langroid

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Langroid is an intuitive, lightweight, extensible and principled Python framework to easily build LLM-powered applications, from 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. This Multi-Agent paradigm is inspired by the Actor Framework (but you do not need to know anything about this!).

Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain, or any other LLM framework, and works with practically any LLM.

:fire: Read the (WIP) overview of the langroid architecture, and a quick tour of Langroid.

:fire: MCP Support: Allow any LLM-Agent to leverage MCP Servers via Langroid's simple MCP tool adapter that converts the server's tools into Langroid's ToolMessage instances.

📢 Companies are using/adapting Langroid in production. Here is a quote:

Nullify uses AI Agents for secure software development. It finds, prioritizes and fixes vulnerabilities. We have internally adapted Langroid's multi-agent orchestration framework in production, after evaluating CrewAI, Autogen, LangChain, Langflow, etc. We found Langroid to be far superior to those frameworks in terms of ease of setup and flexibility. Langroid's Agent and Task abstractions are intuitive, well thought out, and provide a great developer experience. We wanted the quickest way to get something in production. With other frameworks it would have taken us weeks, but with Langroid we got to good results in minutes. Highly recommended!
-- Jacky Wong, Head of AI at Nullify.

:fire: See this Intro to Langroid blog post from the LanceDB team

:fire: Just published in ML for Healthcare (2024): a Langroid-based Multi-Agent RAG system for pharmacovigilance, see blog post

We welcome contributions: See the contributions document for ideas on what to contribute.