DeerFlow's core architectural innovations
The innovation of DeerFlow as an open source research framework is reflected in its multi-intelligent body system architecture design. The system consists of three types of professional intelligences: Researcher is responsible for information retrieval, Coder handles code execution, and Reporter organizes report output. This division of labor breaks through the traditional single-intelligent body limitations, and each module can call the exclusive tool chain:
- Tavily/Brave Search API Enables Precise Information Access
- Python REPL environment supports real-time code verification
- Marp engine guarantees standardized output of document formats
The framework is built based on LangChain and LangGraph, and realizes task flow through the state machine model, so that the complex research process can be decomposed into discrete state nodes. For example, when dealing with the task of "quantum computing research", the system will automatically trigger the progressive workflow of search → analysis → verification → report.
This answer comes from the articleDeerFlow: an open source automated framework for deep researchThe
