How Apixify Works

Transform images into insights with our powerful AI API

1

Define Your Skill

Create a reusable Skill that tells Apixify how to analyze images. Skills can be applied repeatedly across images and refined over time.

2

Upload Your Image

Send any image (JPG, PNG, GIF, WebP) to our API endpoint. Images are processed securely and stored temporarily.

3

Get Reliable Results

Receive text-based analysis by default. Structured formats like JSON or HTML can be enforced directly in your Skill definition.

API Integration

Simple REST API with comprehensive documentation

Basic API Request

curl -X POST "https://apixify.com/api/public/PUBLIC_TOKEN" \
     -H "Content-Type: multipart/form-data" \
     -F "image=@/path/to/your/image.jpg"

import requests

url = "https://apixify.com/api/public/PUBLIC_TOKEN"
files = {
    'image': open('/path/to/your/image.jpg', 'rb')
}
                          
response = requests.post(url, files=files)

# Check content type to handle both JSON and plain text
content_type = response.headers.get("content-type", "")
if "application/json" in content_type:
    result = response.json()
    print(result["response"])  # JSON response
else:
    result = response.text
    print(result)  # Plain text response

const formData = new FormData();
formData.append("image", fileInput.files[0]);

fetch("https://apixify.com/api/public/PUBLIC_TOKEN", {
  method: "POST",
  body: formData
})
.then(response => {
  const contentType = response.headers.get("content-type");
  const isJson = contentType && contentType.includes("application/json");
  if (isJson) {
    return response.json().then(data => console.log(data.response));
  } else {
    return response.text().then(text => console.log(text));
  }
})
.catch(error => console.error("Error:", error));

Response Format

Plain text by default, JSON when requested in your Skill

Plain Text Response (Default)

This appears to be a cheeseburger with fries. 
Estimated 850 calories. Ingredients: beef patty, 
cheddar cheese, lettuce, tomato, bun, french fries.

JSON Response (When Skill requests JSON)

{
  "response": {
    "label": "Cheeseburger with Fries",
    "weight_grams": 350,
    "calories": 850,
    "fat_grams": 45.2,
    "protein_grams": 28.5,
    "carbs_grams": 65.3
  },
  "run_time_ms": 1250
}

Use Cases

Endless possibilities for image analysis

🍕

Food Analysis

Analyze ingredients, estimate calories, identify allergens, and provide nutritional information.

🛒

E-commerce Product Uploads

Automatically extract product titles, attributes, and descriptions from images to streamline catalog creation and reduce manual data entry.

📄

Document Processing

Extract text from receipts, invoices, forms, and documents with structured data output.

Integration Examples

See how to integrate Apixify into your applications

HTML Embed - Web Application Integration

// HTML Form with File Upload
<form id="imageForm">
  <input type="file" id="imageInput" accept="image/*">
  <button type="submit">Analyze Image</button>
</form>

<div id="result"></div>

<script>

// JavaScript Integration
document.getElementById('imageForm').addEventListener('submit', async (e) => {
  e.preventDefault();
  
  const formData = new FormData();
  formData.append('image', document.getElementById('imageInput').files[0]);
  formData.append('prompt', document.getElementById('promptInput').value);
  
  try {
    const response = await fetch("https://apixify.com/api/public/PUBLIC_TOKEN", {
      method: "POST",
      body: formData
    });
    const contentType = response.headers.get("content-type");
    const isJson = contentType && contentType.includes("application/json");
    
    if (response.ok) {
      if (isJson) {
        const result = await response.json();
        document.getElementById("result").innerHTML = "Result:
" + JSON.stringify(result.response, null, 2) + "";
      } else {
        const result = await response.text();
        document.getElementById("result").innerHTML = "Result:
" + result + "";
      }
    } else {
      let errorData;
      if (isJson) {
        errorData = await response.json();
      } else {
        const errorText = await response.text();
        errorData = { error: errorText };
      }
      document.getElementById("result").innerHTML = "Error: " + (errorData.error || "Unknown error") + "";
    }
  } catch (error) {
    document.getElementById("result").innerHTML = "Error: " + error.message + "";
  }
});
</script>