To further facilitate the adoption of Chemspyd and its rapid implementation into new laboratory routines, we provide a natural language interface for generating Chemspyd code. Such interfaces have recently proven to be powerful enabling technologies for automated or self-driving laboratories. Similar to our recent work, we provide a web interface that uses a large language model to convert the natural language inputs into structured Chemspyd output. In our implementation, all Chemspyd functions, along with their natural language documentation and all parameters, are organized in an associative array. Incoming natural language instructions are segmented into structured commands, which are then matched to the classes and functions in the associative array based on cosine distance. Subsequently, OpenAI's GPT-4 is employed to translate the instructions into the corresponding code. Command-by-command, each section of the generated Chemspyd code is sent back to the user for feedback and validation. This match-translate cycle is repeated iteratively until satisfactory Chemspyd code is reached (Figure ). Eventually, the outcome is a responsive interface that effectively bridges the gap between user intent and the correct Chemspyd code, showcasing the power of NLP in user-system interactions, and providing a useful tool for nonexpert programmers to generate experiments with Chemspyd.