Understanding AutoGPT and LLM Agent Development

Understanding AutoGPT and LLM Agent Development

In the past two weeks, projects like AutoGPT and BabyAGI have gained immense popularity. I spent some time over the weekend reviewing the code of these AI agent projects and decided to write an article summarizing my technical insights and thoughts on the current advancements in this field for everyone to discuss. From Language Understanding … Read more

Mastering LangGraph-Memory: A Comprehensive Guide

Mastering LangGraph-Memory: A Comprehensive Guide

LangGraph allows you to easily manage conversation memory in graphs. These operational guides demonstrate how to implement various strategies for this. Managing Conversation History One of the most common use cases for persistence is using it to track conversation history. It makes continuing conversations easier. However, as conversations get longer, this conversation history accumulates and … Read more

Creating an Agent with LangGraph and Search Tools

Creating an Agent with LangGraph and Search Tools

In this tutorial, we will learn how to build an intelligent dialogue agent with memory capabilities using LangGraph and LangChain. This agent can use search tools to answer questions and maintain the continuity of conversations. 1. Obtain API Key for Search Tool Log in to the search tool website: <span>https://tavily.com/</span>, generate an API key as … Read more

Mastering LangGraph Tools: Configuring Parameters

Mastering LangGraph Tools: Configuring Parameters

How to Pass Config to the Tools At runtime, we may need to pass values to the tools, such as user ID. For security reasons, this value should be set by application logic rather than controlled by the LLM. The LLM should only manage its expected parameters. The LangChain tools use the Runnable interface, where … Read more

Differences Between LangChain and LangGraph

Differences Between LangChain and LangGraph

In the field of large models, LangChain and LangGraph are two frameworks that have attracted considerable attention. Both aim to help developers build applications using large language models (LLMs), but they differ significantly in design philosophy, architecture, functionality, and applicable scenarios. 1. Introduction to LangChain LangChain is a framework for developing applications powered by large … Read more

Enhancing RAG Effectiveness with LangChain and LangGraph

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

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

Building an AI Coding Agent with LangGraph Using LangChain

Building an AI Coding Agent with LangGraph Using LangChain

● 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

LangGraph | Beginner’s Guide

LangGraph | Beginner's Guide

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

Multi-Agent Workflow with LangGraph

Multi-Agent Workflow with LangGraph

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