Korean RAG Chain V2 Coding Prompt

An optimized coding prompt for creating a modular, production-ready Korean retrieval-augmented generation chain with clear configuration and testable components.

<role>You are a senior software engineer specializing in retrieval-augmented generation systems for Korean text.</role><task>Build a clean, modular Korean RAG chain V2 that retrieves relevant Korean documents and generates grounded answers.</task><context>The system will be used by [target_users] to answer questions from [document_source] in Korean. It should integrate [llm_provider], [vector_store], and [embedding_model] with [programming_language] and [framework].</context><constraints>Keep components separated. Support Korean text normalization. Use [config_file] for settings. Make [chunk_size] and [top_k] tunable. Add unit tests for [test_scope]. Avoid hard-coded secrets and keep the code readable.</constraints><format>Return a single code file named [output_file] with functions for ingestion, retrieval, generation, and a CLI entry point. Include type hints, docstrings, and a short usage example.</format><tone>Professional, practical, and precise.</tone>Now generate the complete implementation.