> ## Documentation Index
> Fetch the complete documentation index at: https://io.net/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Uploading Images

> The io.net Intelligence API supports image inputs for vision-enabled AI models. This allows users to send images as part of their API requests, enabling advanced multimodal AI capabilities.

**Supported Models for Image Processing**

| Model Name                                 | Capabilities                                                   |
| ------------------------------------------ | -------------------------------------------------------------- |
| *meta-llama/Llama-3.2-90B-Vision-Instruct* | Multi-modal vision model supporting image understanding.       |
| *Qwen/Qwen2-VL-7B-Instruct*                | Supports both text and image-based inputs for AI interactions. |

### Sending an Image via API Request

The API allows **two methods** to send an image:

1. **Passing an Image URL** (recommended for publicly hosted images)
2. **Sending a Base64 Encoded Image** (for local images)

<CodeGroup>
  ```python Passing a URL theme={null}
  import requests

  url = "https://api.intelligence.io.solutions/api/v1/chat/completions"

  headers = {
      "Authorization": "Bearer \$IOINTELLIGENCE_API_KEY",
      "Content-Type": "application/json"
  }

  data = {
      "model": "meta-llama/Llama-3.2-90B-Vision-Instruct", 
      "messages": [
          {"role": "system", "content": "You are an AI assistant."},
          {"role": "user", "content": [
              {"type": "text", "text": "What is in this image?"},
              {"type": "image_url", "image_url": {"url": "https://your-image-url.com/image.jpg"}}
          ]}
      ]
  }

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

  ```python Passing a Base64 encoded image theme={null}
  import requests
  import base64

  url = "https://api.intelligence.io.solutions/api/v1/chat/completions"

  headers = {
      "Authorization": "Bearer \$IOINTELLIGENCE_API_KEY",
      "Content-Type": "application/json"
  }

  image_url = "path_to_your_image.jpg"

  image_response = requests.get(image_url)
  if image_response.status_code == 200:
      image_data = image_response.content  # Get raw image bytes
  else:
      print("Error: Unable to download image")
      exit()

  base64_image = base64.b64encode(image_data).decode("utf-8")

  data = {
      "model": "meta-llama/Llama-3.2-90B-Vision-Instruct", 
      "messages": [
          {"role": "system", "content": "You are an AI assistant."},
          {"role": "user", "content": [
              {"type": "text", "text": "What is in this image?"},
              {"type": "image", "image": base64_image} 
          ]}
      ]
  }

  response = requests.post(url, json=data, headers=headers)

  try:
      print(response.json())  # Parse JSON response
  except requests.exceptions.JSONDecodeError:
      print("Error: Unable to parse response. Raw response:", response.text)
  ```
</CodeGroup>

<Info>
  The image URL must be publicly accessible. Private or authentication-required URLs will not work.
</Info>

### Image Input Requirements

To ensure successful processing, images must meet the following requirements:

| Requirement           | Details                                          |
| --------------------- | ------------------------------------------------ |
| *Format*              | JPEG, PNG, WEBP, or GIF (static)                 |
| *Max File Size*       | 20MB                                             |
| *Resolution*          | At least 512x512 pixels (recommended)            |
| *Max Dimensions*      | 4096×4096 pixels                                 |
| *Accessibility*       | If using a URL, ensure it is publicly accessible |
| *Multi-Image Support* | Up to 10 images per request                      |

**Best Practices for Image Uploads**

* **Optimize File Size**: While the maximum limit is 20MB, smaller files (1-5MB) ensure faster processing.
* **Use Clear Images**: Avoid blurry or low-resolution images for better AI analysis.
* **Ensure Public URLs**: If passing a URL, test it in a browser to confirm that it is accessible.

### Expected API Response

Upon successful submission, the API will return a structured response with AI-generated insights based on the image.

**Example Response:**

<CodeGroup>
  ```json json theme={null}
  {
      "id": "chatcmpl-abc123",
      "object": "chat.completion",
      "created": 1710456789,
      "model": "meta-llama/Llama-3.2-90B-Vision-Instruct",
      "choices": [
          {
              "index": 0,
              "message": {
                  "role": "assistant",
                  "content": "This is an image of a cat sitting on a table."
              },
              "finish_reason": "stop"
          }
      ],
      "usage": {
          "prompt_tokens": 120,
          "completion_tokens": 20,
          "total_tokens": 140
      }
  }
  ```
</CodeGroup>

### Common Issues & Troubleshooting

| Issue                                                  | Possible Cause                      | Solution                                                  |
| ------------------------------------------------------ | ----------------------------------- | --------------------------------------------------------- |
| *"An image? I'm in text format, so I can't see it..."* | Model does not support image input. | Ensure you are using one of the supported vision models.  |
| *"Invalid image format"*                               | Image not encoded properly.         | Convert image to base64 before sending.                   |
| *"Unauthorized"*                                       | API key is missing or incorrect.    | Check that your API key is valid and correctly formatted. |