Explanation of Multi-Intelligent Body Collaboration Mechanisms
DeerFlow's intelligent body system utilizesStreamlined collaborationmode to accomplish the research task:
- Mission planning phase::
After the user enters a research question (e.g., "The impact of quantum computing on cryptography"), the Planner intelligence breaks down the task:- Developing search terms
- Determine the type of data to be analyzed
- Planning the structure of the report
- Implementation phase::
- Researcher Intelligence: Web search and content crawling via Tavily/Brave API, supports deep search parameter configuration
- Coder Intelligence: Execute data analysis code (Python REPL) to process structured data
- Integration phase::
Reporter intelligently summarizes information and generates output in multiple formats:- Structured reports (Markdown/PDF)
- Presentation (converted to PPT via Marp)
- Voice podcasts (using Volcengine TTS)
Dynamic adjustment mechanism: When enabled--interactiveparameters, the system waits for the user to confirm or adjust them at each critical node to ensure that the research direction is as expected.
This answer comes from the articleDeerFlow: an open source automated framework for deep researchThe
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