Grok Imagine Video Image-to-Video API by xAI
xai/grok-imagine-video/image-to-video
Image-to-video
xAI Grok Imagine Video animates a starting frame image with natural-language motion prompts at 480p or 720p.
xAI Grok Imagine Video animates a starting frame image with natural-language motion prompts at 480p or 720p.
Join the Discord community for the latest model updates, prompts, and support.
Votre requête coûtera $0.05 par exécution. Avec $10, vous pouvez exécuter ce modèle environ 200 fois.
Vous pouvez continuer avec :
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": "xai/grok-imagine-video/image-to-video", # Required. Model name
"prompt": "A beautiful sunset over the ocean with gentle waves", # Required. Natural-language motion prompt
"image_url": "example_value", # Required. Public HTTPS URL or base64 data URI of the starting-frame image (JPEG, PNG, or WebP)
"duration": 8, # Length of generated video in seconds. (min: 1, max: 15)
"resolution": "720p", # Output resolution. options: 480p | 720p
"aspect_ratio": "16:9", # Output aspect ratio
}
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()Installez le package requis pour votre langage.
pip install requestsToutes 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"import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}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.
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())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.
/api/v1/model/generateVideoimport requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "xai/grok-imagine-video/image-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']}"){
"code": 200,
"data": {
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}
}Interrogez le point de terminaison de prédiction pour vérifier le statut actuel de votre requête.
/api/v1/model/prediction/{prediction_id}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)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.{
"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"
}
}Téléversez des fichiers vers le stockage Atlas Cloud et obtenez une URL utilisable dans vos requêtes API. Utilisez multipart/form-data pour le téléversement.
/api/v1/model/uploadMediaimport 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}"){
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Les paramètres suivants sont acceptés dans le corps de la requête.
{
"model": "xai/grok-imagine-video/image-to-video",
"prompt": "A beautiful landscape",
"image_url": "example_image_url",
"duration": 8,
"resolution": "720p",
"aspect_ratio": "16:9"
}L'API renvoie une réponse de prédiction avec les URL des résultats générés.
{
"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 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.
npx skills add AtlasCloudAI/atlas-cloud-skillsObtenez 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"Une fois installé, vous pouvez utiliser le langage naturel dans votre assistant IA pour accéder à tous les modèles Atlas Cloud.
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.
npx -y atlascloud-mcpAjoutez 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"
}
}
}
}{
"info": {
"title": "AtlasCloud API",
"version": "1.0.0",
"description": "The AtlasCloud API."
},
"paths": {
"/api/v1/model/generateVideo": {
"post": {
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "The request status."
}
},
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Input"
}
}
},
"required": true
}
},
"x-api-name": "model_run"
},
"/api/v1/model/prediction/{request_id}": {
"get": {
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "Result of the request."
}
},
"parameters": [
{
"in": "path",
"name": "request_id",
"schema": {
"type": "string",
"description": "Request ID"
},
"required": true
}
]
},
"x-api-name": "model_result"
}
},
"openapi": "3.0.0",
"servers": [
{
"url": "https://api.atlascloud.ai"
}
],
"components": {
"schemas": {
"Input": {
"type": "object",
"required": [
"model",
"prompt",
"image_url"
],
"properties": {
"model": {
"type": "string",
"description": "Model name.",
"default": "xai/grok-imagine-video/image-to-video"
},
"prompt": {
"type": "string",
"description": "Natural-language motion prompt. The starting frame is taken from the image."
},
"image_url": {
"type": "string",
"description": "Public HTTPS URL or base64 data URI of the starting-frame image (JPEG, PNG, or WebP)."
},
"duration": {
"type": "integer",
"default": 8,
"minimum": 1,
"maximum": 15,
"description": "Length of generated video in seconds. Range: 1–15."
},
"resolution": {
"type": "string",
"default": "720p",
"enum": [
"480p",
"720p"
],
"description": "Output resolution."
},
"aspect_ratio": {
"type": "string",
"default": "16:9",
"enum": [
"1:1",
"16:9",
"9:16",
"4:3",
"3:4",
"3:2",
"2:3"
],
"description": "Output aspect ratio. The default matches the input image; specifying a different value stretches the image."
}
},
"x-order-properties": [
"model",
"prompt",
"image_url",
"duration",
"resolution",
"aspect_ratio"
]
},
"PredictionResponse": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the prediction."
},
"urls": {
"type": "object",
"description": "Object containing related API endpoints."
},
"model": {
"type": "string",
"description": "Model ID used for the prediction."
},
"status": {
"type": "string",
"description": "Status of the task: created, processing, completed, or failed."
},
"outputs": {
"type": "array",
"items": {
"type": "string"
},
"description": "Array of URLs to the generated video (empty when status is not completed)."
},
"created_at": {
"type": "string",
"format": "date-time",
"description": "ISO timestamp of when the request was created."
},
"has_nsfw_contents": {
"type": "array",
"items": {
"type": "boolean"
},
"description": "Array of boolean values indicating NSFW detection for each output."
}
}
}
},
"securitySchemes": {
"apiKeyAuth": {
"in": "header",
"name": "Authorization",
"type": "apiKey"
}
}
}
}# xai/grok-imagine-video/image-to-video
> xAI Grok Imagine Video animates a starting frame image with natural-language motion prompts at 480p or 720p.
## 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**: `xai/grok-imagine-video/image-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: `"xai/grok-imagine-video/image-to-video"`
- **`prompt`** (`string`, _required_):
Natural-language motion prompt. The starting frame is taken from the image.
- **`image_url`** (`string`, _required_):
Public HTTPS URL or base64 data URI of the starting-frame image (JPEG, PNG, or WebP).
- **`duration`** (`integer`, _optional_):
Length of generated video in seconds. Range: 1–15.
- Default: `8`
- Min: 1
- Max: 15
- **`resolution`** (`string`, _optional_):
Output resolution.
- Default: `"720p"`
- Options: "480p", "720p"
- **`aspect_ratio`** (`string`, _optional_):
Output aspect ratio. The default matches the input image; specifying a different value stretches the image.
- Default: `"16:9"`
- Options: "1:1", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3"
**Required Parameters Example**:
```json
{
"model": "xai/grok-imagine-video/image-to-video",
"prompt": "",
"image_url": ""
}
```
**Full Example**:
```json
{
"model": "xai/grok-imagine-video/image-to-video",
"prompt": "",
"image_url": "",
"duration": 8,
"resolution": "720p",
"aspect_ratio": "16:9"
}
```
### Output Schema
The API returns the following output format:
- **`id`** (`string`, _optional_):
Unique identifier for the prediction.
- **`urls`** (`object`, _optional_):
Object containing related API endpoints.
- **`model`** (`string`, _optional_):
Model ID used for the prediction.
- **`status`** (`string`, _optional_):
Status of the task: created, processing, completed, or failed.
- **`outputs`** (`array[string]`, _optional_):
Array of URLs to the generated video (empty when status is not completed).
- **`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.
**Example Response**:
```json
{
"id": "",
"urls": {},
"model": "",
"status": "",
"outputs": [
""
],
"created_at": "",
"has_nsfw_contents": []
}
```
## 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": "xai/grok-imagine-video/image-to-video",
"prompt": "",
"image_url": "",
"duration": 8,
"resolution": "720p",
"aspect_ratio": "16:9"
}'
# 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/xai/grok-imagine-video/image-to-video)
The astronaut slowly walks forward
The astronaut slowly walks forward