MindSearch
by InternLM
LLM-driven multi-agent web search framework with role-based agent workflows
Overview
Implements a multi-agent web search framework that composes LLM-powered agents to perform search, summarization, and citation tasks. Agents coordinate via message passing and specialized roles (retriever, summarizer, verifier) to mimic modern LLM search assistants. Notable for its web-focused agent workflows and emphasis on combining retrieval with agent-level reasoning and citation generation. See the Hierarchical Multi-Agent Pattern for related architectural guidance.
Why It Matters
When to Use
Researchers and engineers building experimental multi-agent search assistants who need a role-oriented, web-centric agent workflow to prototype retrieval, summarization, and verification pipelines. See also the role-oriented design for governance and coordination patterns, and the Model Context Protocol (MCP) for integration guidance.
Use Cases
- Prototype search assistants that split retrieval, summarization, and verification across specialized agents
- Analyze agent failure modes by tracing which agent introduced hallucinations or citation errors
- Build pre-production demos that show provenance and agent role assignments for QA and evaluation