🔗 Building LLM-powered applications in Go - The Go Programming Language

As the capabilities of LLMs (Large Language Models) and adjacent tools like embedding models grew significantly over the past year, more and more developers are considering integrating LLMs into their applications.

Since LLMs often require dedicated hardware and significant compute resources, they are most commonly packaged as network services that provide APIs for access. This is how the APIs for leading LLMs like OpenAI or Google Gemini work; even run-your-own-LLM tools like Ollama wrap the LLM in a REST API for local consumption. Moreover, developers who take advantage of LLMs in their applications often require supplementary tools like Vector Databases, which are most commonly deployed as network services as well.

In other words, LLM-powered applications are a lot like other modern cloud-native applications: they require excellent support for REST and RPC protocols, concurrency and performance. These just so happen to be the areas where Go excels, making it a fantastic language for writing LLM-powered applications.

This blog post works through an example of using Go for a simple LLM-powered application. It starts by describing the problem the demo application is solving, and proceeds by presenting several variants of the application that all accomplish the same task, but use different packages to implement it. All the code for the demos of this post is available online.

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