Search Results for "apache" - Page 87
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Showing 11373 open source projects for "apache"
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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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carbon-components-svelte
Svelte implementation of the Carbon Design System
Carbon Components Svelte is a Svelte-native implementation of IBM’s Carbon Design System, built to bring the structure, consistency, and scalability of a mature enterprise design system into Svelte applications. Rather than being a small collection of ad hoc widgets, it functions as a comprehensive component library intended to support design reuse, predictable development, and long-term extensibility across products. Because it is tied to Carbon, the project is especially valuable for teams... -
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heroui-native
Beautiful, fast and modern React Native UI library
heroui-native is a modern React Native UI component library designed to provide developers with beautiful, high-performance, and accessible mobile interface elements out of the box. Built with Tailwind CSS principles through Uniwind, it allows developers to apply familiar utility-first styling patterns to native mobile development. The library emphasizes design consistency and usability, offering components that are visually polished while maintaining flexibility for customization. Each... -
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Ratzilla
Build terminal-themed web applications with Rust and WebAssembly
Ratzilla is a Rust-based framework for building terminal-style user interfaces that run in the browser using WebAssembly, effectively bringing the aesthetics and interaction patterns of terminal applications to modern web environments. It is built on top of the Ratatui library, which provides composable UI components inspired by text-based interfaces, and adapts them to render within a browser through WebAssembly and DOM-based backends. The framework allows developers to create applications... -
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Stlite
n-browser Streamlit
Stlite is a WebAssembly-powered framework that enables Streamlit applications to run entirely in the browser without requiring a Python backend server. It achieves this by using Pyodide, a WebAssembly-based Python runtime, to execute Python code directly within the browser environment. This allows developers to build interactive data applications using familiar Streamlit APIs while eliminating the need for server-side infrastructure. Stlite supports a wide range of Python libraries and... -
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Wasmi
Efficient and versatile WebAssembly interpreter for embedded systems
wasmi is a lightweight WebAssembly interpreter written in Rust that is designed to execute Wasm binaries efficiently in constrained or embedded environments. Unlike JIT-based runtimes, wasmi focuses on interpretation, prioritizing portability, determinism, and low resource usage over maximum raw performance. It is particularly well-suited for blockchain systems, embedded devices, and other contexts where predictable execution and minimal dependencies are critical. The runtime implements the... -
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wazero
The zero dependency WebAssembly runtime for Go developers
wazero is a zero-dependency WebAssembly runtime written in Go that enables developers to execute WebAssembly modules directly within Go applications without relying on external toolchains or CGO. It fully implements the WebAssembly core specification and supports both interpreter and compiler execution modes, allowing developers to choose between portability and performance. One of its defining characteristics is its pure Go implementation, which simplifies cross-compilation and deployment... -
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wasm-bindgen
Facilitating high-level interactions between Wasm modules and Js
wasm-bindgen is a foundational Rust tool that enables seamless interoperability between Rust and JavaScript by generating the necessary bindings and glue code for WebAssembly modules. It allows developers to write performance-critical code in Rust, compile it to WebAssembly, and then expose functions, structs, and APIs directly to JavaScript in a natural and idiomatic way. The tool automates the process of bridging differences between Rust’s type system and JavaScript’s dynamic environment,... -
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Team9
Team9 is a collaborative workspace for AI agents
Team9 is an AI-native collaborative workspace designed to deploy, manage, and coordinate autonomous agents as if they were members of a human team, enabling organizations to automate complex workflows with minimal setup. It builds on agent frameworks like OpenClaw and introduces a managed environment where agents can be assigned roles, share context, and execute tasks collaboratively. The system emphasizes a “local-first” architecture, allowing agents to run on user-controlled infrastructure... -
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Edgee
AI gateway with token compression for Claude Code, Codex, and more
Edgee is an edge-native execution platform designed to run AI-driven logic and data processing directly at the network edge, reducing latency and improving responsiveness for modern applications. It enables developers to deploy functions and workflows closer to users, allowing real-time processing without relying heavily on centralized cloud infrastructure. The platform is built to support event-driven architectures, where actions are triggered by incoming requests, user behavior, or... -
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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ruff-pre-commit
A pre-commit hook for Ruff
ruff-pre-commit is a lightweight integration that enables the Ruff linter and formatter to run automatically as part of Git pre-commit hooks, ensuring code quality checks are enforced before changes are committed to a repository. It is distributed as a standalone repository to simplify installation and allow developers to use prebuilt wheels directly from package managers. By integrating Ruff into the pre-commit workflow, it helps maintain consistent coding standards across teams by... -
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Elia
Terminal-based LLM chat tool with multi-model and local support
Elia is an open source terminal-based interface designed for interacting with large language models in a fast and efficient way. It runs entirely in the command line, offering a keyboard-driven experience that reduces the need for switching between apps. Users can chat with both proprietary models like ChatGPT and Claude, as well as local models such as Llama 3, Mistral, and Gemma. Elia stores conversations in a local SQLite database, making it easy to revisit past interactions. It supports... -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
PipesHub AI is an open-source, enterprise-grade workplace AI platform designed to unify search, knowledge management, and workflow automation across distributed organizational systems. It connects to a wide range of enterprise tools such as Google Workspace, Slack, Jira, and Confluence, aggregating data into a centralized knowledge layer that can be queried using natural language. The platform uses knowledge graphs and ranking algorithms to provide context-rich answers along with traceable... -
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RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
RAG Web UI is an open-source intelligent dialogue system built on retrieval-augmented generation technology, designed to enable users to create AI-powered question answering systems grounded in their own knowledge bases. It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. The platform supports ingestion of multiple document formats, including PDFs, Word files, Markdown, and plain... -
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database.build
In-browser Postgres sandbox with AI assistance
database.build is an innovative in-browser development environment that allows users to instantly create and interact with fully functional PostgreSQL databases directly within their browser, powered by WebAssembly technology. It eliminates the need for traditional database setup by running a lightweight version of PostgreSQL locally using PGlite, enabling developers to experiment, prototype, and analyze data without relying on external servers. Each database instance is paired with a large... -
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Embabel Agent Framework
Agent framework for the JVM. Pronounced Em-BAY-bel
Embabel Agent Framework is a JVM-based framework for building advanced AI agent systems that combine structured programming with large language model interactions to execute complex, goal-oriented workflows. The framework introduces a planning-driven approach where agents dynamically determine sequences of actions required to achieve objectives, rather than relying on fixed pipelines or predefined flows. It models agent behavior through concepts such as goals, actions, and conditions,... -
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ZML
Any model. Any hardware. Zero compromise
ZML is a high-performance machine learning inference stack designed to run AI models efficiently across heterogeneous hardware environments using a modern systems programming approach. Built with technologies such as Zig, MLIR, and Bazel, it focuses on production-grade deployment where performance, portability, and scalability are critical. The system allows models to be compiled and executed across multiple types of accelerators, including GPUs and TPUs, even when distributed across... -
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DeepProve
Framework to prove inference of ML models blazingly fast
DeepProve is an advanced cryptographic framework designed to verify machine learning model inference using zero-knowledge proofs, enabling trustless validation of AI computations without exposing underlying data. The project focuses on zkML, a rapidly emerging field that combines machine learning with zero-knowledge cryptography to ensure both privacy and correctness. It supports neural network architectures such as multilayer perceptrons and convolutional neural networks, allowing... -
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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory... -
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Cosmos-RL
Cosmos-RL is a flexible and scalable Reinforcement Learning framework
Cosmos-RL is a scalable reinforcement learning framework designed specifically for physical AI systems such as robotics, autonomous agents, and multimodal models. It provides a distributed training architecture that separates policy learning and environment rollout processes, enabling efficient and asynchronous reinforcement learning at scale. The framework supports multiple parallelism strategies, including tensor, pipeline, and data parallelism, allowing it to leverage large GPU clusters... -
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NVIDIA AI Cluster Runtime (AICR)
Tooling for optimized and reproducible GPU-accelerated AI runtime
NVIDIA AI Cluster Runtime (AICR) is an emerging project within NVIDIA’s AI infrastructure ecosystem focused on enabling advanced AI compute and runtime workflows, though publicly available documentation remains limited. Based on its positioning within NVIDIA’s repositories, it is designed to support scalable AI runtime environments, potentially addressing challenges related to orchestration, resource management, or reproducible AI execution. The project likely aligns with NVIDIA’s broader... -
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Numbast
Build an automated pipeline that converts CUDA APIs into Numba
Numbast is an automated toolchain that bridges CUDA C++ and Python by generating Numba-compatible bindings directly from CUDA header files. Its primary goal is to eliminate the manual effort required to expose CUDA libraries to Python, enabling developers to use GPU-accelerated functionality in Python environments more easily. The system parses CUDA C++ declarations and converts them into Python bindings that can be used within Numba, allowing seamless integration with Python-based GPU... -
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CUDA-QX
Accelerated libraries for quantum-classical computing built on CUDA-Q
CUDA-QX is a collection of accelerated libraries built on top of the CUDA-Q platform, designed to enable rapid development of hybrid quantum-classical applications. It extends the CUDA-Q programming model by providing optimized implementations of domain-specific quantum computing primitives and workflows. The libraries are intended to help researchers and developers leverage GPUs, CPUs, and quantum processing units together in a unified computational model. CUDA-QX focuses on key areas such... -
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
CCCL, or CUDA Core Compute Libraries, is a unified repository that consolidates several foundational CUDA C++ libraries into a single, cohesive development platform. It brings together Thrust, CUB, and libcudacxx, which collectively provide high-level abstractions, low-level performance primitives, and a CUDA-compatible standard library for GPU programming. The goal of CCCL is to simplify CUDA development by offering reusable building blocks that enable developers to write efficient and... -
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TensorRT LLM
TensorRT LLM provides users with an easy-to-use Python API
TensorRT-LLM is an open-source high-performance inference library specifically designed to optimize and accelerate large language model deployment on NVIDIA GPUs. It provides a Python-based API built on top of PyTorch that allows developers to define, customize, and deploy LLMs efficiently across a variety of hardware configurations, from single GPUs to large multi-node clusters. The library focuses on maximizing throughput and minimizing latency through advanced techniques such as... -
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LitServe
Minimal Python framework for scalable AI inference servers fast
LitServe is a minimal Python framework designed for building custom AI inference servers with full control over how models are executed and served. It allows developers to define their own inference logic, making it suitable for complex systems such as multi-model pipelines, agents, and retrieval-augmented generation workflows. Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and...
