Langchain multi agents. Contribute to langchain-ai/langgraph development by creating an account on GitHub. For economic viability, multi-agent systems require tasks where the value of the task is high enough to pay for the increased performance. This guide covers the following: In this tutorial, we'll explore how to implement a multi-agent network using LangGraph. By the end of the tutorial you will: First, let's install required packages and set our API keys. Dec 29, 2024 · LangChain simplifies the implementation of multi-agent systems by providing a flexible framework for building and managing autonomous agents. Apr 29, 2025 · At the heart of this evolution lies LangChain, a powerful framework redefining the way developers build, orchestrate, and scale multi-agent systems. Jun 22, 2025 · In this tutorial, we will build our own multi-agent framework (inspired by MetaGPT) using LangChain and its workflow orchestration toolkit LangGraph. May 1, 2024 · Collaborative Multi-Agents Much like human collaboration, different AI agents in a collaborative multi-agent workflow communicate using a shared scratchpad of messages. Jun 16, 2025 · Multi-agent systems work mainly because they help spend enough tokens to solve the problem…. The various AI agents could be based on the same LLM but in different roles. Each approach has distinct strengths A single agent might struggle if it needs to specialize in multiple domains or manage many tools. . In multi-agent systems, agents need to communicate between each other. I implement and compare three main architectures: Plan and Execute, Multi-Agent Supervisor Multi-Agent Collaborative. They do so via handoffs — a primitive that describes which agent to hand control to and the payload to send to that agent. I searched the LangChain documentation with the integrated search. Apr 18, 2025 · In this blog, we explored what an AI agent is, the key differences between single-agent and multi-agent workflows, and walked through practical examples using open-source models with the LangChain This project explores multiple multi-agent architectures using Langchain (LangGraph), focusing on agent collaboration to solve complex problems. We've added three separate example of multi-agent workflows to the langgraph repo. Jan 23, 2024 · Multi-agent designs allow you to divide complicated problems into tractable units of work that can be targeted by specialized agents and LLM programs. In this tutorial, you will build a supervisor system with two agents — a research and a math expert. Matching single agent performance Why don’t swarm and supervisor perform as well as single agent when there is a single distractor domain? Author: Sungchul Kim Peer Review: Proofread : Juni Lee This is a part of LangChain Open Tutorial Overview In this tutorial, we will explore the existing supervisor with tool-calling , hierarchical , and custom multi-agent workflow structures, following the previous tutorial. A multi-agent network is an architecture that leverages a "divide-and-conquer" approach by breaking LangGraph provides control for custom agent and multi-agent workflows, seamless human-in-the-loop interactions, and native streaming support for enhanced agent reliability and execution. In this tutorial, we'll explore how to build a multi-agent system using LangGraph , efficiently coordinate tasks between agents, and manage them through a Supervisor . Here, we introduce how to manage agents through LLM-based Supervisor and coordinate the entire team based on the results of each agent node. Sep 10, 2024 · In this tutorial, we will explore how to build a multi-agent system using LangGraph within the LangChain framework to get a better… May 9, 2024 · How to Build the Ultimate AI Automation with Multi-Agent Collaboration Assaf Elovic, Head of R&D at Wix, walks through how to build an autonomous research assistant using LangGraph with a team of specialized agents. Jan 30, 2024 · Checked other resources I added a very descriptive title to this question. Every agent within a GPTeam simulation has their own unique personality, memories, and directives, leading to interesting emergent behavior as they interact. Build resilient language agents as graphs. To tackle this, you can break your agent into smaller, independent agents and composing them into a multi-agent system. Jun 5, 2023 · On May 16th, we released GPTeam, a completely customizable open-source multi-agent simulation, inspired by Stanford’s ground-breaking “ Generative Agents ” paper from the month prior. This allows each agent to view other agents’ work and observe all the individual steps taken. We would like to explore performance on questions that require multiple sub agents. I used the GitHub search to find a similar question and Jun 10, 2025 · Multi-hop across agents Right now, all questions only require a single sub agent to respond. Multi-agent architectures effectively scale token usage for tasks that exceed the limits of single agents. Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. xhgq dcxr jdkxo tahdw dbkueuwg zankxj gdrkl ttmfpg nsiu tyjjn