AI AGENTS

Langroid

by Langroid

agentsource:langroid.github.iopythonmulti-agentllmagentsragtool-callingorchestrationagent-frameworktask-delegationopen-source

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Overview

Python framework for multi-agent LLM programming with Agent and Task abstractions, tool/function calling, RAG, and orchestration.

Details

Langroid is a Python framework for building LLM-powered applications, described in its official sources as intuitive, lightweight, and extensible. It focuses on multi-agent LLM programming with first-class Agent and Task abstractions. The documentation includes quick-start material for a simple chat agent and a multi-agent task delegation guide, where ChatAgent and Task abstractions are used to decompose applications into tasks with different skills, tools, vector stores, or LLM access.

When to Use

Build Python LLM applications that need explicit Agent and Task abstractions. Decompose an application into multiple collaborating tasks with different skills, tools, vector stores, or LLM access. Prototype chat-agent workflows using the official quick-start examples.

Getting Started

Read the official documentation at https://langroid.github.io/langroid/.
Install the Python package using the PyPI project page instructions at https://pypi.org/project/langroid/.
Follow the simple chat-agent quick start in the Langroid documentation.
Review the multi-agent task delegation guide to understand ChatAgent and Task-based decomposition.
Use the GitHub repository at https://github.com/langroid/langroid for source code and project context.

Key Features

•First-class Agent and Task abstractions for LLM applications.
•Multi-agent collaboration through task delegation.
•Tool/function calling support.
•RAG support, including use with vector stores.
•Quick-start documentation for simple chat-agent workflows.

Capabilities

•multi-agent LLM programming
•agent/task abstraction
•task delegation
•tool/function calling
•RAG
•chat-agent workflows

Last updated Jun 12, 2026