LaVague VS autogen

Compare LaVague vs autogen and see what are their differences.

LaVague

Large Action Model framework to turn natural language into browser actions (by lavague-ai)

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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LaVague autogen
4 32
3,965 25,506
13.4% 7.7%
9.5 9.9
1 day ago 3 days ago
Python Jupyter Notebook
Apache License 2.0 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.

LaVague

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

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 2024-05-02.

What are some alternatives?

When comparing LaVague and autogen you can also consider the following projects:

skyvern - Automate browser-based workflows with LLMs and Computer Vision

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

mergekit - Tools for merging pretrained large language models.

semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps

lorabridge - Long-Range Data Bridge (LoRaBridge) project repository

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

flink-sql-lineage - The Lineage Analysis system for FlinkSQL supports advanced syntax such as Watermark, UDTF, CEP, Windowing TVFs, and CTAS.

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.

spring-ai - An Application Framework for AI Engineering

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

langchain - 🦜🔗 Build context-aware reasoning applications

langroid - Harness LLMs with Multi-Agent Programming