beulah0/Multi-Agent-Fact-Check-System
Multi Agent system where two LLM agents argue opposite sides of a claim, a third agent judges based on retrieved evidence, and a final verdict is issued with confidence score. LangGraph is used for multi-agent orchestration. Applied it to detect misinformation on Indian news.
SUMMARY AI summary by gpt-5-mini
Multi-Agent-Fact-Check-System is an open-source pipeline that evaluates the truthfulness of user claims (tested on Indian news) by combining retrieval and multi-agent LLM reasoning. It is intended for developers, researchers, fact‑checkers and journalists who need automated evidence-based verification. Key features: retrieval-augmented generation using hybrid retrieval (live web search via Tavily + FAISS vector search over an Indian news corpus), three LLM agents (Advocate supports the claim, Refuter challenges it, Judge issues a final verdict with confidence), LangGraph for orchestration, and a Gradio UI that emits structured JSON (verdict, confidence, reasoning, sources). Requires Groq LLM and Tavily API keys; FAISS index must be built before running. Modular code (agents, retriever, ingestion) enables extension and evaluation work.
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Total AI relevance score: 75 / 100
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We track 19,340 Python repos, of which 15,086 score 40 or above on AI relevance. 3,410 have more stars than this one (top 17.6%), and 907 score higher (top 4.7%).
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Dates
| Created on GitHub | 2026-05-23 |
| Last push | 2026-05-23 |
| First seen here | 2026-05-23 |
| Last fetched | 2026-09-28 16:25 |
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