Tagged articles

ToolCalling

3 articles · Page 1 of 1

Apr 25, 2026 · Artificial Intelligence

Analyzing the 2026 ReAct Agent Architecture: Native Tool Calling and LangGraph State Machine

This article walks through building a production‑ready ReAct loop in 2026, replacing fragile string‑based tool parsing with native JSON tool calls, persisting state via LangGraph and Postgres, structuring evidence collection, handling errors, and addressing loop‑termination and cost‑control challenges.

LLMLangGraphPython

0 likes · 19 min read

Analyzing the 2026 ReAct Agent Architecture: Native Tool Calling and LangGraph State Machine

Tech Ocean

Apr 23, 2026 · Artificial Intelligence

Day 7: LangChain Full‑Map Overview and 6 Interview Questions

This article presents a complete LangChain architecture diagram, quick‑reference tables for core modules, a side‑by‑side comparison with LlamaIndex and Haystack, practical interview Q&A covering advantages, RAG optimization, Agent vs Chain differences, token‑cost reduction, and a seven‑day recap with advanced learning paths.

AgentChainInterviewPrep

0 likes · 13 min read

Day 7: LangChain Full‑Map Overview and 6 Interview Questions

Alibaba Cloud Developer

Feb 24, 2026 · Artificial Intelligence

Master ReAct Agents: From Observation to Action with Real Code Examples

This article introduces the ReAct agent paradigm—combining reasoning and acting—explains its observation‑think‑act loop, showcases a step‑by‑step weather‑and‑clothing example, outlines essential components, provides pseudo‑code for the execution flow, and links to the Lynxe Func‑Agent framework on GitHub.

AgentLLMReact

0 likes · 11 min read

Master ReAct Agents: From Observation to Action with Real Code Examples