llm-app-patterns

Topics in the source

• 🤖 LLM Application Patterns
• When to Use This Skill
• 1. RAG Pipeline Architecture
• Overview
• 1.1 Document Ingestion
• 1.2 Embedding & Storage
• 1.3 Retrieval Strategies
• 1.4 Generation with Context

Production-ready patterns for building LLM applications, inspired by Dify and industry best practices. Use this skill when: Designing LLM-powered applications Implementing RAG (Retrieval-Augmented Generation) Building AI agents with tools Setting up LLMOps monitoring Choosing between agent architectures -- RAG (Retrieval-Augmented Generation) grounds LLM responses in your data. -- -- -- -- -- | Pattern | Use When | Complexity | Cost | | :------------------- | :--------------- | :--------- | :-------- | | Simple RAG | FAQ, docs search | Low | Low | | Hybrid RAG | Mixed queries | Medium | Medium | | ReAct Agent | Multi-step tasks | Medium | Medium | | Function Calling | Structured tools | Low | Low | | Plan-Execute | Complex tasks | High | High | | Multi-Agent | Research tasks | Very High | Very High | -- Dify Platform LangChain Docs LlamaIndex Anthropic Cookbook