Pulse is a real-time monitoring tool designed for Proxmox, Docker, and Kubernetes infrastructure. It provides a unified dashboard to consolidate metrics, alerts, and AI-powered insights into a single interface. Suitable for homelabs, sysadmins, and MSPs, Pulse offers core monitoring features, AI-powered functionalities, multi-platform support, security and operations features, and community integrations. Pulse Pro unlocks advanced AI analysis and auto-fix capabilities. The tool is privacy-focused, secure by design, and offers detailed documentation for installation, configuration, security, troubleshooting, and more.

Netdata is an open-source, real-time infrastructure monitoring platform that provides instant insights, zero configuration deployment, ML-powered anomaly detection, efficient monitoring with minimal resource usage, and secure & distributed data storage. It offers real-time, per-second updates and clear insights at a glance. Netdata's origin story involves addressing the limitations of existing monitoring tools and led to a fundamental shift in infrastructure monitoring. It is recognized as the most energy-efficient tool for monitoring Docker-based systems according to a study by the University of Amsterdam.

Handit.ai is an autonomous engineer tool designed to fix AI failures 24/7. It catches failures, writes fixes, tests them, and ships PRs automatically. It monitors AI applications, detects issues, generates fixes, tests them against real data, and ships them as pull requests—all automatically. Users can write JavaScript, TypeScript, Python, and more, and the tool automates what used to require manual debugging and firefighting.

Atom is an open-source, self-hosted AI agent platform that allows users to automate workflows by interacting with AI agents. Users can speak or type requests, and Atom's specialty agents can plan, verify, and execute complex workflows across various tech stacks. Unlike SaaS alternatives, Atom runs entirely on the user's infrastructure, ensuring data privacy. The platform offers features such as voice interface, specialty agents for sales, marketing, and engineering, browser and device automation, universal memory and context, agent governance system, deep integrations, dynamic skills, and more. Atom is designed for business automation, multi-agent workflows, and enterprise governance.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

Rhesis is a comprehensive test management platform designed for Gen AI teams, offering tools to create, manage, and execute test cases for generative AI applications. It ensures the robustness, reliability, and compliance of AI systems through features like test set management, automated test generation, edge case discovery, compliance validation, integration capabilities, and performance tracking. The platform is open source, emphasizing community-driven development, transparency, extensible architecture, and democratizing AI safety. It includes components such as backend services, frontend applications, SDK for developers, worker services, chatbot applications, and Polyphemus for uncensored LLM service. Rhesis enables users to address challenges unique to testing generative AI applications, such as non-deterministic outputs, hallucinations, edge cases, ethical concerns, and compliance requirements.

AionUi is a user interface library for building modern and responsive web applications. It provides a set of customizable components and styles to create visually appealing user interfaces. With AionUi, developers can easily design and implement interactive web interfaces that are both functional and aesthetically pleasing. The library is built using the latest web technologies and follows best practices for performance and accessibility. Whether you are working on a personal project or a professional application, AionUi can help you streamline the UI development process and deliver a seamless user experience.

Osaurus is a native, Apple Silicon-only local LLM server built on Apple's MLX for maximum performance on M‑series chips. It is a SwiftUI app + SwiftNIO server with OpenAI‑compatible and Ollama‑compatible endpoints. The tool supports native MLX text generation, model management, streaming and non‑streaming chat completions, OpenAI‑compatible function calling, real-time system resource monitoring, and path normalization for API compatibility. Osaurus is designed for macOS 15.5+ and Apple Silicon (M1 or newer) with Xcode 16.4+ required for building from source.

Transformer Lab is an app that allows users to experiment with Large Language Models by providing features such as one-click download of popular models, finetuning across different hardware, RLHF and Preference Optimization, working with LLMs across different operating systems, chatting with models, using different inference engines, evaluating models, building datasets for training, calculating embeddings, providing a full REST API, running in the cloud, converting models across platforms, supporting plugins, embedded Monaco code editor, prompt editing, inference logs, all through a simple cross-platform GUI.

MemMachine is an open-source long-term memory layer designed for AI agents and LLM-powered applications. It enables AI to learn, store, and recall information from past sessions, transforming stateless chatbots into personalized, context-aware assistants. With capabilities like episodic memory, profile memory, working memory, and agent memory persistence, MemMachine offers a developer-friendly API, flexible storage options, and seamless integration with various AI frameworks. It is suitable for developers, researchers, and teams needing persistent, cross-session memory for their LLM applications.

sandboxed.sh is a self-hosted cloud orchestrator for AI coding agents that provides isolated Linux workspaces with Claude Code, OpenCode & Amp runtimes. It allows users to hand off entire development cycles, run multi-day operations unattended, and keep sensitive data local by analyzing data against scientific literature. The tool features dual runtime support, mission control for remote agent management, isolated workspaces, a git-backed library, MCP registry, and multi-platform support with a web dashboard and iOS app.

AstronRPA is an enterprise-grade Robotic Process Automation (RPA) desktop application that supports low-code/no-code development. It enables users to rapidly build workflows and automate desktop software and web pages. The tool offers comprehensive automation support for various applications, highly component-based design, enterprise-grade security and collaboration features, developer-friendly experience, native agent empowerment, and multi-channel trigger integration. It follows a frontend-backend separation architecture with components for system operations, browser automation, GUI automation, AI integration, and more. The tool is deployed via Docker and designed for complex RPA scenarios.

NodeTool is a platform designed for AI enthusiasts, developers, and creators, providing a visual interface to access a variety of AI tools and models. It simplifies access to advanced AI technologies, offering resources for content creation, data analysis, automation, and more. With features like a visual editor, seamless integration with leading AI platforms, model manager, and API integration, NodeTool caters to both newcomers and experienced users in the AI field.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

Explain OpenClaw is a comprehensive documentation repository for the OpenClaw framework, a self-hosted AI assistant platform. It covers various aspects such as plain English explanations, technical architecture, deployment scenarios, privacy and safety measures, security audits, worst-case security scenarios, optimizations, and AI model comparisons. The repository serves as a living knowledge base with beginner-friendly explanations and detailed technical insights for contributors.

Natively is a free, open-source, privacy-first AI assistant designed to help users in real time during meetings, interviews, presentations, and conversations. Unlike traditional AI tools that work after the conversation, Natively operates while the conversation is happening. It runs as an invisible, always-on-top desktop overlay, listens when prompted, observes the screen content, and provides instant, context-aware assistance. The tool is fully transparent, customizable, and grants users complete control over local vs cloud AI, data, and credentials.

BentoVLLM is an example project demonstrating how to serve and deploy open-source Large Language Models using vLLM, a high-throughput and memory-efficient inference engine. It provides a basis for advanced code customization, such as custom models, inference logic, or vLLM options. The project allows for simple LLM hosting with OpenAI compatible endpoints without the need to write any code. Users can interact with the server using Swagger UI or other methods, and the service can be deployed to BentoCloud for better management and scalability. Additionally, the repository includes integration examples for different LLM models and tools.

Melty is an open source AI code editor designed to help developers write production-ready code by collaborating with them from the terminal to GitHub. It can refactor code, create web apps from scratch, navigate large codebases, and write its own commits. Melty aims to help developers understand their code better, watch every change made, learn and adapt to the codebase, and integrate with various development tools.

TraceRoot is a tool that helps engineers debug production issues 10× faster using AI-powered analysis of traces, logs, and code context. It accelerates the debugging process with AI-powered insights, integrates seamlessly into the development workflow, provides real-time trace and log analysis, code context understanding, and intelligent assistance. Features include ease of use, LLM flexibility, distributed services, AI debugging interface, and integration support. Users can get started with TraceRoot Cloud for a 7-day trial or self-host the tool. SDKs are available for Python and JavaScript/TypeScript.

Pulse is a real-time monitoring tool designed for Proxmox, Docker, and Kubernetes infrastructure. It provides a unified dashboard to consolidate metrics, alerts, and AI-powered insights into a single interface. Suitable for homelabs, sysadmins, and MSPs, Pulse offers core monitoring features, AI-powered functionalities, multi-platform support, security and operations features, and community integrations. Pulse Pro unlocks advanced AI analysis and auto-fix capabilities. The tool is privacy-focused, secure by design, and offers detailed documentation for installation, configuration, security, troubleshooting, and more.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

LLMariner is an extensible open source platform built on Kubernetes to simplify the management of generative AI workloads. It enables efficient handling of training and inference data within clusters, with OpenAI-compatible APIs for seamless integration with a wide range of AI-driven applications.

OpenMeter is a real-time and scalable usage metering tool for AI, usage-based billing, infrastructure, and IoT use cases. It provides a REST API for integrations and offers client SDKs in Node.js, Python, Go, and Web. OpenMeter is licensed under the Apache 2.0 License.

Batteries Included is an all-in-one platform for building and running modern applications, simplifying cloud infrastructure complexity. It offers production-ready capabilities through an intuitive interface, focusing on automation, security, and enterprise-grade features. The platform includes databases like PostgreSQL and Redis, AI/ML capabilities with Jupyter notebooks, web services deployment, security features like SSL/TLS management, and monitoring tools like Grafana dashboards. Batteries Included is designed to streamline infrastructure setup and management, allowing users to concentrate on application development without dealing with complex configurations.

MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

This repository contains reference architectures and test cases for distributed model training with Amazon SageMaker Hyperpod, AWS ParallelCluster, AWS Batch, and Amazon EKS. The test cases cover different types and sizes of models as well as different frameworks and parallel optimizations (Pytorch DDP/FSDP, MegatronLM, NemoMegatron...).

The AWS Generative AI Constructs Library is an open-source extension of the AWS Cloud Development Kit (AWS CDK) that provides multi-service, well-architected patterns for quickly defining solutions in code to create predictable and repeatable infrastructure, called constructs. The goal of AWS Generative AI CDK Constructs is to help developers build generative AI solutions using pattern-based definitions for their architecture. The patterns defined in AWS Generative AI CDK Constructs are high level, multi-service abstractions of AWS CDK constructs that have default configurations based on well-architected best practices. The library is organized into logical modules using object-oriented techniques to create each architectural pattern model.

OpenVINO™ Model Server (OVMS) is a high-performance system for serving models. Implemented in C++ for scalability and optimized for deployment on Intel architectures, the model server uses the same architecture and API as TensorFlow Serving and KServe while applying OpenVINO for inference execution. Inference service is provided via gRPC or REST API, making deploying new algorithms and AI experiments easy.

Deploy langgenius/dify, an LLM based chat bot app on kubernetes with helm chart.