Search Results for "hydra"
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Showing 67 open source projects for "hydra"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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hydra
Cloud native, security-first, API security for your infrastructure
Secure access to your applications and APIs, and authenticate third party users. Ory / Hydra is Open Source and OpenID Connect Certified® technology that integrates with any login system. Get started in minutes, and provide secure access to your application and API endpoints. Ory / Hydra works with any login system and only a few lines of code are required. Ory / Hydra is written in Go and we provide SDKs for every language. -
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thc-hydra
Shows how easy it would be to gain unauthorized access to a system
Number one of the biggest security holes are passwords, as every password security study shows. This tool is a proof of concept code, to give researchers and security consultants the possibility to show how easy it would be to gain unauthorized access from remote to a system. There are already several login hacker tools available, however, none does either support more than one protocol to attack or support parallelized connects. It was tested to compile cleanly on Linux, Windows/Cygwin,... -
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Hydra Columnar
Postgres-native columnar storage extension
Hydra enables hybrid row-column storage, making it ideal for OLAP workloads on Postgres. -
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fosite
Extensible security first OAuth 2.0 and OpenID Connect SDK for Go
...OpenID Connect is implemented according to OpenID Connect Core 1.0 incorporating errata set 1 and includes all flows: code, implicit, and hybrid. OAuth2 and OpenID Connect are difficult protocols. If you want quick wins, we strongly encourage you to look at Hydra. Hydra is a secure, high-performance, cloud native OAuth2 and OpenID Connect service that integrates with every authentication method imaginable and is built on top of Fosite. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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ts-hydra-rfc8693
An implementation of RFC 8693 for Ory Hydra, providing powerful capabilities for token exchange in OAuth 2.0 and OpenID Connect servers.
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Reactive Trader
Real-time FX trading showcase by Adaptive
Reactive Trader® is a real-time FX trading platform designed to showcase reactive programming principles across the full application stack. Written in React and RxJs / React-RxJs and running on Hydra, the platform will continue to evolve and use the latest technologies. -
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Pocket ID
Easy-to-use OIDC provider that allows to authenticate with passkeys
...By supporting passkeys instead of traditional passwords, Pocket-ID aligns with evolving web authentication standards, letting users sign in with devices, hardware keys like YubiKey, or platform-managed credentials. It’s designed to be simpler to install and use than larger identity solutions like Keycloak or Hydra and integrates smoothly with other self-hosted applications that understand OIDC protocols. With Docker-ready setup and broad community interest, the project supports a fully self-managed authentication stack where you control user identity, sessions, and login flows without relying on third-party services. It has gained popularity in the self-hosted ecosystem as a straightforward way to add single sign-on capabilities and modern security to your apps. -
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OpenUSD
Universal Scene Description
...With many of its features geared towards performance and large-scale collaboration among many artists, USD is ideal for the complexities of the modern pipeline. One such feature is Hydra, a high-performance preview renderer capable of interactively displaying large data sets. USD supports a variety of file formats, including usda, usdc, and usdz (a zero-compression, unencrypted zip archive), facilitating flexibility in data representation and exchange. The framework also includes tools like usdedit, a script that converts any single USD-readable file into its .usda text equivalent for easy editing. -
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Inscryption Hydra Tracker
A tool to help unlock the Hydra in Inscryption
This tool will help you transform the Curious Egg card into a Hydra by making it easy to see which cards you have, what you need, and what you can get rid of. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Eclipse UXP Projects Lun3r and Hydra
Lun3r/Hydra are forks of Pale Moon/Basilisk with more optimizations.
...Some advantages over upstream and roytam1's New Moon are more optimizations and better interoperability with upstream. (using SQL storage intead of DBM) Eclipse Hydra is a fork of Basilisk made for Windows XP. Some advantages over upstream and roytam1's Serpent are more optimizations and better interoperability with upstream. (using SQL storage intead of DBM) -
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API Platform Core
The server component of API Platform, hypermedia and GraphQL APIs
...It is a component of the API Platform framework and it can be integrated with the Symfony framework using the bundle distributed with the library. It natively supports popular open formats including JSON for Linked Data (JSON-LD), Hydra Core Vocabulary, OpenAPI v2 (formerly Swagger) and v3, HAL and Problem Details. Build a working and fully-featured CRUD API in minutes. Leverage the awesome features of the tool to develop complex and high-performance API-first projects. Extend or override everything you want. -
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Diffusion for World Modeling
Learning agent trained in a diffusion world model
Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within... -
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Fast3R
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Fast3R is Meta AI’s official CVPR 2025 release for “Towards 3D Reconstruction of 1000+ Images in One Forward Pass.” It represents a next-generation feedforward 3D reconstruction model capable of producing dense point clouds and camera poses for hundreds to thousands of images or video frames in a single inference pass—eliminating the need for slow, iterative structure-from-motion pipelines. Built on PyTorch Lightning and extending concepts from DUSt3R and Spann3r, Fast3R unifies multi-view... -
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Matcha-TTS
A fast TTS architecture with conditional flow matching
Matcha-TTS is a non-autoregressive neural text-to-speech architecture that uses conditional flow matching to generate speech quickly while maintaining natural quality. It models speech as an ODE-based generative process, and conditional flow matching lets it reach high-quality audio in only a few synthesis steps, which greatly reduces latency compared to score-matching diffusion approaches. The model is fully probabilistic, so it can generate diverse realizations of the same text while still... -
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Solar Thermal Pipe Network Analysis
HYDRA - pipe network analysis for solar plants
HYDRA is an VBA/EXCEL program for pipe network analysis of large solar thermal plants with collector areas of several thousands of square meters. - Hydraulic solar circuits can be modelled in detail. The main capabilities are: - Stationary flow-, temperature- and pressure distribution of large collector fields are calculated under arbitrary boundary conditions - cost-effective pipe routing and pipe dimensioning - automatic generation of diagrams for documentation - Dimensioning of Drainback systems with atmospheric storage tank, including the following tasks: - Pipe dimensioning for proper venting - Dimensioning of overflow valve - Proof of dissipation capability by simulation of steam range - Dimensioning overflow valve -
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hookprobe
Free AI that blocks hackers while you sleep. Runs on cheap hardware
...It combines eBPF/XDP kernel-level packet filtering with machine learning threat classification to deliver autonomous network security with zero cloud dependency. The stack includes NAPSE (AI packet inspection), HYDRA (threat intelligence pipeline), SENTINEL (ML classification engine), and AEGIS (autonomous defense orchestrator). In production, a single Raspberry Pi 5 processes 11M+ security events, classifies 177K ML verdicts, and tracks 11,800+ attacker IPs — all autonomously. Key features: - 5-minute install on Raspberry Pi 5 or any Linux device - eBPF/XDP wire-speed packet filtering and DDoS mitigation - ML-based threat classification (benign/suspicious/malicious - Real-time QSecBit security posture scoring - Web dashboard with live threat visualization - Post-quantum cryptography (Kyber KEM) - Collective mesh defense across nodes -
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*Until you install the operating system, the default user = live / no password. DragonOS Noble (24.04) DragonOS FocalX (22.04) and DragonOS Focal (20.04) are out-of-the-box Lubuntu based x86_64 operating systems for anyone interested in software defined radios. All source installed software is located in the /usr/src directory while the remaining software was installed by package managers. What is DragonOS and why do you want it? The shortest distance between two points is a...
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Lightning-Hydra-Template
PyTorch Lightning + Hydra. A very user-friendly template
...Not fitted for data engineering - the template configuration setup is not designed for building data processing pipelines that depend on each other. PyTorch Lightning, a lightweight PyTorch wrapper for high-performance AI research. Think of it as a framework for organizing your PyTorch code. Hydra, a framework for elegantly configuring complex applications. The key feature is the ability to dynamically create a hierarchical configuration by composition and override it through config files and the command line. -
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Changelog: • Upstreamed to 4.14.318 • Used Ubuntu Pure Linux Clang 14.0.1 in HYDRA PLUS • Used Azure Clang 15.0.0 in HYDRA Stable • Used AOSP Clang 14.0.0 in SuperUser Version • Schedutil default in Stable Variant and Plus Variant • Reduced display power usage significantly only (11%/h → 6%/h) (for both plus and stable variant) • Supports Fast Charging in Plus Variant • Major Other Changelogs aren't stated here 6.13 : HYDRA KERNELS DRAGON TC AND PROTON CLANG CHANGELOGS : Last changelog: 6.13 - DragonTC1 hour ago - Linux 4.14.301 - Build with DragonToolchain 10.0 + LLD Linker - Sychronized codes with Redmi Note 8 pro MIUI 12.5-R-OSS(DragonTC) - Fixed all the bugs which were present in v5.13 - Saturated Source according to modifies branches with SLMK - Flash Charging Enabled - Fixed All Other Problem with Laggy UI - Added Better battery balance in Proton Clang - UI/UX More smooth Note : 1.)Dragon TC for gaming (note that this is particularly for gaming,
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Hydra Framework
Framework for elegantly configuring complex applications
Hydra lets you focus on the problem at hand instead of spending time on boilerplate code like command-line flags, loading configuration files, logging etc. With Hydra, you can compose your configuration dynamically, enabling you to easily get the perfect configuration for each run. You can override everything from the command line, which makes experimentation fast, and removes the need to maintain multiple similar configuration files. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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Hydra Booster
A DHT Indexer node & Peer Router
...The total number of heads a single Hydra can have depends on the resources of the machine it's running on. To get the desired number of heads you may need to run multiple Hydras on multiple machines. -
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
...The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. Task driven implementation with dynamic model and dataset resolution from arguments. ... -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
...The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. The codebase includes training and evaluation scripts, configuration management via Hydra, and pretrained models on standard noise datasets.
