Given a prompt describing the requested chemistry simulation (X), our model aims to create the corresponding ORCA input file (ŷ). We rely on three techniques to achieve this: prompt engineering to best extract pretrained knowledge of GPT-3.5 Turbo, Naive RAG to provide the model with external documentation about ORCA inputs, and model finetuning on three synthetic datasets to teach it the syntax and semantics of an ORCA input.