RAG

After splitting a document, not every chunk is worth keeping. Ads, nav bars, disclaimers, and duplicates are noise that pollutes retrieval. This walks rule-based, structural, semantic, and LLM filtering strategies, with a Java pipeline you can adapt.

• #RAG
• #Data Pipeline
• #Embedding

The first decision in RAG isn't picking a vector DB, it's what you store after chunking the PDF. Full-text ingestion and structured extraction are two completely different paths; data from a medical scenario makes this very clear.

• #RAG
• #LLM
• #Vector Database