[B-01] Implement StructuredChunk Mock Data Generation for Search Testing

[qowlgur121]

Objective

Implement StructuredChunk Mock data generation to support early testing of search and retrieval APIs while the full ingestion pipeline is being developed.

Implementation Details

• Create StructuredChunk DTO class matching Elasticsearch document structure
• Implement MockDataGenerator service for creating realistic test data
• Generate hierarchical document chunks with parent-child relationships
• Create sample documents covering different file types (PDF, Markdown)
• Include Korean and English content for nori analyzer testing

Acceptance Criteria

• StructuredChunk DTO matches PRD Section 4.2 Elasticsearch schema
• Mock data includes all required fields: chunkId, content, embedding, metadata
• Generated data supports hierarchy testing with different levels
• Sample data covers various document structures and languages
• Unit tests validate mock data generation logic

Related Documentation

• Reference PRD Section 4.2: Elasticsearch Index Specification
• Reference PRD Section 6.1: Ingestion & Storage Logic
• Supports upcoming B-02, B-03, B-04 search implementation tasks

Technical Notes

• Generate embedding vectors as 1024-dimensional L2-normalized floats
• Follow PRD naming conventions and field types exactly
• Prepare foundation for Ollama integration and Elasticsearch indexing