---
title: FactEval
emoji: 🔍
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 5.29.0
python_version: "3.12"
app_file: app.py
pinned: false
license: mit
short_description: Find exactly which parts of your LLM output are hallucinated
---

# 🔍 FactEval

**Find exactly which parts of your LLM output are hallucinated.**

Debug hallucinations in RAG and LLM pipelines with claim-level verification.

Paste an LLM-generated answer and reference contexts. FactEval highlights ✅ **supported**, ❌ **contradicted**, and ❓ **unverifiable** claims with human-readable reasons and pipeline diagnostics.

## How it works

1. **Claim Extraction** — Breaks the answer into atomic claims (Qwen2.5-1.5B)
2. **Evidence Retrieval** — Finds the most relevant sentences from your contexts (MiniLM + FAISS)
3. **NLI Verification** — Checks each claim against evidence (DeBERTa-v3)
4. **Calibration** — Produces trustworthy confidence scores (Isotonic Regression)

📦 [GitHub Repository](https://github.com/sahilaf/FactEval)