LangChain is a powerful library for Python and Javascript/Typescript that allows you to quickly prototype large language model applications. It allows you to chain together LLM tasks (hence the name) and even allows you to run autonomous agents quickly and easily. In this blog post, we’ll explore how to create agents and define custom tools that those agents can use. Prerequisites Python 3.9 3.10 and up have some issues with some of LangChain’s modules.

LangChain is a powerful library for Python and Javascript/Typescript that allows you to quickly prototype large language model applications. It allows you to chain together LLM tasks (hence the name) and even allows you to run autonomous agents quickly and easily. Today we will be going over the basics of chains, so you can hit the ground running with your newest LLM projects! Prerequisites Python 3.9 3.10 and up have some issues with some of LangChain’s modules.

Unlike OpenAI and Google, Meta is taking a very welcomed open approach to Large Language Models (LLMs). Similarly to Stability AI’s now ubiquitous diffusion models, Meta has released their newest LLM, Llama 2, under a new permissive license. This license allow for commercial use of their new model, unlike the previous research-only license of Llama 1. This means that anyone, anywhere can use Llama 2 to do whatever they want (provided that its legal in your jurisdiction).

OpenAI’s ChatGPT has revolutionized the way we interact with AI models, providing users with impressive language generation capabilities. To further enhance ChatGPT’s functionality, OpenAI has introduced ChatGPT Plugins, which are currently in closed alpha and may not be accessible to everyone. If you’re interested in gaining access, you can join the waitlist here. ChatGPT Plugins enable users to connect ChatGPT with third-party applications and APIs, extending its capabilities beyond the core model.

Let me get something out of the way: LTT getting hacked is what inspired me to write this. If you were not aware, Linus Tech Tips, one of YouTube biggest tech channels, was hacked. They made a video about the situation, but here is the TLDR: an employee received what they thought was a PDF from a legitimate sponsor for the channel. They downloaded the PDF, tried to open it, and when it didn’t open, went back to work.

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Those of you who know me well would know that I am a massive fan of Linux. I love the versatility and customization potential, and I think developing on the platform that most of my applications are going to be run on (as I develop a lot of backend applications) makes the most sense. However, at my current company, I was the only person using Linux, and I was curious as to why all the other developers choose to use macOS over any other development platform.