This guide introduces AgentScope, a multi‑agent framework for Java that brings ReAct reasoning, tool calling, memory management, RAG, and serverless capabilities to LLM‑powered applications, and provides step‑by‑step code examples for basic and advanced usage.
This article summarizes three cutting‑edge AI search and recommendation techniques—Alibaba Cloud's Agentic RAG architecture, Huawei's LLM‑enhanced recommendation system evolution, and Baidu's generative ranking model GRAB—detailing their challenges, design choices, performance gains, and practical deployment insights.
This article reviews the emerging field of large‑language‑model (LLM) based AI agents, outlining their overall architecture, core modules such as profiling, memory, planning and action, discussing current challenges, presenting concrete use‑cases, and highlighting promising research directions.
