#大模型应用开发
4 related articles
Deep Dives·2 min
How AI Agents Work: The Four Core Elements and ReAct Loop Decision-Making Mechanism Explained
Deep dive into AI Agent's four core elements (LLM, Tools, Prompts, Executor) and ReAct loop decision mechanism, with a weather query example walkthrough.
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Deep Dives·4 min
Agent Loop Core Mechanism Explained: Building a ReAct Loop from Scratch (With Debugging War Stories)
Deep dive into Agent Loop, the core mechanism of AI Agents, based on ReAct architecture. Covers Tool Call ID handling, context management, assistant message feedback, with full Python code and common bug fixes.
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Tutorials·1 min
LangGraph 1.0.5 Tutorial: Master AI Agent Orchestration & Multi-Agent Systems in Six Lessons
Complete guide to LangGraph 1.0.5 tutorial series covering durable execution, memory management, Human in the Loop, streaming, time travel, and multi-agent collaboration.
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Tutorials·4 min
Langmanus Multi-Agent Framework Deep Dive: Architecture Principles and Agent Extension in Practice
Deep dive into Langmanus multi-agent framework architecture, explaining LangGraph orchestration with Coordinator, Planner, Supervisor and execution agents, plus a hands-on guide to adding custom agents.
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