---
title: Multimodal Support
description: "Enable multimodal support in Mem0 to process images alongside text and extract visual information into memory."
icon: "image"
iconType: "solid"
---

Mem0 extends its capabilities beyond text by supporting multimodal data, including images. You can seamlessly integrate images into your interactions, allowing Mem0 to extract pertinent information from visual content and enrich the memory system.

## How It Works

When you provide an image, Mem0 processes it to extract textual information and relevant details, which are then added to your memory. This feature enhances the system's ability to understand and remember details based on visual inputs.

<Note>
To enable multimodal support, you must set `enable_vision = True` in your configuration. The `vision_details` parameter can be set to "auto" (default), "low", or "high" to control the level of detail in image processing.
</Note>

<CodeGroup>
```python Code
from mem0 import Memory

config = {
    "llm": {
        "provider": "openai",
        "config": {
            "enable_vision": True,
            "vision_details": "high"
        }
    }
}

client = Memory.from_config(config=config)

messages = [
    {
        "role": "user",
        "content": "Hi, my name is Alice."
    },
    {
        "role": "assistant",
        "content": "Nice to meet you, Alice! What do you like to eat?"
    },
    {
        "role": "user",
        "content": {
            "type": "image_url",
            "image_url": {
                "url": "https://www.superhealthykids.com/wp-content/uploads/2021/10/best-veggie-pizza-featured-image-square-2.jpg"
            }
        }
    },
]

# Calling the add method to ingest messages into the memory system
client.add(messages, user_id="alice")
```

```typescript TypeScript
import { Memory, Message } from "mem0ai/oss";

const client = new Memory();

const messages: Message[] = [
    {
        role: "user",
        content: "Hi, my name is Alice."
    },
    {
        role: "assistant",
        content: "Nice to meet you, Alice! What do you like to eat?"
    },
    {
        role: "user",
        content: {
            type: "image_url",
            image_url: {
                url: "https://www.superhealthykids.com/wp-content/uploads/2021/10/best-veggie-pizza-featured-image-square-2.jpg"
            }
        }
    },
]

await client.add(messages, { userId: "alice" })
```

```json Output
{
  "results": [
    {
      "memory": "Name is Alice",
      "event": "ADD",
      "id": "7ae113a3-3cb5-46e9-b6f7-486c36391847"
    },
    {
      "memory": "Likes large pizza with toppings including cherry tomatoes, black olives, green spinach, yellow bell peppers, diced ham, and sliced mushrooms",
      "event": "ADD",
      "id": "56545065-7dee-4acf-8bf2-a5b2535aabb3"
    }
  ]
}
```
</CodeGroup>

## Image Integration Methods

Mem0 allows you to add images to user interactions through two primary methods: by providing an image URL or by using a Base64-encoded image. Below are examples demonstrating each approach.

### Using an Image URL (Recommended)

You can include an image by passing its direct URL. This method is simple and efficient for online images.

<CodeGroup>
```python
# Define the image URL
image_url = "https://www.superhealthykids.com/wp-content/uploads/2021/10/best-veggie-pizza-featured-image-square-2.jpg"

# Create the message dictionary with the image URL
image_message = {
    "role": "user",
    "content": {
        "type": "image_url",
        "image_url": {
            "url": image_url
        }
    }
}
```

```typescript TypeScript
import { Memory, Message } from "mem0ai/oss";

const client = new Memory();

const imageUrl = "https://www.superhealthykids.com/wp-content/uploads/2021/10/best-veggie-pizza-featured-image-square-2.jpg";

const imageMessage: Message = {
    role: "user",
    content: {
        type: "image_url",
        image_url: {
            url: imageUrl
        }
    }
}

await client.add([imageMessage], { userId: "alice" })
```
</CodeGroup>

### Using Base64 Image Encoding for Local Files

For local images or scenarios where embedding the image directly is preferable, you can use a Base64-encoded string.

<CodeGroup>
```python Python
import base64

# Path to the image file
image_path = "path/to/your/image.jpg"

# Encode the image in Base64
with open(image_path, "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode("utf-8")

# Create the message dictionary with the Base64-encoded image
image_message = {
    "role": "user",
    "content": {
        "type": "image_url",
        "image_url": {
            "url": f"data:image/jpeg;base64,{base64_image}"
        }
    }
}
```

```typescript TypeScript
import { Memory, Message } from "mem0ai/oss";

const client = new Memory();

const imagePath = "path/to/your/image.jpg";

const base64Image = fs.readFileSync(imagePath, { encoding: 'base64' });

const imageMessage: Message = {
    role: "user",
    content: {
        type: "image_url",
        image_url: {
            url: `data:image/jpeg;base64,${base64Image}`
        }
    }
}

await client.add([imageMessage], { userId: "alice" })
```
</CodeGroup>

### OpenAI-Compatible Message Format

You can also use the OpenAI-compatible format to combine text and images in a single message:

<CodeGroup>
```python Python
import base64

# Path to the image file
image_path = "path/to/your/image.jpg"

# Encode the image in Base64
with open(image_path, "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode("utf-8")

# Create the message using OpenAI-compatible format
message = {
    "role": "user",
    "content": [
        {
            "type": "text",
            "text": "What is in this image?",
        },
        {
            "type": "image_url",
            "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
        },
    ],
}

# Add the message to memory
client.add([message], user_id="alice")
```

```typescript TypeScript
import { Memory, Message } from "mem0ai/oss";

const client = new Memory();

const imagePath = "path/to/your/image.jpg";

const base64Image = fs.readFileSync(imagePath, { encoding: 'base64' });

const message: Message = {
    role: "user",
    content: [
        {
            type: "text",
            text: "What is in this image?",
        },
        {
            type: "image_url",
            image_url: {
                url: `data:image/jpeg;base64,${base64Image}`
            }
        },
    ],
}

await client.add([message], { userId: "alice" })
```
</CodeGroup>

This format allows you to combine text and images in a single message, making it easier to provide context along with visual content.

By utilizing these methods, you can effectively incorporate images into user interactions, enhancing the multimodal capabilities of your Mem0 instance.

If you have any questions, please feel free to reach out to us using one of the following methods:

<Snippet file="get-help.mdx" />
