toxicity-detection

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

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.

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

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

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

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.

A supervised learning based tool to identify toxic code review comments

🛡️ Programmable Guardrails for LLM Applications in Java. A framework-agnostic toolkit for input/output validation, PII masking, and jailbreak detection. The Java alternative to NVIDIA NeMo Guardrails.

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

NLP deep learning model for multilingual toxicity detection in text 📚

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.

Fast, drop-in multilingual profanity and toxicity screener for Node.js, powered by System 1 models like TypeSafe AI Jev and Laya. Catches leetspeak, character spacing, and romanized profanity across languages including Kannada, Telugu, Tamil, Hindi, and Bengali. ~50-500ms latency.

Using Language Models to Identify and Classify Toxicity Inside In-Game Chat

Telegram bot that detects toxic comments based on Perspective API

Simple Multi-Language HTTP Server Text Toxicity Detector

It is a trained Deep Learning model to predict different level of toxic comments. Toxicity like threats, obscenity, insults, and identity-based hate.

State-of-the-art Chinese toxicity detection — dual-LoRA ensemble (Qwen3-8B) exceeding PCR-ToxiCN SOTA with homophone attack defense. 中文毒性偵測 · 超越 SOTA · 諧音攻擊防禦

This repository presents a comprehensive comparison of traditional machine learning, deep learning, encoder-based, and decoder-based large language models (LLMs) for Chinese toxic comment detection.

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

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.