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Python framework for adversarial attacks, data augmentation, and model training in NLP. Augment datasets to increase model robustness and generate adversarial examples. MIT licensed.
Section: Scanners, Evals & Guardrails · 🟢🔬 — Python framework for adversarial attacks, data augmentation, and training for NLP models; useful for robustness testing beyond chat-only LLM scanners. · updated 2026-08-15)
Section: Tools · A Python framework for adversarial attacks, data augmentation, and model training in NLP.
Section: Adversarial Attack · (from UVa) - A Python framework for adversarial attacks, data augmentation, and model training in NLP.
Section: Libraries · Adversarial attacks, adversarial training, and data augmentation in NLP
Section: 1. Core Frameworks & Libraries · Python framework for adversarial attacks, data augmentation, and model training in NLP. Augment datasets to increase model robustness and generate adversarial examples. MIT licensed.
Section: LLM Security & AI Security · Framework for adversarial attacks in NLP.
Test your prompts, models, RAGs. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality. LLM evals for OpenAI/Azure GPT, Anthropic Claude, VertexAI Gemini, Ollama, Local & private models like Mistral/Mixtral/Llama with CI/CD
🙌 OpenHands: Code Less, Make More. (formerly OpenDevin), a platform for software development agents powered by AI. github
Input/output validation framework for building reliable AI applications. Detects and mitigates risks through composable validators for PII, toxicity, prompt injection, and structured output validation. Features Guardrails Hub with 50+ pre-built validators. Apache 2.0 licensed.
NVIDIA's programmable guardrails toolkit: define input, dialog, retrieval, execution, and output rails that intercept the agent loop at five distinct layers using the Colang DSL. The execution rail layer specifically governs what tools the LLM can invoke and what their inputs/outputs may contain —…
Stanford NLP Python library for 100+ human languages. State-of-the-art neural pipelines for tokenization, NER, parsing, and sentiment analysis with pre-trained models. Apache 2.0 licensed.