All 174 Dependencies
Every package argilla depends on, ranked by repo health score.
Argilla is an open source data annotation and collaboration platform designed for AI and ML teams who need full ownership of their training datasets. It bridges the gap between domain experts who understand the data and AI engineers who build the models, offering a structured workflow for labeling, reviewing, and improving data quality at every stage of the AI development lifecycle.
At its core, Argilla lets you define flexible dataset schemas — text fields, image fields, custom fields — and configure annotation tasks using label questions, ranking questions, span questions, and more. Records flow into the platform via a Python SDK, and annotators interact with them through a polished web UI. AI-generated suggestions can be pre-loaded alongside human annotations, enabling efficient preference-tuning workflows for RLHF and DPO training.
Argilla integrates tightly with the Hugging Face ecosystem, allowing datasets to be pushed and pulled from the Hub with minimal friction. The platform supports semantic search powered by vector embeddings, metadata filtering, and active learning patterns that help annotators focus on the records most likely to improve model performance. It has been used by organizations like the Red Cross, Loris.ai, and Prolific to accelerate their labeling pipelines.
The server backend is built on FastAPI and SQLAlchemy with support for both SQLite and PostgreSQL, while Elasticsearch or OpenSearch powers the full-text and vector search layer. A Vue.js/Nuxt frontend is served from the same process, making deployment straightforward. Teams can run Argilla on their own infrastructure or spin it up instantly via Hugging Face Spaces, keeping data and models under their own control.