Popular GitHub Repositories for Address Validation

structured outputs for llms

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

? Open-Source Evaluation & Testing library for LLM Agents

? Open-Source Evaluation & Testing for AI & LLM systems

A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

An extension of Open3D to address 3D Machine Learning tasks

A high-level machine learning and deep learning library for the PHP language.

Zero-boilerplate REST API framework for PHP 8+. Auto-generates routes, docs, validation.

Automatically find issues in image datasets and practice data-centric computer vision.

Perception toolkit for sim2real training and validation in Unity

Claude Code Skill for browser automation with Playwright. Model-invoked - Claude autonomously writes and executes custom automation for testing and validation.

? Autonomous AI development with 19 specialized sub-agents coordinated through Claude Code. Production-ready applications from natural language requests with browser validation.

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

openai-proxy is a solution provided for Chinese users to address the issue of being unable to make requests to the OpenAI API.

This methodology provides a structured approach for collaborating with AI systems on software development projects. It addresses common issues like code bloat, architectural drift, and context dilution through systematic constraints and validation checkpoints.

A full pipeline AutoML tool for tabular data

Fast, comprehensive DNS performance testing with DNSSEC validation, DoH/DoT support, and enterprise features