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Text chunk

As explained in Microsoft Azure in Action

Chunking is the division of text into smaller segments for processing by a language model or retrieval system.

A language model can view only so much text at once. When a book or conversation is too large, chunking splits it into smaller pieces instead of trying to fit everything into one request. section 7.1

Chunking is one way to manage that limit. Summarization packs the text down; retrieval fetches relevant pieces when needed. Choose an approach that gives the model useful information without overloading it, then test speed, cost, and quality. section 7.1

How Microsoft Azure in Action covers it

How deep it goes
Defines chunking through a suitcase analogy but gives no splitting procedure or configuration.
Examples
Uses an oversized book or conversation as the case for splitting text into smaller pieces.
What you can do after
Evaluate/understand when splitting text may help keep an LLM request within its input limit.
How it connects
Connects chunking to large language models, summarization, retrieval, and model selection.

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This explainer was generated by Manning's knowledge graph from the text of Microsoft Azure in Action. The section links point to the parts of the book it draws on.