Elite

Welcome to the AI-Powered Marketing Intelligence Platform! This full-stack application provides competitive ad analysis, AI-driven campaign generation, and predictive insights to help you maximize your marketing ROI.

✨ Features

• Multi-Platform Ad Monitoring: Track competitor advertisements across various platforms.
• AI-Powered Campaign Generation: Automatically create ad copy, define target audiences, and suggest budget allocations.
• Smart Analytics: Leverage NLP and Computer Vision for in-depth analysis of competitor strategies.
• Predictive Insights: Receive AI-driven recommendations to optimize your campaigns before they launch.
• Interactive AI Assistant: Chat with a marketing expert chatbot for instant business and marketing knowledge.
• User Authentication: Secure registration and login functionality for users.

📸 Screenshots

Landing Page	Dashboard	Insights View

🛠️ Tech Stack

• Frontend: React, Vite, Tailwind CSS, GSAP, Lucide React
• Backend: Python, Flask (for Authentication), FastAPI (for AI Insights)
• AI/ML: Google Gemini, Pandas, NLTK, spaCy, Transformers
• Database: SQLite

📋 Prerequisites

Before you begin, ensure you have the following installed on your system:

• Node.js (v18 or later)
• Python (v3.9 or later) and pip
• Tesseract-OCR: Required for OCR tasks. Make sure to add it to your system's PATH.
• WebDriver: A browser-specific WebDriver (e.g., ChromeDriver) for Selenium. Ensure it's in your system's PATH.

🚀 Getting Started

Follow these steps to get your development environment set up and running.

1. Clone the Repository

git clone <https://github.com/GDGVITM/hackbuild-Elite.git>
cd hackbuild-Elite

2. Environment Variables

You need to create two .env files for the project to work correctly.

• Root Directory (.env): For the Vite frontend.

  VITE_GEMINI_API_KEY=your_google_gemini_api_key
  

• Backend Directory (backend/.env): For the FastAPI/Gemini backend.

  GEMINI_API_KEY=your_google_gemini_api_key
  

3. Backend Setup

The backend consists of two services: a Flask app for authentication and a FastAPI app for AI insights.

# Navigate to the backend directory
cd backend

# Create and activate a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

# Install the required Python packages
pip install -r requirements.txt

# Perform one-time setup for NLTK and spaCy
python -m spacy download en_core_web_sm
python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords'); nltk.download('vader_lexicon');"

4. Frontend Setup

Open a new terminal and navigate to the project's root directory.

# (From the root directory)
npm install

🏃‍♂️ Running the Application

1. Start the AI Insights Backend (FastAPI)

In your second terminal:

# In the project's root directory
python insight_gen.py
# The FastAPI server will start, typically on http://localhost:8000

2. Start the Frontend (Vite)

In your third terminal:

# In the project's root directory
npm run dev
# Your React application will be available at http://localhost:5173

You can now open your browser and navigate to http://localhost:5173 to use the application.