How to Build a Freshness Gate in Python to Filter Stale RAG Documents

Retrieval-augmented generation (RAG) systems can surface outdated documents that match a query but are no longer approved for current use, posing a reliability risk in AI-generated responses. A freshness gate addresses this by checking retrieved documents against three criteria: whether the revision is currently approved, whether the document is already in effect, and whether its review deadline has passed. The gate is implemented in Python 3.12 using only the standard library, with timezone-aware UTC timestamps to ensure reproducible and consistent evaluation. Authority over which revision is approved must come from an external revision register, not inferred by the model from filenames or document text. This approach narrows the gate to a specific policy use case — answering questions about currently approved material — and does not validate factual accuracy.