Image Inputs

Send images to multimodal models for analysis, description, OCR, and more. AgnicPay supports multiple image formats and both URL-based and base64-encoded images.

Overview

Image requests are available via the /v1/chat/completions API with a multi-part messages parameter. The image_url can either be a URL or a base64-encoded image.

Multiple images can be sent in separate content array entries. We recommend sending the text prompt first, then the images for best results.

Using Image URLs

For publicly accessible images, send the URL directly:

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="openai/gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "What's in this image?"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                    }
                }
            ]
        }
    ]
)
 
print(response.choices[0].message.content)

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: 'openai/gpt-4o',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: "What's in this image?"
        },
        {
          type: 'image_url',
          image_url: {
            url: 'https://example.com/image.jpg'
          }
        }
      ]
    }
  ]
});
 
console.log(response.choices[0].message.content);

cURL

curl https://api.agnic.ai/v1/chat/completions \
  -H "Authorization: Bearer agnic_tok_YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o",
    "messages": [
      {
        "role": "user",
        "content": [
          {"type": "text", "text": "What is in this image?"},
          {
            "type": "image_url",
            "image_url": {
              "url": "https://example.com/image.jpg"
            }
          }
        ]
      }
    ]
  }'

Using Base64 Encoded Images

For locally stored images, use base64 encoding:

Python

from openai import OpenAI
import base64
 
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')
 
client = OpenAI(
    api_key="agnic_tok_YOUR_TOKEN",
    base_url="https://api.agnic.ai/v1"
)
 
# Read and encode the image
image_path = "path/to/your/image.jpg"
base64_image = encode_image(image_path)
data_url = f"data:image/jpeg;base64,{base64_image}"
 
response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "What's in this image?"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": data_url
                    }
                }
            ]
        }
    ]
)
 
print(response.choices[0].message.content)

JavaScript

import OpenAI from 'openai';
import fs from 'fs';
 
const client = new OpenAI({
  apiKey: 'agnic_tok_YOUR_TOKEN',
  baseURL: 'https://api.agnic.ai/v1'
});
 
// Read and encode the image
const imagePath = 'path/to/your/image.jpg';
const imageBuffer = fs.readFileSync(imagePath);
const base64Image = imageBuffer.toString('base64');
const dataUrl = `data:image/jpeg;base64,${base64Image}`;
 
const response = await client.chat.completions.create({
  model: 'openai/gpt-4o',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: "What's in this image?"
        },
        {
          type: 'image_url',
          image_url: {
            url: dataUrl
          }
        }
      ]
    }
  ]
});
 
console.log(response.choices[0].message.content);

Supported Image Formats

Format	MIME Type	Extension
PNG	`image/png`	`.png`
JPEG	`image/jpeg`	`.jpg`, `.jpeg`
WebP	`image/webp`	`.webp`
GIF	`image/gif`	`.gif`

Multiple Images

Send multiple images in a single request:

response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Compare these two images"
                },
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/image1.jpg"}
                },
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/image2.jpg"}
                }
            ]
        }
    ]
)

Compatible Models

Models with vision capabilities include:

Provider	Models
OpenAI	`openai/gpt-4o`, `openai/gpt-4o-mini`, `openai/gpt-4-turbo`
Anthropic	`anthropic/claude-3.5-sonnet`, `anthropic/claude-3-opus`, `anthropic/claude-3-haiku`
Google	`google/gemini-2.0-flash`, `google/gemini-1.5-pro`, `google/gemini-1.5-flash`

Check the model's architecture.input_modalities for "image" support.

Best Practices

Use URLs for public images - More efficient than base64 encoding
Compress large images - Reduce payload size without losing quality
Send text first - Place your prompt before the images
Check model limits - Different models have different image count limits

Image Inputs

Image Inputs

Overview

Using Image URLs

Python

JavaScript

cURL

Using Base64 Encoded Images

Python

JavaScript

Supported Image Formats

Multiple Images

Compatible Models

Best Practices

Image Generation

PDF Processing

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