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Adala: Autonomous DAta (Labeling) Agent framework
Agents
GitHub
Added 1 June 2026
Overview
Adala is an open-source framework for building autonomous data labeling agents. It enables developers to create agents that label data without manual intervention. Built in Python, it leverages community-contributed components.
Best for
Best for
Data scientists and ML engineers who need to automate labeling at scale
Use cases
- Automating large-scale data labeling tasks
- Building custom labeling agents for specific datasets
- Integrating autonomous labeling into ML pipelines
Notes
Adala is an open-source framework for building autonomous data labeling agents. It enables developers to create agents that label data without manual intervention. Built in Python, it leverages community-contributed components.
1,593 stars on GitHub. Last updated 2026-05-19. Licensed Apache-2.0.
Use cases
- Automating large-scale data labeling tasks
- Building custom labeling agents for specific datasets
- Integrating autonomous labeling into ML pipelines
Pros
- Open source with active community support
- Python-based, easy to integrate with ML workflows
- Focuses specifically on labeling, reducing complexity
Cons
- Limited to data labeling tasks, not a general agent framework
- Requires understanding of agent design and labeling workflows
- Documentation may still be evolving as a community project
Indexed from awesome-ai-agents and enriched against its public facts.
Pros
- Open source with active community support
- Python-based, easy to integrate with ML workflows
- Focuses specifically on labeling, reducing complexity
Cons
- Limited to data labeling tasks, not a general agent framework
- Requires understanding of agent design and labeling workflows
- Documentation may still be evolving as a community project
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