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ML Academy

RAG and agents

Interview question

  • seniorlevel
  • 15 minsuggested time
  • 2Applied AI, ML engineer

Your production RAG system uses a 1,024-dimension embedding model over 4 million chunks. The provider announces that the model will be retired in six months and offers a new model with a different dimension. How do you migrate without degrading answers or causing an outage?

Tests: Operating a retrieval index over time: embedding-space incompatibility, dual indexes, golden-set comparison, capacity estimation and staged cutover.

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