet_chinese_operagallery_ringmuscle_petsqueeze_screamrunning_mandisappearmythic_stylesteampunkc4d_cartoon3d_cartoon_13d_cartoon_2eagle_snatchhug_from_pastfireworkhugkissheart_gesturefightemojilet's_ridelet’s_ridesnatchedmagic_broomfelt_feltjumpdropcelebrationsplashsplashhulasurfsurffairy_wingangel_wingdark_wingskateskateplushcutjelly_pressjelly_slicejelly_squishjelly_jigglepixelpixelyearbookinstant_filmanime_figurerocketrocketbloombloomdizzydizzyfuzzyfuzzysquishexpansionsanta_giftssanta_huggirlfriendboyfriendboylfriendheart_gesture_1pet_wizardpet_lionsmoke_smokethumbs_uppet_chefpet_deliveryinstant_kiddollar_raincry_crybuilding_collapsegun_shotmushroomdouble_gunpet_warriorlightning_powerjesus_hugmagic_fireballshark_alertlong_hairlie_flatpolar_bear_hugbrown_bear_hugjazz_jazzoffice_escape_plowoffic_escape_plowfly_flywatermelon_bombpet_danceboss_comingwool_curlyiron_warriorpet_moto_riderpet_beemarry_meswing_swingday_to_nightpiggy_morphwig_outcar_explosionski_skitiger_hugsiblingsconstruction_workermedia_interview

imagestringrequired

Image URL or Base64 encoding, in the format of data:image/png;base64,...

Beispiel-Anfragekörper

{
  "model": "kwaivgi/kling-effects",
  "effect_scene": "example_effect_scene",
  "image": "example_image"
}

Ausgabe-Schema

Die API gibt eine Vorhersage-Antwort mit den generierten Ausgabe-URLs zurück.

created_atstring

ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

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.

Beispielantwort

{
  "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 integriert über 400 KI-Modelle direkt in Ihren KI-Programmierassistenten. Ein Befehl zur Installation, dann generieren Sie per natürlicher Sprache Bilder und Videos und chatten mit LLMs.

Unterstützte Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ unterstützte clients

Installieren

npx skills add AtlasCloudAI/atlas-cloud-skills

API-Schlüssel einrichten

Erhalten Sie Ihren API-Schlüssel über das Atlas Cloud Dashboard und setzen Sie ihn als Umgebungsvariable.

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

Funktionen

Nach der Installation können Sie natürliche Sprache in Ihrem KI-Assistenten verwenden, um auf alle Atlas Cloud Modelle zuzugreifen.

BildgenerierungGenerieren Sie Bilder mit Modellen wie Nano Banana 2, Z-Image und mehr.

VideoerstellungErstellen Sie Videos aus Text oder Bildern mit Kling, Vidu, Veo usw.

LLM-ChatChatten Sie mit Qwen, DeepSeek und anderen großen Sprachmodellen.

Medien-UploadLaden Sie lokale Dateien für Bildbearbeitung und Bild-zu-Video-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/atlas-cloud-skills

MCP-Server

Der Atlas Cloud MCP-Server verbindet Ihre IDE mit über 400 KI-Modellen über das Model Context Protocol. Funktioniert mit jedem MCP-kompatiblen Client.

Unterstützte Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ unterstützte clients

Installieren

npx -y atlascloud-mcp

Konfiguration

Fügen Sie die folgende Konfiguration zur MCP-Einstellungsdatei Ihrer IDE hinzu.

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

Verfügbare Werkzeuge

atlas_generate_imageGenerieren Sie Bilder aus Textbeschreibungen.

atlas_generate_videoErstellen Sie Videos aus Text oder Bildern.

atlas_chatChatten Sie mit großen Sprachmodellen.

atlas_list_modelsDurchsuchen Sie über 400 verfügbare KI-Modelle.

atlas_quick_generateInhaltserstellung in einem Schritt mit automatischer Modellauswahl.

atlas_upload_mediaLaden Sie lokale Dateien für API-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/mcp-server

API-Schema

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "kwaivgi/kling-effects"
          },
          "effect_scene": {
            "description": "Effect scene",
            "enum": [
              "firework_2026",
              "glamour_photo_shoot",
              "box_of_joy",
              "first_toast_of_the_year",
              "my_santa_pic",
              "santa_gift",
              "steampunk_christmas",
              "snowglobe",
              "ornament_crash",
              "santa_express",
              "instant_christmas",
              "particle_santa_surround",
              "coronation_of_frost",
              "building_sweater",
              "spark_in_the_snow",
              "scarlet_and_snow",
              "cozy_toon_wrap",
              "bullet_time_lite",
              "magic_cloak",
              "balloon_parade",
              "jumping_ginger_joy",
              "bullet_time",
              "c4d_cartoon_pro",
              "pure_white_wings",
              "black_wings",
              "golden_wing",
              "pink_pink_wings",
              "venomous_spider",
              "throne_of_king",
              "luminous_elf",
              "woodland_elf",
              "japanese_anime_1",
              "american_comics",
              "guardian_spirit",
              "swish_swish",
              "snowboarding",
              "witch_transform",
              "vampire_transform",
              "pumpkin_head_transform",
              "demon_transform",
              "mummy_transform",
              "zombie_transform",
              "cute_pumpkin_transform",
              "cute_ghost_transform",
              "knock_knock_halloween",
              "halloween_escape",
              "baseball",
              "inner_voice",
              "a_list_look",
              "memory_alive",
              "trampoline",
              "trampoline_night",
              "pucker_up",
              "guess_what",
              "feed_mooncake",
              "rampage_ape",
              "flyer",
              "dishwasher",
              "pet_chinese_opera",
              "gallery_ring",
              "muscle_pet",
              "squeeze_scream",
              "running_man",
              "disappear",
              "mythic_style",
              "steampunk",
              "c4d_cartoon",
              "3d_cartoon_1",
              "3d_cartoon_2",
              "eagle_snatch",
              "hug_from_past",
              "firework",
              "hug",
              "kiss",
              "heart_gesture",
              "fight",
              "emoji",
              "let's_ride",
              "let’s_ride",
              "snatched",
              "magic_broom",
              "felt_felt",
              "jumpdrop",
              "celebration",
              "splashsplash",
              "hula",
              "surfsurf",
              "fairy_wing",
              "angel_wing",
              "dark_wing",
              "skateskate",
              "plushcut",
              "jelly_press",
              "jelly_slice",
              "jelly_squish",
              "jelly_jiggle",
              "pixelpixel",
              "yearbook",
              "instant_film",
              "anime_figure",
              "rocketrocket",
              "bloombloom",
              "dizzydizzy",
              "fuzzyfuzzy",
              "squish",
              "expansion",
              "santa_gifts",
              "santa_hug",
              "girlfriend",
              "boyfriend",
              "boylfriend",
              "heart_gesture_1",
              "pet_wizard",
              "pet_lion",
              "smoke_smoke",
              "thumbs_up",
              "pet_chef",
              "pet_delivery",
              "instant_kid",
              "dollar_rain",
              "cry_cry",
              "building_collapse",
              "gun_shot",
              "mushroom",
              "double_gun",
              "pet_warrior",
              "lightning_power",
              "jesus_hug",
              "magic_fireball",
              "shark_alert",
              "long_hair",
              "lie_flat",
              "polar_bear_hug",
              "brown_bear_hug",
              "jazz_jazz",
              "office_escape_plow",
              "offic_escape_plow",
              "fly_fly",
              "watermelon_bomb",
              "pet_dance",
              "boss_coming",
              "wool_curly",
              "iron_warrior",
              "pet_moto_rider",
              "pet_bee",
              "marry_me",
              "swing_swing",
              "day_to_night",
              "piggy_morph",
              "wig_out",
              "car_explosion",
              "ski_ski",
              "tiger_hug",
              "siblings",
              "construction_worker",
              "media_interview"
            ],
            "type": "string",
            "x-placeholder": "Select effect scene",
            "x-ui-component": "select-filter"
          },
          "image": {
            "description": "Image URL or Base64 encoding, in the format of data:image/png;base64,... ",
            "type": "string"
          }
        },
        "required": [
          "model",
          "effect_scene",
          "image"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "effect_scene",
          "image"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).",
            "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"
    }
  ]
}

LLM-freundliche Prompt-Vorlage

# kwaivgi/kling-effects

> Adds post-processing and stylistic motion effects, expanding creative editing within Kling’s video suite.


## 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-effects`


## 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-effects"`

- **`effect_scene`** (`string`, _required_):
  Effect scene
  - Options: "firework_2026", "glamour_photo_shoot", "box_of_joy", "first_toast_of_the_year", "my_santa_pic", "santa_gift", "steampunk_christmas", "snowglobe", "ornament_crash", "santa_express", "instant_christmas", "particle_santa_surround", "coronation_of_frost", "building_sweater", "spark_in_the_snow", "scarlet_and_snow", "cozy_toon_wrap", "bullet_time_lite", "magic_cloak", "balloon_parade", "jumping_ginger_joy", "bullet_time", "c4d_cartoon_pro", "pure_white_wings", "black_wings", "golden_wing", "pink_pink_wings", "venomous_spider", "throne_of_king", "luminous_elf", "woodland_elf", "japanese_anime_1", "american_comics", "guardian_spirit", "swish_swish", "snowboarding", "witch_transform", "vampire_transform", "pumpkin_head_transform", "demon_transform", "mummy_transform", "zombie_transform", "cute_pumpkin_transform", "cute_ghost_transform", "knock_knock_halloween", "halloween_escape", "baseball", "inner_voice", "a_list_look", "memory_alive", "trampoline", "trampoline_night", "pucker_up", "guess_what", "feed_mooncake", "rampage_ape", "flyer", "dishwasher", "pet_chinese_opera", "gallery_ring", "muscle_pet", "squeeze_scream", "running_man", "disappear", "mythic_style", "steampunk", "c4d_cartoon", "3d_cartoon_1", "3d_cartoon_2", "eagle_snatch", "hug_from_past", "firework", "hug", "kiss", "heart_gesture", "fight", "emoji", "let's_ride", "let’s_ride", "snatched", "magic_broom", "felt_felt", "jumpdrop", "celebration", "splashsplash", "hula", "surfsurf", "fairy_wing", "angel_wing", "dark_wing", "skateskate", "plushcut", "jelly_press", "jelly_slice", "jelly_squish", "jelly_jiggle", "pixelpixel", "yearbook", "instant_film", "anime_figure", "rocketrocket", "bloombloom", "dizzydizzy", "fuzzyfuzzy", "squish", "expansion", "santa_gifts", "santa_hug", "girlfriend", "boyfriend", "boylfriend", "heart_gesture_1", "pet_wizard", "pet_lion", "smoke_smoke", "thumbs_up", "pet_chef", "pet_delivery", "instant_kid", "dollar_rain", "cry_cry", "building_collapse", "gun_shot", "mushroom", "double_gun", "pet_warrior", "lightning_power", "jesus_hug", "magic_fireball", "shark_alert", "long_hair", "lie_flat", "polar_bear_hug", "brown_bear_hug", "jazz_jazz", "office_escape_plow", "offic_escape_plow", "fly_fly", "watermelon_bomb", "pet_dance", "boss_coming", "wool_curly", "iron_warrior", "pet_moto_rider", "pet_bee", "marry_me", "swing_swing", "day_to_night", "piggy_morph", "wig_out", "car_explosion", "ski_ski", "tiger_hug", "siblings", "construction_worker", "media_interview"

- **`image`** (`string`, _required_):
  Image URL or Base64 encoding, in the format of data:image/png;base64,... 



**Required Parameters Example**:

```json
{
  "model": "kwaivgi/kling-effects",
  "effect_scene": "firework_2026",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "kwaivgi/kling-effects",
  "effect_scene": "firework_2026",
  "image": ""
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

- **`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-effects",
  "effect_scene": "firework_2026",
  "image": ""
}'

# 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-effects)

Wird geladen...

Kling Effects

Kling effects is an AI-powered video generation model that creates stunning 5-second videos from a single image. It's perfect for creating engaging social media content, product showcases, and more. With its advanced technology, the model can generate a wide range of styles and effects, from futuristic and abstract to realistic and cinematic.

Kling V3.0 Turbo Text-to-Video

Kling V3.0 Turbo Text-to-Video generates dynamic cinematic videos from text prompts using MVL technology. Supports first/last frame control and audio generation.

Kling Effects API by Kuaishou

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Eine API für alle Media-KI.

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