### Vertex AI

To use Google Cloud's Vertex AI for text embedding models, set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable to point to the path of your service account's credentials JSON file. These credentials can be created in the [Google Cloud Console](https://console.cloud.google.com/).

### Usage

```python
import os
from mem0 import Memory

# Set the path to your Google Cloud credentials JSON file
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/your/credentials.json"
os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM

config = {
    "embedder": {
        "provider": "vertexai",
        "config": {
            "model": "text-embedding-004"
        }
    }
}

m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```

### Config

Here are the parameters available for configuring the Vertex AI embedder:

| Parameter                 | Description                                      | Default Value        |
| ------------------------- | ------------------------------------------------ | -------------------- |
| `model`                   | The name of the Vertex AI embedding model to use | `text-embedding-004` |
| `vertex_credentials_json` | Path to the Google Cloud credentials JSON file   | `None`               |
| `embedding_dims`          | Dimensions of the embedding model                | `256`                |
