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
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
In the field of artificial intelligence, knowledge base systems are one of the core components for building intelligent agents. CrewAI’s memory system provides a comprehensive and flexible knowledge management solution by combining RAG (Retrieval-Augmented Generation) technology with traditional database storage. This article will take you step-by-step through configuring the knowledge base using Crew.ai, … Read more
Click the blue text above to follow us 1. Introduction AI Agents development is a hot topic in the current software innovation field. With the continuous advancement of Large Language Models (LLMs), the integration of AI agents with existing software systems is expected to see explosive growth. With AI agents, we can accomplish tasks that … Read more
Introduction Recently, there have been many free APIs available, making it unnecessary to waste resources. To fully leverage the capabilities of large models, multi-agent systems are a great approach. Issue – Installation After a recommendation from Cursor, I chose CrewAI as my development object. However, I encountered issues during the installation of CrewAI and was … Read more
In the rapidly evolving field of AI, the ability to provide accurate, context-aware responses to user queries is a game changer. Retrieval-Augmented Generation (RAG) is a powerful paradigm that combines the retrieval of relevant information from external sources with the generative capabilities of large language models (LLMs). However, as queries become increasingly complex and diverse, … Read more
Large Language Models (LLMs) have made significant progress in the field of generative artificial intelligence, but they face the “hallucination” problem, which is the tendency to generate inaccurate or irrelevant information. This issue is particularly severe in high-risk applications such as medical assessments and insurance claims processing. To address this challenge, researchers from the University … Read more
Roaming RAG, as an innovative RAG technology, can be elaborated on in detail regarding its characteristics and advantages from the following aspects: Working Principle and Process The core of Roaming RAG lies in utilizing the hierarchical structure of documents to enhance the information retrieval capabilities of large language models (LLMs). The specific process includes: Document … Read more
Are you still troubled by the mixed quality of AI in China and its poor performance? Then let’s take a look at Developer Cat AI (3in1)! This is an integrated AI assistant that combines GPT-4, Claude3, and Gemini. It covers all models of the three AI tools. Including GPT-4o and Gemini flash Now you can … Read more
Click 👇🏻 to follow, article from “ With the expanding application of large language models (LLMs), Retrieval-Augmented Generation (RAG) has become a mature technology. The popularity of products like txt2sql and ChatBI highlights the increasing importance of query construction techniques. This article analyzes the process of query construction and illustrates, through examples, how to transform … Read more