
Kling v3.0 Std Image-to-Video API by Kuaishou
Kling v3.0 Standard Image-to-Video model by Kuaishou. High-quality video generation from images.
INPUT
OUTPUT
MenungguPermintaan Anda akan dikenakan biaya $0.071 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 140 kali.
Berikut yang dapat Anda lakukan selanjutnya:
Contoh kode
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-v3.0-std/image-to-video",
"prompt": "A beautiful sunset over the ocean with gentle waves",
"width": 512,
"height": 512,
"duration": 3,
"fps": 24,
}
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()Instalasi
Instal paket yang diperlukan untuk bahasa pemrograman Anda.
pip install requestsAutentikasi
Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.
export ATLASCLOUD_API_KEY="your-api-key-here"HTTP Headers
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.
Kirim permintaan
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())Kirim Permintaan
Kirim permintaan pembuatan asinkron. API mengembalikan prediction ID yang dapat Anda gunakan untuk memeriksa status dan mengambil hasil.
/api/v1/model/generateVideoIsi Permintaan
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-v3.0-std/image-to-video",
"input": {
"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['id']}")
print(f"Status: {result['status']}")Respons
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Periksa Status
Polling prediction endpoint untuk memeriksa status permintaan Anda saat ini.
/api/v1/model/prediction/{prediction_id}Contoh Polling
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)Nilai Status
processingPermintaan masih diproses.completedPembuatan selesai. Output tersedia.succeededPembuatan berhasil. Output tersedia.failedPembuatan gagal. Periksa field error.Respons Selesai
{
"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"
}
}Unggah File
Unggah file ke penyimpanan Atlas Cloud dan dapatkan URL yang dapat Anda gunakan dalam permintaan API Anda. Gunakan multipart/form-data untuk mengunggah.
/api/v1/model/uploadMediaContoh Unggah
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}")Respons
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Input Schema
Parameter berikut diterima di isi permintaan.
Tidak ada parameter yang tersedia.
Contoh Isi Permintaan
{
"model": "kwaivgi/kling-v3.0-std/image-to-video"
}Output Schema
API mengembalikan respons prediction dengan URL output yang dihasilkan.
Contoh Respons
{
"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 mengintegrasikan 300+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.
Klien yang Didukung
Instalasi
npx skills add AtlasCloudAI/atlas-cloud-skillsAtur API Key
Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.
export ATLASCLOUD_API_KEY="your-api-key-here"Kemampuan
Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.
MCP Server
Atlas Cloud MCP Server menghubungkan IDE Anda dengan 300+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.
Klien yang Didukung
Instalasi
npx -y atlascloud-mcpKonfigurasi
Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Alat yang Tersedia
Schema API
Schema tidak tersediaTidak ada contoh yang tersedia
Silakan masuk untuk melihat riwayat permintaan
Anda perlu masuk untuk mengakses riwayat permintaan model Anda.
MasukKling V3.0 Standard Image-to-Video
Kling V3.0 Standard Image-to-Video is Kuaishou's latest image-to-video generation model. Upload a reference image and describe the motion — the model generates cinematic video with optional synchronized sound, voice support, and start-to-end frame guidance.
Why Choose This?
- Latest Kling generation V3.0 delivers improved motion quality and visual fidelity over V2.6.
- Start-end frame guidance Optional end image for controlled transitions between two frames.
- Sound generation Optional synchronized sound effects generated alongside the video.
- Voice list support Add up to 2 custom voice entries for character dialogue.
- CFG scale control Fine-tune the balance between prompt adherence and creative freedom.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | No | Text description of the desired motion and action |
| negative_prompt | No | Elements to exclude from generation |
| image | Yes | Start frame image to animate (URL or upload) |
| end_image | No | End frame image for guided transitions |
| duration | No | Video length: 5 or 10 seconds (default: 5) |
| cfg_scale | No | Prompt adherence strength (default: 0.5) |
| sound | No | Generate synchronized sound (default: disabled) |
| voice_list | No | Custom voice entries, up to 2 (click "+ Add Item") |
How to Use
- Upload your image — provide the reference image to animate.
- Write your prompt (optional) — describe the motion, camera movement, and action.
- Upload end image (optional) — provide an end frame for guided transitions.
- Add negative prompt (optional) — specify what you want to avoid.
- Set duration — 5 seconds or 10 seconds.
- Adjust cfg_scale (optional) — higher for stricter prompt following, lower for more freedom.
- Enable sound (optional) — generate synchronized audio with the video.
- Add voices (optional) — add up to 2 voice entries for dialogue.
- Run — submit and download your video.
Best Use Cases
- Photo Animation — Bring portraits, landscapes, and product images to life.
- Scene Transitions — Use start and end frames for smooth visual transitions.
- Social Media Content — Create engaging videos with sound from still images.
- Marketing & Ads — Generate dynamic promotional videos from product photos.
- Storytelling — Animate scenes with synchronized audio and dialogue.
Pro Tips
- Use clear, descriptive prompts with specific motion details for best results.
- Add an end_image for controlled transitions between two visual states.
- Enable sound for a complete video experience with synchronized audio.
- Use negative prompts to avoid artifacts (e.g., "blurry, low quality, distorted").
- Lower cfg_scale for more creative variation, higher for strict prompt adherence.
- Use high-quality source images for better video results.
Notes
- Image is the only required field; prompt is optional but recommended.
- Duration options are 5 or 10 seconds only.
- Voice list supports a maximum of 2 entries.
- Ensure uploaded image URLs are publicly accessible.
Related Models
- Kling V3.0 Standard Text-to-Video — Generate video from text descriptions with V3.0 quality.
- Kling V2.6 Standard Image-to-Video — Previous generation image-to-video.
- Kling V2.6 Standard Text-to-Video — Previous generation text-to-video.






