JetBrains explains how Air Context stores and retrieves code vectors
Overview
JetBrains explains in its AI blog how Air Context stores millions of code vectors in approximate nearest-neighbor indexes and retrieves them in milliseconds.
The post, the second in a series, compares pre-filtering, filtered ANN and post-filtering for enforcing repository, branch and permission constraints, and describes updating the indexes incrementally as commits land.
Air Context is in public preview and included with JetBrains AI subscriptions, according to the post.
Written by AI from the articles below · updated Nov 5, 11:07 AM ET
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- JetBrains AI BlogOfficialJetBrains explains storage and search for its Air Context code RAG system
AIJetBrains explains how Air Context stores millions of code vectors with approximate nearest-neighbor indexes and retrieves them in milliseconds. The post, the second in a series, compares pre-filtering, filtered ANN and post-filtering for enforcing repository, branch and permission constraints, and describes incremental index updates as commits land. Air Context is in public preview and included with JetBrains AI subscriptions.
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