Implements advanced Self-RAG and Corrective-RAG architectures for self-correcting AI retrieval systems.
Agentic RAG Patterns provides a comprehensive framework for building sophisticated retrieval-augmented generation pipelines using LangGraph. It enables Claude to implement adaptive retrieval strategies, including document grading, query rewriting, and web-search fallbacks (CRAG). This skill is essential for developers building production-grade AI agents that need to verify information quality, handle insufficient data gracefully, and reduce hallucinations through multi-step reasoning and recursive feedback loops.
主な機能
01Knowledge Graph integration for entity-rich retrieval
02Corrective-RAG (CRAG) with automated web search fallback
03Self-correcting retrieval workflows using LangGraph 1.0.6
04Query transformation and adaptive re-writing logic
0569 GitHub stars
06Automated document grading for relevance verification
ユースケース
01Developing research agents that fallback to web search when internal data is insufficient
02Implementing complex data pipelines requiring multi-step reasoning and state management
03Building a customer support bot that validates source documents before answering
