Turb GPT Register Tutorial: Build a Local Registration Workflow and WebUI

Project Overview

Turb GPT Register is a local registration workflow tool based on and extended from gpt-free-register. It centrally manages email, proxies, and registration workflows. It supports both protocol-driven operation and connections to local fingerprint browsers.

The project can be started from the command line and provides a local WebUI for configuring the runtime environment and managing tasks. Note that it does not provide accounts, email services, or proxies, and cannot guarantee that third-party services will always be available.

Run it only in environments you are authorized to use, and comply with the rules of the relevant services, email providers, and proxy providers.

Key Features and Project Structure

Key Features

• Runs locally, with configuration and results stored on the local machine.
• Centrally manages email services, proxies, and registration workflows.
• Supports protocol-driven registration components.
• Can connect to local fingerprint browsers.
• Provides a command-line entry point and local WebUI.
• Organizes core logic, configuration, pages, tools, and third-party components into separate directories.

Directory Guide

• core/: Main program and core logic.
• config/: Project configuration.
• webui/: Local management interface.
• tools/: Utility scripts.
• vendor/gpt-register-tool/协议: Protocol registration components and related files.

When troubleshooting code or configuration issues, locate the relevant directory by feature first. This is usually more efficient than searching the entire repository.

Before Installation

The project recommends using Python 3.11. The installation commands below are for Windows PowerShell and assume that you have already downloaded the repository locally.

You must also prepare a usable email service and proxy configuration yourself. If you use a browser driver, you may need to install an additional browser or provider client. Running pip install installs only Python dependencies and does not automatically install these external programs.

Installation and Startup

Step 1: Create a Virtual Environment

Open PowerShell in the repository root, then create a Python virtual environment named .venv:

python -m venv .venv

Step 2: Activate the Virtual Environment

.venv\Scripts\Activate.ps1

After activation, subsequently installed Python packages will be placed in the project's virtual environment, avoiding interference with other Python projects on the system.

Step 3: Install Dependencies

pip install -r requirements.txt

If installation fails, record the complete error message and check the Python version, network environment, and dependency installation logs.

Step 4: Create the Local Configuration File

Copy-Item .env.example .env

.env.example is a configuration template. After copying it, edit your own .env and enter the settings required by your runtime environment.

Do not write real email credentials, proxy keys, or other sensitive information back to .env.example, and do not commit an .env containing real credentials to Git.

Step 5: Start the WebUI

python web.py

After the program starts, open the local WebUI and use the configuration fields provided by the page to enter your own email service and proxy information, then manage the relevant tasks. The README does not promise a fixed page address or field names, so follow the startup logs and the current WebUI page.

Basic Usage Workflow

1. Confirm that Python 3.11, the virtual environment, and project dependencies are ready.
2. Create .env from .env.example and enter your own runtime configuration.
3. Start the local management page with python web.py.
4. Configure email services and proxies that you are authorized to use in the WebUI.
5. Choose the protocol-driven or browser-driven method based on your local environment.
6. After running a task, check the results and logs to confirm that the email, proxy, and driver stages are working correctly.

A complete PowerShell startup example is shown below:

python -m venv .venv
.venv\Scripts\Activate.ps1
pip install -r requirements.txt
Copy-Item .env.example .env
python web.py

Using the Protocol Registration Component Separately

The protocol registration component is located at vendor/gpt-register-tool/协议. To run it independently of the main WebUI, enter that directory, read the component's own documentation, and install the required dependencies as instructed.

Components in this directory may have independent upstream sources, licenses, and copyright notices. Before using them, review their documentation and license files separately instead of assuming that the main project's installation method and license cover everything.

Advanced Usage and Maintenance

Start Troubleshooting with Logs and Configuration

The registration workflow depends on the email provider, proxy service, and browser environment. Changes to any interface, network fluctuations, or client behavior adjustments can cause the workflow to fail. When a problem occurs, check the following in order:

1. Review the complete logs and locate the first error.
2. Check the configuration in .env and the WebUI.
3. Verify that the email service is still accessible.
4. Check proxy credentials, network connectivity, and stability.
5. If using a browser driver, confirm that the browser or provider client is correctly installed and running.
6. If using the protocol component, check its directory for dependencies and upstream documentation.

Protect Local Runtime Data

Email pools, proxy credentials, account databases, browser profiles, logs, and exported files are all local runtime data. These files may contain sensitive information and should not be committed to public or shared repositories.

Although the project's .gitignore excludes common data files, you should still review the pending changes before committing code. Do not rely solely on filenames or ignore rules to protect credentials.

Prepare Effective Issue Reports

If you need to submit an Issue or Pull Request to the project, include enough diagnostic information:

• The complete error message or key error details.
• The operating system, Python version, and relevant runtime environment.
• Reproduction steps that can be executed consistently.
• Whether you are using the protocol-driven or browser-driven method.
• Necessary configuration details with passwords, tokens, and proxy credentials removed.

Do not publicly paste real credentials. Clear environment information and reproduction steps usually make issues easier to locate than a simple description such as “it does not work.”

Monitor Third-Party Dependency Changes

Email interfaces, proxy networks, and browser provider clients may change independently. The project separates these components into configuration and drivers so they can be adjusted for your environment, but this design cannot eliminate errors caused by third-party changes. Before upgrading or modifying anything, keep a copy of the currently working configuration and validate each component separately.

License and Usage Boundaries

The main project is adapted from xiaoguzuiniu/gpt-free-register and released under the MIT License. See the repository's LICENSE for the exact terms.

Components in vendor/gpt-register-tool/协议 retain their respective upstream licenses and copyright notices. Before distributing, modifying, or deploying these components, verify their licensing requirements separately.

Summary

Turb GPT Register integrates email, proxies, protocol components, and browser drivers into a local workflow, while providing a unified management entry point through the WebUI. Before using it, prepare the Python 3.11 environment, dependencies, and .env configuration, then choose a driver method suitable for your authorized environment. When problems occur, check the logs, configuration, and third-party service status first, while properly protecting all local credentials and runtime data.