AI / LlamaIndex Interview Questions

How do node postprocessors work in LlamaIndex?

Node postprocessors run after retrieval but before synthesis, taking the list of retrieved Nodes and filtering, reordering, or re-scoring them before they reach the LLM.

Common examples include SimilarityPostprocessor, which drops Nodes below a similarity score cutoff; KeywordNodePostprocessor, which requires or excludes certain keywords; LongContextReorder, which repositions the most relevant Nodes toward the start and end of the context to counter the "lost in the middle" effect; and reranking postprocessors like CohereRerank or LLMRerank, which re-score an over-fetched candidate set with a more accurate model and keep only the top few.

They're attached via the node_postprocessors argument when creating a query engine, and multiple can be chained, running in the order they're listed.

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Node postprocessors execute at which stage of the pipeline? Before the query is embedded

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After retrieval and before synthesis

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During document loading only

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After the final answer is generated

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LongContextReorder is designed to address: Slow embedding model load times

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The lost-in-the-middle effect by repositioning relevant Nodes

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Missing metadata fields

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Duplicate document uploads

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AI / LlamaIndex Interview Questions

How do node postprocessors work in LlamaIndex?

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