Click the “Blue Word” to Follow Us In today’s rapidly evolving AI field, building Agents (Which Multi-Agent Framework is Better? A Deep Dive into Five Popular Options) has become an important means of achieving automation and decision optimization. LangGraph, as a powerful tool, provides developers with an intuitive and efficient way to build AI Agents … Read more
Overview When building AI applications, we often need to handle complex workflows, including serial and parallel execution of multiple steps, state management, event notifications, etc. LangGraph provides a powerful event stream mechanism and a flexible node return value system to support these needs. This article will delve into the event streams and node return value … Read more
LangGraph is a library developed by LangChainAI for creating workflows for agents and multi-agent systems. It offers the following core advantages: cycles, controllability, and persistence, which undoubtedly reduce the workload for agent developers. This article will highlight the key points and usage methods of LangGraph from my perspective during the development process. Basic Introduction The … Read more
Introduction on how to use LangGraph to improve RAG. Long press to follow “Python Learning Base”, join the reader group, and share more wonderful content. 1. Introduction LangGraph is the latest member of the LangChain, LangServe, and LangSmith series, aimed at building generative AI applications using LLMs. Remember, all these are independent packages and must … Read more
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
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
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
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
● 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
▼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