606 skills found · Page 1 of 21
mlflow / MlflowThe open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
DataTalksClub / Mlops ZoomcampFree MLOps course from DataTalks.Club
evidentlyai / EvidentlyEvidently 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.
traceloop / OpenllmetryOpen-source observability for your GenAI or LLM application, based on OpenTelemetry
SeldonIO / Seldon CoreAn MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Pimzino / Spec Workflow MCPA Model Context Protocol (MCP) server that provides structured spec-driven development workflow tools for AI-assisted software development, featuring a real-time web dashboard and VSCode extension for monitoring and managing your project's progress directly in your development environment.
deepchecks / DeepchecksDeepchecks: 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.
labmlai / Labml🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
NannyML / Nannymlnannyml: post-deployment data science in python
microsoft / Responsible AI ToolboxResponsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
shuyu-labs / AntSKAn AI knowledge base/agent built with .Net 9, AntBlazor, Semantic Kernel, and Kernel Memory, supporting local offline AI large models. It can run offline without an internet connection. Supports Aspire for monitoring application data.
modelfoxdotdev / ModelfoxModelFox makes it easy to train, deploy, and monitor machine learning models.
Time-Appliances-Project / Time CardDevelop an end-to-end hypothetical reference model, network architectures, precision time tools, performance objectives and the methods to distribute, operate, monitor time synchronization within data center and much more...
whylabs / Langkit🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
BMW-InnovationLab / BMW YOLOv4 Training AutomationThis repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.
binafy / Laravel User MonitoringLaravel User Monitoring is a package that tracks user activities like logins, page visits, and model interactions in Laravel apps. It provides a detailed dashboard with insights such as IP address, browser info, and user behavior
jgyates / GenmonGenerac (and other models) Generator Monitoring using a Raspberry Pi and WiFi
ravitemer / MCP HubA centralized manager for Model Context Protocol (MCP) servers with dynamic server management and monitoring
traceloop / Openllmetry JsSister project to OpenLLMetry, but in Typescript. Open-source observability for your LLM application, based on OpenTelemetry
labring / AiproxyAI Proxy is a high performance AI gateway using OpenAI / Claude / Gemini protocol as the entry point. It features intelligent error handling, multi-channel management, and comprehensive monitoring. With support for multiple models, rate limiting, and multi-tenant isolation.
