It is a low-code multi-agent automation framework designed to simplify and enhance workflow efficiency by enabling the creation of multiple agents coupled with specific tasks.
It is a low-code multi-agent automation framework designed to simplify and enhance workflow efficiency by enabling the creation of multiple agents coupled with specific tasks. These agents and tasks can operate independently to complete instructions, achieving a stable state. The framework, Lyzr Automata, was developed as an experiment, leading to initial imperfections, but the team is committed to improving its stability and structure in future releases. Contributions from the community are encouraged to advance the project further.
Lyzr Automata is built on fundamental components: Models, Agents, Tools, Tasks, and Pipelines. Models serve as the core unit, allowing users to connect various LLMs or AI models to workflows. Prebuilt model classes for OpenAI and Perplexity are available, or users can extend the base AIModel class to support custom models. Agents are specialized entities with defined roles, personas, and memory, enhancing the effectiveness of LLMs. Tools enable agents to interact with external software components like APIs or functions, with prebuilt tools and custom tool creation supported. Tasks are the smallest functional units, combining agents and tools to define specific actions. Pipelines organize tasks in a structured manner, currently supporting linear async pipelines, with plans to introduce async DAG pipelines in future updates.
The framework is designed to be user-friendly, with examples provided for creating models, agents, tools, tasks, and pipelines. Installation is straightforward, and the team actively seeks feedback to refine and improve the framework. For queries or contributions, users can reach out via [email protected].
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