Question 35: AI-500: Designing and Implementing Multi-Agent AI Solutions
You have a Microsoft Foundry multi-agent customer support solution that retrieves grounding data from a shared vector index. The indexed corpus contains product runbooks in Markdown and support articles in HTML Both document types use a consistent hierarchical markup. You discover that current fixed-size token chunkin…
Nội dung câu hỏi
You have a Microsoft Foundry multi-agent customer support solution that retrieves grounding data from a shared vector index. The indexed corpus contains product runbooks in Markdown and support articles in HTML Both document types use a consistent hierarchical markup. You discover that current fixed-size token chunking creates chunks that cross section boundaries. You need to recommend a chunking approach for the ingestion pipeline. The solution must preserve existing document structure boundaries and minimize custom chunking code. What should you recommend?
Các lựa chọn
Đáp án được giữ gọn theo nhãn A, B, C, D trong phần bình chọn tương tác.
- A. semantic chunking with topic-shift detection
- B. format-specific chunking with header splitters — đáp án hiện tại
- C. recursive character chunking with structure-aware separators
- D. fixed-size chunking with token overlap
Answer researched independently against supporting documentation; not a published source answer key. Markdown and HTML header splitters preserve the existing hierarchy without custom topic detection. References: https://docs.databricks.com/aws/en/agents/tutorials/ai-cookbook/quality-data-pipeline-rag
Cộng đồng
0 bình luận công khai. Tên thành viên được ẩn một phần.