Lunaris: AI-Powered Video Clip Generator

Lunaris is an innovative platform that uses AI to generate viral video clips from long-form content. This repository contains both the frontend and backend components of the application.

Getting Started

To get started with Lunaris, clone the repository:

git clone https://github.com/savnani5/Lunaris.git
cd Lunaris

Table of Contents

• Frontend
  • Prerequisites
  • Installation
  • Environment Setup
  • Running the Frontend
• Backend
  • Prerequisites
  • Installation
  • Environment Setup
  • Running the Backend
  • Docker Setup
  • Conda Environment Setup

Frontend

Frontend Prerequisites

• Node.js (v14 or later)
• npm (v6 or later)

Frontend Installation

1. Navigate to the frontend directory:

   cd Lunaris/frontend
   

2. Install dependencies:

   npm install
   

Frontend Environment Setup

1. Create a .env.local file in the frontend directory:

   touch .env.local
   

2. Add the following environment variables to .env.local:

   # Clerk
   NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=your_clerk_publishable_key
   CLERK_SECRET_KEY=your_clerk_secret_key
   NEXT_PUBLIC_CLERK_SIGN_IN_URL=/sign-in
   NEXT_PUBLIC_CLERK_SIGN_UP_URL=/sign-up
   
   # MongoDB
   MONGODB_URI=your_mongodb_uri
   
   # Backend URL
   NEXT_PUBLIC_BACKEND_URL=backend_url
   
   # YouTube API Key
   YT_API_KEY=your_youtube_api_key
   

   Replace the placeholders with your actual credentials and settings.

Running the Frontend

1. Start the development server:

   npm run dev
   

2. Open your browser and navigate to http://localhost:3000

Backend

Backend Prerequisites

• Python 3.11 or later
• pip
• FFmpeg
• ImageMagick

Backend Installation

1. Navigate to the backend directory:

   cd Lunaris/backend
   

2. Install dependencies:

   pip install -r requirements.txt
   

Backend Environment Setup

1. Create a .env file in the backend directory:

   touch .env
   

2. Add the following environment variables to .env:

   FLASK_ENV=development
   MONGODB_URI=your_mongodb_uri
   AWS_ACCESS_KEY_ID=your_aws_access_key
   AWS_SECRET_ACCESS_KEY=your_aws_secret_key
   AWS_REGION=your_aws_region
   S3_BUCKET_NAME=your_s3_bucket_name
   OPENAI_API_KEY=your_openai_api_key
   DG_API_KEY=your_deepgram_api_key
   

   Replace the placeholders with your actual credentials and settings.

Running the Backend

1. Start the Flask development server:

   python app.py
   

   The server will start on http://localhost:5001

Docker Setup

To run the backend using Docker:

1. Build the Docker image:

   docker build -t lunaris-backend .
   

2. Run the Docker container:

   docker run -p 8080:8080 --env-file .env lunaris-backend
   

   The server will be accessible at http://localhost:8080

Conda Environment Setup

To set up a Conda environment for the backend:

1. Create a new Conda environment:

   conda create -n lunaris python=3.11
   

2. Activate the environment:

   conda activate lunaris
   

3. Install Python dependencies:

   pip install -r requirements.txt
   

4. Install system dependencies:

   FFmpeg and ImageMagick are system-level dependencies. The installation method depends on your operating system:

   • On Ubuntu/Debian:

     sudo apt-get update
     sudo apt-get install ffmpeg imagemagick
     

   • On macOS (using Homebrew):

     brew install ffmpeg imagemagick
     

   • On Windows: Download and install FFmpeg from https://ffmpeg.org/download.html Download and install ImageMagick from https://imagemagick.org/script/download.php

   Alternatively, if you prefer using Conda for these dependencies:

   conda install -c conda-forge ffmpeg imagemagick
   

   Note: Using Conda for system packages may not always be ideal for production environments.

5. Run the backend server:

   python app.py
   

Additional Information

• The frontend is built with Next.js and uses Tailwind CSS for styling.
• The backend uses Flask and integrates with various AI services for video processing.
• Make sure to set up the necessary cloud services (MongoDB, AWS S3, OpenAI, Deepgram) before running the application.
• For production deployment, consider using a process manager like PM2 for the backend and a production-ready server for the frontend.

Contributing

Please read our Contributing Guidelines for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.