.01 Overview In the rapidly evolving field of artificial intelligence, Generative AI and Agentic AI are two highly regarded technologies. They not only operate independently in terms of functionality but also exhibit different advantages in application scenarios and industry demands. As we approach 2025, the demand for AI from enterprises and developers is gradually shifting … Read more
Aitrainee | Public Account: AI Progress Student 🌟AgentGPT allows you to configure and deploy autonomous AI Agents. It is an improved version of AutoGPT based on Langchain, requiring no deployment, and provides a website that can be used directly. The customized agents will attempt to achieve their goals by thinking about the tasks to complete, … Read more
Follow us on WeChat: “Full Stack AI Knowledge” Set as a “Star”, bringing you new insights every day When building smart agents, Phidata and Langchain are undoubtedly the focal points in the industry. Both aim to enhance the performance of large language models (LLMs), but each has its unique focus and advantages. This article provides … Read more
AliMei’s Introduction This article shares detailed development experience and best practices using the AI framework LangChain, Alibaba Cloud Tongyi large model, and AnalyticDB vector engine, taking the construction of an AIGC application ChatBot and AI Agent as examples to provide a reference for quickly implementing AIGC applications. Introduction On September 13, the Tongyi Qianwen large … Read more
With the rapid development of large model technology, how to fully utilize AI while ensuring data privacy has become a hot topic. Open-source local large language models (LLMs) are gradually becoming an important tool to solve this problem. Today, we will introduce a star-level open-source model—LLaMA2, and see how it seamlessly implements the “text to … Read more
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
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
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
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
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