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https://github.com/khederta/ro-draft-with-react-django
This is the Refugee Ontology Web Application built with React.js, Django, and AllegroGraph.
https://github.com/khederta/ro-draft-with-react-django
Last synced: about 1 hour ago
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This is the Refugee Ontology Web Application built with React.js, Django, and AllegroGraph.
- Host: GitHub
- URL: https://github.com/khederta/ro-draft-with-react-django
- Owner: khederTa
- Created: 2024-06-10T12:03:13.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-06-10T13:59:58.000Z (8 months ago)
- Last Synced: 2024-11-22T19:38:46.649Z (2 months ago)
- Language: JavaScript
- Size: 1.12 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Refugee Ontology Web Application
This is a **Draft** of the Refugee Ontology Web Application built with React.js, Django, and AllegroGraph. The main goal is to provide a simple user interface for non-technical people and decision-makers in NGOs and related organizations to study refugee situations using a knowledge graph (ontology) and derive insights from the data. The application supports a QA system built with Retrieval Augmented Generation (RAG), relying on significant resources (books and scientific papers) related to social science.
## Project Structure
The repository contains two main folders:
1. **backend**: Handles the backend operations. It contains all the API endpoints and types/schemas needed.
2. **frontend**: Contains the React frontend built with Vite and styled with Bootstrap.
## Getting Started
### Prerequisites
- Python (Django)
- NPM (or Yarn)
- AllegroGraph
### Setup
1. **Clone the repository**:
```bash
git clone https://github.com/khederTa/ro-draft-with-react-django.git
cd ro-draft-with-react-django
```
2. **Backend Setup**: After installing AllegroGraph on your local machine and running the server ([Download AllegroGraph](https://franz.com/agraph/downloads/)), follow these steps:
- **Install `virtualenv` if you don't have it:**
```bash
pip install virtualenv
```
- **Create a virtual environment:**
Navigate to your project directory and create a virtual environment:
```bash
virtualenv venv
```
- **Activate the virtual environment:**
- On Windows:
```bash
venv\Scripts\activate
```
- On macOS/Linux:
```bash
source venv/bin/activate
```
- **Install the dependencies:**
```bash
pip install -r requirements.txt
```
- **Configure Your OpenAI API Key**:
Add your actual OpenAI API key in the `.env` file:
```plaintext
OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
```
- **Start the backend server:**
- On Windows:
```bash
python manage.py runserver
```
- On macOS/Linux:
```bash
python3 manage.py runserver
```
3. **Frontend Setup**:
- **Install dependencies**:
```bash
cd frontend
npm install
```
- **Start the frontend server**:
```bash
npm run dev
```
### Folder Structure
#### Frontend
- **utils**: Configuration and utilities related to authentication.
- **views**: Contains all the UI components.
#### Backend
- **api**: Handles APIs in the Django app.
- **backend**: Main configuration for the backend.
- **rag**: Contains the RAG implementation using the OpenAI API key (not yet integrated with the backend).
- **userauth**: Handles user authentication.
### Core Features
1. Each user has their own sub-graph in the AllegroGrpah Database(The knowledge Graph) with a randomly generated name, allowing access and manipulation of their data and analysis in an isolated manner.
2. A QA system built with RAG (not yet completed) will enable users to use their data(files) to answer questions from the RAG.