Definition
Deduplication in RAG pipelines is the process of identifying and removing redundant data chunks—using either cryptographic hashing for exact matches or semantic similarity for near-duplicates—to optimize vector store efficiency and prevent the LLM from processing repetitive context. Architecturally, it involves a trade-off between increased ingestion-time computational overhead and decreased inference-time token costs and noise.
Focuses on content redundancy within vector databases and prompts, rather than block-level storage optimization in traditional file systems.
"A sieve that prevents identical or near-identical puzzle pieces from being added to a box, ensuring every piece retrieved adds unique value to the final image."
- Semantic Similarity(Mechanism)
- Chunking(Prerequisite)
- Vector Database(Component)
- Token Limits(Constraint)
Conceptual Overview
Deduplication in RAG pipelines is the process of identifying and removing redundant data chunks—using either cryptographic hashing for exact matches or semantic similarity for near-duplicates—to optimize vector store efficiency and prevent the LLM from processing repetitive context. Architecturally, it involves a trade-off between increased ingestion-time computational overhead and decreased inference-time token costs and noise.
Disambiguation
Focuses on content redundancy within vector databases and prompts, rather than block-level storage optimization in traditional file systems.
Visual Analog
A sieve that prevents identical or near-identical puzzle pieces from being added to a box, ensuring every piece retrieved adds unique value to the final image.