Databricks Generative AI Engineer Associate Question 116
Select 3You are designing a document retrieval system using a large language model (LLM) and need to select a chunking strategy for splitting long documents into smaller segments. The goal is to optimize both retrieval accuracy and the model's context window usage. Which of the following considerations should guide your chunking strategy?
- A
Ensure chunks are smaller than the model's maximum context window to prevent truncation.
- B
Split text based solely on fixed token limits, ignoring semantic coherence.
- C
Include overlapping content between chunks to preserve context during retrieval.
- D
Use domain-specific knowledge to define chunk boundaries when semantic meaning is critical.
- E
Minimize the size of chunks to reduce the number of retrieval calls, even if semantic meaning is lost.
Show answer and explanation
Correct answers: A, C, D
Explanation
An effective chunking strategy for an LLM-based retrieval system should balance the model's context window limitations with the need to preserve semantic relevance. Chunks must be small enough to fit within the model's context window while considering overlaps and domain-specific boundaries to ensure accurate retrieval and coherent responses. Focusing purely on token limits or reducing chunk size at the expense of meaning can lead to suboptimal results.
- A. Correct.
Correct: Ensuring that chunks are smaller than the model’s context window prevents truncation and ensures all key information is processed by the model.
- B. Incorrect.
Incorrect: Splitting text based solely on fixed token limits without considering semantic coherence can degrade retrieval accuracy and lead to irrelevant or fragmented results.
- C. Correct.
Correct: Including overlaps between chunks helps preserve semantic context and ensures that related concepts are not lost when splitting text.
- D. Correct.
Correct: Leveraging domain-specific knowledge to define chunk boundaries improves semantic relevance, which can enhance retrieval and model performance.
- E. Incorrect.
Incorrect: Minimizing chunk size without regard for semantic meaning can result in incomplete or incoherent context for the model, negatively impacting retrieval performance.