RAG Implementation

Master Retrieval-Augmented Generation (RAG) to build LLM applications that provide accurate, grounded responses using external knowledge sources.

Use this skill when

• Building Q&A systems over proprietary documents
• Creating chatbots with current, factual information
• Implementing semantic search with natural language queries
• Reducing hallucinations with grounded responses
• Enabling LLMs to access domain-specific knowledge
• Building documentation assistants
• Creating research tools with source citation

Do not use this skill when

• You only need purely generative writing without retrieval
• The dataset is too small to justify embeddings
• You cannot store or process the source data safely