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.
Jede Ausführung kostet $0.05. Für $10 können Sie ca. 200 Mal ausführen.
Sie können fortfahren mit:
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()Installieren Sie das erforderliche Paket für Ihre Programmiersprache.
pip install requestsAlle 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"import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Geben Sie Ihren API-Schlüssel niemals in clientseitigem Code oder öffentlichen Repositories preis. Verwenden Sie stattdessen Umgebungsvariablen oder einen Backend-Proxy.
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())Senden Sie eine asynchrone Generierungsanfrage. Die API gibt eine Vorhersage-ID zurück, mit der Sie den Status prüfen und das Ergebnis abrufen können.
/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"
}
}Fragen Sie den Vorhersage-Endpunkt ab, um den aktuellen Status Ihrer Anfrage zu überprüfen.
/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)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.{
"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"
}
}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.
/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
}
}Die folgenden Parameter werden im Anfragekörper akzeptiert.
{
"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"
}Die API gibt eine Vorhersage-Antwort mit den generierten Ausgabe-URLs zurück.
{
"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 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.
npx skills add AtlasCloudAI/atlas-cloud-skillsErhalten Sie Ihren API-Schlüssel über das Atlas Cloud Dashboard und setzen Sie ihn als Umgebungsvariable.
export ATLASCLOUD_API_KEY="your-api-key-here"Nach der Installation können Sie natürliche Sprache in Ihrem KI-Assistenten verwenden, um auf alle Atlas Cloud Modelle zuzugreifen.
Der Atlas Cloud MCP-Server verbindet Ihre IDE mit über 400 KI-Modellen über das Model Context Protocol. Funktioniert mit jedem MCP-kompatiblen Client.
npx -y atlascloud-mcpFügen 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"
}
}
}
}{
"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