Image Processing

A guide to sending images via Base64 or URLs in API requests.

Overview

FastRouter lets you include images in chat completions using an OpenAI-compatible message format. This enables vision use cases like image captioning, visual Q&A, object recognition, and multimodal chat across supported providers and models.

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Supported Image Types

• Images: URLs or base64-encoded data URLs

  • Common formats: jpg, jpeg, png, webp (and others depending on the model/provider)

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Supported Models

Use models that support Image as an input modality in the FastRouter model catalog: https://fastrouter.ai/models?input_modalities=image

Examples include multimodal/vision-capable models such as x-ai/grok-4 (availability varies).

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Sending Image Inputs

Images are sent inside messages[].content[] as entries of type "image_url", either pointing to a public URL or a base64-encoded data URL.

Example: Sending an Image via URL (Python)

import requests

url = "https://api.fastrouter.ai/api/v1/chat/completions"
headers = {
  "Authorization": "Bearer API-KEY",
  "Content-Type": "application/json"
}

messages = [
  {
    "role": "user",
    "content": [
      {"type": "text", "text": "Describe this image and identify any landmarks."},
      {
        "type": "image_url",
        "image_url": {
          "url": "https://upload.wikimedia.org/wikipedia/commons/d/da/Taj-Mahal.jpg"
        }
      }
    ]
  }
]

payload = {
  "model": "openai/gpt-4.1-nano",
  "messages": messages
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

Example: Sending a Base64-Encoded Image (Python)

Use base64 data URLs for local/private images.

import requests
import base64

def encode_image_to_base64(image_path: str) -> str:
  with open(image_path, "rb") as f:
    return base64.b64encode(f.read()).decode("utf-8")

url = "https://api.fastrouter.ai/api/v1/chat/completions"
headers = {
  "Authorization": "Bearer API-KEY",
  "Content-Type": "application/json"
}

image_path = "/path/to/your/image.jpg"
base64_image = encode_image_to_base64(image_path)

# Match the MIME type to your file (e.g., image/png for .png)
data_url = f"data:image/jpeg;base64,{base64_image}"

messages = [
  {
    "role": "user",
    "content": [
      {"type": "text", "text": "What's in this image?"},
      {"type": "image_url", "image_url": {"url": data_url}}
    ]
  }
]

payload = {
  "model": "openai/gpt-4.1-nano",
  "messages": messages
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

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Tips & Best Practices

• Put text first: Send your prompt before the image(s) for best results.

• Multiple images: Add multiple "image_url" items within the same content array if your model supports it.

• Prefer URLs for large images: URLs avoid base64 overhead and request-size limits.

• Use the correct MIME type: For base64 data URLs, ensure data:image/... matches the actual file type.

• Model limits vary: Image count/size support differs by model/provider — check the model’s docs in the FastRouter catalog.