Openai GPT Image 1 Mini Edit API by OpenAI
GPT Image 1 Mini is a cost-efficient, natively multimodal OpenAI model that pairs GPT-5 language understanding with compact image editing and generation from text and image inputs to produce high-quality images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
INPUT
OUTPUT
MenungguPermintaan Anda akan dikenakan biaya $0.004 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 2500 kali.
Berikut yang dapat Anda lakukan selanjutnya:
Contoh kode
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": "openai/gpt-image-1-mini/edit",
"prompt": "A beautiful landscape with mountains and lake",
"width": 512,
"height": 512,
"steps": 20,
"guidance_scale": 7.5,
}
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()Instalasi
Instal paket yang diperlukan untuk bahasa pemrograman Anda.
pip install requestsAutentikasi
Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.
export ATLASCLOUD_API_KEY="your-api-key-here"HTTP Headers
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.
Kirim permintaan
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())Kirim Permintaan
Kirim permintaan pembuatan asinkron. API mengembalikan prediction ID yang dapat Anda gunakan untuk memeriksa status dan mengambil hasil.
/api/v1/model/generateImageIsi Permintaan
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "openai/gpt-image-1-mini/edit",
"input": {
"prompt": "A beautiful landscape with mountains and lake"
}
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")Respons
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Periksa Status
Polling prediction endpoint untuk memeriksa status permintaan Anda saat ini.
/api/v1/model/prediction/{prediction_id}Contoh Polling
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)Nilai Status
processingPermintaan masih diproses.completedPembuatan selesai. Output tersedia.succeededPembuatan berhasil. Output tersedia.failedPembuatan gagal. Periksa field error.Respons Selesai
{
"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"
}
}Unggah File
Unggah file ke penyimpanan Atlas Cloud dan dapatkan URL yang dapat Anda gunakan dalam permintaan API Anda. Gunakan multipart/form-data untuk mengunggah.
/api/v1/model/uploadMediaContoh Unggah
import 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}")Respons
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Input Schema
Parameter berikut diterima di isi permintaan.
Tidak ada parameter yang tersedia.
Contoh Isi Permintaan
{
"model": "openai/gpt-image-1-mini/edit"
}Output Schema
API mengembalikan respons prediction dengan URL output yang dihasilkan.
Contoh Respons
{
"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
Atlas Cloud Skills mengintegrasikan 300+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.
Klien yang Didukung
Instalasi
npx skills add AtlasCloudAI/atlas-cloud-skillsAtur API Key
Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.
export ATLASCLOUD_API_KEY="your-api-key-here"Kemampuan
Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.
MCP Server
Atlas Cloud MCP Server menghubungkan IDE Anda dengan 300+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.
Klien yang Didukung
Instalasi
npx -y atlascloud-mcpKonfigurasi
Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Alat yang Tersedia
Schema API
Schema tidak tersediaTidak ada contoh yang tersedia
Silakan masuk untuk melihat riwayat permintaan
Anda perlu masuk untuk mengakses riwayat permintaan model Anda.
Masukopenai/gpt-image-1-mini/edit
GPT Image 1 Mini (Edit) is a cost-efficient multimodal image editing model powered by OpenAI’s GPT-5 architecture. It enables users to refine, modify, or transform existing images using natural language instructions, while maintaining the original style, composition, and visual integrity.
🌟 Key Features
🧠 GPT-5-Powered Visual Understanding
Understands complex textual instructions and applies targeted edits that match intent and context.
🎨 Intelligent Image Editing
Add, remove, or modify elements in an image with precision — from subtle adjustments to full stylistic transformations.
🖼 Multi-Image Support
Accepts one or more image inputs to guide the edit or style reference process.
💡 Context-Aware Refinement
Preserves the key artistic or photographic features, such as lighting, tone, and pose, while applying changes only where needed.
💰 Efficient and Accessible
Offers professional-quality visual editing at a low cost, ideal for rapid prototyping, design iteration, or creative workflows.
⚙️ Parameters
| Parameter | Description |
|---|---|
prompt* | Describe how you want to edit or modify the image (e.g. “change outfit colors to pastel tones, add neon city lights in the background”) |
images* | Upload one or more reference images (JPG / PNG) to be edited or used as visual input |
💡 Example Prompt
Three fashionable young women in a nighttime urban scene, showcasing Y2K and streetwear aesthetics. Each has distinct styling: plaid shirt with ripped jeans, off-shoulder top with retro socks and chunky sneakers, crop top with cowboy boots and accessories. Enhance lighting and color balance for a cinematic look.
🎯 Use Cases
- Product & Fashion Editing — Adjust outfits, lighting, or background for catalog or campaign visuals.
- UI/UX & Brand Design — Apply aesthetic refinements to mockups or visual assets.
- Creative Direction — Evolve photo concepts while preserving original mood and framing.
- Photography & Illustration — Fix, enhance, or restyle images using natural text prompts.
