Mastering LangGraph: Controllability 02

Mastering LangGraph: Controllability 02

Map-reduce operations are crucial for efficient task decomposition and parallel processing. This method involves breaking down tasks into smaller sub-tasks, processing each sub-task in parallel, and aggregating the results of all completed sub-tasks. Consider this example: Given a general topic from the user, generate a list of related topics, create a joke for each topic, … Read more

Mastering LangGraph Persistence

Mastering LangGraph Persistence

LangGraph Persistence allows for easy state persistence between graph execution (thread-level persistence) and threads (cross-thread persistence). This tutorial demonstrates how to add persistence to a graph. LangGraph has a built-in persistence layer that is implemented through checkpoints. When compiling a graph with a checkpoint, the checkpoint saves a snapshot of the graph’s state at each … Read more

Detailed Explanation of Event Streams and Node Return Values in LangGraph

Detailed Explanation of Event Streams and Node Return Values in LangGraph

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

AI Travel Assistant Built on LangGraph: AI-Travel-Agent

AI Travel Assistant Built on LangGraph: AI-Travel-Agent

An AI travel assistant built on LangGraph: ai-travel-agent, which can search for flights, book hotels, and organize itineraries to email you. It has a memory capability, able to remember user interaction history and continue from where the last conversation left off. It adopts a human-machine collaboration model, allowing users to control key operations, such as … Read more

Exploring LangGraph: A New Path for AI Agent Building

Exploring LangGraph: A New Path for AI Agent Building

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

Dissecting the Design and Technical Details of Multi-Agent Projects Based on LangGraph

Dissecting the Design and Technical Details of Multi-Agent Projects Based on LangGraph

Andrew Ng recently said in his public lecture: I believe that AI Agent workflows will drive significant advances in artificial intelligence this year, possibly surpassing the next-generation foundational models. This is an important trend, and I urge everyone working in AI to pay attention to it. Coupled with the four paradigms for implementing Agent workflows … Read more

Building a Memory Chatbot Using LangGraph

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

Comprehensive Guide to Creating Multi-Agent Methods in Langgraph

Comprehensive Guide to Creating Multi-Agent Methods in Langgraph

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

Building Agentic Workflows Using LangGraph

Building Agentic Workflows Using LangGraph

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