Showing 2395 open source projects for "mac on windows"

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  • 1
    Instill Core

    Instill Core

    Instill Core is a full-stack AI infrastructure tool for data

    Instill Core is an open-source, full-stack AI infrastructure platform designed to orchestrate data pipelines, machine learning models, and unstructured data processing into a unified, production-ready system. It provides an end-to-end solution that enables developers to build, deploy, and manage AI-powered applications without needing to manually stitch together multiple tools across the data and model lifecycle. The platform focuses heavily on handling unstructured data such as documents,...
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  • 2
    Elia

    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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  • 3
    PipesHub

    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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  • 4
    clip-retrieval

    clip-retrieval

    Easily compute clip embeddings and build a clip retrieval system

    clip-retrieval is an open-source toolkit designed to build large-scale semantic search systems for images and text by leveraging CLIP embeddings to enable multimodal retrieval. It allows developers to compute embeddings for both images and text efficiently and then index them for fast similarity search across massive datasets. The system is optimized for performance and scalability, capable of processing tens or even hundreds of millions of embeddings using GPU acceleration. It includes...
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  • 5
    Reflexion

    Reflexion

    Reflexion: Language Agents with Verbal Reinforcement Learning

    Reflexion is a research-oriented AI framework that focuses on improving the reasoning and problem-solving capabilities of language model agents through iterative self-reflection and feedback loops. Instead of relying solely on a single-pass response, Reflexion enables agents to evaluate their own outputs, identify errors, and refine their reasoning over multiple iterations, leading to more accurate and reliable results. The framework introduces a mechanism where agents maintain a memory of...
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  • 6
    ZML

    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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  • 7
    Cosmos-RL

    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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  • 8
    LitServe

    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...
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  • 9
    autoMate

    autoMate

    AI tool for automating desktop tasks via natural language input

    autoMate is an AI-powered local automation tool designed to enable users to control and automate their computers using natural language instructions instead of traditional scripting or rule-based systems. It combines large language models with computer vision techniques to interpret user intent and understand on-screen content, allowing it to interact with graphical interfaces similarly to a human user. autoMate follows an observe-decide-act workflow, where it analyzes the screen, plans...
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  • 10
    Text Embeddings Inference

    Text Embeddings Inference

    High-performance inference server for text embeddings models API layer

    Text Embeddings Inference is a high-performance server designed to serve text embedding models efficiently in production environments. It focuses on delivering fast and scalable embedding generation by leveraging optimized inference techniques and modern hardware acceleration. It is built to support transformer-based embedding models, making it suitable for tasks such as semantic search, clustering, and retrieval-augmented systems. It provides an API interface that allows developers to...
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  • 11
    ComfyUI-Copilot

    ComfyUI-Copilot

    AI assistant for ComfyUI workflow generation, debugging, and tuning

    ComfyUI-Copilot is an AI-powered assistant designed to extend the capabilities of ComfyUI by simplifying and automating complex workflow development tasks. It functions as a custom node integrated directly into the ComfyUI environment, allowing users to interact with workflows through natural language and intelligent suggestions. ComfyUI-Copilot focuses on reducing the complexity of building node-based pipelines for generative AI tasks such as image generation, making it more accessible to...
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  • 12
    Kiln

    Kiln

    Open source platform for managing, testing, and deploying AI apps

    Kiln is an open source platform designed to help developers build, evaluate, and deploy AI-powered applications with greater structure and reliability. It provides a unified environment for managing prompts, datasets, and evaluation workflows, allowing teams to iterate on AI behavior in a controlled and measurable way. Kiln emphasizes reproducibility, enabling users to track changes to prompts and models while comparing outputs across different configurations. Kiln also supports systematic...
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  • 13
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective...
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  • 14
    Swarms

    Swarms

    Enterprise multi-agent orchestration framework for scalable AI apps

    Swarms is an enterprise-grade multi-agent orchestration framework designed to help developers build, manage, and scale collaborative AI systems composed of multiple agents. It provides a structured infrastructure for coordinating agents in hierarchical, parallel, or sequential workflows, enabling complex task execution across distributed components. It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale...
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  • 15
    TADA

    TADA

    Open Source Speech Language Model

    TADA is an open-source speech-language modeling framework designed to unify spoken audio and text representations within a single generative architecture. The system focuses on aligning speech and text streams using a dual-alignment mechanism that synchronizes the acoustic signal with its textual representation. By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This...
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  • 16
    TypeAgent Python

    TypeAgent Python

    Structured RAG: ingest, index, query

    TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language...
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  • 17
    Google Research: Language

    Google Research: Language

    Shared repository for open-sourced projects from the Google AI Lang

    Google Research: Language is a shared repository maintained by Google Research that contains open-source projects developed by the Google AI Language team. The repository hosts multiple subprojects related to natural language processing, machine learning, and large-scale language understanding systems. Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. These...
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  • 18
    PySINDy

    PySINDy

    A package for the sparse identification of nonlinear dynamical systems

    PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a...
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  • 19
    Humanoid-Gym

    Humanoid-Gym

    Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real

    Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training....
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  • 20
    machine-learning-refined

    machine-learning-refined

    Master the fundamentals of machine learning, deep learning

    machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric...
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  • 21
    skfolio

    skfolio

    Python library for portfolio optimization built on top of scikit-learn

    skfolio is a Python library designed for portfolio optimization and financial risk management that integrates closely with the scikit-learn ecosystem. The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and...
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  • 22
    Diffrax

    Diffrax

    Numerical differential equation solvers in JAX

    Diffrax is a numerical differential equation solving library built for the JAX ecosystem, with a strong focus on composability, differentiability, and high-performance scientific computing. The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with...
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  • 23
    SimpleHTR

    SimpleHTR

    Handwritten Text Recognition (HTR) system implemented with TensorFlow

    SimpleHTR is an open-source implementation of a handwriting text recognition system based on deep learning techniques. The project focuses on converting images of handwritten text into machine-readable digital text using neural networks. The system uses a combination of convolutional neural networks and recurrent neural networks to extract visual features and model sequential character patterns in handwriting. It also employs connectionist temporal classification (CTC) to align predicted...
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  • 24
    Apache Hamilton

    Apache Hamilton

    Helps data scientists define testable self-documenting dataflows

    Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph...
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  • 25
    NVIDIA PhysicsNeMo

    NVIDIA PhysicsNeMo

    Open-source deep-learning framework for building and training

    NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference...
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