ByteCast - Live Streaming Platform

A live streaming platform similar to Twitch, built with C# .NET 9 backend and React/TypeScript frontend.

Prerequisites

Backend Requirements

• .NET 9 SDK
• PostgreSQL or SQL Server
• FFmpeg
• Redis (optional, for caching)

Frontend Requirements

• Node.js 18+
• npm or yarn

Setup Instructions

1. Backend Setup

1. Install FFmpeg

   # Windows: Download from https://ffmpeg.org/download.html
   # macOS:
   brew install ffmpeg
   # Linux:
   sudo apt-get install ffmpeg

2. Configure Database

   • Update connection string in appsettings.json
   • Ensure PostgreSQL/SQL Server is running

3. Install Dependencies

   cd ByteCast
   dotnet restore

4. Build Project

   dotnet build

2. Frontend Setup

1. Navigate to Frontend Directory

   cd /Users/mac/Documents/Projects/Node/bytecast

2. Install Dependencies

   npm install

Running the Application

1. Start Backend

cd ByteCast
dotnet run

• API will run on: https://localhost:7001
• RTMP server will run on: rtmp://localhost:1935

2. Start Frontend

cd /Users/mac/Documents/Projects/Node/bytecast
npm run dev

• Frontend will run on: http://localhost:5173

Testing the Streaming

For Streamers:

1. Create an account through the frontend
2. Go to Studio page and create a new stream
3. Generate an API key for streaming
4. Configure OBS Studio:
   • Server: rtmp://localhost:1935/live
   • Stream Key: Your generated API key
5. Start streaming in OBS
6. View preview in Studio page
7. Click "Go Live" to make stream public

For Viewers:

1. Visit the home page to browse live streams
2. Click on any stream to watch
3. Login to participate in chat and social features

Architecture

• Backend: C# .NET 9 with SignalR, Entity Framework, integrated RTMP server
• Frontend: React/TypeScript with Vite, Tailwind CSS
• Streaming: RTMP ingestion with HLS conversion via FFmpeg
• Real-time: SignalR for chat, notifications, and live updates

Features

• Live streaming with RTMP/HLS
• Real-time chat and notifications
• User authentication and profiles
• Stream discovery and categories
• Social features (likes, comments, follows)
• Stream analytics and viewer tracking
• Anonymous stream viewing