Mastering LangGraph: Controllability 01

Mastering LangGraph: Controllability 01

LangGraph provides a high level of control over the execution of charts. How to Create Parallel Execution Branches The parallel execution of nodes is crucial for speeding up overall graph operations. LangGraph offers native support for parallel execution of nodes, which can significantly enhance the performance of graph-based workflows. This parallelization is achieved through fan-out … Read more

LangGraph Platform Business Model Overview

LangGraph Platform: Business Model Summary LangGraph is a platform for developing, deploying, and managing generative AI applications. Its core features revolve around the implementation of dynamic AI agents, including task queue management, API calls, storage and updating of conversation states and long-term memories. LangGraph supports everything from experimental applications by startup teams to enterprise-level large-scale … 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

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

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

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

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

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

LangGraph: A Framework for Developing Intelligent Agents Based on Graph Structures

LangGraph: A Framework for Developing Intelligent Agents Based on Graph Structures

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