Agnic
AI Gateway/Multimodal

Image Generation

Generate images using AI models through the Agnic AI Gateway

Image Generation

Generate images from text prompts using AI models with image output capabilities. Agnic supports various image generation models that can create high-quality images based on your descriptions.

Overview

Image generation is available through models that have "image" in their output_modalities. These models can create images from text prompts when you specify the appropriate modalities in your request.

Basic Image Generation

Python

from openai import OpenAI

client = OpenAI(
    api_key="agnic_tok_YOUR_TOKEN",
    base_url="https://api.agnic.ai/v1"
)

response = client.chat.completions.create(
    model="google/gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": "Generate a beautiful sunset over mountains"
        }
    ],
    extra_body={
        "modalities": ["image", "text"]
    }
)

# The generated image will be in the response
message = response.choices[0].message
if hasattr(message, 'images') and message.images:
    for image in message.images:
        image_url = image["image_url"]["url"]  # Base64 data URL
        print(f"Generated image: {image_url[:50]}...")

JavaScript

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'agnic_tok_YOUR_TOKEN',
  baseURL: 'https://api.agnic.ai/v1'
});

const response = await client.chat.completions.create({
  model: 'google/gemini-2.0-flash',
  messages: [
    {
      role: 'user',
      content: 'Generate a beautiful sunset over mountains'
    }
  ],
  modalities: ['image', 'text']
});

// The generated image will be in the response
const message = response.choices[0].message;
if (message.images) {
  message.images.forEach((image, index) => {
    const imageUrl = image.image_url.url; // Base64 data URL
    console.log(`Generated image ${index + 1}: ${imageUrl.substring(0, 50)}...`);
  });
}

cURL

curl https://api.agnic.ai/v1/chat/completions \
  -H "Authorization: Bearer agnic_tok_YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-2.0-flash",
    "messages": [
      {
        "role": "user",
        "content": "Generate a beautiful sunset over mountains"
      }
    ],
    "modalities": ["image", "text"]
  }'

Image Configuration Options

Some models support additional configuration through the image_config parameter.

Aspect Ratio

Set image_config.aspect_ratio to request specific aspect ratios:

RatioResolutionUse Case
1:11024×1024Social media, avatars
16:91344×768Widescreen, presentations
9:16768×1344Mobile, stories
4:31184×864Standard photos
3:21248×832Classic photography

Example with Configuration

response = client.chat.completions.create(
    model="google/gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": "Create a panoramic landscape of a futuristic city"
        }
    ],
    extra_body={
        "modalities": ["image", "text"],
        "image_config": {
            "aspect_ratio": "16:9"
        }
    }
)

Response Format

Generated images are returned in the assistant message:

{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "I've generated a beautiful sunset image for you.",
        "images": [
          {
            "type": "image_url",
            "image_url": {
              "url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
            }
          }
        ]
      }
    }
  ]
}

Image Format Details

  • Format: Images are returned as base64-encoded data URLs
  • Type: Typically PNG format (data:image/png;base64,)
  • Multiple Images: Some models can generate multiple images
  • Size: Dimensions vary by model and configuration

Saving Generated Images

Python

import base64

# Extract base64 data from response
image_data = response.choices[0].message.images[0]["image_url"]["url"]
# Remove the data URL prefix
base64_data = image_data.split(",")[1]

# Decode and save
with open("generated_image.png", "wb") as f:
    f.write(base64.b64decode(base64_data))

JavaScript

import fs from 'fs';

const imageData = response.choices[0].message.images[0].image_url.url;
const base64Data = imageData.split(',')[1];

fs.writeFileSync('generated_image.png', Buffer.from(base64Data, 'base64'));

Compatible Models

Models with image generation capabilities:

ModelProviderFeatures
google/gemini-2.0-flashGoogleFast generation, configurable

Check the model's architecture.output_modalities for "image" support. Visit AI Gateway Pricing for the full list.

Best Practices

  1. Clear prompts - Provide detailed descriptions for better results
  2. Specify style - Include artistic style, mood, lighting preferences
  3. Set aspect ratio - Match the ratio to your use case
  4. Error handling - Check for the images field before processing

Troubleshooting

No images in response?

  • Verify the model supports image generation
  • Ensure modalities: ["image", "text"] is in your request
  • Check that your prompt requests image generation

Wrong dimensions?

  • Use the image_config.aspect_ratio parameter
  • Check model-specific documentation for supported ratios

Image Inputs

Video Inputs

Image Inputs

Send images to vision models through the Agnic AI Gateway

PDF Inputs

Send PDF documents to models through the Agnic AI Gateway

On this page

Image GenerationOverviewBasic Image GenerationPythonJavaScriptcURLImage Configuration OptionsAspect RatioExample with ConfigurationResponse FormatImage Format DetailsSaving Generated ImagesPythonJavaScriptCompatible ModelsBest PracticesTroubleshooting