Generating Images

The /v1/images/generations endpoint takes a text prompt and returns one or more images. It is compatible with the OpenAI images.generate() SDK method — only the base URL and key need to change.

Basic example

Python
Node.js
cURL

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.routeway.ai/v1",
    api_key=os.getenv("ROUTEWAY_API_KEY")
)

response = client.images.generate(
    model="flux-1-schnell",
    prompt="A serene Japanese garden at dawn, soft mist, cherry blossoms, photorealistic",
    size="1024x1024",
    n=1,
)

print(response.data[0].url)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.routeway.ai/v1",
  apiKey: process.env.ROUTEWAY_API_KEY,
});

const response = await client.images.generate({
  model: "flux-1-schnell",
  prompt: "A serene Japanese garden at dawn, soft mist, cherry blossoms, photorealistic",
  size: "1024x1024",
  n: 1,
});

console.log(response.data[0].url);

curl https://api.routeway.ai/v1/images/generations \
  -H "Authorization: Bearer $ROUTEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-1-schnell",
    "prompt": "A serene Japanese garden at dawn, soft mist, cherry blossoms, photorealistic",
    "size": "1024x1024",
    "n": 1
  }'

Request parameters

Parameter	Type	Default	Description
`model`	string	required	Image model ID (e.g. `"flux-1-schnell"`, `"dall-e-3"`)
`prompt`	string	required	Text description of the image to generate
`n`	integer	`1`	Number of images to generate (1–10)
`size`	string	model default	Output resolution, e.g. `"1024x1024"`, `"1792x1024"`
`quality`	string	model default	Provider-specific preset, e.g. `"standard"`, `"hd"`
`response_format`	string	`"url"`	`"url"` or `"b64_json"`

Response object

{
  "created": 1749052800,
  "data": [
    {
      "url": "https://cdn.routeway.ai/images/abc123.png",
      "revised_prompt": "A serene Japanese garden at dawn..."
    }
  ]
}

Field	Description
`data[].url`	Temporary URL to the generated image (expires in 1 hour)
`data[].b64_json`	Base64 PNG data, present when `response_format: "b64_json"`
`data[].revised_prompt`	The prompt as interpreted by the model, if the model revised it

Saving images locally

URLs expire after 1 hour. Download the image immediately if you need to keep it.

Python
Node.js

import os
import requests
from openai import OpenAI

client = OpenAI(
    base_url="https://api.routeway.ai/v1",
    api_key=os.getenv("ROUTEWAY_API_KEY")
)

response = client.images.generate(
    model="flux-1-schnell",
    prompt="A futuristic cityscape at night, neon lights, rain-slicked streets",
    size="1024x1024",
)

image_url = response.data[0].url
image_bytes = requests.get(image_url).content

with open("output.png", "wb") as f:
    f.write(image_bytes)

print("Saved to output.png")

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  baseURL: "https://api.routeway.ai/v1",
  apiKey: process.env.ROUTEWAY_API_KEY,
});

const response = await client.images.generate({
  model: "flux-1-schnell",
  prompt: "A futuristic cityscape at night, neon lights, rain-slicked streets",
  size: "1024x1024",
});

const imageUrl = response.data[0].url;
const imageResponse = await fetch(imageUrl);
const buffer = Buffer.from(await imageResponse.arrayBuffer());
fs.writeFileSync("output.png", buffer);

console.log("Saved to output.png");

Alternatively, request response_format: "b64_json" to receive the image bytes directly in the API response — no second HTTP request needed.

import base64

response = client.images.generate(
    model="flux-1-schnell",
    prompt="Abstract watercolour landscape",
    response_format="b64_json",
)

image_bytes = base64.b64decode(response.data[0].b64_json)

with open("output.png", "wb") as f:
    f.write(image_bytes)

Generating multiple images

Set n to receive several variations in a single call. Each item in data is an independent generation.

response = client.images.generate(
    model="flux-1-schnell",
    prompt="A cosy mountain cabin in winter, warm light from the windows",
    size="1024x1024",
    n=4,
)

for i, image in enumerate(response.data):
    print(f"Image {i + 1}: {image.url}")

Choosing size and quality

Available sizes and quality presets vary by model. As a general guide:

Size	Aspect ratio	Typical use
`1024x1024`	Square	Social media, avatars, thumbnails
`1792x1024`	Landscape	Banners, hero images
`1024x1792`	Portrait	Mobile wallpapers, posters

Quality	Trade-off
`standard`	Faster, lower cost, slightly less detail
`hd`	Slower, higher cost, finer details

Use flux-1-schnell for iteration and prototyping — it generates in seconds. Switch to flux-1-dev or dall-e-3 when quality matters for production output.

Writing effective prompts

Image models are sensitive to how prompts are written. A few techniques that consistently improve results:

Be specific about style and medium

Vague prompts produce generic results. Name a style, medium, or artist reference to anchor the output.

# Vague
"A forest"

# Specific
"A dense pine forest at dusk, oil painting, dramatic lighting, muted earth tones"

Describe composition and perspective

Tell the model where to place things and from what angle.

"Close-up portrait of an elderly sailor, weathered face, looking off-camera,
shallow depth of field, golden hour light"

Add technical photography terms

Terms like shallow depth of field, 35mm lens, shot on film, bokeh, and golden hour reliably improve photorealistic outputs.

Use negative prompts where supported

Some models (like FLUX) accept a negative_prompt parameter to exclude unwanted elements.

{
  "prompt": "A clean minimal product photo of a white ceramic mug",
  "negative_prompt": "blurry, watermark, text, cluttered background, low quality"
}

Error handling

from openai import BadRequestError

try:
    response = client.images.generate(
        model="flux-1-schnell",
        prompt="...",
    )
    print(response.data[0].url)
except BadRequestError as e:
    # Prompt was rejected (content policy, invalid parameters, etc.)
    print(f"Request error: {e.message}")
except Exception as e:
    print(f"Unexpected error: {e}")

Common errors:

Status	Cause
`400`	Invalid parameters or prompt rejected by content policy
`401`	Missing or invalid API key
`429`	Rate limit or insufficient balance
`500`	Upstream model error — retry with exponential backoff

Get Started

Platform Details

Help & Resources

Core Concepts

Account Management

Guides

Basic example

Request parameters

Response object

Saving images locally

Generating multiple images

Choosing size and quality

Writing effective prompts

Error handling

​Basic example

​Request parameters

​Response object

​Saving images locally

​Generating multiple images

​Choosing size and quality

​Writing effective prompts

​Error handling

Basic example

Request parameters

Response object

Saving images locally

Generating multiple images

Choosing size and quality

Writing effective prompts

Error handling