Argilla

A collaboration tool that lets AI engineers and domain experts build and label high-quality datasets for text classification, LLM and multimodal projects.

Visit website argilla-io.github.io

Argilla supports collecting human feedback for traditional NLP tasks such as text classification and named-entity recognition, LLM tasks such as RAG and preference tuning, and multimodal models such as text-to-image. A programmatic approach lets a team build workflows for continuous evaluation and model improvement.

Filters, AI feedback suggestions and semantic search speed up labeling; it can be deployed on Hugging Face Spaces, with sign-in through a Hugging Face account for trying the UI directly.

It is written in Python and licensed under Apache-2.0. As of this material, the original authors have moved to other projects, so the codebase is in maintenance mode, receiving bug fixes and patches but no new features, and is looking for new maintainers.

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