ZeroGraph has designed a perfect multi-agent collaboration mechanism specifically for complex AI scenarios:
- dynamic routing: Conditional branching via exec() return value, support if-else/switch and other multi-way logic
- data sharing: Shared memory (shared objects) mechanism allows transfer of structured data across nodes
- Parallel Processing</gt;: BatchFlow can process 200+ task units simultaneously with up to 3x the throughput of traditional solutions.
- fault isolation: Individual node crashes do not affect the overall process, and the exception context is automatically logged
Microsoft Research Asia adopted the framework to build a paper writing assistant, which successfully coordinated six types of specialized Agents such as retrieval Agents, generation Agents, and checking Agents, and improved the efficiency of academic literature output by 120%.
This answer comes from the articleZeroGraph: a lightweight AI agent programming frameworkThe
May not be reproduced without permission:AI productivity tools " ZeroGraph's Multi-Agent Collaboration Capabilities in Complex AI Scenarios
English 
简体中文 
日本語 
Deutsch 
Português do Brasil