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DataFreeOpen Source
ARGILLA
Build high-quality datasets for AI
Apache-2.0
ABOUT
Building high-quality datasets for AI projects is a fragmented, manual process — data scientists use one-off scripts for annotation, domain experts lack accessible interfaces, and there's no systematic way to track data quality or iterate on annotations. Argilla provides a shared workspace where AI engineers and domain experts collaborate on dataset creation through an intuitive web UI and a Python SDK. It supports text classification, NER, preference tuning for LLMs, and multimodal annotation, with built-in quality monitoring and active learning workflows.
INSTALL
pip install argillaINTEGRATION GUIDE
1. Create high-quality training datasets for LLM fine-tuning through collaborative human annotation
2. Build RLHF preference datasets by collecting and ranking model outputs with domain expert feedback
3. Annotate named entities and text classifications at scale with active learning to minimize labeling effort
4. Set up continuous evaluation pipelines where model outputs are reviewed and annotated for quality monitoring
5. Collaborate across teams with programmatic data access via the Python SDK and real-time web UI dashboards
TAGS
pythondata-annotationdatasetsactive-learningnlpllmrlhfhuman-in-the-loop