building-rag-pipelines

What problem does it solve?

This Skill addresses the challenge of building robust and intelligent Retrieval-Augmented Generation (RAG) systems that can accurately answer questions from large document sets, adapt to new information, and operate with advanced reasoning capabilities.

Core Features & Use Cases

• Hybrid Search: Combines vector and keyword search for comprehensive retrieval.
• Reranking: Improves precision by re-evaluating search results.
• Agentic Patterns: Enables iterative reasoning and tool use for complex queries.
• Continuous Learning: Incorporates relevance feedback to improve over time.
• Use Case: Develop an AI assistant that can answer complex technical questions by querying internal documentation, code repositories, and system logs, providing precise and context-aware answers.

Quick Start

Design and implement a RAG pipeline that combines hybrid search and reranking for accurate document retrieval.