
Openai GPT Image 1 Text-to-Image API by OpenAI
OpenAI GPT Image-1 generates images from text prompts from OpenAI's latest text-to-image model, ideal for creating visual assets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
INPUT
OUTPUT
MenungguPermintaan Anda akan dikenakan biaya $0.009 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 1111 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/text-to-image",
"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/text-to-image",
"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/text-to-image"
}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
GPT Image 1 is OpenAI’s latest multimodal image generation model, built to understand both text and image inputs and produce visually coherent, high-quality image outputs. It combines the reasoning power of GPT-4-Turbo with DALL·E-class visual synthesis, allowing for creative, controllable, and context-aware generation across illustration, photography, design, and visualization tasks.
🧠 Key Features
-
Multimodal Understanding
Accepts both text and image inputs, enabling style transfer, editing, or contextual composition. -
Flexible Styles
Produces photorealistic renders, stylized artwork, concept art, infographics, and 3D-style illustrations. -
High Visual Fidelity
Maintains object relationships, lighting consistency, and color balance with strong adherence to prompts. -
Accurate Text Rendering
Capable of generating clean typography, ideal for posters, memes, comics, and branding visuals. -
Knowledge-Grounded Creativity
Uses GPT-4’s world knowledge to generate factual, contextually appropriate visuals.
⚙️ Parameters
| Parameter | Description |
|---|---|
prompt | Required text description of the desired image |
size | Supports 1024×1024, 1024×1536, and 1536×1024 |
quality | Choose between low, medium, and high |
💡 Tips for Best Results
- Write prompts that specify style, subject, composition, and lighting.
- Example:
A small robot exploring an abandoned city, cartoon style, bright colors.
- Use high quality for detailed or large-format outputs.
- Prefer landscape (
1536×1024) for cinematic or wide compositions. - Prefer portrait (
1024×1536) for characters or vertical art.
📝 Notes
- All generated content follows OpenAI’s safety and content policies.
- If a prompt triggers moderation, rephrase or simplify it.
- This model supports multi-image input via API, enabling creative editing and composition workflows.
- For performance- and latency-sensitive cases, use medium quality as the balanced default.






