DeepSearch Agents
A tutorial project that builds a multi-agent research assistant: a main agent delegates a task to web search, database and private knowledge base sub-agents, then merges their findings into a Markdown or PDF report streamed over WebSocket.
deepsearch-agents is a full-stack, runnable teaching project for a deep-research style assistant built with DeepAgents, LangGraph, RAGFlow, Tavily and FastAPI. A main agent analyzes the user's task, decides which sources it needs (public web search, a structured MySQL database, a private RAGFlow knowledge base, or files the user uploaded), dispatches work to expert sub-agents for each source, and merges their findings into a final answer that can be exported as Markdown or converted to PDF.
Each task runs in an isolated session directory identified by a thread ID, and a monitor pushes tool calls, sub-agent calls, progress and results to a React frontend over WebSocket in real time so the process stays observable rather than opaque. The repository is paired with a free, chapter-by-chapter written course and matching Git branches that walk through building the same system from scratch.