Showing 1844 open source projects for "context"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build 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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  • 1
    Swift Algorithm Club

    Swift Algorithm Club

    Algorithms and data structures in Swift, with explanations

    ...Its purpose is not primarily to be a utility library, but rather to teach the how and why behind algorithms—readers can study implementations, complexity, and design choices in a Swift context. The repository includes common classic algorithms (sorting, searching, trees, graphs, dynamic programming, etc.) and structures (queues, heaps, tries, balanced trees) along with writeups explaining them. Because it's in Swift, the code is idiomatic and leverages Swift language features and standard patterns, which helps learners see how algorithmic ideas map into modern code. ...
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  • 2
    Cats Effect

    Cats Effect

    The pure asynchronous runtime for Scala

    Cats-Effect is a high-quality functional programming library for Scala that provides a principled way to represent and manage side effects, particularly asynchronous and concurrent computations. It is part of the broader Typelevel ecosystem and builds on the abstractions from Cats (such as Functor, Monad, etc.). The core abstraction is the IO type (or effect types more generally), which encodes effectful computations in a pure, referentially transparent way. Cats-Effect offers capabilities...
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  • 3
    Geodesic

    Geodesic

    Geodesic is a DevOps Linux Toolbox in Docker

    ...It achieves this without the need for installing additional software on your workstation. Think of Geodesic as a containerized parallel to Vagrant, offering similar functionality within a Docker container context.
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  • 4
    Goa

    Goa

    Design-based APIs and microservices in Go

    ...Goa is extensible via plugins, for example the goakit plugin generates code that leverage the Go kit library. The service design describes the transport independent layer of the services in the form of simple methods that accept a context and a payload and return a result and an error. The design also describes how the payloads, results and errors are serialized in the transport (HTTP or gRPC). For example a service method payload may be built from an HTTP request by extracting values from the request path, headers and body. This clean separation of layers makes it possible to expose the same service using multiple transports. ...
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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  • 5
    Jest Puppeteer

    Jest Puppeteer

    Run your tests using Jest & Puppeteer

    Most continuous integration platforms limit the number of threads one can use. If you have more than one test suite running puppeteer chances are that your test will timeout. This is because jest will try to run puppeteer in parallel and the CI platform won't be able to handle all the parallel jobs in time. A fix to this is to run your test serially when in a CI environment. Users have discovered that running test serially in such environments can render up to 50% of performance gains....
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  • 6
    VarDumper Component

    VarDumper Component

    Provides mechanisms for walking through any arbitrary PHP variable

    ...Repeated occurrences of the same object/array/resource won’t appear again and again anymore. Moreover, you’ll be able to inspect the reference structure of your data. Ability to operate in the context of an output buffering handler.
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  • 7
    go-github

    go-github

    Go library for accessing the GitHub API

    ...Construct a new GitHub client, then use the various services on the client to access different parts of the GitHub API. Some API methods have optional parameters that can be passed. Using the context package, one can easily pass cancelation signals and deadlines to various services of the client for handling a request.
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  • 8
    Specification for GraphQL

    Specification for GraphQL

    A working draft of the Specification for GraphQL, a query language

    This is the specification for GraphQL, a query language and execution engine originally created at Facebook in 2012 for describing the capabilities and requirements of data models for client-server applications. The development of this open standard started in 2015. This specification was licensed under OWFa 1.0 in 2017. Copyright and trademark was transferred to the GraphQL Foundation in 2019. GraphQL has evolved and may continue to evolve in future editions of this specification. GraphQL...
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  • 9
    Semantix

    Semantix

    Non-Pydantic, Non-JSON Schema, efficient AutoPrompting

    Semantix empowers developers to infuse meaning into their code through enhanced variable typing (semantic typing). By leveraging the power of large language models (LLMs) behind the scenes, Semantix transforms ordinary functions into intelligent, context-aware operations without explicit LLM calls.
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  • Go from Code to Production URL in Seconds Icon
    Go from Code to Production URL in Seconds

    Cloud Run deploys apps in any language instantly. Scales to zero. Pay only when code runs.

    Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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  • 10

    Context Free Grammar Kit

    Context-Free Grammar Interpreter

    Recursive Production Grammar (RPG) is a lightweight generative-literature engine designed for writers, researchers, and experimental coders who want maximum expressive power in a minimal footprint. RPG uses a clean, production-rule syntax to generate text recursively—ideal for poetry, stories, linguistics experiments, artificial languages, and procedural content. Built for speed, clarity, and creative flexibility, RPG supports nested rules, controlled randomness, variable binding,...
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  • 11
    rav1e

    rav1e

    The fastest and safest AV1 encoder

    rav1e is an open-source implementation of an encoder for the AV1 video codec, developed in Rust (with some assembly) by the community around Xiph Foundation. Its design philosophy is to start from a correct, minimal, and fast AV1 encoder — sacrificing some encoding speed/efficiency of reference encoders in exchange for simplicity, stability, and compilability across platforms — and then gradually improve. This makes rav1e particularly attractive for scenarios where you need AV1 encoding but...
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  • 12
    AWS Lambda for .NET

    AWS Lambda for .NET

    Libraries, samples and tools to help .NET Core developers

    ...Its goal is to make serverless in AWS feel natural for .NET developers—abstracting away boilerplate and letting you focus on business logic rather than deployment artifacts. It also supports advanced use cases such as .NET Core integration, source-generator annotations, and custom middleware within a function context.
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  • 13
    Tongyi DeepResearch

    Tongyi DeepResearch

    Tongyi Deep Research, the Leading Open-source Deep Research Agent

    DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. It uses a mix of synthetic data generation, fine-tuning and...
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  • 14
    Tambo

    Tambo

    Add generative UI components to your AI assistant, copilot, or agent

    ...It acts as the bridge between an AI assistant and the React front end, letting your AI agent not only send text responses, but also generate interactive UI elements (forms, charts, dashboards, etc.). The library includes tools to scaffold a Tambo app, manage state, and integrate with its backend protocol (Model Context Protocol, or MCP). Developers use Tambo to shift UI logic toward the AI model: instead of hardcoding UI flows, the AI can decide what component to show next. Tambo also supports streaming updates (i.e. progressively rendering UI) and embedding interactions between LLM outputs and front-end state.
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  • 15
    JupyterLab LSP

    JupyterLab LSP

    Coding assistance for JupyterLab (code navigation + hover suggestions

    Hover over any piece of code; if an underline appears, you can press Ctrl to get a tooltip with function/class signature, module documentation or any other piece of information that the language server provides. Critical errors have red underline, warnings are orange, etc. Hover over the underlined code to see a more detailed message. Use the context menu entry, or Alt + 🖱️ to jump to definitions/references (you can change it to Ctrl/⌘ in settings); use Alt + o to jump back. Place your cursor on a variable, function, etc and all the usages will be highlighted. When a kernel is available the suggestions from the kernel (such as keys of a dict and columns of a DataFrame) are merged with the suggestions from the Language Server (in notebook). ...
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  • 16
    Murex

    Murex

    A smarter shell and scripting environment with advanced features

    ...Meaning all of your existing UNIX tools to work more intelligently and without any additional configuration. Usability improvements such as in-line spell checking, context-sensitive hint text that details the behavior of a command before you hit return, and auto-parsing man pages for auto-completions on commands that don't have auto-completions already defined. Smarter handling of errors and debugging tools. For example try/catch blocks, line numbers included in error messages, STDOUT highlighted in red and script testing and debugging frameworks baked into the language itself.
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  • 17
    Boilerplate and Starter for Next JS 12+

    Boilerplate and Starter for Next JS 12+

    Boilerplate and Starter for Next.js 12+, Tailwind CSS 3 and TypeScript

    ...With the plugins installed on your VSCode, ESLint and Prettier can automatically fix the code and show you the errors. Same goes for testing, you can install VSCode Jest extension to automatically run your tests and it also show the code coverage in context.
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  • 18
    doctest

    doctest

    Fastest feature-rich C++11/14/17/20 single-header testing framework

    doctest is a new C++ testing framework but is by far the fastest both in compile times (by orders of magnitude) and runtime compared to other feature-rich alternatives. It brings the ability of compiled languages such as D / Rust / Nim to have tests written directly in the production code thanks to a fast, transparent and flexible test runner with a clean interface. The framework is and will stay free but needs your support to sustain its development. There are lots of new features and...
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  • 19
    Sentry

    Sentry

    Cross-platform application monitoring and error tracking software

    Sentry is a cross-platform, self-hosted error monitoring solution that helps software teams discover, monitor and fix errors in real-time. The most users and logs will have to provide are the clues, and Sentry provides the answers. Sentry offers enhanced application performance monitoring through information-laden stack traces. It lets you build better software faster and more efficiently by showing you all issues in one place and providing the trail of events that lead to errors. It also...
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  • 20
    GLM-4.5V

    GLM-4.5V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    ...GLM-4.5V emerged from a training framework that leverages scalable reinforcement learning (with curriculum sampling) to boost performance across tasks ranging from STEM problem solving to long-context reasoning, giving it broad applicability beyond narrow benchmarks. When it was released, it achieved state-of-the-art results on a large collection of public multimodal benchmarks for open-source models.
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  • 21
    Robyn

    Robyn

    Experimental, AI/ML-powered and open sourced Marketing Mix Modeling

    ...Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. It explicitly models “carry-over” (adstock) and diminishing-returns (saturation) effects per channel, enabling realistic modeling of how advertising persists over time and saturates.
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  • 22
    Vidi2

    Vidi2

    Large Multimodal Models for Video Understanding and Editing

    Vidi is a family of large multimodal models developed for deep video understanding and editing tasks, integrating vision, audio, and language to allow sophisticated querying and manipulation of video content. It’s designed to process long-form, real-world videos and answer complex queries such as “when in this clip does X happen?” or “where in the frame is object Y during that moment?” — offering temporal retrieval, spatio-temporal grounding (i.e. locating objects over time + space), and...
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  • 23
    Mini Agent

    Mini Agent

    A minimal yet professional single agent demo project

    Mini-Agent is a minimal yet production-minded demo project that shows how to build a serious command-line AI agent around the MiniMax-M2 model. It is designed both as a reference implementation and as a usable agent, demonstrating a full execution loop that includes planning, tool calls, and iterative refinement. The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during...
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  • 24
    MiniMax-M2

    MiniMax-M2

    MiniMax-M2, a model built for Max coding & agentic workflows

    ...Benchmarks show that it achieves highly competitive scores on a wide range of intelligence and agent benchmarks, including SWE-Bench variants, Terminal-Bench, BrowseComp, GAIA, and several long-context reasoning suites.
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  • 25
    files-to-prompt

    files-to-prompt

    Concatenate a directory full of files into a single prompt

    files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It...
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