Grok Imagine Video Extend API by xAI
xai/grok-imagine-video/extend-video
Extend-video
xAI Grok Imagine Video continues an existing 2-15s mp4 with a 2-10s prompt-driven extension. Output matches input, capped at 720p.
xAI Grok Imagine Video continues an existing 2-15s mp4 with a 2-10s prompt-driven extension. Output matches input, capped at 720p.
Join the Discord community for the latest model updates, prompts, and support.
每次运行将花费 $0.07。$10 可运行约 142 次。
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/extend-video", # Required. Model name
"prompt": "A beautiful sunset over the ocean with gentle waves", # Required. Natural-language description of what should happen after the input video's last frame
"video_url": "example_value", # Required. Public URL of an mp4 file (H
"duration": 6, # Length of the extension segment in seconds. (min: 2, max: 10)
}
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()安装所需的依赖包。
pip install requests所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。
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}"
}切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。
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())提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。
/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/extend-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"
}
}轮询 prediction 端点以检查请求的当前状态。
/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)processing请求仍在处理中。completed生成完成，输出可用。succeeded生成成功，输出可用。failed生成失败，请检查 error 字段。{
"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"
}
}将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。
/api/v1/model/uploadMediaimport requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}"){
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}以下参数在请求体中被接受。
{
"model": "xai/grok-imagine-video/extend-video",
"prompt": "A beautiful landscape",
"video_url": "example_video_url",
"duration": 6
}API 返回包含生成输出 URL 的 prediction 响应。
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.mp4"
],
"metrics": {
"predict_time": 45.2
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills 将 400+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。
npx skills add AtlasCloudAI/atlas-cloud-skills从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。
export ATLASCLOUD_API_KEY="your-api-key-here"安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。
Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 400+ AI 模型连接。支持任何兼容 MCP 的客户端。
npx -y atlascloud-mcp将以下配置添加到您的 IDE 的 MCP 设置文件中。
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}{
"info": {
"title": "AtlasCloud API",
"version": "1.0.0",
"description": "The AtlasCloud API."
},
"paths": {
"/api/v1/model/generateVideo": {
"post": {
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$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",
"video_url"
],
"properties": {
"model": {
"type": "string",
"description": "Model name.",
"default": "xai/grok-imagine-video/extend-video"
},
"prompt": {
"type": "string",
"description": "Natural-language description of what should happen after the input video's last frame."
},
"video_url": {
"type": "string",
"description": "Public URL of an mp4 file (H.264/H.265/AV1, etc.). Input duration must be 2–15 seconds."
},
"duration": {
"type": "integer",
"default": 6,
"minimum": 2,
"maximum": 10,
"description": "Length of the extension segment in seconds. Range: 2–10 (default 6). Total returned video = input duration + extension. Output is capped at 720p."
}
},
"x-order-properties": [
"model",
"prompt",
"video_url",
"duration"
]
},
"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/extend-video
> xAI Grok Imagine Video continues an existing 2-15s mp4 with a 2-10s prompt-driven extension. Output matches input, capped at 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/extend-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/extend-video"`
- **`prompt`** (`string`, _required_):
Natural-language description of what should happen after the input video's last frame.
- **`video_url`** (`string`, _required_):
Public URL of an mp4 file (H.264/H.265/AV1, etc.). Input duration must be 2–15 seconds.
- **`duration`** (`integer`, _optional_):
Length of the extension segment in seconds. Range: 2–10 (default 6). Total returned video = input duration + extension. Output is capped at 720p.
- Default: `6`
- Min: 2
- Max: 10
**Required Parameters Example**:
```json
{
"model": "xai/grok-imagine-video/extend-video",
"prompt": "",
"video_url": ""
}
```
**Full Example**:
```json
{
"model": "xai/grok-imagine-video/extend-video",
"prompt": "",
"video_url": "",
"duration": 6
}
```
### 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/extend-video",
"prompt": "",
"video_url": "",
"duration": 6
}'
# 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/extend-video)
Change the car's color to blue and drive it on a racetrack.
Change the car's color to blue and drive it on a racetrack.