Search Results for "dynamicreports-examples" - Page 67
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Showing 3974 open source projects for "dynamicreports-examples"
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fosite
Extensible security first OAuth 2.0 and OpenID Connect SDK for Go
The security first OAuth2 & OpenID Connect framework for Go. Built simple, powerful, and extensible. This library implements peer-reviewed IETF RFC6749, counterfeits weaknesses covered in peer-reviewed IETF RFC6819 and countermeasures various database attack scenarios, keeping your application safe when that hacker penetrates or leaks your database. OpenID Connect is implemented according to OpenID Connect Core 1.0 incorporating errata set 1 and includes all flows: code, implicit, and... -
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zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite... -
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remark-math
remark and rehype plugins to support math
This project is a monorepo that contains several packages for dealing with math in markdown and HTML. This repository contains unified (rehype and remark) plugins to add support for math. You can use them to add support for parsing and serializing a syntax extension and to render math with KaTeX or MathJax. This project is useful when you want to support LaTeX math. This mechanism works well when you want authors, who have some LaTeX experience, to be able to embed rich diagrams of math to... -
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Jaeger Operator for Kubernetes
Jaeger Operator for Kubernetes simplifies deploying and running Jaeger
The Jaeger Operator is an implementation of a Kubernetes Operator. Operators are pieces of software that ease the operational complexity of running another piece of software. More technically, Operators are a method of packaging, deploying, and managing a Kubernetes application. A Kubernetes application is an application that is both deployed on Kubernetes and managed using the Kubernetes APIs and kubectl (Kubernetes) or oc (OKD) tooling. To be able to make the most of Kubernetes, you need a... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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AutoMLOps
Build MLOps Pipelines in Minutes
AutoMLOps is a service that generates, provisions, and deploys CI/CD integrated MLOps pipelines, bridging the gap between Data Science and DevOps. AutoMLOps provides a repeatable process that dramatically reduces the time required to build MLOps pipelines. The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives... -
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Population Shift Monitoring
Monitor the stability of a Pandas or Spark dataframe
popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two... -
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Hakaton Starter
A boilerplate for Node.js web applications
A boilerplate for Node.js web applications. If you have attended any hackathons in the past, then you know how much time it takes to get a project started: decide on what to build, pick a programming language, pick a web framework, pick a CSS framework. A while later, you might have an initial project up on GitHub, and only then can other team members start contributing. Or how about doing something as simple as Sign in with Facebook authentication? You can spend hours on it if you are not... -
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SOFA
The best way to create REST APIs
Sofa takes your GraphQL Schema, looks for available queries, mutations and subscriptions and turns all of that into REST API. Setup Sofa within a single line of code and start using REST API right away. We want to hear from you, our community of fellow engineers, and come to be collaborators. Sofa takes your GraphQL Schema, looks for available queries, mutations and subscriptions, and turns all of that into REST API. The idea behind Models is to not expose full objects in every response,... -
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Tonic
Easy to audit, zero-dependencies and build-tool-free
...No build tools are required. Native web components. Ideal for JAM stacks. Identical on client & server. Composition oriented. Event delegation by default. Lots of examples. Building a component with Tonic starts by creating a function or a class. The class should have at least one method named render which returns a template literal of HTML. onic is a thin wrapper around web components. Web components require a name with two or more parts. So your class name should be CamelCased (starting with an uppercase letter). ... -
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IndraDB
A graph database written in rust
...IndraDB departs from TAO (and most graph databases) in its support for properties. IndraDB offers a variety ways to work with it: as a server with cross-language support, as a rust library, and via CLI. What follows are a few examples of each use case. -
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Vowpal Wabbit
Machine learning system which pushes the frontier of machine learning
...Vowpal Wabbit is a destination for implementing and maturing state-of-the-art algorithms with performance in mind. The input format for the learning algorithm is substantially more flexible than might be expected. Examples can have features consisting of free-form text, which is interpreted in a bag-of-words way. There can even be multiple sets of free-form text in different namespaces. Similar to the few other online algorithm implementations out there. There are several optimization algorithms available with the baseline being sparse gradient descent (GD) on a loss function. -
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Monoio
Rust async runtime based on io-uring
Monoio is a Rust asynchronous runtime designed for high-performance I/O-bound servers and applications, built around native OS async I/O primitives (e.g. io_uring on Linux, epoll / kqueue on other Unix-like systems), rather than layering atop an existing runtime. Its design philosophy centers on a “thread-per-core” model where each core runs its own event loop, minimizing cross-thread synchronization needs, avoiding the overhead and complexity of task scheduling, and letting developers write... -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
...This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic tour notebook to learn how to use the package's most important features. Take a look at the advanced tour notebook to learn how to make the package more flexible, how to deal with categorical parameters, how to use observers, and more. Explore the options exemplifying the balance between exploration and exploitation and how to control it. ... -
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Bear Stone Smart Home
Custom Home Assistant configuration with automations and scripts setup
...Bear Stone Smart Home also showcases custom automations and scripts designed to improve convenience, energy efficiency, and overall smart home behavior. Additionally, it may include examples of dashboards and user interface customization to enhance usability and visualization of home data. Overall, it serves as a practical reference for building and refining a tailored Home Assistant setup. -
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GC Build official builder images
Builder images and examples commonly used for Google Cloud Build
GC Build official builder images is a repository that provides a collection of prebuilt and customizable container images used with Google Cloud Build to automate CI/CD pipelines. These builder images act as modular steps within build pipelines, allowing developers to perform tasks such as compiling code, running tests, building Docker images, and deploying applications. The repository includes a wide range of builders for different languages, tools, and workflows, enabling flexible and... -
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Interactive Machine Learning Experiments
Interactive Machine Learning experiments
Interactive Machine Learning Experiments is a collection of interactive demonstrations that showcase how various machine learning models can be trained and used in real applications. The project combines Jupyter or Colab notebooks with browser-based visual demos that allow users to see trained models operating in real time. Many experiments involve tasks such as image classification, object detection, gesture recognition, and simple generative models. The models are typically trained in... -
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Generative AI for beginners with JS
Join a time-traveling adventure where you meet history’s legends
Generative AI with JavaScript is an educational repository created by Microsoft that teaches developers how to build applications powered by large language models using the JavaScript ecosystem. The project is structured as a multi-lesson curriculum that introduces the concepts, tools, and practical techniques required to create generative AI applications. Each lesson includes written explanations, hands-on exercises, quizzes, and supporting videos to help developers learn the material... -
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RAG from Scratch
Demystify RAG by building it from scratch
RAG From Scratch is an educational open-source project designed to teach developers how retrieval-augmented generation systems work by building them step by step. Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into... -
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PKU Beaver
Constrained Value Alignment via Safe Reinforcement Learning
...The framework introduces techniques that separate helpfulness and harmlessness signals during training, allowing models to optimize for useful responses while minimizing harmful behavior. To support this process, the project provides datasets containing human-labeled examples that encode both performance preferences and safety constraints across multiple dimensions. These annotations include categories such as harmful language, unethical behavior, privacy violations, and other sensitive topics. By incorporating constraint-based optimization methods, Safe-RLHF trains models that balance reward objectives with safety requirements, ensuring that harmful outputs are penalized during training. -
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Magicoder
Empowering Code Generation with OSS-Instruct
...This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real open-source examples, Magicoder aims to reduce bias and improve the reliability of code generation results compared to models trained solely on synthetic instructions. The project includes model implementations, training resources, and evaluation benchmarks that demonstrate how the approach improves instruction-following and code synthesis capabilities. ... -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external... -
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LearnLLM.AI
Sharing knowledge about big models that everyone can understand
...It covers a wide range of topics including attention mechanisms, tokenization strategies, training techniques, model optimization, and deployment approaches. The repository aims to provide intuitive explanations and practical examples so readers can understand both the theoretical and applied aspects of large language models. In addition to technical explanations, it includes curated interview questions and discussion topics that help readers prepare for industry interviews related to machine learning and generative AI. -
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RSC Explorer
A tool for people curious about the React Server Components protocol
...The core experience is the ability to step through the RSC stream incrementally, seeing what data arrives at each moment and how that data maps to the React tree being constructed. It includes a set of curated examples that demonstrate how server and client features can interoperate, helping you develop intuition for boundaries, references, and progressive rendering. This makes it useful for educators, workshop leaders, and engineers who want to demystify RSC mechanics without relying on framework-specific abstractions. In practice, it functions like a “packet analyzer” for RSC, turning a normally opaque stream into something you can study and explain. -
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ralph-loop-agent
Continuous Autonomy for the AI SDK
...It includes loop control primitives like stop conditions and context management, allowing developers to build sophisticated agent workflows that can persist state, evaluate when to pause, and manage decision boundaries programmatically. Ralph-Loop-Agent is written in TypeScript and designed to integrate smoothly with the broader Vercel AI SDK ecosystem, including examples that tie into web interfaces, Playwright automation, PostgreSQL, and GitHub PR workflows. -
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LLM TLDR
95% token savings. 155x faster queries. 16 languages
...The system supports both extractive and abstractive summarization styles so that users can choose whether they want condensed highlights or a more narrative paraphrase of key ideas. To enhance usability, LLM-TLDR includes command-line tools and integration examples for common workflows like batch summarization, webhook ingestion, and automation in documentation pipelines.
