Introduction Langchain recently launched an impressive course focused on LangGraph and its key features in developing powerful agent and multi-agent workflows. In this series, we will explore the essential insights from the course and create applications that leverage agent workflows. In the first part, we will cover the basic concepts of LangGraph and how to … Read more
There are five ways to create multi-agents in Langgraph: Network: Each agent can communicate with all other agents, and all agents can decide which agent to call next. Supervisor: Each agent can communicate with a supervisor agent, which decides which agent to call next. Supervisor (tool-calling): This is a special case of the supervisor architecture … Read more
This article introduces how to build a memory chatbot using LangChain and LangGraph. LangGraph is a Python library developed by the LangChain team specifically for creating complex AI workflows and multi-agent systems that can remember state. Its core goal is to address key pain points in traditional AI orchestration: • Inability to handle complex decision … Read more
● Understand what LangGraph is. ● Explore the basics of LangGraph for building stateful agents. ● Explore TogetherAI to access open-access models like DeepSeekCoder. ● Build an AI coding agent using LangGraph to write unit tests. This article is published as part of the Data Science Blog Marathon. What is LangGraph? LangGraph is an extension … Read more
Click 01 Muggle Society Follow the official account, and you won’t get lost in AI learning LangGraph is an important feature recently released by LangChain, marking its move towards a multi-agent framework. LangGraph is built on top of LangChain, helping developers easily create powerful agent runtimes. LangChain and its expression language (LCEL) provide technical support … Read more
Introduction The emergence of large language models (LLMs) has reshaped how AI systems interact with and interpret the world. Traditionally, single-agent architectures have been used to handle inputs, make decisions, and produce outputs. However, as AI systems scale to manage more complex, multi-step tasks, researchers and developers are increasingly turning to multi-agent systems and advanced … Read more
Using ToolNode for tool calls ToolNode is a LangChain Runnable that takes a graphical state (with a list of messages) as input and outputs a state update using the results of tool calls. It is designed to work out of the box with LangGraph’s pre-built ReAct agent, but it can also work with any StateGraph … Read more
How to Add and Use Subgraphs Subgraphs allow the construction of complex systems with multiple components, each of which is a graph. A common use case for using subgraphs is building multi-agent systems. The main issue when adding subgraphs is how the parent graph and the subgraph communicate, i.e., how they pass state to each … Read more
▼Recently, there have been many live broadcasts,make an appointment to ensure you gain something —1— The Two Core Concepts of LangChain 1、Process-Oriented Architecture Design of Chains：Programs written based on large models that follow predefined steps and rules, which cannot be flexibly adjusted, used for executing tasks like: automatic SQL writing or multi-turn dialogue, etc. 2、Goal-Oriented … Read more
With the rapid development of large model technology, agent technology is increasingly applied in various fields, profoundly changing people’s work and lifestyle. In complex and dynamic system environments, multiple agents complete complex tasks that a single agent cannot accomplish through division of labor and collaboration. This article explores the comprehensive application of LangGraph and CrewAI. … Read more