Voster - AI-Powered Video Distribution Platform

Voster is a modern web application that simplifies video distribution across multiple social media platforms using AI. It automatically transcribes video content, generates platform-specific descriptions, and allows for seamless publishing to various social media platforms.

Features

• Video Upload & Management: Easily upload and manage your video content.
• AI Transcription: Automatic video transcription powered by AssemblyAI.
• Smart Description Generation: Generate optimized descriptions for each platform using Llama on Groq.
• Multi-Platform Publishing: Distribute your content to multiple social platforms from a single dashboard.
• Real-time Processing: Track the status of your video processing in real-time.

Technology Stack

• Frontend: Next.js, React, TypeScript, TailwindCSS
• Backend: Next.js API Routes
• Database: GibsonAI Cloud Database
• AI Services:
  • AssemblyAI for video transcription
  • Llama on Groq for description generation
• Deployment: Vercel

Getting Started

Prerequisites

• Node.js (v16+)
• npm or yarn
• GibsonAI Cloud Database credentials
• AssemblyAI API key
• Groq API key

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/voster.git
   cd voster

2. Install dependencies:

   npm install
   # or
   yarn install

3. Create a .env.local file in the root directory with the following environment variables:

   # API Keys
   ASSEMBLYAI_API_KEY=your_assemblyai_api_key
   GROQ_API_KEY=your_groq_api_key
   
   # GibsonAI Cloud Database
   GIBSON_API_URL=your_gibson_api_url
   GIBSON_API_KEY=your_gibson_api_key
   
   # App Configuration
   NEXT_PUBLIC_API_URL=http://localhost:3000
   

4. Start the development server:

   npm run dev
   # or
   yarn dev

5. Open http://localhost:3000 in your browser.

Project Structure

voster/
├── public/            # Static assets
│   └── uploads/       # Uploaded videos
├── src/
│   ├── app/           # App router pages
│   │   ├── api/       # API routes
│   │   ├── dashboard/ # Dashboard page
│   │   ├── upload/    # Upload page
│   │   └── videos/    # Video detail pages
│   ├── components/    # Reusable components
│   ├── lib/           # Utility functions and API clients
│   ├── styles/        # Global styles
│   └── types/         # TypeScript type definitions
├── next.config.js     # Next.js configuration
└── tailwind.config.js # TailwindCSS configuration

API Endpoints

Video Management

• POST /api/videos/upload - Upload a new video
• GET /api/videos - Get all videos for a user
• GET /api/videos/:id - Get a specific video
• DELETE /api/videos/:id/delete - Delete a video

Social Publishing

• POST /api/videos/:id/publish - Publish a video to a social platform

Webhooks

• POST /api/webhooks/transcription - Webhook for AssemblyAI transcription completion

Workflow

1. Upload: Users upload their video through the upload page.
2. Processing: The video is stored, and audio is extracted for transcription.
3. Transcription: The audio is sent to AssemblyAI for transcription.
4. Description Generation: Once transcribed, the text is sent to Llama on Groq to generate platform-specific descriptions.
5. Publishing: Users can review generated descriptions and publish to selected platforms.

Development

Adding a New Social Platform

1. Add the platform to the Platform enum in src/types/index.ts.
2. Implement the platform-specific publishing logic in the API service.
3. Update the UI components to include the new platform.

Custom Description Templates

Description templates for each platform can be modified in the Groq prompt within src/lib/groq.ts.

License

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

Acknowledgements

• AssemblyAI for providing transcription services
• Groq for powering the description generation with Llama
• Next.js for the React framework
• TailwindCSS for styling