Background to the issue
When multiple intelligences work in parallel, problems such as message confusion and response conflicts are likely to occur, affecting system reliability.
Specific solutions
- Instrumentalized proxy handover mechanisms: Standardize inter-agent communication protocols using LangGraph Supervisor's standard interface
- Centralized message management: all messages are passed through the supervising agent, avoiding direct inter-agent communication
- Establishing a message prioritization system: Setting message prioritization rules in workflow definitions
- <strong]Implementation of locking mechanisms: Access to shared resources requires the application of locks through a supervisory agent
- Clear contextual segregation: maintains a separate message history for each interaction session
Optimization Recommendations
It can be combined with the human-in-the-loop mechanism to pause the system and request human intervention when a communication conflict is detected. It is also recommended to use LangGraph's message history management feature to record the complete interaction process, so as to facilitate the analysis and optimization of the communication protocol afterwards.
This answer comes from the articleLangGraph Supervisor: a tool for managing multi-intelligence collaboration using supervising intelligencesThe
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