> For the complete documentation index, see [llms.txt](https://docs.rememberizer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rememberizer.ai/developer-resources/api-docs/vector-store/get-vector-stores-information.md).

# Get vector store's information

{% openapi src="/files/7T1Jx6BU3fZ2U5LsImW1" 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.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.rememberizer.ai/developer-resources/api-docs/vector-store/get-vector-stores-information.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.