corrective-rag

What problem does it solve?

This Skill addresses the unreliability of standard RAG systems by implementing a robust framework for validating retrieved information and automatically correcting errors, ensuring higher quality and more grounded AI responses.

Core Features & Use Cases

• Retrieval Validation: Assesses the relevance and accuracy of retrieved documents against the user's query.
• Fallback Strategies: Integrates web search as a fallback when initial retrieval is insufficient or incorrect.
• Self-Correction: Refines knowledge by extracting only pertinent information and generates answers based on validated and augmented data.
• Use Case: When building a customer support chatbot that must provide accurate product information, this skill ensures that the AI only uses verified data, falling back to a web search if internal knowledge is ambiguous or missing, and then synthesizing a precise answer.

Quick Start

Use the corrective-rag skill to answer the question "What is the latest LangChain version?"