Search Results for "mac framework" - Page 51

Showing 10521 open source projects for "mac framework"

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  • 1
    Passmark

    Passmark

    The open-source Playwright library for AI browser regression testing

    The Passmark project is an open-source AI-powered regression testing framework built on top of Playwright that enables developers to write end-to-end browser tests using natural language instead of traditional scripting. It is designed to simplify and accelerate testing workflows by allowing AI models to interpret human-readable instructions and translate them into executable browser actions. One of its defining features is a cache-first execution model, where AI is used initially to...
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  • 2
    dockview

    dockview

    Zero dependency docking layout manager supporting tabs

    dockview is a zero-dependency docking layout manager written in TypeScript that enables developers to create highly dynamic, IDE-like interfaces with draggable panels, tabs, and resizable layouts. It supports multiple layout paradigms, including split views, grid layouts, and dockable panels, allowing complex UI arrangements similar to tools like Visual Studio Code. The library is framework-agnostic at its core, with official bindings for React, Vue, and Angular, as well as support for...
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  • 3
    Tamagui

    Tamagui

    Style React fast with 100% parity on React Native

    Tamagui is a cross-platform UI framework and styling system for React and React Native that enables developers to build high-performance applications with a single codebase shared across web and mobile platforms. It combines a universal style system with a powerful optimizing compiler that transforms styled components into efficient, platform-specific output, significantly improving runtime performance. The framework provides a superset of the React Native styling API, allowing developers to...
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  • 4
    HybridClaw

    HybridClaw

    The enterprise operating layer for open agents

    HybridClaw is an emerging open-source framework focused on enabling hybrid AI agent systems that combine local execution, tool integration, and multi-agent orchestration into a cohesive development environment. It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. The project emphasizes modularity, allowing developers to define and...
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    BMad Method

    BMad Method

    Breakthrough Method for Agile Ai Driven Development

    BMad Method is a comprehensive AI-driven software development framework that structures the entire lifecycle of building applications through coordinated agent workflows and agile methodologies. It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. The system guides users through phases including analysis, planning, solution design, and implementation, ensuring...
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  • 6
    Cheshire Cat AI

    Cheshire Cat AI

    AI agent microservice

    Cheshire Cat AI Core is an open-source framework for building customizable AI agents as scalable microservices, designed to integrate conversational intelligence into applications through an API-first architecture. It allows developers to create advanced AI assistants that can interact through WebSockets, REST APIs, and embedded chat interfaces, making it suitable for both backend services and user-facing applications. The framework includes built-in support for retrieval-augmented...
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  • 7
    Deep Chat

    Deep Chat

    Customizable AI chat component for websites with API support

    Deep Chat is a highly customizable web component designed to simplify the integration of AI-powered chat interfaces into websites. It allows developers to embed a fully functional chatbot using minimal setup, while still offering extensive control over behavior, appearance, and integrations. Deep Chat supports connections to a wide range of AI services as well as custom backends, enabling flexible deployment for different use cases. It is built as a framework-agnostic solution, meaning it...
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  • 8
    Agent Starter Pack

    Agent Starter Pack

    Ship AI Agents to Google Cloud in minutes, not months

    Agent Starter Pack is a production-focused framework that provides pre-built templates and infrastructure for rapidly developing and deploying generative AI agents on Google Cloud. It is designed to eliminate the complexity of moving from prototype to production by bundling essential components such as deployment pipelines, monitoring, security, and evaluation tools into a single package. Developers can create fully functional agent projects with a single command, generating both backend and...
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  • 9
    OpenUI

    OpenUI

    The Open Standard for Generative UI

    OpenUI is an open-source framework focused on enabling AI-driven generation and manipulation of user interfaces through natural language and programmatic inputs. The project aims to bridge the gap between design and development by allowing users to describe UI components and layouts in plain language, which are then translated into structured code or interactive components. It leverages modern AI models and frontend technologies to dynamically generate UI elements that can be customized,...
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  • 10
    Rig

    Rig

    Rust framework for building modular and scalable LLM-powered apps

    Rig is an open source Rust framework designed to help developers build modular and scalable applications powered by large language models. It provides a unified set of abstractions that allow applications to interact with many AI model providers and vector databases through a single interface. Its architecture emphasizes modularity, enabling developers to integrate only the components and integrations they need for a specific application. Rig includes built-in support for agent workflows,...
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  • 11
    Guardrails

    Guardrails

    Framework for validating and controlling LLM outputs in AI apps

    Guardrails is an open source Python framework designed to help developers build more reliable and controlled applications powered by large language models. It provides mechanisms for validating and constraining both the inputs sent to a model and the outputs generated by it, helping reduce risks such as harmful content, prompt injection, or inaccurate responses. Guardrails works by applying configurable guards that intercept and evaluate interactions with the model before results are...
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  • 12
    hls4ml

    hls4ml

    Machine learning on FPGAs using HLS

    hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast...
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  • 13
    FISSURE

    FISSURE

    The RF and reverse engineering framework for everyone

    FISSURE is an open-source radio frequency analysis and signal intelligence framework built to support software-defined radio research, wireless security experimentation, and protocol reverse engineering. The project brings together tools for capturing, inspecting, decoding, replaying, and analyzing RF signals across a wide range of wireless technologies. It is designed as a practical environment for researchers and operators who need to move from raw spectrum observation to structured...
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  • 14
    kimuraframework

    kimuraframework

    AI-first Ruby framework for building fast, flexible web scraping spide

    Kimurai is an open source web scraping framework written in Ruby that simplifies the process of building automated data extraction tools. It provides a clean domain-specific language that allows developers to define scraping logic and data schemas with minimal boilerplate code. Kimurai can use AI-assisted extraction to identify where data resides in HTML pages, automatically generating selectors that are cached for future use so subsequent scraping runs operate with pure Ruby performance....
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  • 15
    Rogue

    Rogue

    AI Agent Evaluator & Red Team Platform

    Rogue is an open-source evaluation and red-team framework designed to test the reliability, safety, and policy compliance of AI agents. The platform automatically interacts with an AI agent by generating dynamic scenarios and multi-turn conversations that simulate real-world interactions. Instead of relying solely on static test scripts, Rogue uses an agent-as-a-judge architecture where one agent probes another agent to detect failures or unexpected behaviors. The system allows developers to...
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  • 16
    QueryList

    QueryList

    Progressive PHP web crawler framework with jQuery-like DOM parsing

    QueryList is an extensible PHP web scraping and crawling framework designed to extract and process data from web pages. It provides a simple and expressive API that allows developers to collect structured information from HTML documents using familiar DOM traversal techniques. It is built on top of phpQuery and uses CSS3 selectors similar to those found in jQuery, making it easy for developers to query and manipulate page elements during scraping tasks. QueryList supports common data...
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  • 17
    LLM Colosseum

    LLM Colosseum

    Benchmark LLMs by fighting in Street Fighter 3

    LLM-Colosseum is an experimental benchmarking framework designed to evaluate the capabilities of large language models through gameplay interactions rather than traditional text-based benchmarks. The system places language models inside the environment of the classic video game Street Fighter III, where they must interpret the game state and decide which actions to perform during combat. This setup creates a dynamic environment that tests reasoning, situational awareness, and decision-making...
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  • 18
    RLHF-Reward-Modeling

    RLHF-Reward-Modeling

    Recipes to train reward model for RLHF

    RLHF-Reward-Modeling is an open-source research framework focused on training reward models used in reinforcement learning from human feedback for large language models. In RLHF pipelines, reward models are responsible for evaluating generated responses and assigning scores that guide the model toward outputs that better match human preferences. The repository provides training recipes and implementations for building reward and preference models using modern machine learning frameworks. It...
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  • 19
    ModernBERT

    ModernBERT

    Bringing BERT into modernity via both architecture changes and scaling

    ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces...
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  • 20
    Agentless

    Agentless

    An agentless approach to automatically solve software development

    Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most...
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  • 21
    MaxText

    MaxText

    A simple, performant and scalable Jax LLM

    MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small...
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  • 22
    InternLM-XComposer-2.5

    InternLM-XComposer-2.5

    InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System

    InternLM-XComposer is an open-source multimodal AI system designed to generate long-form content that combines text with visual elements such as images and diagrams. The model is built on top of the InternLM language model architecture and extends its capabilities to handle multimodal inputs and outputs. Instead of producing only textual responses, the system can generate visually enriched documents such as illustrated articles, presentations, and educational materials. It incorporates...
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  • 23
    AgentBench

    AgentBench

    A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

    AgentBench is an open-source benchmark designed to evaluate the capabilities of large language models when used as autonomous agents. Unlike traditional language model benchmarks that focus on static text tasks, AgentBench measures how models perform in interactive environments that require planning, reasoning, and decision-making. The benchmark includes multiple environments that simulate realistic scenarios such as web interaction, database querying, and problem solving tasks. These...
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  • 24
    Chitu

    Chitu

    High-performance inference framework for large language models

    Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations....
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  • 25
    NExT-GPT

    NExT-GPT

    Code and models for ICML 2024 paper, NExT-GPT

    NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different...
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