PRODUCTION SCENARIO
A Generative AI Engineer chunks lab protocols at 1,600 tokens and embeds them with a model whose maximum input is 512 tokens. Questions about steps near the end of each protocol return nothing relevant.
What should the engineer change in the pipeline?
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Answer: Reduce the chunk size so each chunk fits the embedding model's token limit
Chunks longer than the embedding model's maximum input are truncated, so text past the limit never enters the vector and cannot be retrieved. Overlap, hybrid search, and more results cannot restore content that was cut before embedding.