Before diving deeper, let’s review some fundamental concepts:
Key Concepts
First, let’s talk about APIs (Application Programming Interface). In simple terms, an API is a way to expose methods, functions, and procedures from your application, independent of the programming language being used.
Next is the REST API concept, which is a method of exposing your API using HTTP verbs. As IT professionals, we hear these terms – HTTP, REST, API – almost daily, but we might not fully grasp their core concepts. Let me explain how they relate to software automation using AI.
HTTP (Hypertext Transfer Protocol) is fundamentally a way for two applications to communicate using text. This is its beauty – text serves as the basic layer of understanding between systems, meaning almost any system or programming language can produce a client or server that can interact via HTTP.
REST (Representational State Transfer) is a methodology for systems to communicate and either change or read the state of another system.
Levels of System Interaction
When implementing LLMs for system automation, we first need to determine our desired level of interaction. Here are several approaches:
- Human-like Interaction: An LLM can interact with your operating system using mouse and keyboard inputs, effectively mimicking human behavior.
- REST API Integration: Your application can communicate using HTTP verbs and the REST protocol.
- SDK Implementation: You can create a software development kit that describes your application’s functionality and expose this to the LLM.
The connection method will vary depending on your chosen technology. For instance:
- Microsoft Semantic Kernel allows you to create plugins that interact with your system through REST API, database, or SDK.
- Microsoft AI extensions require you to decide on your preferred interaction level before implementation.
- The Model Context Protocol is a newer approach that enables application exposure for LLM agents, with Claude from Anthropic being a notable example.
Implementation Considerations
When automating your system, you need to consider:
- Available Integration Options: Not all systems provide an SDK or API, which can limit automation possibilities.
- Interaction Protocol Choice: You’ll need to decide between REST API, HTTP, or Model Context Protocol.
This overview should help you understand the various levels of resolution needed to automate your application. What’s your preferred method for integrating LLMs with your applications? I’d love to hear your thoughts and experiences.