Cloud Run is an ideal platform for hosting AI applications – for example, you can use Cloud Run with AI frameworks like LangChain or Firebase Genkit to orchestrate calls to AI models on Vertex AI, vector databases, and other APIs. In this session, we’ll dive deep into building AI agents on Cloud Run to solve complex tasks and explore several techniques, including tool calling, multi-agent systems, memory state management, and code execution. We’ll showcase interactive examples using popular frameworks.

Developers love Cloud Run. In this demo-driven talk, you’ll discover why Cloud Run offers simplicity alongside flexibility for running your code. We’ll begin with a couple of basic getting-started concepts. Then we’ll go into “How do I” scenarios that cover every feature from Virtual Private Cloud (VPC) access to startup probes. Too much info? We’ll have codelabs for you to do at your own pace.

LangChain is the most popular open-source framework for building LLM-based apps. Google Cloud is the easiest place to deploy LangChain apps to production. In this session technical practitioners will learn how to combine LangChain on Cloud Run with Cloud SQL's pgvector for vector storage and Vertex Endpoints to create generative AI applications.

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