toxicity-detection

Self-hosted content moderation API that outperforms Amazon Comprehend. 100% offline, your data never leaves your server. Text + Image moderation.

A supervised learning based tool to identify toxic code review comments

Open-source ML-powered profanity filter with TensorFlow.js toxicity detection, leetspeak & Unicode obfuscation resistance. 21M+ ops/sec, 23 languages, React hooks, LRU caching. npm & PyPI.

AntiToxicBot is a bot that detects toxics in a chat using Data Science and Machine Learning technologies. The bot will warn admins about toxic users. Also, the admin can allow the bot to ban toxics.

Enterprise LLM Evaluation & Responsible AI Framework — Benchmark bias, hallucination, PII leakage, and toxicity across Healthcare, BFSI, Retail & Legal industries. Supports OpenAI, Anthropic, Gemini & HuggingFace. Python SDK + CLI + Web Dashboard. 191 tests. Compliance-ready reports.

An Explainable Toxicity detector for code review comments. Published in ESEM'2023

Multilingual profanity filter with a Rust core — Python, JavaScript/WASM and Rust, with optional multi-label toxicity scoring

Web safety project that scans online content and helps identify harmful, offensive, or bullying messages directly in the browser.

This is a simple python program which uses a machine learning model to detect toxicity in tweets, developed in Flask.

This demo shows the functionality of the Voximplant instant messaging SDK, including silent supervision by a bot.

This work focuses on the development of machine learning models, in particular neural networks and SVM, where they can detect toxicity in comments. The topics we will be dealing with: a) Cost-sensitive learning, b) Class imbalance

ToxiGuard AI is a browser extension that detects and censors toxic language in real-time using TensorFlow.js. It offers fine-grained controls, visual feedback, auto-censor, adjustable sensitivity, and respects user privacy.

This is a simple python program which uses a machine learning model to detect toxicity in tweets, GUI in Tkinter.

🛡️ An AI-powered Discord moderation bot that automatically detects and handles toxicity, spam, and hate speech using Gemini's API. Features configurable warning systems, auto-moderation actions, and comprehensive logging for server safety.

This library can detect toxicity in the text or string or content and in return provide you the toxicity percentage in text or content with toxic words found in text.

Impact Analyzer is a web app that helps you detect toxicity and analyze nuance in your writing before publishing, ensuring your content is respectful, clear, and aligned with your intent.

NLP deep learning model for multilingual toxicity detection in text 📚

An AI-powered content moderation system using Python and Hugging Face Transformers. Combines rule-based filtering and machine learning to detect and block toxic, profane, and politically sensitive content, built for developers and communities to create safer, positive online spaces.

FastAPI-based multilingual NLP backend for code-mixed text analysis — featuring language detection, sentiment & toxicity analysis, translation, and Indic script conversion.

The Toxic Comment Detector is a tool powered by Hugging Face’s unitary/toxic-bert model, designed to identify harmful, offensive, or abusive language in real time. Built with a ReactJS frontend and a Flask backend, it provides detailed insights into toxicity levels, enabling safer online environments.