Technical background
Complex research tasks need to be rationally assigned to Researcher/Coder/Reporter and other intelligences.DeerFlow realizes dynamic task assignment based on LangGraph.
prescription
- Plan Amendment: Enter 'revise plan' in interactive mode to manually adjust the division of labor among the intelligences.
- weighting: Set the agent_priority parameter (0-1 range) in conf.yaml to control the resource allocation ratio
- Exception handling: When an intelligence times out (default 300 seconds), Planner automatically reassigns tasks
- Customized Modules: Develop a proprietary intelligence by inheriting the BaseAgent class and registering it with agent_registry to participate in the collaboration.
practical skill
Data analysis tasks can be adjusted with higher Coder weights:
agent_priority.
researcher: 0.3
coder: 0.5
reporter: 0.2
This answer comes from the articleDeerFlow: an open source automated framework for deep researchThe
May not be reproduced without permission:AI productivity tools " How to overcome the task assignment challenge in DeerFlow multi-intelligence collaboration?
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