rag-data-pipeline

Use when designing, building, or debugging a RAG (Retrieval-Augmented Generation) data pipeline — document ingestion, chunking strategies (fixed/recursive/semantic/structure-aware), embedding models (OpenAI/Cohere/sentence-transformers), vector stores (pgvector/Chroma/Qdrant/Weaviate), incremental refresh, hybrid retrieval (dense + BM25 + RRF), re-ranking with cross-encoders, metadata filtering, and production…