langchain-architecture

Guide LLM application architecture with LangChain agents, chains, and memory.

5|Updated Dec 1, 2025

Search Tags:#langchain #llm #tooling #agents #memory #chains

One-click install

npx skills add https://github.com/zsutxz/ClaudeLearning --skill langchain-architecture-zsutxz

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: langchain-architecture
Source: https://github.com/zsutxz/ClaudeLearning/tree/main/.claude/skills/langchain-architecture
Command: npx skills add https://github.com/zsutxz/ClaudeLearning --skill langchain-architecture-zsutxz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Guides building sophisticated LLM applications using LangChain patterns—agents, memory, chains, and tool integration—reducing complexity in architecture decisions.

Core Features & Use Cases

Agents, including ReAct, OpenAI Functions, and memory-enabled patterns.
Chains (LLMChain, SequentialChain, RouterChain, MapReduce, etc.) for modular workflows.
Memory systems (ConversationBufferMemory, ConversationSummaryMemory, VectorStoreMemory).
Document processing pipelines and robust callback patterns.
Production-oriented patterns for tooling, tracing, and observability.

Quick Start

Initialize an OpenAI-based agent with memory and tools, then run a multi-step query to illustrate layered reasoning.