Practical Solutions for Balancing Intelligent Body Workloads
When the supervisor intelligences assign tasks unevenly, the following measures can be taken:
- Monitor workflow status::
- View each smart body in real time through the Livekit console's
CPU/内存norm - exist
app/monitoring/Add custom logging of task processing time in
- View each smart body in real time through the Livekit console's
- Adjusting the LangGraph Configuration::
- modifications
app/agents/langchain/config/workflow.jsonhit the nail on the headmax_concurrentParameters limit the number of parallel tasks - Exclusive queue paths for time-consuming operations (e.g. image recognition)
- modifications
- Classification of Intelligent Body Capabilities::
- exist
app/agents/implementations/Implementing the Load Checking Interface in the - Supervisor intelligences prioritize task assignment to idle instances
- exist
Other possible options include 1) using Kubernetes to automate scaling up and down 2) using theagent-search-by-jsonImplementing Task Priority Markers in 3) Refer toexamples/load_balancing/Sample code to implement polling scheduling in the
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