System Architecture Principle
VoltAgent realizes multi-intelligence collaboration through a hierarchical structure of "Head Intelligence + Sub-intelligence". The supervisor is responsible for task decomposition and result summarization, while the sub-intelligences focus on specific functions.
Typical Workflow
- Receipt of tasks: User requests are received by the supervising intelligence
- task sth.: Distribute to the appropriate sub-intelligence according to the content
- parallel processing: Sub-intelligence invokes tools to perform specific operations
- Integration of results:: Supervisory intelligences summarize and output the final result
Complex Functionality Implementation
- GitHub Analytics: Includes starred statistics, contributor analysis, report generation and other intelligent features
- Enterprise Customer Service:: Automated routing of specialized questions to corresponding domain intelligences
- Data Analysis Pipeline:: Achievement of the full process of data acquisition, cleansing, analysis and visualization
Development Advantages
Through the local debugging console, you can monitor the status and interaction process of each intelligent body in real time, and the visualization interface greatly reduces the difficulty of debugging.
This answer comes from the articleVoltAgent: TypeScript Open Source Framework for Rapidly Building AI IntelligentsiaThe
May not be reproduced without permission:AI productivity tools " How does VoltAgent's multi-intelligent body system work? What complex functions does it perform?
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