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  • Why Rememberizer?
  • Background
    • What are Vector Embeddings and Vector Databases?
    • Glossary
    • Standardized Terminology
  • Personal Use
    • Getting Started
      • Search your knowledge
      • Mementos Filter Access
      • Common knowledge
      • Manage your embedded knowledge
  • Integrations
    • Rememberizer App
    • Rememberizer Slack integration
    • Rememberizer Google Drive integration
    • Rememberizer Dropbox integration
    • Rememberizer Gmail integration
    • Rememberizer Memory integration
    • Rememberizer MCP Servers
    • Manage third-party apps
  • Developer Resources
    • Developer Overview
  • Integration Options
    • Registering and using API Keys
    • Registering Rememberizer apps
    • Authorizing Rememberizer apps
    • Creating a Rememberizer GPT
    • LangChain integration
    • Vector Stores
    • Talk-to-Slack the Sample Web App
  • Enterprise Integration
    • Enterprise Integration Patterns
  • API Reference
    • API Documentation Home
    • Authentication
  • Core APIs
    • Search for documents by semantic similarity
    • Retrieve documents
    • Retrieve document contents
    • Retrieve Slack content
    • Memorize content to Rememberizer
  • Account & Configuration
    • Retrieve current user account details
    • List available data source integrations
    • Mementos
    • Get all added public knowledge
  • Vector Store APIs
    • Vector Store Documentation
    • Get vector store information
    • Get a list of documents in a Vector Store
    • Get document information
    • Add new text document to a Vector Store
    • Upload files to a Vector Store
    • Update file content in a Vector Store
    • Remove a document in Vector Store
    • Search for Vector Store documents by semantic similarity
  • Additional Resources
    • Notices
      • Terms of Use
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      • B2B
        • About Reddit Agent
  • Releases
    • Release Notes Home
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  • 2024 Releases
    • Dec 27th, 2024
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  • Jan 22nd, 2024
  • Jan 15th, 2024
  • LLM Documentation
    • Rememberizer LLM Ready Documentation
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On this page
  • Endpoint
  • Authentication
  • Request
  • Response
  • User Profile (Extended Information)
  • Extended Response
  • Error Responses
  • Usage Example
  • Using cURL
  • Using JavaScript
  • Using Python
  1. Account & Configuration

Retrieve current user account details

This endpoint allows you to retrieve the details of the currently authenticated user's account.

Endpoint

GET /api/v1/account/

Authentication

This endpoint requires authentication using a JWT token.

Request

No request parameters are required.

Response

{
  "id": "user_id",
  "email": "user@example.com",
  "name": "User Name"
}

User Profile (Extended Information)

For more detailed user profile information, you can use:

GET /api/v1/me/

Extended Response

{
  "id": "username",
  "email": "user@example.com",
  "name": "User Name",
  "user_onboarding_status": 7,
  "dev_onboarding_status": 3,
  "company_name": "Company",
  "website": "https://example.com",
  "bio": "User bio",
  "team": [
    {
      "id": "team_id", 
      "name": "Team Name", 
      "image_url": "url", 
      "role": "admin"
    }
  ],
  "embed_quota": 10000,
  "current_usage": 500,
  "email_verified": true
}

Error Responses

Status Code
Description

401

Unauthorized - Invalid or missing authentication credentials

403

Forbidden - User does not have permission to access this resource

500

Internal Server Error - Something went wrong on the server

Usage Example

Using cURL

curl -H "Authorization: Bearer YOUR_JWT_TOKEN" https://api.rememberizer.ai/api/v1/account/

Using JavaScript

const response = await fetch('https://api.rememberizer.ai/api/v1/account/', {
  method: 'GET',
  headers: {
    'Authorization': 'Bearer YOUR_JWT_TOKEN'
  }
});
const data = await response.json();
console.log(data);

Using Python

import requests

headers = {"Authorization": "Bearer YOUR_JWT_TOKEN"}
response = requests.get("https://api.rememberizer.ai/api/v1/account/", headers=headers)
data = response.json()
print(data)
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Last updated 1 month ago