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---
title: TruthLens
emoji: 🦀
colorFrom: red
colorTo: pink
sdk: gradio
sdk_version: 5.46.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: 'Here’s TruthLens – Lite: a public demo that verifies claims '
---

# 🧭 TruthLens – Misinformation-Aware RAG

TruthLens is a **fact-checking AI demo** that shows how modern GenAI can be made **responsible, transparent, and safe**.  
It verifies controversial claims (vaccines, climate, elections, etc.) using **retrieval-augmented generation**, checks its own answers for **faithfulness**, and applies **safety filters**.

---

## 🚀 How it works
1. **Input a claim/question**  
   Example: *“Did humans cause global warming?”*  

2. **Retrieve sources**  
   The app looks at trusted sources (WHO, IPCC, election reports). You can also paste your own text.  

3. **Generate grounded answer**  
   TruthLens writes an answer with [1], [2] style citations from those sources.  

4. **Self-check**  
   It tests how well the answer actually matches the sources (faithfulness score).  

5. **Safety filters**  
   - Removes personal info (PII redaction).  
   - Flags toxicity levels if the language is harmful.  

---

## 🛠️ Tech stack
- **Gradio** (UI & deployment)  
- **Transformers** (Flan-T5 generation, DeBERTa NLI, BERT NER, Toxic-BERT)  
- **SentenceTransformers** (MiniLM embeddings)  
- **CrossEncoder** (MS-MARCO reranker)  
- **scikit-learn / pandas / numpy / matplotlib**  

All models are **CPU-friendly**, so the demo runs in a free Hugging Face Space.

---

## 🌍 Why it matters
- Tackles **misinformation** around health, climate, and politics.  
- Demonstrates **responsible AI practices** (grounding, self-checking, safety).  
- Shows how a **Lead AI Developer** designs not just models, but **systems** ready for production.

---

## ▶️ Try it
1. Enter a claim or question.  
2. (Optional) Paste your own text sources.  
3. Click **Run TruthLens** → see answer, citations, faithfulness score, and safe-share version.  

---

## 👔 About this project
Created by **Aso Bozorgpanah** as a portfolio demo for **Lead AI Developer** roles.  
Focus: Explainability, safety, and production-readiness in Generative AI.