semantic-kernel VS autogen

Compare semantic-kernel vs autogen and see what are their differences.

semantic-kernel

Integrate cutting-edge LLM technology quickly and easily into your apps (by microsoft)

autogen

A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap (by microsoft)
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semantic-kernel autogen
47 31
18,111 24,917
6.4% 10.8%
9.9 9.9
5 days ago 4 days ago
C# Jupyter Notebook
MIT License Creative Commons Attribution 4.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

semantic-kernel

Posts with mentions or reviews of semantic-kernel. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-04.

autogen

Posts with mentions or reviews of autogen. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-25.

What are some alternatives?

When comparing semantic-kernel and autogen you can also consider the following projects:

langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]

Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]

langchain - 🦜🔗 Build context-aware reasoning applications

SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.

guidance - A guidance language for controlling large language models.

haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]

AgentVerse - 🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation

private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks

dspy - DSPy: The framework for programming—not prompting—foundation models

langroid - Harness LLMs with Multi-Agent Programming