> ## Documentation Index
> Fetch the complete documentation index at: https://docs.anannas.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Image Input
> Send images to vision models through the Anannas API.
Requests with images, to multimodal models, are available via the `/chat/completions` API with a multi-part `messages`parameter. The `image_url` can either be a **URL** or a **base64-encoded image**. You can send multiple images by adding more content entries in the same message.
URLs are preferred for large files since they avoid payload bloat. Use base64 encoding when working with local or private files.
Anannas supports both **direct URLs** and **base64-encoded data** for images:
* **URLs**: More efficient for publicly accessible images as they don't require local encoding
* **Base64**: Required for local files or private images that aren't publicly accessible
### Using Image URLs
Here's how to send an image via URL:
```python Python theme={null}
import requests
import json
url = "https://api.anannas.ai/v1/chat/completions"
headers = {
"Authorization": f"Bearer {API_KEY_REF}",
"Content-Type": "application/json"
}
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "What do you see in this image?"},
{
"type": "image_url",
"image_url": {
"url": "https://upload.wikimedia.org/wikipedia/commons/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
"detail": "high"
}
}
]
}
]
payload = {"model": "{{MODEL}}", "messages": messages, "max_tokens": 300}
response = requests.post(url, headers=headers, json=payload)
print(response.json())
```
```typescript Typescript theme={null}
const response = await fetch('https://api.anannas.ai/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: `Bearer ${API_KEY_REF}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: '{{MODEL}}',
max_tokens: 300,
messages: [
{
role: 'user',
content: [
{ type: 'text', text: "What do you see in this image?" },
{
type: 'image_url',
image_url: {
url: 'https://upload.wikimedia.org/wikipedia/commons/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg',
detail: 'high',
},
},
],
},
],
}),
});
const data = await response.json();
console.log(data);
```
### Using Base64 Encoded Images (OpenAI only)
For **OpenAI models**, you can send local images as base64:
```python Python theme={null}
import requests, base64
def encode_image_to_base64(image_path):
with open(image_path, "rb") as f:
return base64.b64encode(f.read()).decode("utf-8")
url = "https://api.anannas.ai/v1/chat/completions"
headers = {
"Authorization": f"Bearer {API_KEY_REF}",
"Content-Type": "application/json"
}
base64_image = encode_image_to_base64("path/to/image.jpg")
data_url = f"data:image/jpeg;base64,{base64_image}"
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "What do you see in this image?"},
{
"type": "image_url",
"image_url": {"url": data_url, "detail": "high"}
}
]
}
]
payload = {"model": "{{MODEL}}", "messages": messages, "max_tokens": 300}
response = requests.post(url, headers=headers, json=payload)
print(response.json())
```
```typescript Typescript theme={null}
import fs from 'fs/promises';
async function encodeImageToBase64(path: string): Promise {
const buffer = await fs.readFile(path);
return `data:image/jpeg;base64,${buffer.toString('base64')}`;
}
const imageData = await encodeImageToBase64('path/to/image.jpg');
const response = await fetch('https://api.anannas.ai/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: `Bearer ${API_KEY_REF}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: '{{MODEL}}',
max_tokens: 300,
messages: [
{
role: 'user',
content: [
{ type: 'text', text: "What do you see in this image?" },
{
type: 'image_url',
image_url: { url: imageData, detail: 'high' },
},
],
},
],
}),
});
const data = await response.json();
console.log(data);
```
### Supported image types:
For models that support image inputs and their capabilities, visit [anannas.ai/models](https://anannas.ai/models).
* `image/png`
* `image/jpeg`
* `image/webp`
* `image/gif`