Hackathon-AD-Services

Table of Contents

1. Overview
2. Hackathon Problem
   • Challenge 1: Streamlining Internal Opinion Request Processes
   • Challenge 2: Automating & Centralizing Research and Benchmarking for Key Topics
3. Solution
4. Technology Stack
5. Reasoning Behind Technical Choices
6. Setup Instructions

---

Overview

This project addresses inefficiencies in internal processes for Abu Dhabi government departments. Team 3Bit has designed solutions that enhance workflow efficiency, reduce redundancies, and ensure standardized outputs.

---

Hackathon Problem

Challenge 1: Streamlining Internal Opinion Request Processes

Problem:

• Inconsistent responses across departments.
• Duplicated efforts in document analysis.
• Lack of standardized formats for recommendations.

Solution: A platform that:

• Standardizes and automates task assignments.
• Offers response templates for consistency.
• Leverages a shared knowledge base for past analyses.

Challenge 2: Automating & Centralizing Research and Benchmarking for Key Topics

Problem:

• Excessive manual effort in research.
• Redundant work by different teams.
• Risk of missing critical data.

Solution: An AI-powered tool that:

• Aggregates data from trusted sources.
• Summarizes key insights automatically.
• Centralizes research into a unified repository.

---

Solution

Key Features:

• Internal Opinion Request Platform: Automates request routing, standardizes response templates, and minimizes duplication with shared knowledge.
• AI-Driven Research Tool: Scrapes data from trusted sources, summarizes insights with GPT-powered AI, and centralizes research findings.

---

Technology Stack

Component	Technology
Backend	Django (Python)
Frontend	React (JavaScript)
Database	PostgreSQL
AI Integration	OpenAI API (ChatGPT)

---

Reasoning Behind Technical Choices

Backend: Django

• Robust framework with built-in ORM and admin panel for rapid development.
• Easy integration with PostgreSQL and AI services.

Frontend: React

• Modern, dynamic, and reusable component-based UI.
• Excellent for managing state and rendering complex interfaces.

Database: PostgreSQL

• Reliable, scalable relational database.
• Supports complex queries for data-intensive applications.

OpenAI API

• GPT models provide advanced natural language processing capabilities.
• Streamlines response generation and data summarization.

Trade-offs

• Time Constraints: Focused on core functionalities; advanced features like analytics dashboards were deprioritized.
• AI Dependence: Requires an OpenAI API key, which incurs cost; scalability of the solution depends on API usage limits.

Future Enhancements

• Add analytics dashboards for deeper insights.
• Expand source scraping for the research tool to include government and academic repositories.
• Introduce multilingual support for broader usability.

---

Setup Instructions

Prerequisites

• Docker and Docker Compose installed on your system.
• A .env file configured with the necessary environment variables (e.g., OpenAI API key, database credentials). Refer to the .env.example file for the env setup.

Steps to Run the Project

1. Clone the Repository:

   git clone <repository-url>
   cd Hackathon-AD-Services

2. Prepare the Environment:

   • Create a .env file in the root directory.

3. Run the Project:

   • Build and start the containers using make:

     make

   • This will:
     • Build the Docker images for the backend and frontend.
     • Set up the PostgreSQL database.
     • Start the services.

4. Access the Application:

   • The application will be available at:
     • Frontend: http://localhost

5. Stop the Project:

   • Use the following command to stop and remove the containers:

     make down

---