Distributed AI Task Collaboration Framework
ai-gradio enables high-level abstraction of multi-intelligence collaborative systems by deeply integrating the CrewAI framework. This feature upgrades traditional single-model invocations into a task execution network consisting of multiple specialized AI agents, each with specific role capabilities and knowledge domains.
The system architecture adopts a master-slave design: the coordinating agent (Manager) is responsible for task decomposition and result aggregation, while the expert agent (Specialist) handles specific subtasks, such as code generation agent specializing in programming issues, and research agent specializing in information retrieval. The developer can configure the collaboration strategy of different roles through team parameters, and support a variety of collaboration modes, including sequential execution, parallel processing, debating and decision-making.
In the technical support work order processing scenario, the system can automatically form a virtual team including product experts, code debuggers, document retrievers, etc., and each agent can solve complex problems together through chain calls or group discussions. This design can significantly improve the processing accuracy and completion of complex tasks compared with a single model.
This answer comes from the articleai-gradio: Easily Integrate Multiple AI Models and Build Multimodal Applications Based on GradioThe
