Chess Coaching RAG System

TLDR

• Built an LLM-powered RAG chess coach that grounds move explanations in similar historical positions and concept templates.

• Extracted tactical and strategic features from board states, then retrieved relevant context instead of relying on raw model guesses.

• Developed an offline evaluation pipeline over 2M+ positions to test multiple LLMs with and without generated hints.