Popular GitHub Repositories for Regex

Structured Text Generation

Natural-language event parser for Javascript

Headless chatbot that detects spam and posts links to it in chatrooms for quick deletion.

A Github scanning tool that identifies hardcoded credentials while filtering the false positive data through machine learning models :lock:

Enforce structured output from LLMs 100% of the time

Faster structured generation

Extract indicators of compromise from text, including "escaped" ones.

ReLM is a Regular Expression engine for Language Models

this ai tool(gpt-3.5) is for those who hate regex!

Malicious actors often reuse code to deploy their malware, phishing website or CNC server. As a result, similiaries can be found on URLs path by inspecting internet traffic. Moreover, deep learning models or even regular ML model do not fit for inline deployment in terms of running performance. However, regexes ( or YARA rules ) can be deployed on a proxy and work in real time on all the traffic. LUDA can take a set of malicious and benign URLs and return a list of regexes ready to be deployed inline !

A Domain Specific Language (DSL) for building language patterns. These can be later compiled into spaCy patterns, pure regex, or any other format

Caribou: Distributed Smart Storage built with FPGAs

A rust implementation of ELIZA - a natural language processing program developed by Joseph Weizenbaum in 1966.

English to RegEx converter, powered by gpt-3.5-turbo and Vercel Edge Functions.

TensorRT-LLM server with Structured Outputs (JSON) built with Rust

A curated list of resources related to structured generation ?

xVerify: Efficient Answer Verifier for Large Language Model Evaluations

Extracting details from Resume(CVs) and matching with Job Description(JDs) using pretrained model like DistilBERT and ranking them using cosine similarity.

MLX.zig: Lightweight Zig language bindings for Apple's MLX framework, enabling efficient machine learning directly on Apple Silicon with zero external dependencies.

A chatbot developed to help FIB students. It uses NLP + Machine learning techniques such as sentence classification, or entity recognition (NER), along with a Deep Learning dialogue management model.