Skip to content

Get vector store's information

GET /vector-stores/me

Retrieve information about the vector store associated with the API key.

Parameter In Type Required Description
x-api-key header string yes The API key for authentication.

Responses

  • 200 — Vector store information retrieved successfully.

Example Requests

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

Info

Replace YOUR_API_KEY with your actual Vector Store API key.

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();

Info

Replace YOUR_API_KEY with your actual Vector Store API key.

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()

Info

Replace YOUR_API_KEY with your actual Vector Store API key.

Response Format

{
  "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.