Search Results for "design" - Page 2
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Showing 214 open source projects for "design"
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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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Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
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KJNodes for ComfyUI
Various custom nodes for ComfyUI
...It supports tasks such as creating parameter schedules, managing conditioning inputs, and combining outputs from different nodes. By expanding the available building blocks, it allows users to design more precise and customizable workflows. The repository is frequently updated with new nodes that address emerging needs in generative AI pipelines. Overall, it serves as a foundational toolkit for advanced ComfyUI users. -
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Trame
Weave various components and technologies into a Web App
Developed by Kitware, trame is a Python-based framework that allows developers to create web applications with desktop-like functionality. It enables the integration of various components and technologies, such as VTK and ParaView, into web applications written entirely in Python. With best-in-class platforms at its core, trame provides complete control of 3D visualizations and data processing. Developers benefit from a write-once environment from trame. trame is an open source project... -
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AudioCraft
Audiocraft is a library for audio processing and generation
...It also contains training code and recipes, so researchers can fine-tune on custom data or explore new objectives without building infrastructure from scratch. Example notebooks, CLI tools, and audio utilities help with prompt design, conditioning on reference audio, and post-processing to produce ready-to-share outputs. -
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Amazon Braket Python SDK
A python SDK for interacting with quantum devices on Amazon Braket
The Amazon Braket Python SDK is an open-source library to design and build quantum circuits, submit them to Amazon Braket devices as quantum tasks, and monitor their execution. Before you begin working with the Amazon Braket SDK, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. As a managed service, Amazon Braket performs operations on your behalf on the AWS hardware that is managed by Amazon Braket. ... -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
...It contains numerous Python scripts organized by topic (lists, dictionaries, loops, functions, classes, modules, etc.), each with code examples, explanations, test assertions, and links to further readings. The design supports “learn by doing”: you can modify the code, run the tests, see how behavior changes, and thus internalize Python language features, idioms, and good style practices (including linting and PEP8). Because it is organized in bite-sized chunks, it’s ideal for beginners or people refreshing their Python skills who want to revisit syntax and common patterns before moving into larger frameworks or applications. ... -
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DeepXDE
A library for scientific machine learning & physics-informed learning
...Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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Azure SDK for Python
Active development of the Azure SDK for Python
...They might not implement the guidelines or have the same feature set as the November releases. They do however offer wider coverage of services. A new set of management libraries that follow the Azure SDK Design Guidelines for Python are now available. -
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bu-agent-sdk
An agent is just a for-loop
...The SDK emphasizes simplicity and control, avoiding heavy orchestration frameworks and instead letting developers specify exactly what tools an agent can employ and how it should signal task completion. This lightweight design means developers can rapidly prototype AI agent behavior, test custom tools, and integrate models like Anthropic’s Claude with minimal overhead. -
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Django Hijack
With Django Hijack, admins can log in and work on behalf of others
With Django Hijack, admins can log in and work on behalf of other users without having to know their credentials. 3.x docs are available in the docs folder. This version provides a security-first design, easy integration, customization, out-of-the-box Django admin support and dark mode. It is a complete rewrite and all former APIs are broken. A form is used to perform a POST including a CSRF-token for security reasons. The field user_pk is mandatory and the value must be set to the target users' primary key. The optional field next determines where a user is forwarded after a successful hijack. ... -
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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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
...Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to plug in custom models, track experiments, tune hyperparameters, and generate visualizations that highlight anomalous regions. Its design supports unsupervised or semi-supervised paradigms, making it especially powerful for scenarios where only “normal” data is readily available and defects must be detected without exhaustive labeling. Combined with its CLI and integration with optimization tools like OpenVINO, it’s suitable for both research and edge deployment tasks. -
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repren
Rename anything
Repren is a “rename anything” command-line tool that performs regex-based search and replace across file contents while also renaming or moving files and directories according to patterns. It’s meant for sweeping refactors: change a class or package name everywhere and update filenames to match in one pass. The design favors explicitness and safety, providing dry-run output so you can preview exactly what will change before executing it. It handles recursive directory walks, lets you filter which files to touch, and supports multiple patterns in a single run to keep transformations consistent. Because it’s script-friendly, it slots well into project maintenance, codebase migrations, or release engineering tasks. ... -
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nbstripout
strip output from Jupyter and IPython notebooks
...You can choose to set the attributes in .gitattributes and commit this file to your repository, however there is no way to have git set up the filters automatically when someone clones a repository. This is by design, to prevent you from executing arbitrary and potentially malicious code when cloning a repository. -
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). The project was originally started as zalando-incubator/kopf in March 2019, and then forked as nolar/kopf in August 2020: but it is the same codebase, the same packages, the same developer(s). ... -
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RecBole
A unified, comprehensive and efficient recommendation library
A unified, comprehensive and efficient recommendation library. We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. -
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Lambda Builders
Python library to compile, build & package AWS Lambda functions
...A build action is a module that knows how to build for a particular programming language & framework (ex: Python+PIP). Build actions can be implemented in Python or in the native programming language. Each build action has its own design document. -
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EKS Best Practices
A best practices guide for day 2 operations
...The repository is maintained by AWS but open to contributions from the community, making it a living document that evolves as Kubernetes and AWS features evolve. Each section dives into operational details—for example, how to manage IAM roles for service accounts, secure the EKS endpoint, handle node auto-scaling, and design for multi-AZ resilience. Because running Kubernetes in production demands many “day-2” considerations (upgrades, drift, monitoring, incident response), the guide provides practical advice beyond simple cluster provisioning. -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation,... -
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Flax
Flax is a neural network library for JAX
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging and compilation model. ... -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
...Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. Its modular design includes tools for tree manipulation, named axes, and declarative neural network construction. The library integrates tightly with Treescope, an advanced pretty-printer for visualizing deeply nested JAX pytrees and NDArray structures. Penzai’s penzai.nn module provides a compositional, combinator-based API for building neural networks. -
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Synthetic Data Kit
Tool for generating high quality Synthetic datasets
...It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. The kit’s design goal is to shorten the “data prep” bottleneck by turning dataset creation into a repeatable pipeline rather than ad-hoc notebooks. It supports generation of rationales/chain-of-thought variants, configurable sampling, and guardrails so outputs meet format constraints and quality checks. Examples and guides show how to target task-specific behaviors like tool use or step-by-step reasoning, then save directly into training-ready files. -
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Multimodal
TorchMultimodal is a PyTorch library
...It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained. -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
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DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP... -
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Status - a Mobile Ethereum OS
A free (libre) open source, mobile OS for Ethereum
...Safely send, store and receive cryptocurrencies including ERC20 and ERC721 tokens with the Status crypto wallet. Only you hold the keys to your funds. Status' intuitive design protects you and your funds from attacks. Status uses an open-source, peer-to-peer protocol, and end-to-end encryption to protect your messages from third parties. Keep your private messages private with Status. Browse the growing ecosystem of DApps including marketplaces, exchanges, games, and social networks. The latest security standards ensure a private browsing experience. ... -
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The Falcon Web Framework
The no-nonsense REST API and microservices framework
...When it comes to building HTTP APIs, other frameworks weigh you down with tons of dependencies and unnecessary abstractions. Falcon cuts to the chase with a clean design that embraces HTTP and the REST architectural style. Highly optimized, extensible code base. Easy access to headers and bodies through request and response objects. DRY request processing via middleware components and hooks. Strict adherence to RFCs. Idiomatic HTTP error responses. Straightforward exception handling. Snappy testing with WSGI/ASGI helpers and mocks. ...
