OldBailey AI

OldBailey AI is a project developed to assist researchers and historians by providing insights into historical trends, facilitating data analysis, and offering an immersive experience through role-play. This AI leverages OpenAI to analyze the Old Bailey dataset, utilizing prompt engineering to create an AI capable of analyzing historic trends, generating tables, and role-playing as people from that era.

Table of Contents

• OldBailey AI
  • Table of Contents
  • About
  • Technologies Used
  • Features
  • Installation
  • Usage
  • Contact
  • References
  • Ideas

About

OldBailey AI is designed to enhance historical research by offering advanced data analysis and immersive role-play capabilities. By analyzing the Old Bailey dataset, this AI provides valuable insights into historical trends and helps users explore history in a more interactive and engaging way.

Technologies Used

• Frontend:

  • Next.js
  • TypeScript
  • SCSS/SASS

• Backend:

  • Flask
  • Python
  • Docker

• Database:

  • MongoDB

• AI Integration:

  • OpenAI

Features

• Historical Data Analysis: Provides insights into historical trends by analyzing the Old Bailey dataset.
• Interactive Role-Play: Allows users to role-play as people from the historical era, enhancing the immersive experience.
• Data Visualization: Generates tables and visualizations to facilitate data analysis.
• Prompt Engineering: Utilizes advanced prompt engineering to maximize the capabilities of OpenAI.

Installation

To run this project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/HassanChowdhry/OldBailey-AI.git

2. Navigate to the project directory:

   cd app

3. Install the dependencies:

   npm install

4. Create a virtual environment:

   python3 -m venv venv

5. Activate the virtual environment:

   source venv/bin/activate

6. Install the Python dependencies:

   pip install -r requirements.txt

7. Start the development server:

   python3 run.py

Usage

You can access the application by navigating to http://localhost:3000 in your web browser. Explore the various features and capabilities offered by OldBailey AI.

Contact

Feel free to reach out to me for any professional inquiries or questions:

• Email: hassan.chowdhry@dal.ca
• LinkedIn: Hassan Chowdhry
• Website: HassanChowdhry.live

References

Tim Hitchcock, Robert Shoemaker, Clive Emsley, Sharon Howard and Jamie McLaughlin, et al., The Old Bailey Proceedings Online, 1674-1913 (www.oldbaileyonline.org, version 9.0, Autumn 2023).

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Thank you for exploring OldBailey AI!

Ideas

Future Features:

• 2FA
• Localization
• IAM ; User Roles (to support paid plans & permissions)
• User preferences
• Email verification
• User notifications (newsletters, updates, etc.)

Feedback:

• Use Poetry
• Dockerize the App (Backend, Frontend & MongoDB)
• Have a local vs production setup (local should run in debug mode)
• Look into DB ORM.
• Introduce Checkstyles (Pylint)
• Intoduce static-type checking (MyPy)
• Introduce test coverage
• Introduce Unit Testing (PyTest)
• Introduce Integration Testing (PyTest)
• Introduce CI/CD
• Introduce proper logging (info, warning, error) & metrics
• Introduce monitoring (alert system)
• Do the token authentication & refresh in interceptor/middleware