Chunking documents

After this lesson you can: Split a document so retrieved pieces are actually answerable.

First: Why RAG exists

Watch

• Advanced RAG techniques for developers - Google Cloud Tech, 8 min. Developer-focused advanced RAG overview likely fits chunking as a practical retrieval-quality lever after RAG basics.
• How to use Retrieval Augmented Generation (RAG) - Google Cloud Tech, 7 min. Short Google Cloud RAG explainer can reinforce retrieval flow before tuning document splits for answerability.

Notes

Chunking is the decision of where to cut source documents before embedding and indexing them. In RAG, the model does not retrieve whole manuals or repos; it retrieves small text pieces. Those pieces must contain enough context to answer a likely question, but not so much unrelated material that the embedding becomes vague or the prompt fills with noise.

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