This week, I focused on building the frontend user interface using React and integrating it with the backend systems. I implemented core UI components for interacting with the chessboard and began setting up integration tests to verify correct communication between the frontend and backend. These tests help ensure that board state updates, move validation, and engine responses are properly synchronized across the system.
In addition to development work, I conducted further research into implementing retrieval-augmented generation (RAG) and agent state management using LangChain. This exploration focuses on how the system can maintain contextual knowledge and structured reasoning when generating explanations for moves. The goal is to design a pipeline where the engine outputs and relevant game context can be retrieved and incorporated into the LLM’s reasoning process while maintaining consistency with the validated move set.