Build AI Generated Podcasts 5 - Deploying to AWS

In Part 5 of the AI-powered podcast series, we’ll be deploying our project to AWS and bringing it to life in the cloud. This final video will guide you through the steps necessary to set up your cloud environment, optimize model caching, and ensure efficient deployment using Nitric.

You'll learn how to configure AWS resources, deploy the AI models for high-performance audio generation, and monitor your cloud infrastructure effectively.

If you haven’t seen the previous videos, be sure to check them out to get up to speed with the setup and project architecture!

• Part 1: Python Project Setup
• Part 2: Create Resources
• Part 3: Batch Job & API Setup
• Part 4: Testing Locally

Resources

• Project Code: https://github.com/nitrictech/ai-podcast
• Nitric Docs: https://nitric.io/docs
• Install Nitric: https://nitric.io/docs/get-started/installation
• Suno’s Bark Model: https://github.com/suno-ai/bark

Asset links for video:

• Link to torch.dockerfile: https://github.com/nitrictech/ai-podcast/blob/main/torch.dockerfile
• Link to torch.dockerfile.dockerignore: https://github.com/nitrictech/ai-podcast/blob/main/torch.dockerfile.dockerignore

Stay Connected

🌐 Learn more and explore the Nitric docs: https://nitric.io ⭐️ Support us on GitHub by starring the Nitric repository: https://github.com/nitrictech/nitric 🧑‍💻 Join our community on Discord: https://nitric.io/chat 🔔 Don't forget to like, comment, and subscribe to our YouTube channel! https://www.youtube.com/@nitric_io

If you're interested in a bonus video on integrating LLMs like Llama 3.2 for generating podcast scripts, let me know in the comments! Alternatively, you can follow this guide: https://nitric.io/docs/guides/python/ai-podcast-part-2