opendatalab/LabelLLM

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1277 stars · 132 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LabelLLM is an open-source data annotation platform designed to streamline the labeling workflows needed for LLM development. It offers configurable annotation tasks, multimodal data support (audio, image, video), AI-assisted pre-annotation, and comprehensive task management with progress and quality monitoring.

Use cases

• annotate conversation data for LLM fine-tuning
• label audio, image, and video datasets in one platform
• manage annotation teams with progress and quality tracking
• pre-annotate data with AI and have humans refine it
• set up custom annotation task configurations
• prepare training data for model development

When to choose

• you are an independent developer or small/medium team preparing LLM training data
• you need multimodal annotation support under a unified self-hosted platform
• you want AI-assisted pre-annotation to speed up labeling
• you need task management with real-time progress and quality control

When to avoid

• you only need simple image bounding-box annotation for computer vision
• you require a fully managed SaaS annotation service
• you need large-enterprise annotation workforce management features

Facets

application · maturity active

machine-learning data-science workflow-automation developer-tools machine-learning artificial-intelligence large-language-models self-hosted cross-platform data-annotation labeling llm-training-data multimodal task-management human-in-the-loop data-engineering web-server docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="opendatalab/LabelLLM")