This project implements a Retrieval-Augmented Generation (RAG) system to allow users to query
			information about characters from the Frieren: Beyond Journey's End series based on parsed
			wiki data. It showcases a full RAG pipeline, including data loading, chunking, embedding using
			large language models (OpenAI/Google), and vector storage (with support for in-memory and
			ChromaDB). The system retrieves relevant context to ground responses generated by a separate
			LLM. It features both a command-line interface and a streaming web API with a simple static
			frontend, demonstrating practical application of AI/NLP concepts and backend development.