I'm surprised by how uncommon SK is compared to LangChain. Microsoft is very active in the space and has a few other related LLM frameworks of different nature - Semantic Memory and Guidance.
Semantic Memory (renamed to Kernel Memory - https://github.com/microsoft/kernel-memory) complements SK. Guidance's features are being absorbed into SK, following the departure of that team from Microsoft. Additionally, we have TypeChat (https://github.com/microsoft/TypeChat), which aims to ensure type-safe responses from LLMs. Most features of Autogen are also being integrated into SK, along with Assistants. SK serves as the orchestration engine powering Microsoft Copilots.
We’ve been building the Langroid[1] Multi-Agent LLM framework, starting several months before AutoGen. Langroid has an elegant Inter-agent orchestration mechanism[2], among many other things. We’ve taken a measured approach to avoid bloat and excess abstractions (unlike that other framework that I won’t mention :) )
Langroid is an intuitive, lightweight, extensible and principled Python framework to easily build LLM-powered applications, from ex-CMU and UW-Madison researchers. You set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages.
Seems nice if you're using c# or java. It also supports python, but for that Simon's llm library is nice because he designed it as both a library and a command line tool: https://github.com/simonw/llm