We have just open sourced Adala - a robust framework for implementing agents that specialize in advanced data processing tasks, starting with data labeling and generation.
What is Adala?
Adala offers a robust framework for implementing agents specialized in data processing, with an emphasis on diverse data labeling tasks. These agents are autonomous, meaning they can independently acquire one or more skills through iterative learning. This learning process is influenced by their operating environment, observations, and reflections. Users define the environment by providing a ground truth dataset. Every agent learns and applies its skills in what we refer to as a "runtime", synonymous with LLM.
To ensure agents remember and build upon their experiences, Adala provides a Memory component—a dynamic storage space for the agent's acquired knowledge. For instance, retrieving the previous experiences of an agent’s errors (and subsequent human feedback) allows them a starting point from which to branch off into learning or improving skills.
Reliability in Agents Through Human Signal
To allow Adala to produce reliable agents, we devised two main strategies:
Supervision Integration: Provide agents with 'ground truth data'—well-defined examples that serve as a learning foundation. This foundational data not only sets the learning parameters for the agent but also defines its operational environment.
Constrained Generation: Ensuring that an agent's predictions are within a defined and bounded range of outputs.
Progress Through Open Source
We believe that true progress in the field of AI comes when knowledge is accessible and collaborative, and there’s a strong feedback loop. By releasing Adala with an OSI-approved open source license, we hope to inspire creativity and new applications we couldn’t have imagined, as well as drive important standards and best practices in a rapidly changing market.
We've designed Adala with modularity at its core, emphasizing our belief in strong contributions from the community. We eagerly invite the AI community to contribute by:
- Developing various agent skills and scaling up their reasoning abilities.
- Adding support for more runtimes and dataset formats.
- Creating new environments to capture ground truth feedback.
- Testing and improving the core software, examples, and docs.
What’s Next?
Can't wait to see what you'll build!
Let us know what you think in the comments below or by contributing to the repo.
- Adala GH repo: https://github.com/HumanSignal/Adala
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