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.
Cada ejecución costará $0.02. Con $10 puedes ejecutar aproximadamente 500 veces.
Puedes continuar con:
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()Instala el paquete de dependencias necesario.
pip install requestsTodas las solicitudes de API requieren autenticación mediante una clave de API. Puedes obtener tu clave de API desde el panel de 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}"
}Nunca expongas tu clave de API en código del lado del cliente ni en repositorios públicos. Usa variables de entorno o un proxy de backend en su lugar.
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())Envía una solicitud de generación asíncrona. La API devuelve un ID de predicción que puedes usar para verificar el estado y obtener el resultado.
/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"
}
}Consulta el endpoint de predicción para verificar el estado actual de tu solicitud.
/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)processingLa solicitud aún se está procesando.completedLa generación está completa. Las salidas están disponibles.succeededLa generación fue exitosa. Las salidas están disponibles.failedLa generación falló. Verifica el campo de 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"
}
}Sube archivos al almacenamiento de Atlas Cloud y obtén una URL que puedes usar en tus solicitudes de API. Usa multipart/form-data para subir.
/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
}
}Los siguientes parámetros se aceptan en el cuerpo de la solicitud.
{
"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
}La API devuelve una respuesta de predicción con las URL de salida generadas.
{
"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 integra más de 400 modelos de IA directamente en tu asistente de codificación con IA. Un solo comando para instalar y luego usa lenguaje natural para generar imágenes, videos y chatear con LLM.
npx skills add AtlasCloudAI/atlas-cloud-skillsObtén tu clave de API desde el panel de Atlas Cloud y configúrala como variable de entorno.
export ATLASCLOUD_API_KEY="your-api-key-here"Una vez instalado, puedes usar lenguaje natural en tu asistente de IA para acceder a todos los modelos de Atlas Cloud.
Atlas Cloud MCP Server conecta tu IDE con más de 400 modelos de IA a través del Model Context Protocol. Funciona con cualquier cliente compatible con MCP.
npx -y atlascloud-mcpAgrega la siguiente configuración al archivo de configuración de MCP de tu IDE.
{
"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