Search Results for "node-red" - Page 17
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Showing 1427 open source projects for "node-red"
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BehaviorTree.CPP
C++ behavior tree library for robotics and AI decision systems
BehaviorTree.CPP is a C++ library designed to create, manage, and execute behavior trees, a widely used model for decision-making in robotics and artificial intelligence systems. It provides a flexible and modular framework that allows developers to define complex behaviors as reusable tree structures composed of nodes. BehaviorTree.CPP emphasizes performance and real-time execution, making it particularly suitable for robotics applications where responsiveness is critical. It supports... -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. ... -
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Cube Studio
Cube Studio open source cloud native one-stop machine learning
Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data... -
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Hypermind
The high-availability solution to a problem that doesn't exist
Hypermind is a whimsical yet technically intriguing decentralized application that combines a peer-to-peer (P2P) network counter with ephemeral chat functionality, built to “solve” the meta-problem of tracking how many peers are running its container in a decentralized mesh. There’s no central server or database; instead, Hypermind leverages a Distributed Hash Table (DHT) using Hyperswarm to discover peers and maintain approximate counts of active nodes, architected to be a fully... -
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Christmas Tree
Just a simple Christmas tree, based on reddit story
atree is a lightweight JavaScript library for managing and visualizing hierarchical tree data structures in a flexible and efficient way. It offers core abstractions for creating nodes, building parent–child relationships, and traversing trees with utilities for depth, breadth, and custom iteration strategies. Because tree structures are ubiquitous in computing—from file systems and organizational charts to DOM structures and evolutionary taxonomies—atree provides a reusable foundation for... -
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Dafthunk
A workflow execution platform built on top of the fantastic Cloudflare
Dafthunk is a browser-first visual workflow automation platform that lets you build, run, and monitor workflows without standing up a traditional server stack. It’s designed around durable, multi-step execution so workflows can keep going (and recover) even when individual steps fail, time out, or need retries. The platform is closely aligned with Cloudflare’s ecosystem, using edge-native building blocks for execution, orchestration, and storage so workflows can run near users with low... -
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Memories
Build a full stack MERN application
Project MERN Memories is a full-stack application built as a learning tutorial, using the MERN stack: React on the front end, Node.js and Express on the back end, and MongoDB for data persistence. The app is called “Memories” and allows users to post interesting events from their lives (memories), providing a simple social media–style interface and back-end API to support create, read, update, delete of posts. The repository is tied to a video tutorial series that covers the project from... -
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EPLB
Expert Parallelism Load Balancer
...EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. It uses policies like hierarchical load balancing (grouped experts placed at node and then GPU level) and global load balancing depending on configuration. The logic is implemented in eplb.py and supports predicting placements given estimated expert usage weights. EPLB aims to reduce hot-spotting and ensure more uniform usage of compute resources in large MoE deployments. -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,... -
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OpenYurt
Extending your native Kubernetes to edge(project under CNCF)
OpenYurt is built based on upstream Kubernetes and is now hosted by the Cloud Native Computing Foundation(CNCF) as a Sandbox Level Project. OpenYurt has been designed to meet various DevOps requirements against typical edge infrastructures. It provides a consistent user experience for managing the edge applications as if they were running in the cloud infrastructure. It addresses specific challenges for cloud-edge orchestration in Kubernetes such as unreliable or disconnected cloud-edge... -
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qryn
All-in-one Polyglot Observability stack with ClickHouse storage
...Let's get Polyglot. qryn independently implements popular observability standards, protocols and query languages. Make sure you have sufficient memory and disk resources allocated for your node service and clickhouse server when dealing with large amounts of data and fingerprints. We suggest 8GB RAM or higher for most setups with 100k-1M fingerprints. Observe your daily and weekly data consumption to forecast your disk usage requirements. Compression codecs and other optimizations can be performed at the ClickHouse level. -
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Hyprspace
A Lightweight VPN Built on top of IPFS + Libp2p
...Libp2p is a networking library created by Protocol Labs that allows nodes to discover each other using a Distributed Hash Table. Paired with NAT hole punching this allows Hyprspace to create a direct encrypted tunnel between two nodes even if they're both behind firewalls. Moreover! Each node doesn't even need to know the other's ip address prior to starting up the connection. This makes Hyprspace perfect for devices that frequently migrate between locations but still require a constant virtual ip address. -
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Project Lotus
Reference implementation of the Filecoin protocol, written in Go
Lotus is the reference implementation for the Filecoin network. It is written in Go, and is maintained by the Protocol Labs team. This website contains all the information you need to spin up a Lotus node, become a Filecoin storage provider, or just tinker around with the Filecoin network! Filecoin is a network of computers that allows you to store your data online. But while online storage services aren't anything new, Filecoin is different. It doesn't use centralized servers to store your data or rely on aggressive analytics tactics to make a profit and pay its shareholders. ... -
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Ember Infinity
Simple, flexible Infinite Scroll for Ember CLI Apps
Simple, flexible Infinite Scroll for Ember CLI Apps. As of v2.0.0, we support Node 10 and above. We test against ember-source > 3.8. Try out v2.0.0. If it doesn't work or you don't have the right polyfills because you are on an older Ember version, then v1.4.9 will be your best bet. Ember Infinity is based on a component-service approach wherein your application is viewed as an interaction between your components (ephemeral state) and service (long-term state). -
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level
Universal abstract-level database for Node.js and browsers
...At the time of writing, level works in Node.js 12+ and Electron 5+ on Linux, Mac OS, Windows and FreeBSD, including any future Node.js and Electron release thanks to Node-API, including ARM platforms like Raspberry Pi and Android, as well as in Chrome, Firefox, Edge, Safari, iOS Safari and Chrome for Android. -
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Stacks
The Stacks 2.0 blockchain implementation
...Normal releases in this repository that add features such as improved RPC endpoints, improved boot-up time, new event observer fields or event types, etc., are released on a monthly schedule. The currently staged changes for such releases are in the development branch. It is generally safe to run a stacks-node from that branch, though it has received less rigorous testing than release tags. If bugs are found in the develop branch, please do report them as issues on this repository. -
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Babel Loader
Babel loader for webpack
...You can instead require the Babel runtime as a separate module to avoid the duplication. Webpack supports bundling multiple targets. For cases where you may want different Babel configurations for each target (like web and node), this loader provides a target property via Babel's caller API. -
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Murex
A smarter shell and scripting environment with advanced features
...Usability improvements such as in-line spell checking, context-sensitive hint text that details the behavior of a command before you hit return, and auto-parsing man pages for auto-completions on commands that don't have auto-completions already defined. Smarter handling of errors and debugging tools. For example try/catch blocks, line numbers included in error messages, STDOUT highlighted in red and script testing and debugging frameworks baked into the language itself. -
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Pacu
The AWS exploitation framework, designed for testing security
...Written in Python 3 with a modular architecture, Pacu has tools for every step of the pen testing process, covering the full cyber kill chain. Pacu is the aggregation of all of the exploitation experience and research from our countless prior AWS red team engagements. Automating components of the assessment not only improves efficiency but also allows our assessment team to be much more thorough in large environments. What used to take days to manually enumerate can be now be achieved in minutes. There are currently over 35 modules that range from reconnaissance, persistence, privilege escalation, enumeration, data exfiltration, log manipulation, and miscellaneous general exploitation. -
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Harvester
Open source hyperconverged infrastructure (HCI) software
Harvester is a modern, open, interoperable, hyperconverged infrastructure (HCI) solution built on Kubernetes. It is an open-source alternative designed for operators seeking a cloud-native HCI solution. Harvester runs on bare metal servers and provides integrated virtualization and distributed storage capabilities. In addition to traditional virtual machines (VMs), Harvester supports containerized environments automatically through integration with Rancher. It offers a solution that unifies... -
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Exq
Job processing library for Elixir - compatible with Resque / Sidekiq
...Exq uses Redis as a store for background processing jobs. Exq handles concurrency, job persistence, job retries, reliable queueing and tracking so you don't have to. Jobs are persistent so they would survive across node restarts. You can use multiple Erlang nodes to process from the same pool of jobs. Exq uses a format that is Resque/Sidekiq compatible. This means you can use it to integrate with existing Rails / Django projects that also use a background job that's Resque compatible - typically with little or no changes needed to your existing apps. ... -
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FreeTAKServer
Situational Awareness Server compatible with TAK clients
FTS is a Python3 implementation of a TAK Server for devices like ATAK, WinTAK, and ITAK, it is cross-platform and runs from a multi-node installation on AWS down to the Android edition. It's free and open source (released under the Eclipse Public License. FTS allows you to connect ATAK clients to share geo-information, to chat with all the connected clients, exchange files and more. It intends to support all the major use cases of the original TAK server. -
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Fractals
Fractals is a recursive task orchestrator for agent swarm
...The system takes a high-level goal and decomposes it into a hierarchy of smaller subtasks, forming a self-similar tree that resembles a fractal structure. Each leaf node of this tree represents a specific executable task that can be processed independently by an AI agent. The framework runs these subtasks in isolated Git worktrees so agents can work on separate components of a project without interfering with one another. By coordinating these agents through a recursive task decomposition strategy, the system allows large problems to be solved collaboratively by multiple AI processes. ... -
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OmAgent
Build multimodal language agents for fast prototype and production
...The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. Its architecture uses a graph-based workflow engine where tasks are represented as nodes in a directed workflow, enabling modular composition of complex reasoning pipelines. The framework also includes support for various reasoning strategies commonly used in language agents, such as chain-of-thought prompting, self-consistency reasoning, and ReAct-style decision loops. -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
...The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. A prompt-based loss function is then applied to evaluate the quality of the outcome, generating language-based gradients that guide improvements to the agent pipeline.
