ModelRefs / Metadata Filtering — AI Glossary
Metadata Filtering — AI Glossary
Pre- or post-filtering retrieved documents by structured metadata fields (date, source, author, category) to improve precision.
Overview
Metadata filtering combines vector similarity search with structured constraints: 'find semantically similar chunks AND published after 2024 AND source=documentation'. Reduces the effective search space and prevents stale or off-topic chunks from polluting context. Supported by Pinecone, Weaviate, Qdrant, pgvector, and Chroma.
Reference details
| Topic | rag |
|---|---|
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is Metadata Filtering?
Pre- or post-filtering retrieved documents by structured metadata fields (date, source, author, category) to improve precision.
What concepts are related to Metadata Filtering?
Closely related concepts include namespace, dense retrieval, retrieval pipeline.