Free open-source framework gives Go developers a unified generation API, native vector database support, and composable abstractions that simplify the development of AI workflows. Credit: monticello / Shutterstock Google has unveiled Genkit for Go, an open-source framework for building AI-powered applications and cloud services natively in Go. The project is a collaboration between Google’s Firebase and Go language teams. Introduced July 17 and currently in an alpha state, Genkit for Go enables developers to build generative AI applications by combining Go’s performance and concurrency advantages with Genkit’s libraries and tools. Potential use cases include intelligent assistants that understand complex requests, customer support agents using retrieval-augmented generation (RAG), and data transformation tools that convert unstructured data such as natural language into structured formats (SQL, queries, tables) for deeper analysis. A guide to getting started with Genkit for Go can be found at firebase.google.com. Genkit for Go follows the May introduction of Firebase Genkit for Node.js, for JavaScript and TypeScript developers. Genkit provides lightweight, composable abstractions to simplify development of sophisticated AI workflows without sacrificing control and customizability, Google said. The framework features: A unified generation API, for generating content from models such as Gemini or Gemma via a single interface. Flows for AI workflows, providing functions offering built-in observability for monitoring and debugging. Native vector database support, to make AI models context-aware by integrating RAG into applications with indexing and retrieval APIs working across database providers. Dotprompt, a file format to streamline the prompt engineering process. Genkit for Go is billed as a lightweight, provider-agnostic framework. A collection of plugins is offered to integrate with specific models, vector databases, and cloud services from Google and third-party providers. The Genkit CLI and browser-based developer UI offer a toolkit to streamline generative AI development. Developers using Microsoft’s Visual Studio Code editor or Google’s Project IDX cloud IDE can open the Genkit developer UI in the IDE’s integrated browser, for use side-by-side with code. Developers can file issues and feature requests for Genkit for Go on GitHub. Google on July 17 also rolled out other tools including Project Oscar, a reference architecture for an AI agent. Related content feature What is Rust? Safe, fast, and easy software development Unlike most programming languages, Rust doesn't make you choose between speed, safety, and ease of use. Find out how Rust delivers better code with fewer compromises, and a few downsides to consider before learning Rust. By Serdar Yegulalp Nov 20, 2024 11 mins Rust Programming Languages Software Development how-to Kotlin for Java developers: Classes and coroutines Kotlin was designed to bring more flexibility and flow to programming in the JVM. Here's an in-depth look at how Kotlin makes working with classes and objects easier and introduces coroutines to modernize concurrency. By Matthew Tyson Nov 20, 2024 9 mins Java Kotlin Programming Languages news F# 9 adds nullable reference types Latest version of Microsoft’s functional .NEt programming language provides a type-safe way to handle reference types that can have null as a valid value. By Paul Krill Nov 18, 2024 3 mins Microsoft .NET Programming Languages Software Development news Go language evolving for future hardware, AI workloads The Go team is working to adapt Go to large multicore systems, the latest hardware instructions, and the needs of developers of large-scale AI systems. By Paul Krill Nov 15, 2024 3 mins Google Go Generative AI Programming Languages Resources Videos