Docta-ai/docta

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3486 stars · 257 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Docta is a Python library for data-centric AI that diagnoses and fixes issues in datasets such as label errors, noise, and misannotations. It works training-free on tabular data, text, images, and pre-trained model embeddings, including LLM alignment/RLHF data.

Use cases

• find label errors in my dataset
• clean noisy labels in RLHF data
• detect human annotation mistakes in LLM alignment data
• curate and diagnose image datasets
• fix mislabeled tabular data before training
• audit dataset quality without training a model

When to choose

• you suspect label noise or annotation errors are hurting model performance
• you need training-free data diagnosis on tabular, text, or image data
• you are preparing RLHF or LLM alignment datasets and want to audit label quality

When to avoid

• you need a fully automated production data pipeline rather than diagnostic tooling
• your use is commercial and you cannot accept the non-commercial CC BY-NC 4.0 license
• you need active data labeling or annotation workflow management

Facets

library · maturity active

data-science machine-learning nlp etl data-science machine-learning large-language-models developer-tools python cross-platform data-curation data-diagnosis label-errors data-quality rlhf training-free data-centric-ai

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Docta-ai/docta")