rLLM is a deep learning framework designed for relational table learning tasks, leveraging LLMs to process and understand structured tabular data. The library provides PyTorch-based implementations of graph neural networks and transformer-style architectures adapted for relational data. It includes a SQL-like API (TLSQL) for easier interaction with table learning workflows, supporting tasks like knowledge graph reasoning and tabular data analysis.