# Get vector store's information

{% openapi src="<https://2952947711-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FyNqpTh7Mh66N0RnO0k24%2Fuploads%2Fgit-blob-77b6137eeb641262ec8e531c78123c02b825b865%2Frememberizer_openapi.yml?alt=media&token=cbad765b-1613-4222-b591-9ae17a3b7cfa>" path="/vector-stores/me" method="get" %}
[rememberizer\_openapi.yml](https://2952947711-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FyNqpTh7Mh66N0RnO0k24%2Fuploads%2Fgit-blob-77b6137eeb641262ec8e531c78123c02b825b865%2Frememberizer_openapi.yml?alt=media\&token=cbad765b-1613-4222-b591-9ae17a3b7cfa)
{% endopenapi %}

## Example Requests

{% tabs %}
{% tab title="cURL" %}

```bash
curl -X GET \
  https://api.rememberizer.ai/api/v1/vector-stores/me \
  -H "x-api-key: YOUR_API_KEY"
```

{% hint style="info" %}
Replace `YOUR_API_KEY` with your actual Vector Store API key.
{% endhint %}
{% endtab %}

{% tab title="JavaScript" %}

```javascript
const getVectorStoreInfo = async () => {
  const response = await fetch('https://api.rememberizer.ai/api/v1/vector-stores/me', {
    method: 'GET',
    headers: {
      'x-api-key': 'YOUR_API_KEY'
    }
  });
  
  const data = await response.json();
  console.log(data);
};

getVectorStoreInfo();
```

{% hint style="info" %}
Replace `YOUR_API_KEY` with your actual Vector Store API key.
{% endhint %}
{% endtab %}

{% tab title="Python" %}

```python
import requests

def get_vector_store_info():
    headers = {
        "x-api-key": "YOUR_API_KEY"
    }
    
    response = requests.get(
        "https://api.rememberizer.ai/api/v1/vector-stores/me",
        headers=headers
    )
    
    data = response.json()
    print(data)

get_vector_store_info()
```

{% hint style="info" %}
Replace `YOUR_API_KEY` with your actual Vector Store API key.
{% endhint %}
{% endtab %}
{% endtabs %}

## Response Format

```json
{
  "id": "vs_abc123",
  "name": "My Vector Store",
  "description": "A vector store for product documentation",
  "embedding_model": "sentence-transformers/all-mpnet-base-v2",
  "indexing_algorithm": "ivfflat",
  "vector_dimension": 128,
  "search_metric": "cosine_distance",
  "created": "2023-06-01T10:30:00Z",
  "modified": "2023-06-15T14:45:00Z"
}
```

## Authentication

This endpoint requires authentication using an API key in the `x-api-key` header.

## Error Responses

| Status Code | Description                               |
| ----------- | ----------------------------------------- |
| 401         | Unauthorized - Invalid or missing API key |
| 404         | Not Found - Vector Store not found        |
| 500         | Internal Server Error                     |

This endpoint retrieves information about the vector store associated with the provided API key. It's useful for checking configuration details, including the embedding model, dimensionality, and search metric being used. This information can be valuable for optimizing search queries and understanding the vector store's capabilities.