YS0meone/Corvus
Multi-agent AI research system — finds academic papers via semantic search & citation snowballing, then answers questions over them using agentic RAG with self-reflection. Built with LangGraph, FastAPI, Celery, and Qdrant.
Employs a supervisor-subagent architecture where a top-level coordinator classifies queries, generates multi-step plans, and routes to specialized agents—Paper Finding (with iterative search, citation snowballing, and Cohere reranking) and Q&A (with scoped vector retrieval and self-evaluation loops). Integrates Semantic Scholar (200M+ papers), Tavily web search, Grobid PDF extraction, and OpenAI embeddings into a unified stack with Postgres checkpoints, Redis task queuing, and a React frontend; also exposes search capabilities via MCP server for Claude Desktop integration.
Stars
84
Forks
10
Language
Python
License
MIT
Category
Last pushed
Feb 28, 2026
Commits (30d)
0
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