data-privacy-stack/presidio
Presidio is an open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data, leveraging NLP and customizable pipelines.
Awesome Infra for AI › AI Safety & Guardrails
NVIDIA-NeMo/Guardrails
NVIDIA NeMo Guardrails is an open-source library designed to integrate programmable guardrails into large language model (LLM) based conversational applications. Its primary goal is to enhance the safety, trustworthiness, and controlled behavior of AI assistants by enabling developers to define specific rules and constraints for LLM outputs and interactions. The toolkit helps prevent LLMs from generating undesirable content, engaging in off-topic discussions, or deviating from predefined conversational paths. It introduces concepts like input rails, dialog rails, output rails, retrieval rails, and fact-checking rails to provide comprehensive control over the LLM's responses and interactions with external tools and services. NeMo Guardrails allows for the definition of guardrails to address common LLM vulnerabilities such as jailbreaks and prompt injections. It supports various use cases, including question-answering systems over documents (Retrieval Augmented Generation), domain-specific assistants, securing LLM endpoints, and integrating with frameworks like LangChain. The library is designed to be easily integrated into existing LLM applications with minimal code changes, offering both synchronous and asynchronous APIs. It is compatible with a wide range of LLMs, including OpenAI models like GPT-3.5 and GPT-4, LLaMa-2, Falcon, Vicuna, and Mosaic models, making it a flexible solution for enhancing the operational safety and reliability of LLM deployments.
https://github.com/NVIDIA-NeMo/Guardrails
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