A context engineer is evaluating a Databricks agent deployed for a manufacturing company’s field service team. The agent uses a DELTA_SYNC Databricks AI Search index to search a knowledge base of equipment troubleshooting guides. The product line includes closely related models (CX-400, CX-410, CX-420) whose guides share similar procedural language but specify different part numbers, torque values, and calibration sequences for each model. The index uses databricks-gte-large-en embeddings with a chunk_size of 512 tokens and chunk_overlap of 50 tokens. Evaluation reveals that when a technician queries for a specific model, such as “CX-400 belt tensioner replacement procedure,” the agent frequently returns procedures from a different model in the same product family. The returned content appears relevant but contains incorrect part numbers and specifications for the queried model. Which Databricks AI Search configuration change directly addresses this retrieval pattern?
Select one answer.
Marked answer: A
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