Genesis
Genesis is a cross-disciplinary researcher-debate engine.
Core trick
Agents grounded in each researcher's OpenAlex papers via RAG debate over a Zep temporal knowledge graph, then a novelty check queries OpenAlex.
Description
Genesis is a cross-disciplinary researcher-debate engine. You paste a research question, select real researchers from OpenAlex (no API key required), and Genesis convenes a live multi-agent debate: each agent is grounded in that researcher's actual papers (RAG). The agents debate across disciplines — biology, AI, cosmology, philosophy — over a Zep temporal knowledge graph where every claim, rebuttal, and bridge is a real edge. Claude Opus 4.8 then synthesizes the debate into a grounded, novel, testable hypothesis brief, with every claim traced back to a DOI. A Novelty Audit queries OpenAlex to verify whether the cross-disciplinary bridge is genuinely new (NOVEL / PARTIAL / KNOWN verdict). A D3 graph visualization glows each researcher's node by how much their ideas influenced the final hypothesis — clicking reveals their paper and DOI. A second "Debate Network" view shows who endorsed, challenged, and amplified whom across disciplines.
README excerpt
# Genesis — Cross-Disciplinary Research Debate Engine > Convene a live panel of real researchers over their *actual* papers. Watch them > debate your question, discover novel cross-disciplinary hypotheses, and see exactly > whose paper sparked each idea — with DOIs you can verify. Genesis does not assert answers. It surfaces **grounded, novel, testable leads**: - **Grounded**: every claim cites a real paper (DOI) - **Novel**: an OpenAlex Novelty Audit checks whether the bridge is already published - **Testable**: the brief ends with a falsifiable next experiment > Genesis is an AGPL-3.0 fork of [MiroFish](https://github.com/666ghj/MiroFish). > MiroFish's three core ideas are inherited (shared temporal graph / stigmergic > round accumulation / post-hoc synthesis) and the social-simulation semantics are > replaced with a researcher-debate pipeline. --- ## Quick start ```bash # 1) Copy and fill env variables cp .env.example .env # Fill ANTHROPIC_API_KEY and ZEP_API_KEY # 2) Import real researcher papers (one per discipline, 43 disciplines) python backend/scripts/import_openalex_corpus.py --auto # Note the project_id printed # 3) Start backend + frontend docker-compose up # OR: cd backend && python run.py # backend :5001 cd frontend && npm run dev # frontend :3000 # 4) Open http://localhost:3000 # Use the project_id from step 2 to build the graph ``` ## How it works (5-step pipeline) 1. **Graph Build** — OpenAlex papers ingested → Zep temporal knowledg