How RAG Duplicate Context Detection Works: Optimizing Token Costs

Learn how PromptImageLab detects redundant and duplicate chunks in RAG retrieval pipelines using semantic vector cosine similarity and Jaccard token overlap metrics.

Vector database queries in Retrieval-Augmented Generation (RAG) systems frequently return multiple near-identical chunks from different document versions or overlapping chunking boundaries. Feeding duplicate context into LLMs wastes 30-50% of the token budget and degrades model reasoning performance.