xAI Grok Imagine edits one or more reference images with natural-language instructions at 1K or 2K resolution. Supports single image and multi-image (<IMAGE_0>, <IMAGE_1>) reference editing.
كل مرة ستكلف $0.02 مع $10 يمكنك التشغيل حوالي 500 مرة
يمكنك المتابعة بـ:
import requests
import time
# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "xai/grok-imagine-image/edit", # Required. Model name
"prompt": "Render this as a pencil sketch with detailed shading.", # Required. Editing instruction
"image_urls": [], # Required. Source images
"num_images": 1, # Number of edited images to generate. options: 1 | 2 | 3 | 4
"aspect_ratio": "auto", # Aspect ratio of the edited image
"resolution": "1k", # Output resolution. options: 1k | 2k
"enable_base64_output": False, # If enabled, the output will be encoded into a BASE64 string instead of a URL
}
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"] == "completed":
print("Generated image:", 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)
image_url = check_status()قم بتثبيت الحزمة المطلوبة للغة البرمجة الخاصة بك.
pip install requestsتتطلب جميع طلبات API المصادقة عبر مفتاح API. يمكنك الحصول على مفتاح API الخاص بك من لوحة تحكم 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}"
}لا تكشف أبدًا مفتاح API الخاص بك في الكود من جانب العميل أو المستودعات العامة. استخدم متغيرات البيئة أو وكيل الخادم الخلفي بدلاً من ذلك.
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
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())أرسل طلب توليد غير متزامن. تُرجع API معرّف التنبؤ الذي يمكنك استخدامه للتحقق من الحالة واسترداد النتيجة.
/api/v1/model/generateImageimport requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "xai/grok-imagine-image/edit",
"prompt": "A beautiful landscape with mountains and lake"
}
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"
}
}استعلم عن نقطة نهاية التنبؤ للتحقق من الحالة الحالية لطلبك.
/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)processingلا يزال الطلب قيد المعالجة.completedاكتمل التوليد. المخرجات متاحة.succeededنجح التوليد. المخرجات متاحة.failedفشل التوليد. تحقق من حقل الخطأ.{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}ارفع الملفات إلى تخزين Atlas Cloud واحصل على URL يمكنك استخدامه في طلبات API الخاصة بك. استخدم multipart/form-data للرفع.
/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
}
}المعاملات التالية مقبولة في نص الطلب.
{
"model": "xai/grok-imagine-image/edit",
"prompt": "Render this as a pencil sketch with detailed shading.",
"image_urls": [
"https://example.com/file.jpg"
],
"num_images": 1,
"aspect_ratio": "auto",
"resolution": "1k",
"enable_base64_output": false
}تُرجع API استجابة تنبؤ تحتوي على عناوين URL للمخرجات المولّدة.
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}يدمج Atlas Cloud Skills أكثر من 400 نموذج ذكاء اصطناعي مباشرة في مساعد البرمجة بالذكاء الاصطناعي الخاص بك. أمر واحد للتثبيت، ثم استخدم اللغة الطبيعية لتوليد الصور ومقاطع الفيديو والدردشة مع LLM.
npx skills add AtlasCloudAI/atlas-cloud-skillsاحصل على مفتاح API الخاص بك من لوحة تحكم Atlas Cloud وعيّنه كمتغير بيئة.
export ATLASCLOUD_API_KEY="your-api-key-here"بمجرد التثبيت، يمكنك استخدام اللغة الطبيعية في مساعد الذكاء الاصطناعي الخاص بك للوصول إلى جميع نماذج Atlas Cloud.
يربط Atlas Cloud MCP Server بيئة التطوير الخاصة بك بأكثر من 400 نموذج ذكاء اصطناعي عبر Model Context Protocol. يعمل مع أي عميل متوافق مع MCP.
npx -y atlascloud-mcpأضف التكوين التالي إلى ملف إعدادات MCP في بيئة التطوير الخاصة بك.
{
"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/prediction/{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"
},
"/api/v1/model/generateImage": {
"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"
}
},
"openapi": "3.0.0",
"servers": [
{
"url": "https://api.atlascloud.ai"
}
],
"components": {
"schemas": {
"Input": {
"type": "object",
"required": [
"model",
"prompt",
"image_urls"
],
"properties": {
"model": {
"type": "string",
"description": "Model name.",
"default": "xai/grok-imagine-image/edit"
},
"prompt": {
"type": "string",
"default": "Render this as a pencil sketch with detailed shading.",
"description": "Editing instruction. For multi-image references, cite each input as <IMAGE_0>, <IMAGE_1>, ..."
},
"image_urls": {
"type": "array",
"description": "Source images. Each entry is either a public URL or a base64-encoded data URI (e.g. `data:image/png;base64,...`). At least one image is required.",
"items": {
"type": "string"
},
"minItems": 1,
"maxItems": 8
},
"num_images": {
"type": "integer",
"default": 1,
"enum": [
1,
2,
3,
4
],
"description": "Number of edited images to generate. Each output image is billed separately."
},
"aspect_ratio": {
"type": "string",
"default": "auto",
"enum": [
"auto",
"1:1",
"3:4",
"4:3",
"9:16",
"16:9",
"2:3",
"3:2",
"9:19.5",
"19.5:9",
"9:20",
"20:9",
"1:2",
"2:1"
],
"description": "Aspect ratio of the edited image. With a single source image, the output respects the input's aspect ratio regardless of this value. `auto` lets the model pick."
},
"resolution": {
"type": "string",
"default": "1k",
"enum": [
"1k",
"2k"
],
"description": "Output resolution. 1k = 1024x1024, 2k = 2048x2048."
},
"enable_base64_output": {
"type": "boolean",
"title": "Enable Output base64",
"default": false,
"disabled": true,
"description": "If enabled, the output will be encoded into a BASE64 string instead of a URL."
}
},
"x-order-properties": [
"model",
"prompt",
"image_urls",
"num_images",
"aspect_ratio",
"resolution",
"enable_base64_output"
]
},
"PredictionResponse": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the prediction, the ID of the prediction to get."
},
"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 edited images (empty when status is not completed)."
},
"created_at": {
"type": "string",
"format": "date-time",
"description": "ISO timestamp of when the request was created."
}
}
}
},
"securitySchemes": {
"apiKeyAuth": {
"in": "header",
"name": "Authorization",
"type": "apiKey"
}
}
}
}# xai/grok-imagine-image/edit
> xAI Grok Imagine edits one or more reference images with natural-language instructions at 1K or 2K resolution. Supports single image and multi-image (<IMAGE_0>, <IMAGE_1>) reference editing.
## Overview
- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — 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-image/edit`
## 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-image/edit"`
- **`prompt`** (`string`, _required_):
Editing instruction. For multi-image references, cite each input as <IMAGE_0>, <IMAGE_1>, ...
- Default: `"Render this as a pencil sketch with detailed shading."`
- **`image_urls`** (`array[string]`, _required_):
Source images. Each entry is either a public URL or a base64-encoded data URI (e.g. `data:image/png;base64,...`). At least one image is required.
- Min items: 1
- Max items: 8
- **`num_images`** (`integer`, _optional_):
Number of edited images to generate. Each output image is billed separately.
- Default: `1`
- Options: 1, 2, 3, 4
- **`aspect_ratio`** (`string`, _optional_):
Aspect ratio of the edited image. With a single source image, the output respects the input's aspect ratio regardless of this value. `auto` lets the model pick.
- Default: `"auto"`
- Options: "auto", "1:1", "3:4", "4:3", "9:16", "16:9", "2:3", "3:2", "9:19.5", "19.5:9", "9:20", "20:9", "1:2", "2:1"
- **`resolution`** (`string`, _optional_):
Output resolution. 1k = 1024x1024, 2k = 2048x2048.
- Default: `"1k"`
- Options: "1k", "2k"
- **`enable_base64_output`** (`boolean`, _optional_):
If enabled, the output will be encoded into a BASE64 string instead of a URL.
- Default: `false`
**Required Parameters Example**:
```json
{
"model": "xai/grok-imagine-image/edit",
"prompt": "Render this as a pencil sketch with detailed shading.",
"image_urls": [
""
]
}
```
**Full Example**:
```json
{
"model": "xai/grok-imagine-image/edit",
"prompt": "Render this as a pencil sketch with detailed shading.",
"image_urls": [
""
],
"num_images": 1,
"aspect_ratio": "auto",
"resolution": "1k",
"enable_base64_output": false
}
```
### Output Schema
The API returns the following output format:
- **`id`** (`string`, _optional_):
Unique identifier for the prediction, the ID of the prediction to get.
- **`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 edited images (empty when status is not completed).
- **`created_at`** (`string`, _optional_):
ISO timestamp of when the request was created.
**Example Response**:
```json
{
"id": "",
"urls": {},
"model": "",
"status": "",
"outputs": [
""
],
"created_at": ""
}
```
## Usage Examples
### cURL
```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
-H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "xai/grok-imagine-image/edit",
"prompt": "Render this as a pencil sketch with detailed shading.",
"image_urls": [
""
],
"num_images": 1,
"aspect_ratio": "auto",
"resolution": "1k",
"enable_base64_output": false
}'
# 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-image/edit)
Complete the entire arm, matching the style of the image.
Complete the entire arm, matching the style of the image.