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.
แต่ละครั้งจะใช้ $0.02 ด้วย $10 คุณสามารถรันได้ประมาณ 500 ครั้ง
คุณสามารถทำต่อได้:
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()ติดตั้งแพ็กเกจที่จำเป็น
pip install requestsคำขอ API ทั้งหมดต้องมีการยืนยันตัวตนผ่าน API key คุณสามารถรับ API key ได้จากแดชบอร์ด 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}"
}อย่าเปิดเผย API key ของคุณในโค้ดฝั่งไคลเอนต์หรือที่เก็บข้อมูลสาธารณะ ให้ใช้ตัวแปรสภาพแวดล้อมหรือพร็อกซีฝั่งเซิร์ฟเวอร์แทน
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())ส่งคำขอสร้างแบบอะซิงโครนัส API จะส่งคืน prediction ID ที่คุณสามารถใช้ตรวจสอบสถานะและดึงผลลัพธ์ได้
/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"
}
}ตรวจสอบสถานะปัจจุบันของคำขอด้วยการเรียก prediction endpoint เป็นระยะ
/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)processingคำขอยังอยู่ระหว่างการประมวลผลcompletedการสร้างเสร็จสมบูรณ์แล้ว ผลลัพธ์พร้อมใช้งานsucceededการสร้างสำเร็จแล้ว ผลลัพธ์พร้อมใช้งานfailedการสร้างล้มเหลว ตรวจสอบฟิลด์ error{
"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"
}
}อัปโหลดไฟล์ไปยังที่เก็บข้อมูล Atlas Cloud และรับ URL ที่คุณสามารถใช้ในคำขอ API ของคุณ ใช้ multipart/form-data ในการอัปโหลด
/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
}
}พารามิเตอร์ต่อไปนี้ยอมรับในเนื้อหาคำขอ
{
"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
}API จะส่งคืนการตอบกลับ prediction พร้อม URL ของผลลัพธ์ที่สร้างขึ้น
{
"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"
}Atlas Cloud Skills เชื่อมต่อโมเดล AI กว่า 400+ เข้ากับผู้ช่วยเขียนโค้ด AI ของคุณโดยตรง ติดตั้งด้วยคำสั่งเดียว จากนั้นใช้ภาษาธรรมชาติเพื่อสร้างรูปภาพ วิดีโอ และสนทนากับ LLM
npx skills add AtlasCloudAI/atlas-cloud-skillsรับ API key จากแดชบอร์ด Atlas Cloud และตั้งค่าเป็นตัวแปรสภาพแวดล้อม
export ATLASCLOUD_API_KEY="your-api-key-here"เมื่อติดตั้งแล้ว คุณสามารถใช้ภาษาธรรมชาติในผู้ช่วย AI ของคุณเพื่อเข้าถึงโมเดล Atlas Cloud ทั้งหมด
Atlas Cloud MCP Server เชื่อมต่อ IDE ของคุณกับโมเดล AI กว่า 400+ ผ่าน Model Context Protocol ใช้งานได้กับไคลเอนต์ที่รองรับ MCP ทุกตัว
npx -y atlascloud-mcpเพิ่มการกำหนดค่าต่อไปนี้ลงในไฟล์ตั้งค่า MCP ของ IDE ของคุณ
{
"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