AI Agent 
LangGraph provides a hands-on approach to how humans can interact with agents. `LangGraph` is a library for building stateful, multi-participant applications using `LLM`, designed for creating agent and multi-agent workflows. Compared to other `LLM` frameworks, it has the following core advantages: loops, controllability, and persistence. `LangGraph` allows you to define processes that involve loops, which … Read more
How to Obtain 1. Follow the public account below, and click【Like】 and 【Looking】 2. Reply to the public account with【Course】】 to get this course This course is about Getting Started with LangGraph for Large Model Agents Getting Started with LangGraph for Large Model Agents Getting Started with LangGraph for Large Model Agents LangGraph, as a … Read more
Introduction In the field of artificial intelligence, Retrieval-Augmented Generation (RAG) systems have become common tools for handling simple queries and generating contextually relevant responses. However, with the growing demand for more complex AI applications, we need to go beyond these retrieval-capable systems. Thus, AI agents have emerged—these autonomous entities can perform complex multi-step tasks while … Read more
The human-computer interaction feature allows us to involve the user in the decision-making process of the graph. The following guide demonstrates how to implement human-computer interaction workflows in the graph. The human-computer interaction workflow integrates user input into automated processes, allowing for decision-making, validation, or correction at critical stages. This is particularly useful in applications … Read more
In this tutorial, we will learn how to build an intelligent document retrieval system using langgraph. This system can extract information from web pages, perform intelligent segmentation, and achieve precise Q&A functionality through query analysis and vector retrieval. 1. Install Dependencies <span>pip install beautifulsoup4</span> 2. Import Necessary Libraries import bs4 from typing import Literal from … Read more
Utilize LangChain, LangGraph, and Yahoo Finance to build a stock performance analysis agent. Long press to follow “AI Technology Forum” AI Empowered Stock Analysis In stock trading, investors rely on various tools and methods to make informed decisions. One method is fundamental analysis, which provides operational advice by evaluating a company’s financials against stock performance. … Read more
In this article, we will explore how to build a powerful document summarization system using LangChain and LangGraph. This system can handle long texts by chunking, parallel processing, and recursively merging to finally generate a coherent summary. 0. Short Text Summarization When the tokens are sufficient to accommodate the document, no document segmentation is necessary, … Read more
In this blog, we will delve into how to build an intelligent SQL query assistant using LangChain and LangGraph. This assistant can convert natural language questions into SQL queries, execute the queries, and provide human-friendly answers. More importantly, it supports human-machine collaborative workflows, allowing users to intervene at critical steps. 0. Initialize SQL Data We … Read more
An agent is a system that uses LLM to determine the control flow of applications. As you develop these systems, they may become more complex over time, making them harder to manage and scale. For example, we may encounter the following issues: There are too many tools that agents can use, making it overly complex … Read more
How to Pass Private Data Between Nodes In some cases, you may want nodes to exchange information that is crucial to the intermediate logic but does not need to be part of the main architecture of the graph. This private data is unrelated to the overall input/output of the graph and should only be shared … Read more