langchain-patterns

id	SKL-langchain-LANGCHAINPATTERNS
name	Langchain Patterns
description	LangChain is a framework for building applications powered by LLMs. It helps manage the complexity of prompt chaining, memory, retrieval, agents, and tool use, making it faster to build AI application
version	1.0.0
status	active
owner	@cerebra-team
last_updated	2026-02-22
category	Backend
tags	["api","backend","server","database"]
stack	["Python","Node.js","REST API","GraphQL"]
difficulty	Intermediate

Langchain Patterns

Skill Profile

(Select at least one profile to enable specific modules)

• DevOps
• Backend
• Frontend
• AI-RAG
• Security Critical

Overview

LangChain is a framework for building applications powered by LLMs. It helps manage the complexity of prompt chaining, memory, retrieval, agents, and tool use, making it faster to build AI applications. This skill covers basic setup, structured output, RAG (Retrieval-Augmented Generation), conversational memory, agents with tools, streaming, document loaders, LangSmith integration for production monitoring, and production deployment patterns.

Why This Matters

LangChain is essential for production AI applications because:

• Abstraction: Unified interface for various LLM providers
• Composability: Chain components together easily
• RAG Ready: Built-in retrieval and vector store integrations
• Production: LangSmith for monitoring and debugging
• Ecosystem: Extensive library of integrations and tools

Core Concepts & Rules

1. Core Principles

• Follow established patterns and conventions
• Maintain consistency across codebase
• Document decisions and trade-offs

2. Implementation Guidelines

• Start with the simplest viable solution
• Iterate based on feedback and requirements
• Test thoroughly before deployment

Inputs / Outputs / Contracts

Skill Composition

• Depends on: None
• Compatible with: None
• Conflicts with: None
• Related Skills: None

Quick Start

Assumptions

• API keys are available in environment variables
• Vector database is configured and accessible
• Documents are in supported formats (PDF, CSV, text)