DataDreamer

Why we included this project

Most LLM research pipelines scatter the work across a prompting script, a dataset cleanup pass, and a training run, with little to show for how one step fed the next. DataDreamer is a Python library that pulls those stages into one reproducible workflow, letting researchers and small teams go from a rough idea to a trained, aligned model without hand-stitching the pieces. You can call open-source or API models to build and expand synthetic datasets, then train or align models on top of that data. Its defaults are sensible and its caching aggressive, so an interrupted experiment resumes cheaply, and the data and model cards record provenance and the citations a reproduction will need. Built by NLP researchers on top of Hugging Face and LiteLLM, it reads as a practical scaffold for reproducible experiments rather than another thin wrapper.