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.