# Project export: Rellow

This document was generated by HackStack to give an AI agent context about a hackathon project. Sections are labeled with their provenance; content marked as truncated was cut to keep this document small.

## Project metadata

- Hackathon: Cal Hacks 10.0
- Tagline: Rellow is a revolutionary real estate platform driven by advanced AI technology. Rellow simplifies complex tasks - in this case, finding your dream property and making informed investments.
- Devpost: https://devpost.com/software/rellow-h5tayj
- GitHub: https://github.com/vpotturu777/Rellow
- Video: https://www.youtube.com/embed/r-N64r-ZjNw?enablejsapi=1&hl=en_US&rel=0&start=&version=3&wmode=transparent
- Team: 2 GitHub contributor(s) — vpotturu777 (7 commits), Aryan Mathur (1 commits)

## Devpost submission (written by the team)

### What it does

Rellow is a revolutionary real estate platform driven by advanced AI technology. Rellow,simplifies complex tasks - in this case, finding your dream property and making informed investments. Rellow breaks down geographical barriers, allowing you to explore properties globally. We call these diverse locations "investment zones," representing the different opportunities in the real estate landscape. Whether it's urban apartments, countryside villas, or beachfront properties, Rellow associates each option with the relevant zone, ensuring a comprehensive evaluation of your potential investments. The true power of Rellow lies in its ability to provide intelligent insights. Our AI analyzes market trends, property values, and future forecasts within these zones. By understanding the correlations between different investment opportunities, Rellow becomes your trusted advisor, guiding you towards the most lucrative real estate ventures. Moreover, Rellow's AI continually adapts, learning from your preferences and investment history. It refines its understanding of your goals and risk tolerance, ensuring personalized and relevant recommendations tailored to your real estate journey.

### How we built it

Our objective with Rellow was to craft a compelling and user-friendly tool tailored for investors seeking their ideal investment opportunities. With this goal in mind, we designed an intuitive and well-organized interface to ensure effortless navigation. To achieve this, we employed React and Tailwind for the front-end, coupled with Django for the backend. We utilized the CockroachDB database to store our real estate data, enabling us to train our models and generate refined recommendations through filtration. To enhance our predictive capabilities, we harnessed MindsDB, leveraging its user-friendly interface and seamless integration with CockroachDB to generate projections. Additionally, we integrated a chat feature powered by Together AI, enabling investors to receive personalized recommendations and information for their next investment.

### Challenges we ran into

Our foremost challenge was deciding on our feature list and understanding the data that needs to be used to create our projections and personalized investments. We faced difficulty in understanding how we can organize all the amounts of data while keeping the interface easy to understand and use. We were able to work through the challenges to decide what features we want to focus on for the purpose of the hackathon as well as how we can organize our tabs and data to make search, dashboard and the user functionalities easy to use with access to the most data possible.

### Accomplishments we're proud of

Our key achievement was identifying a common problem faced by numerous investors, understanding our user base, and developing a universally applicable solution. We conceived an idea that we believe has the potential to revolutionize investment practices, creating a vision we're committed to pursuing in the future. Despite our small team of two, we collaborated efficiently to produce a result that we are proud of.

### What we learned

Our journey with Rellow has been a transformative experience for our team. Through this venture, we unlocked the immense potential of AI technology in revolutionizing the way individuals approach real estate investing. We worked on harnessing the power of AI to analyze vast property databases, predict market movements, and offer accurate investment projections. Technologically, our proficiency skyrocketed as we honed our skills in developing advanced algorithms, navigating intricate real estate datasets, and integrating various AI APIs. This process empowered us to create a seamless user experience, ensuring that Rellow users can effortlessly explore global properties and make well-informed investment decisions.

### What's next

Moving forward, we have exciting plans for the future of our website. Here's what's next: Enhanced Data Personalization: We recognize the complexity of investing and plan to introduce a tool that considers an array of factors such as taxes, rent, neighborhood dynamics, and user ratings. This tool will empower users to make well-informed investment decisions tailored to their unique preferences and financial circumstances. Seamless Real Estate Agent Connection: Understanding every potential investment is crucial. We're working on creating an effortless way for investors to connect with real estate agents specializing in properties and areas aligned with their interests and the projections generated by our platform. This ensures investors have comprehensive insights before making decisions. Immersive Augmented Reality: Embracing the expanding market of AR, Rellow aims to revolutionize property exploration. Investors will have the ability to virtually tour properties worldwide from the comfort of their homes. This not only saves money but also provides in-depth information about distant properties, enriching the decision-making process.

## README (from the GitHub repository)

# Rellow


## Detected evidence (automated analysis)

Indexed codebase: 42 recognized source files, 67 KB.
- CSS (language) — detected in the code
- HTML (language) — detected in the code
- JavaScript (language) — detected in the code
- Python (language) — detected in the code
- React (technology) — detected in the code
- Tailwind CSS (technology) — detected in the code
- Django (technology) — claimed on Devpost, not found in the code

## Codebase structure (from repository index)

### Files (48 of 48)

```
backend/backend/__init__.py
backend/backend/asgi.py
backend/backend/settings.py
backend/backend/urls.py
backend/backend/wsgi.py
backend/db.sqlite3
backend/listings/__init__.py
backend/listings/admin.py
backend/listings/apps.py
backend/listings/migrations/__init__.py
backend/listings/migrations/0001_initial.py
backend/listings/models.py
backend/listings/tests.py
backend/listings/views.py
backend/manage.py
backend/server/__init__.py
backend/server/admin.py
backend/server/apps.py
backend/server/migrations/__init__.py
backend/server/models.py
backend/server/tests.py
backend/server/views.py
CNAME
frontend/.gitignore
frontend/package.json
frontend/public/index.html
frontend/public/manifest.json
frontend/public/robots.txt
frontend/README.md
frontend/src/App.css
frontend/src/App.js
frontend/src/App.test.js
frontend/src/components/realestate/Chat.js
frontend/src/components/realestate/Dashboard.js
frontend/src/components/realestate/DashboardTable.js
frontend/src/components/realestate/Data.js
frontend/src/components/realestate/ListingCard.js
frontend/src/components/realestate/listings.js
frontend/src/components/realestate/RealestatePage.js
frontend/src/components/realestate/RealestateTabs.js
frontend/src/components/realestate/Realters.js
frontend/src/components/sidebar.js
frontend/src/index.css
frontend/src/index.js
frontend/src/reportWebVitals.js
frontend/src/setupTests.js
frontend/tailwind.config.js
README.md
```

### Dependencies

- frontend/package.json: @testing-library/jest-dom@^5.17.0, @testing-library/react@^13.4.0, @testing-library/user-event@^13.5.0, react@^18.2.0, react-dom@^18.2.0, react-router-dom@^6.17.0, react-scripts@5.0.1, tailwindcss@^3.3.5, web-vitals@^2.1.4

### Recent commits (newest first)

- finished ui
- almost complete frontend
- routing
- Create CNAME
- Django Set Up
- frontend commit
- Create README.md
- initial commit

## Key source files (fetched from GitHub, selected and truncated for size)

### frontend/package.json

```
{
  "name": "frontend",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    "@testing-library/jest-dom": "^5.17.0",
    "@testing-library/react": "^13.4.0",
    "@testing-library/user-event": "^13.5.0",
    "react": "^18.2.0",
    "react-dom": "^18.2.0",
    "react-router-dom": "^6.17.0",
    "react-scripts": "5.0.1",
    "web-vitals": "^2.1.4"
  },
  "scripts": {
    "start": "react-scripts start",
    "build": "react-scripts build",
    "test": "react-scripts test",
    "eject": "react-scripts eject"
  },
  "eslintConfig": {
    "extends": [
      "react-app",
      "react-app/jest"
    ]
  },
  "browserslist": {
    "production": [
      ">0.2%",
      "not dead",
      "not op_mini all"
    ],
    "development": [
      "last 1 chrome version",
      "last 1 firefox version",
      "last 1 safari version"
    ]
  },
  "devDependencies": {
    "tailwindcss": "^3.3.5"
  }
}

```

### frontend/src/index.js

```javascript
import React from 'react';
import ReactDOM from 'react-dom/client';
import './index.css';
import App from './App';
import reportWebVitals from './reportWebVitals';

const root = ReactDOM.createRoot(document.getElementById('root'));
root.render(
  <React.StrictMode>
    <App />
  </React.StrictMode>
);

// If you want to start measuring performance in your app, pass a function
// to log results (for example: reportWebVitals(console.log))
// or send to an analytics endpoint. Learn more: https://bit.ly/CRA-vitals
reportWebVitals();

```

### frontend/src/App.js

```javascript
import Chat from "./components/realestate/Chat";
import Dashboard from "./components/realestate/Dashboard";
import RealestatePage from "./components/realestate/RealestatePage";
import Sidebar from "./components/sidebar";
import { BrowserRouter, Routes, Route } from "react-router-dom";

function App() {
  return (
    <div class="flex flex-row bg-slate">
      <BrowserRouter>
        <div class="flex flex-col w-1/6">
          <Sidebar />
        </div>
        <div class="flex flex-col w-5/6">
          <Routes>
            <Route path="/realestate/manage" element={<RealestatePage />} />
            <Route path="/realestate/dashboard" element={<Dashboard />} />
            <Route path="/realestate/chat" element={<Chat />} />
            {/* <route path="*" element={<h1>Not Found</h1>} /> */}
          </Routes>
        </div>
      </BrowserRouter>
    </div>
  );
}

export default App;

```

### frontend/tailwind.config.js

```javascript
/** @type {import('tailwindcss').Config} */
module.exports = {
  content: ["./src/**/*.{js,jsx,ts,tsx}"],
  theme: {
    extend: {},
  },
  plugins: [],
};

```

### backend/manage.py

```python
#!/usr/bin/env python
"""Django's command-line utility for administrative tasks."""
import os
import sys


def main():
    """Run administrative tasks."""
    os.environ.setdefault("DJANGO_SETTINGS_MODULE", "backend.settings")
    try:
        from django.core.management import execute_from_command_line
    except ImportError as exc:
        raise ImportError(
            "Couldn't import Django. Are you sure it's installed and "
            "available on your PYTHONPATH environment variable? Did you "
            "forget to activate a virtual environment?"
        ) from exc
    execute_from_command_line(sys.argv)


if __name__ == "__main__":
    main()

```

### backend/server/models.py

```python
from django.db import models

# Create your models here.

```

### backend/listings/tests.py

```python
from django.test import TestCase

# Create your tests here.

```

### backend/server/tests.py

```python
from django.test import TestCase

# Create your tests here.

```

### frontend/src/index.css

```css
@tailwind base;
@tailwind components;
@tailwind utilities;


```

### backend/listings/admin.py

```python
from django.contrib import admin

# Register your models here.

```

[25 more indexed source files omitted to keep this export small. The full file list is in the Codebase structure section above.]