Grok Imagine Image Text-to-Image API by xAI
xai/grok-imagine-image/text-to-image
Text-to-image
xAI Grok Imagine generates images from natural-language prompts at 1K or 2K resolution, with 14 aspect ratios.
xAI Grok Imagine generates images from natural-language prompts at 1K or 2K resolution, with 14 aspect ratios.
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/text-to-image", # Required. Model name
"prompt": "A collage of London landmarks in a stenciled street-art style.", # Required. Natural-language description of the image to generate
"num_images": 1, # Number of images to generate. options: 1 | 2 | 3 | 4
"aspect_ratio": "1:1", # Aspect ratio of the generated 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/text-to-image",
"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/text-to-image",
"prompt": "A collage of London landmarks in a stenciled street-art style.",
"num_images": 1,
"aspect_ratio": "1:1",
"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"
],
"properties": {
"model": {
"type": "string",
"description": "Model name.",
"default": "xai/grok-imagine-image/text-to-image"
},
"prompt": {
"type": "string",
"default": "A collage of London landmarks in a stenciled street-art style.",
"description": "Natural-language description of the image to generate."
},
"num_images": {
"type": "integer",
"default": 1,
"enum": [
1,
2,
3,
4
],
"description": "Number of images to generate. Each image is billed separately."
},
"aspect_ratio": {
"type": "string",
"default": "1:1",
"enum": [
"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 generated image."
},
"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",
"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 generated 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/text-to-image
> xAI Grok Imagine generates images from natural-language prompts at 1K or 2K resolution, with 14 aspect ratios.
## 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/text-to-image`
## 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/text-to-image"`
- **`prompt`** (`string`, _required_):
Natural-language description of the image to generate.
- Default: `"A collage of London landmarks in a stenciled street-art style."`
- **`num_images`** (`integer`, _optional_):
Number of images to generate. Each image is billed separately.
- Default: `1`
- Options: 1, 2, 3, 4
- **`aspect_ratio`** (`string`, _optional_):
Aspect ratio of the generated image.
- Default: `"1:1"`
- Options: "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/text-to-image",
"prompt": "A collage of London landmarks in a stenciled street-art style."
}
```
**Full Example**:
```json
{
"model": "xai/grok-imagine-image/text-to-image",
"prompt": "A collage of London landmarks in a stenciled street-art style.",
"num_images": 1,
"aspect_ratio": "1:1",
"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 generated 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/text-to-image",
"prompt": "A collage of London landmarks in a stenciled street-art style.",
"num_images": 1,
"aspect_ratio": "1:1",
"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/text-to-image)
Ancient futuristic city carved into towering desert cliffs, monumental architecture, vast dunes surrounding the city, warm golden tones, mysterious atmosphere, cinematic sci-fi worldbuilding, ultra detailed, epic scale, volumetric sunlight, Dune aesthetic
Ancient futuristic city carved into towering desert cliffs, monumental architecture, vast dunes surrounding the city, warm golden tones, mysterious atmosphere, cinematic sci-fi worldbuilding, ultra detailed, epic scale, volumetric sunlight, Dune aesthetic