Accelerate building AI applications with Cloud Run

Step-by-Step Tutorial: Accelerate Building AI Applications with Cloud Run

Introduction:

1. Welcome and Overview:
   • Watch the video titled "Accelerate Building AI Applications with Cloud Run" from the channel Google Cloud Tech.

Cloud Run Overview:

1. Understanding Cloud Run:
   • Cloud Run allows you to run backend code written in any language and supports running AI workloads.
   • Cloud Run offers a serverless environment that handles autoscaling and performance monitoring out of the box.

Cloud Run Services and Jobs:

1. Differentiating Services and Jobs:
   • Cloud Run services follow request-driven scaling and can handle various trigger sources like HTTP2, gRPC, events, and websockets.
   • Cloud Run jobs run a container to completion and can be executed manually or automatically on a schedule.

Autoscaling and Pricing Options:

1. Utilizing Autoscaling:
   • Cloud Run automatically scales instances based on incoming traffic and CPU utilization.
   • You can set minimum instances to improve latency and pay for them at a reduced rate.

Demo 1 - Incorporating Gemini into a Chatbot App:

1. Setting Up the Chatbot App:
   • Create an Express app with WebSocket functionality for chat interactions.
   • Include references to the Vertex AI client library for connecting to Gemini APIs.

Demo 2 - Using Function Calling with Gemini:

1. Implementing Function Calling:
   • Define a function in the chatbot app that interacts with Gemini for real-time data retrieval like weather information.
   • Modify the WebSocket event handler to handle function calls and responses from Gemini.

Demo 3 - Using Vertex AI APIs for Specific Tasks:

1. Processing Video Scenes:
   • Set up a Cloud Run job to process a video using Vertex AI APIs to generate visual captions for each scene.
   • Use the Video Intelligence API for scene change detection and the Image Text Model for image captioning.

Conclusion:

1. Key Takeaways:
   • Cloud Run simplifies autoscaling and allows you to focus on coding AI applications efficiently.
   • Explore the possibilities of incorporating Gemini, function calling, and specialized Vertex AI APIs for your projects.

Additional Resources:

1. Further Learning:
   • Access the codelabs corresponding to each demo for detailed step-by-step instructions.
   • Explore the provided QR codes for additional resources and hands-on tutorials.

By following these steps, you can accelerate building AI applications with Cloud Run and leverage its capabilities for your projects.