AI tools for cnc
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Toolpath
Toolpath is an AI-powered CAM automation tool for CNC machining. It analyzes parts for machinability, estimates costs, plans machining strategies, and generates CAM programs for Autodesk Fusion. The tool utilizes AI to optimize toolpaths and increase CNC machining productivity. Toolpath simplifies workflow by automating setup and toolpath generation, allowing users to focus on machining. It offers intelligent estimating, seamless CAM integration, and design for manufacturing capabilities. Designed by machinists, Toolpath aims to help both new and experienced users save time, reduce waste, and enhance productivity in the field of CNC machining.

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CNC Master
All things CNC to be learned, calculated and considered here. Lots of model training for typical consumer and pro-sumer CNC machining technology!

kitops
KitOps is a CNCF open standards project for packaging, versioning, and securely sharing AI/ML projects. It provides a unified solution for packaging, versioning, and managing assets in security-conscious enterprises, governments, and cloud operators. KitOps elevates AI artifacts to first-class, governed assets through ModelKits, which are tamper-proof, signable, and compatible with major container registries. The tool simplifies collaboration between data scientists, developers, and SREs, ensuring reliable and repeatable workflows for both development and operations. KitOps supports packaging for various types of models, including large language models, computer vision models, multi-modal models, predictive models, and audio models. It also facilitates compliance with the EU AI Act by offering tamper-proof, signable, and auditable ModelKits.

HAMi
HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

kubesphere
KubeSphere is a distributed operating system for cloud-native application management, using Kubernetes as its kernel. It provides a plug-and-play architecture, allowing third-party applications to be seamlessly integrated into its ecosystem. KubeSphere is also a multi-tenant container platform with full-stack automated IT operation and streamlined DevOps workflows. It provides developer-friendly wizard web UI, helping enterprises to build out a more robust and feature-rich platform, which includes most common functionalities needed for enterprise Kubernetes strategy.

netdata
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.

fluid
Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.

ai-gateway
Envoy AI Gateway is an open source project that utilizes Envoy Gateway to manage request traffic from application clients to Generative AI services. The project aims to provide a seamless and efficient solution for handling communication between clients and AI services. It is designed to enhance the performance and scalability of AI applications by leveraging the capabilities of Envoy Gateway. The project welcomes contributions from the community and encourages collaboration to further develop and improve the functionality of the AI Gateway.

lfai-landscape
LF AI & Data Landscape is a map to explore open source projects in the AI & Data domains, highlighting companies that are members of LF AI & Data. It showcases members of the Foundation and is modelled after the Cloud Native Computing Foundation landscape. The landscape includes current version, interactive version, new entries, logos, proper SVGs, corrections, external data, best practices badge, non-updated items, license, formats, installation, vulnerability reporting, and adjusting the landscape view.

holmesgpt
HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

DaoCloud-docs
DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

k8sgateway
K8sGateway is a feature-rich, fast, and flexible Kubernetes-native API gateway built on Envoy proxy and Kubernetes Gateway API. It excels in function-level routing, supports legacy apps, microservices, and serverless. It offers robust discovery capabilities, seamless integration with open-source projects, and supports hybrid applications with various technologies, architectures, protocols, and clouds.

ai-platform-engineering
The AI Platform Engineering repository provides a collection of tools and resources for building and deploying AI models. It includes libraries for data preprocessing, model training, and model serving. The repository also contains example code and tutorials to help users get started with AI development. Whether you are a beginner or an experienced AI engineer, this repository offers valuable insights and best practices to streamline your AI projects.

mcp-apache-spark-history-server
The MCP Server for Apache Spark History Server is a tool that connects AI agents to Apache Spark History Server for intelligent job analysis and performance monitoring. It enables AI agents to analyze job performance, identify bottlenecks, and provide insights from Spark History Server data. The server bridges AI agents with existing Apache Spark infrastructure, allowing users to query job details, analyze performance metrics, compare multiple jobs, investigate failures, and generate insights from historical execution data.

admet_ai
ADMET-AI is a platform for ADMET prediction using Chemprop-RDKit models trained on ADMET datasets from the Therapeutics Data Commons. It offers command line, Python API, and web server interfaces for making ADMET predictions on new molecules. The platform can be easily installed using pip and supports GPU acceleration. It also provides options for processing TDC data, plotting results, and hosting a web server. ADMET-AI is a machine learning platform for evaluating large-scale chemical libraries.

airflint
Airflint is a tool designed to enforce best practices for all your Airflow Directed Acyclic Graphs (DAGs). It is currently in the alpha stage and aims to help users adhere to recommended practices when working with Airflow. Users can install Airflint from PyPI and integrate it into their existing Airflow environment to improve DAG quality. The tool provides rules for function-level imports and jinja template syntax usage, among others, to enhance the development process of Airflow DAGs.

crab
CRAB is a framework for building LLM agent benchmark environments in a Python-centric way. It is cross-platform and multi-environment, allowing the creation of agent environments supporting various deployment options. The framework offers easy-to-use configuration with the ability to add new actions and define environments seamlessly. CRAB also provides a novel benchmarking suite with tasks and evaluators defined in Python, along with a unique graph evaluator method for detailed metrics.

knowledge
This repository serves as a personal knowledge base for the owner's reference and use. It covers a wide range of topics including cloud-native operations, Kubernetes ecosystem, networking, cloud services, telemetry, CI/CD, electronic engineering, hardware projects, operating systems, homelab setups, high-performance computing applications, openwrt router usage, programming languages, music theory, blockchain, distributed systems principles, and various other knowledge domains. The content is periodically refined and published on the owner's blog for maintenance purposes.

kgateway
Kgateway is a feature-rich, fast, and flexible Kubernetes-native API gateway built on top of Envoy proxy and the Kubernetes Gateway API. It excels in function-level routing, supports legacy apps, microservices, and serverless, offers robust discovery capabilities, integrates seamlessly with open-source projects, and is designed to support hybrid applications with various technologies, architectures, protocols, and clouds.

KAI-Scheduler
KAI Scheduler is a robust, efficient, and scalable Kubernetes scheduler optimized for GPU resource allocation in AI and machine learning workloads. It supports batch scheduling, bin packing, spread scheduling, workload priority, hierarchical queues, resource distribution, fairness policies, workload consolidation, elastic workloads, dynamic resource allocation, GPU sharing, and works in both cloud and on-premise environments.

kai
Kai is an AI-enabled tool that simplifies the process of modernizing application source code to a new platform. It uses Large Language Models (LLMs) guided by static code analysis, along with data from Konveyor. This data provides insights into how the organization solved similar problems in the past, helping streamline and automate the code modernization process. Kai assists developers by providing suggestions and solutions to common problems through Retrieval Augmented Generation (RAG), working with LLMs using Konveyor analysis reports about the codebase and generating solutions based on previously solved examples.

arkflow
ArkFlow is a high-performance Rust stream processing engine that seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis. It supports multiple input/output sources and processors, enabling easy loading and execution of machine learning models for streaming data and inference, anomaly detection, and complex event processing. The tool is built on Rust and Tokio async runtime, offering excellent performance and low latency. It features built-in SQL queries, Python script, JSON processing, Protobuf encoding/decoding, and batch processing capabilities. ArkFlow is extensible with a modular design, making it easy to extend with new components.