Podcast Marketing Automation SaaS

A comprehensive, AI-driven solution designed to streamline the entire podcast production and marketing workflow.

Features

• User-friendly dashboard for podcast management
• AI-powered transcription and content analysis
• Automated marketing content generation
• Social media integration and scheduling
• Real-time analytics and performance tracking

Technology Stack

• Frontend: React with TypeScript
• Backend: Django with Python 3.9+
• Database: PostgreSQL
• Caching: Redis
• AI Services: Google Cloud Speech-to-Text, OpenAI GPT-3
• Cloud Infrastructure: AWS (EC2, RDS, S3, CloudFront, etc.)

Getting Started

Prerequisites

• Node.js 14+
• Python 3.9+
• Docker and Docker Compose
• AWS CLI configured with appropriate permissions

Installation

1. Clone the repository
2. Set up environment variables
3. Run docker-compose up to start the development environment

Project Structure

The src directory contains the main components of the project:

• api: Django backend API
• frontend: React frontend application
• mobile: React Native mobile application
• database: Database models and migrations
• shared: Shared types and utilities

Development

Running Tests

To run backend tests:

cd src/api
python manage.py test

To run frontend tests:

cd src/frontend
npm test

Code Style

We use ESLint and Prettier for JavaScript/TypeScript code formatting, and Black for Python code formatting. Please ensure your code adheres to these standards before submitting pull requests.

Deployment

Our CI/CD pipeline uses GitHub Actions for continuous integration and AWS CodePipeline for continuous deployment. The deployment process involves building Docker images, pushing them to ECR, and deploying to ECS.

Contributing

Please read our CONTRIBUTING.md file 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.