Streamlining Video Uploads with Rust & AWS | Automating YouTube with AI Tools - Episode 198
3In this video, I dive into enhancing my automated video processing pipeline for uploading streams to YouTube using Rust and AWS. Specifically, I work on improving the Glowing Telegram project, a tool I’m building to streamline video creation and automate complex tasks like uploading videos, generating metadata, and handling authentication.
I explore strategies for refining the app context initialization process, leveraging AWS services like DynamoDB, S3, Secrets Manager, and Batch to manage video data and infrastructure. This includes setting up JSON schemas for database records, creating reusable Rust crates, and ensuring proper integration of application configurations. Alongside this, I discuss generating TypeScript and Rust types from JSON schemas to simplify development.
AI plays a critical role in this project, with features like OpenAI Whisper for video transcription and GPT-4 integration to generate YouTube titles and descriptions based on video content. I showcase my custom admin interface, where I analyze transcript-driven insights, create video episodes, and manage uploads, paving the way for a fully AI-driven workflow.
For now, I focus on ensuring smooth configuration and support for user-specific behaviors, such as attaching user credentials for uploading videos to YouTube. This project continues to evolve as I tackle challenges like playlist automation, video tagging, and system authorization while maintaining a user-friendly pipeline.
🛠 Tech Stack: Rust, TypeScript, Docker, AWS (S3, DynamoDB, Batch, Lambda), FFmpeg, GPT-4, Whisper.
🔗 Check out my Twitch channel for more streams: https://www.twitch.tv/saebyn
GitHub: https://github.com/saebyn
Discord: https://discord.gg/N7xfy7PyHs