Search Results for "network tools"
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55 projects for "network tools" with 2 filters applied:
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Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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Next-generation security awareness training. Built for AI email phishing, vishing, smishing, and deepfakes.Assess how your company's digital footprint can be leveraged by cybercriminals. Identify the most at-risk individuals using thousands of public data points and take steps to proactively defend them.
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Python Code Tutorials
The Python Code Tutorials
...The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and applications step by step. Many tutorials focus on practical implementations such as building network scanners, web scraping tools, object detection systems, and automation utilities using Python libraries. The repository is organized into thematic directories that group tutorials by topic, allowing learners to navigate easily between areas such as ethical hacking, multimedia processing, or machine learning. -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. 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. ... -
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BitNet
BitNet: Scaling 1-bit Transformers for Large Language Models
BitNet is a machine learning research implementation that explores extremely low-precision neural network architectures designed to dramatically reduce the computational cost of large language models. The project implements the BitNet architecture described in research on scaling transformer models using extremely low-bit quantization techniques. In this approach, neural network weights are quantized to approximately one bit per parameter, allowing models to operate with far lower memory... -
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TurboQuant PyTorch
From-scratch PyTorch implementation of Google's TurboQuant
TurboQuant PyTorch is a specialized deep learning optimization framework designed to accelerate neural network inference and training through advanced quantization techniques within the PyTorch ecosystem. The project focuses on reducing the computational and memory footprint of models by converting floating-point representations into lower-precision formats while preserving performance. It provides tools for experimenting with different quantization strategies, enabling developers to balance accuracy and efficiency depending on their application. ... -
The ultimate digital workspace.Hundreds of companies and millions of employees use Axero’s intranet software to communicate, collaborate, manage tasks and events, organize content, and develop their company culture.
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Harbor LLM
Run a full local LLM stack with one command using Docker
...It combines a CLI and companion app to launch backends, frontends, and supporting services with minimal setup. With a single command, users can start preconfigured tools like Ollama and Open WebUI, enabling chat, workflows, and integrations immediately. Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user interfaces. It also includes tools for web retrieval, image generation, voice interaction, and workflow automation. Built on Docker, Harbor allows services to run in isolated containers while communicating over a local network. ... -
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TurboQuant+
Implementation of TurboQuant (ICLR 2026)
TurboQuant Plus is an extended and enhanced version of quantization tooling aimed at improving neural network efficiency through advanced compression and optimization strategies. It builds upon the concept of reducing model precision to accelerate inference while attempting to maintain or recover accuracy through refined techniques. The project explores additional enhancements such as improved calibration, adaptive quantization, and potentially hybrid precision approaches that combine... -
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Oh My OpenAgent
The best agent harness
...It builds on the idea that no single model is sufficient, instead enabling coordinated use of multiple models for reasoning, creativity, speed, and cost efficiency within a single workflow. The system is designed as a comprehensive agent harness where tasks are automatically decomposed, delegated, and executed across a network of specialized agents. It emphasizes openness and flexibility, allowing developers to integrate different providers and avoid dependency on any single ecosystem or vendor. The framework includes robust tooling for managing agent workflows, monitoring execution, and integrating external tools, making it suitable for complex, production-level use cases. ... -
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MuseGAN
An AI for Music Generation
MuseGAN is a deep learning research project designed to generate symbolic music using generative adversarial networks. The system focuses specifically on generating multi-track polyphonic music, meaning that it can simultaneously produce multiple instrument parts such as drums, bass, piano, guitar, and strings. Instead of generating raw audio, the model operates on piano-roll representations of music, which encode notes as time-pitch matrices for each instrument track. This representation... -
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imgclsmob Deep learning networks
Sandbox for training deep learning networks
imgclsmob is a deep learning research repository focused on implementing and experimenting with convolutional neural networks for computer vision tasks. The project serves as a sandbox for training and evaluating a wide variety of neural network architectures used in image analysis. It includes implementations of models used for tasks such as image classification, object detection, semantic segmentation, and pose estimation. The repository also contains scripts that help train models,... -
AI-Powered Identity GovernanceDefine governance policies, manage access, and optimize licenses with unified visibility across every identity, app, and file.
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KeepChatGPT
Browser userscript that enhances ChatGPT reliability and usability
KeepChatGPT is an open source browser userscript designed to enhance the reliability, usability, and efficiency of the ChatGPT web interface. It runs through userscript managers and injects additional functionality directly into the page, allowing users to improve their workflow without requiring a backend service or separate application. It focuses on solving common problems experienced during AI conversations, such as session timeouts, network errors, message failures, and interruptions... -
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Integuru v0
The first AI agent that builds permissionless integrations
...This approach allows developers to automate workflows and build integrations with services that do not provide official APIs or developer tools. The project is designed as a research platform for exploring AI-driven automation and integration generation. -
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MiroFlow
Agent framework that enables tool-use agent tasks
...The system introduces a hierarchical architecture that organizes components into control, agent, and foundation layers, allowing developers to manage agent orchestration and tool interactions in a structured manner. One of the core innovations of MiroFlow is its use of agent graphs, which enable flexible orchestration of multiple sub-agents and tools in order to complete complex workflows. This architecture allows agents to perform advanced reasoning tasks such as deep research, future event prediction, and multi-step knowledge analysis. The framework emphasizes reliability and scalability by incorporating robust workflow execution, concurrency management, and fault-tolerant design to handle unstable APIs or network conditions. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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Moltworker
Run OpenClaw on Cloudflare Workers
Moltworker is an experimental Cloudflare Workers-based project that allows users to run OpenClaw (previously known as Moltbot or Clawdbot), a self-hosted personal AI agent, within the Cloudflare Developer Platform rather than on dedicated hardware. Acting as a middleware Worker and script adaptor, moltworker packages the OpenClaw agent and its dependencies into a Cloudflare Sandbox container that can operate at scale on the global edge network, offering an always-on deployment without users... -
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mcpo
A simple, secure MCP-to-OpenAPI proxy server
...This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI documentation that shows end-to-end integration. It supports running multiple tools and makes them discoverable to clients that expect Swagger/JSON schemas. In practice, mcpo shortens the path from a local MCP tool to a shareable, network-accessible microservice. -
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Browser MCP
Browser MCP is a Model Context Provider (MCP) server
Browser MCP is an MCP server plus browser integration that lets AI apps automate the user’s real browser instead of launching a separate automation session. By adapting a Playwright-style approach to control the running browser profile, it reuses logged-in sessions and cookies, which reduces re-authentication friction and helps avoid some bot-detection heuristics. The server exposes structured tools for navigation, element interaction, and artifact capture (DOM, screenshots, logs), all... -
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Beelzebub
A secure low code honeypot framework
Beelzebub is an open-source cybersecurity framework designed to create intelligent honeypot environments for detecting and studying cyber attacks. Honeypots are systems intentionally exposed to attackers in order to capture malicious behavior, and Beelzebub enhances this concept by incorporating artificial intelligence and virtualization techniques. The platform allows organizations and researchers to deploy decoy services that mimic real infrastructure while recording attacker interactions.... -
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face.evoLVe
High-Performance Face Recognition Library on PaddlePaddle & PyTorch
face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. The repository supports multiple neural... -
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Instant Neural Graphics Primitives
Instant neural graphics primitives: lightning fast NeRF and more
Instant Neural Graphics Primitives, is an open-source research project developed by NVIDIA that enables extremely fast training and rendering of neural graphics representations. The system implements several neural graphics primitives including neural radiance fields, signed distance functions, neural images, and neural volumes. These representations are trained using a compact neural network combined with a multiresolution hash encoding that dramatically accelerates both training and... -
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UCCL
UCCL is an efficient communication library for GPUs
UCCL is a high-performance GPU communication library designed to support distributed machine learning workloads and large-scale AI systems. The library focuses on enabling efficient data transfer and collective communication between GPUs during training and inference processes. It supports a variety of communication patterns including collective operations such as all-reduce as well as peer-to-peer transfers that are commonly used in modern machine learning architectures. UCCL is designed to... -
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NativeMind Extension
Your fully private, open-source, on-device AI assistant
...The extension is aimed at everyday browser workflows, offering features like multi-tab context awareness, webpage summarization, document understanding, contextual toolbars, and AI-assisted rewriting directly inside the browsing experience. Because it runs locally after setup, it is also positioned as an always-available assistant that avoids API quotas, network latency, and service outages common in cloud-based AI tools. -
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RunAnywhere
Production ready toolkit to run AI locally
RunAnywhere SDKs are a set of cross-platform development tools that enable applications to run artificial intelligence models directly on user devices instead of relying on cloud infrastructure. The toolkit allows developers to integrate language models, speech recognition, and voice synthesis capabilities into mobile or desktop applications while keeping all computation local. By running models entirely on device, the platform eliminates network latency and protects user data because information does not leave the device. ... -
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SpikingJelly
SpikingJelly is an open-source deep learning framework
SpikingJelly is an open-source deep learning framework for spiking neural networks that is primarily built on top of PyTorch and aimed at neuromorphic computing research. The project provides the components needed to build, train, and evaluate neural models that communicate through discrete spikes rather than the continuous activations used in conventional artificial neural networks. This makes it especially relevant for researchers interested in biologically inspired computing, event-driven... -
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SlowFast
Video understanding codebase from FAIR for reproducing video models
SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without... -
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VoxelMorph
Unsupervised Learning for Image Registration
VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so...
