5532 projects for "apache" with 1 filter applied:

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  • 1
    Universal Commerce Protocol

    Universal Commerce Protocol

    Specification and documentation for the Universal Commerce Protocol

    UCP (Universal Commerce Protocol) is an open standard intended to make commerce integrations interoperable across platforms, agents, businesses, and payment providers without bespoke, one-off connector builds. It defines a shared “common language” and functional primitives so that different systems can express commerce actions and state transitions in a consistent way. The protocol is designed around the realities of existing retail infrastructure, aiming to fit into current operational...
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  • 2
    FinRobot

    FinRobot

    An Open-Source AI Agent Platform for Financial Analysis using LLMs

    FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to...
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  • 3
    BSON parser

    BSON parser

    BSON Parser for node and browser

    BSON parser is the core JavaScript implementation of BSON (Binary JSON), the data format used by MongoDB to represent documents on the wire and in storage. It provides encoding and decoding capabilities so JavaScript environments like Node.js and browsers can serialize rich data structures (including types not native to JSON) into the compact, efficient BSON binary representation used by MongoDB drivers and servers. Value types such as ObjectId, Binary, UTC datetime, Decimal128, and Long are...
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  • 4
    kgateway

    kgateway

    The Cloud-Native API Gateway and AI Gateway

    kgateway is a mature, cloud-native API and ingress gateway designed to provide unified API connectivity for services, microservices, serverless workloads, and AI-centric systems running on Kubernetes clusters. It implements the Kubernetes Gateway API and can operate as both a lightweight in-cluster microgateway and a centralized gateway capable of handling billions of API calls with high performance and low latency. By integrating with Envoy and advanced data planes, it handles modern...
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    Gemini 3 and 200+ AI Models on One Platform

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  • 5
    Step3-VL-10B

    Step3-VL-10B

    Multimodal model achieving SOTA performance

    Step3-VL-10B is an open-source multimodal foundation model developed by StepFun AI that pushes the boundaries of what compact models can achieve by combining visual and language understanding in a single architecture. Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful...
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  • 6
    Chinese-LLaMA-Alpaca-3

    Chinese-LLaMA-Alpaca-3

    Chinese Llama-3 LLMs) developed from Meta Llama 3

    Chinese-LLaMA-Alpaca-3 is an open-source project that provides Mandarin-focused large language models based on Meta’s LLaMA-3 architecture, with both foundational and instruction-tuned variants to support high-quality Chinese natural language understanding and generation. It extends the original LLaMA models with expanded Chinese vocabularies and additional pretraining on Chinese corpora to improve semantic encoding and decoding specifically for Chinese text. Alongside the base models, the...
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  • 7
    Open Model Zoo

    Open Model Zoo

    Pre-trained Deep Learning models and demos

    Open Model Zoo is a large repository of high-quality pre-trained deep learning models and demonstration applications designed to work with the OpenVINO™ toolkit, offering a comprehensive starting point for a wide range of AI and computer vision workloads. It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs,...
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  • 8
    Lingvo

    Lingvo

    Framework for building neural networks

    Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state...
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  • 9
    derive(Error)

    derive(Error)

    derive(Error) for struct and enum error types

    This is a Rust crate that provides a convenient derive macro (#[derive(Error)]) for implementing std::error::Error on your custom error types (structs or enums). The goal is to enable library authors to build expressive, typed error types, with readable Display implementations (via #[error("...")] annotations) as well as From conversions (#[from]), source tracking (#[source]), and optionally backtraces. It is designed so that switching from handwritten error implementation to using this...
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  • 10
    From Java To Kotlin

    From Java To Kotlin

    Your Cheat Sheet For Java To Kotlin

    From Java to Kotlin is a practical guide for Android developers transitioning existing codebases and habits from Java to idiomatic Kotlin. Rather than simply showing syntax translations, it emphasizes Kotlin’s expressive features—null safety, extensions, data classes, sealed hierarchies, and higher-order functions—and how to apply them sensibly. Examples illustrate side-by-side Java and Kotlin snippets, revealing opportunities to reduce boilerplate and improve readability. The guide includes...
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  • 11
    Android Interview Questions

    Android Interview Questions

    Your Cheat Sheet For Android Interview

    This repository is a comprehensive study guide for Android interviews, organized to cover the platform from fundamentals to advanced topics. It includes explanations and Q&A on the Android app lifecycle, activities and fragments, services, broadcast receivers, content providers, and the build system. Modern practices are addressed as well—Kotlin language features, coroutines, Jetpack components, MVVM/MVI architecture, dependency injection, and testing strategies. Performance and reliability...
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  • 12
    Hello Git & GitHub

    Hello Git & GitHub

    Tutorial repository designed to teach how to use the Git vc system

    Hello-Git is a tutorial repository designed to teach how to use the Git version-control system and the GitHub platform from the ground up, aimed at beginners. The course spans around 5 hours of instruction and covers more than 25 Git commands along with GitHub workflows, installation/configuration, terminal usage, branching, merging, collaboration, and authentication. It is structured to introduce learners not only to the syntax of Git commands but also to development workflows such as...
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  • 13
    ZeusDB Vector Database

    ZeusDB Vector Database

    Blazing-fast vector DB with similarity search and metadata filtering

    ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch,...
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  • 14
    Visual Blocks

    Visual Blocks

    Visual Blocks for ML is a Google visual programming framework

    Visual Blocks is a node-based, in-browser environment for building AI and data-processing workflows with drag-and-drop components. It lets you connect sources, transforms, models, and visualizers into a live graph, so changes propagate instantly and results are observable without writing glue code. Under the hood it leans on web-friendly runtimes (e.g., WebGPU/WebGL/WebNN or TensorFlow.js backends) to execute pipelines locally, which is great for demos, teaching, and privacy-sensitive...
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  • 15
    Tunix

    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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  • 16
    Go Jsonnet

    Go Jsonnet

    This an implementation of Jsonnet in pure Go

    go-jsonnet is a pure Go implementation of the Jsonnet data templating language, which extends JSON with variables, functions, imports, and a standard library so you can generate complex configuration safely. Instead of hand-maintaining massive JSON files, you write concise, reusable templates that evaluate to JSON or YAML, with deterministic semantics and rich error messages. The repository ships both an embeddable VM for Go programs and a command-line interpreter, making it easy to...
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  • 17
    Mangle

    Mangle

    Go library for Datalog-style logical reasoning and domain modeling

    Mangle is a programming language developed by Google for deductive database programming, serving as an advanced extension of Datalog. It is designed to unify and query data from multiple sources in a structured, declarative way while allowing developers to model complex relationships and domain knowledge beyond binary predicates. Mangle enhances traditional Datalog by introducing features such as aggregation, function calls, and optional type-checking, which make it more practical for modern...
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  • 18
    Earth Engine API

    Earth Engine API

    Python and JavaScript bindings for calling the Earth Engine API

    The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in...
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  • 19
    Honggfuzz

    Honggfuzz

    Security oriented software fuzzer

    honggfuzz is a general-purpose, high-performance fuzzer that mixes coverage feedback with practical crash triage to uncover memory-safety and logic bugs. It supports multiple fuzzing modes—stdin, file, and networking—so targets can be exercised the same way they run in production. Instrumentation via compiler hooks or hardware/perf counters guides mutations toward previously unseen edges, while persistent mode keeps the target process alive to amortize startup costs. The tool integrates...
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  • 20
    Oboe

    Oboe

    Oboe is a C++ library that makes it easy to build high-performance

    oboe is a C++ library for building high-performance audio apps on Android, providing a unified, low-latency API over AAudio and OpenSL ES. It abstracts device and API-version differences so developers can focus on audio processing instead of platform quirks. The library emphasizes minimal latency and glitch-free playback/recording via tuned buffer strategies and callback-driven I/O. It supports features like floating-point audio, channel configuration, sample-rate negotiation, and stream...
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  • 21
    BTree implementation for Go

    BTree implementation for Go

    BTree provides a simple, ordered, in-memory data structure for Go

    This package is a high-performance, in-memory B-tree for Go that implements an ordered set/map with efficient insert, delete, and range iteration. It’s parameterized by tree degree so callers can tune cache behavior and memory overhead for their workload. Instead of relying on Go’s built-in maps—which are hash-based and unordered—btree preserves sorted order and provides rich traversal APIs like ascending, descending, and range scans. The implementation favors minimal allocations and...
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  • 22
    latexify

    latexify

    A library to generate LaTeX expression from Python code

    latexify_py converts small, math-heavy pieces of Python code into human-readable LaTeX that mirrors the intent of the computation, not just its surface syntax. It parses Python functions and expressions into an abstract syntax tree (AST), applies symbolic rewrites for common mathematical constructs, and then emits LaTeX that compiles cleanly in standard environments. Typical use cases include turning analytical utilities—like probability mass functions, activation formulas, or recurrence...
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  • 23
    LangExtract

    LangExtract

    A Python library for extracting structured information

    LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and...
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  • 24
    ArXiv MCP Server

    ArXiv MCP Server

    A Model Context Protocol server for searching and analyzing arXiv

    arxiv-mcp-server bridges AI assistants and the arXiv repository through a clean MCP interface, enabling search, metadata retrieval, and content access without bespoke scraping. With simple tools like “search” and “fetch,” an agent can find papers, pull abstracts, and download PDFs for downstream summarization or analysis. The project includes packaging and CI to publish to PyPI, plus tests and linting for reliability. Issue threads show feature requests such as extracting embedded LaTeX and...
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  • 25
    4M

    4M

    4M: Massively Multimodal Masked Modeling

    4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things...
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