api.md

Eyeris API Documentation

Base URL

http://localhost:3000/api/v1

Endpoints

Analyze Image

Analyzes an image using AI vision capabilities.

POST /analyze

Request

• Method: POST
• Content-Type: multipart/form-data

Parameters

Name	Type	In	Description
image	file	form	The image file to analyze
model	string	query	(Optional) The model to use for analysis. Default: "gpt-4o"

{
  "success": true,
  "message": "Analysis completed successfully",
  "data": {
    "analysis": "Detailed JSON analysis of the image",
    "token_usage": {
      "prompt_tokens": 123,
      "completion_tokens": 456,
      "total_tokens": 579
    }
  }
}

{
  "success": false,
  "message": "Error message describing what went wrong"
}

Health Check

Check if the API is running and healthy.

GET /health

{
  "success": true,
  "message": "Service is healthy"
}

Error Codes

• 400 Bad Request: Invalid request (missing image, invalid format)
• 500 Internal Server Error: Server-side error

Example Usage

cURL

curl -X POST http://localhost:3000/api/v1/analyze \
  -F "image=@path/to/your/image.jpg" \
  -G -d "model=gpt-4o"

Python

import requests

url = "http://localhost:3000/api/v1/analyze"
files = {"image": open("path/to/your/image.jpg", "rb")}
params = {"model": "gpt-4o"}

response = requests.post(url, files=files, params=params)
print(response.json())

JavaScript

async function analyzeImage(imageFile) {
  const formData = new FormData();
  formData.append("image", imageFile);

  const response = await fetch(
    "http://localhost:3000/api/v1/analyze?model=gpt-4o",
    {
      method: "POST",
      body: formData,
    }
  );

  return await response.json();
}