Description

Private GPT is a customized version of OpenAI's ChatGPT, designed to provide a powerful and versatile interaction experience with artificial intelligence technologies. This assistant can transform how you utilize AI in various daily applications.

Features

• Interactive Chat: View your OpenAI balance, create and manage different chats, and switch assistants during a conversation.
• AI Audio Generation: Create high-quality audio in seconds.
• Artist Assistant: Generate stunning images, like forest landscapes, with the artist AI.
• Scriptwriter Assistant: Create creative and efficient scripts, such as horror video scripts.

Project Structure

• routes/: Contains application routes.
• assistants/: Module for managing assistants.
• instance/: Directory to store generated files, such as audio.
• static/: Static files (CSS, JS, images).
• templates/: HTML templates for rendering in Flask.
• app.py: Entry point of the Flask application.
• config.py: Application configuration.
• models.py: Database models definition.

Installation and Configuration

1. Clone the repository:

   git clone https://github.com/caiolombello/PrivateGPT.git
   cd PrivateGPT

2. Create and activate a virtual environment (optional, but recommended):

   python3 -m venv venv
   source venv/bin/activate

3. Install project dependencies:

   poetry install

4. Create a .env file with the following variables:

   OPENAI_API_KEY=your_openai_api_key
   OPENAI_SESSION_KEY=your_openai_session_key
   OPENAI_ORGANIZATION=your_openai_organization_id
   AUTHENTICATION=False

   • OPENAI_API_KEY: Your OpenAI API key, which you can obtain from your OpenAI account dashboard.
   • OPENAI_SESSION_KEY: Your OpenAI session key. For a detailed guide on how to get your session key, refer to this discussion.
   • OPENAI_ORGANIZATION: Your OpenAI organization ID, which can be found in the OpenAI platform settings.
   • AUTHENTICATION: Set to False if you do not require IP-based authentication; otherwise, set to True and configure accordingly.

5. Initialize the database:

   flask db init
   flask db migrate
   flask db upgrade

6. Run the application:

   flask run

Usage

• Create an Assistant: Send a POST request to /assistant/create with assistant_name, assistant_instructions, image (optional), and voice (optional).
• Initialize a Thread: Send a POST request to /assistant/initialize with assistant_id.
• List Assistants: Send a GET request to /assistant/list.
• Send Message: Send a POST request to /messages/send with thread_name and message.
• Receive Messages: Send a GET request to /messages/receive/<thread_name>.
• Rename Thread: Send a POST request to /messages/thread/rename with thread_name and messages.

Docker

To build and run the application with Docker:

1. Build the Docker image:

   docker build -t private-gpt .

2. Run the container:

   docker run -d -p 5000:5000 --name private-gpt-container private-gpt

Assistant Creation Script

The create.sh script located in the assistants folder can be used to automatically create assistants based on instruction files.

1. Edit the create.sh script to adjust the SERVER_URL if necessary.
2. Add or modify text files with the assistant instructions in the assistants folder.
3. Run the script:

   ./assistants/create.sh

Contribution

Contributions are welcome! Feel free to open issues and pull requests to improve this project.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For more information, contact [email protected].