Previous efforts in the literature have focused on the task of inorganic crystal structure generation. MatterGen 16 is a diffusion model that generates novel stable crystal structures from a text prompt by adjusting the positions, elements, and periodic lattice. It was trained on the Materials Project and Alexandria databases. LLaMP 17 is a multimodal retrieval-augmented generation (RAG) framework consisting of hierarchical reasoning-and-acting (ReAct) agents that interact dynamically with computational and experimental data from the Materials Project to conduct atomistic simulations via a high-throughput workflow interface. LLaMP can edit crystal structures and perform annealing molecular dynamics simulations using pre-trained machine-learning force fields.