margetrp-hub/gpt-account-manager

★ 17PythonAudience · developerComplexity · 3/5Setup · moderate

Mindmap

mindmap
  root((gpt-account-manager))
    What It Does
      Bulk account management
      Credential refresh
      Failure diagnosis
    Tech Stack
      Python
      Node.js
      HTML
      Nginx
    Account Pages
      Main view
      Refresh queue
      Credential warehouse
    Use Cases
      API proxy services
      Team account sharing
      Token management

mindmap root((gpt-account-manager)) What It Does Bulk account management Credential refresh Failure diagnosis Tech Stack Python Node.js HTML Nginx Account Pages Main view Refresh queue Credential warehouse Use Cases API proxy services Team account sharing Token management

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Things people build with this

USE CASE 1

Centrally manage a large pool of OpenAI accounts, refreshing credentials automatically and diagnosing failures like expired tokens or regional bans

USE CASE 2

Export refreshed auth JSON files for use with proxy API services that need valid OpenAI credentials

USE CASE 3

Share one self-hosted instance across a team without exposing each other's account data, since credentials stay in each user's browser local storage

Tech stack

PythonNode.jsHTMLNginx

Getting it running

Difficulty · moderate Time to first run · 1h+

Requires Python and Node.js for the OAuth refresh step, optionally place behind Nginx for production. README is written entirely in Chinese.

No license information is stated in the repository.

In plain English

This project is a self-hosted web application for managing multiple OpenAI and ChatGPT accounts in bulk. It is written in Python and aimed at people who need to maintain a large collection of accounts that rely on either Microsoft Outlook mailboxes or temporary email addresses to receive verification codes. The README is written entirely in Chinese. The tool has two main sides. Regular users connect their own email credentials, receive verification codes through the interface, and submit accounts needing credential refreshes into a processing queue. A site administrator handles maintenance tasks, extracts temporary email tokens, and manages a central store of account credentials used for API access. When accounts need their credentials renewed, the tool runs an OAuth flow against OpenAI, diagnoses why a credential failed (options include expired refresh tokens, session expiry, account bans, regional restrictions, or quota exhaustion), and exports the result as an auth JSON file compatible with proxy API services. Each stage of this workflow has its own browser page: one for the main account management view, one for the refresh queue, one for the credential warehouse, one for local format conversion, and an admin-only section for site maintenance. By default, user data including email addresses, passwords, refresh tokens, and cached messages stays in the browser's local storage rather than on the server, so multiple people can share one instance without seeing each other's data. When server-side features are needed, data is stored under a per-user workspace identifier. Deployment requires running the Python server directly or placing it behind a reverse proxy such as Nginx. No frontend build step is needed because the interface is plain HTML. Node.js is also required for the OAuth refresh step. The project has 17 stars on GitHub and does not appear to offer a hosted version.

Copy-paste prompts

Prompt 1

Set up gpt-account-manager on Ubuntu behind Nginx, configure it for a team of 5, and walk me through adding an OpenAI account and submitting it to the refresh queue

Prompt 2

Explain how gpt-account-manager's OAuth refresh flow diagnoses credential failures, what does it check and what does the exported auth JSON file contain?

Prompt 3

How does gpt-account-manager use browser local storage to isolate multiple users' data on a shared instance, and when does data move to the server?

Prompt 4

Modify gpt-account-manager to store all credentials in a server-side SQLite database with per-user workspaces protected by a login page instead of using browser local storage

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