Showing 16181 open source projects for "linux-tools"

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  • 1
    AI-Media2Doc

    AI-Media2Doc

    AI tool converting video/audio into structured documents instantly

    AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not...
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  • 2
    DeepAnalyze

    DeepAnalyze

    Autonomous LLM agent for end-to-end data science workflows

    DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and...
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  • 3
    Ultravox

    Ultravox

    Fast multimodal LLM for real-time voice interaction and AI apps

    Ultravox is an open source multimodal large language model designed specifically for real-time voice-based interactions. It is built to process both text and spoken audio directly, eliminating the need for a separate speech recognition stage and enabling more seamless conversational experiences. Ultravox works by combining text prompts with encoded audio inputs, allowing it to understand spoken language alongside written instructions in a unified pipeline. Internally, it leverages pretrained...
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  • 4
    myGPTReader

    myGPTReader

    AI Slack bot for reading, summarizing, and chatting with content

    myGPTReader is an AI-powered Slack bot designed to help users read, summarize, and interact with various types of digital content through conversational interfaces. It enables users to quickly understand web pages, documents, and even video content by transforming them into interactive discussions rather than static reading experiences. myGPTReader supports a wide range of file formats, including eBooks, PDFs, and text-based documents, making it flexible for both casual and professional use...
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  • 5
    StableSwarmUI

    StableSwarmUI

    Multi-user UI for managing and running Stable Diffusion workflows tool

    StableSwarmUI is a web-based interface designed to manage and coordinate Stable Diffusion image generation workflows in a multi-user environment. It focuses on enabling multiple users to interact with shared resources, making it suitable for collaborative or server-based deployments. It provides a centralized system where users can submit, monitor, and manage generation tasks through a browser interface. It abstracts much of the complexity involved in running diffusion models by offering a...
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  • 6
    Bear Stone Smart Home

    Bear Stone Smart Home

    Custom Home Assistant configuration with automations and scripts setup

    Bear Stone Smart Home contains a personalized configuration setup for Home Assistant, an open source home automation platform. It defines how various smart home devices, services, and integrations are organized and controlled within a single environment. It includes configuration files that manage entities such as lights, sensors, switches, and media devices, enabling centralized automation and monitoring. It demonstrates how to structure Home Assistant YAML files for scalability and...
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  • 7
    Qodo Cover

    Qodo Cover

    AI tool that generates tests to improve code coverage quickly

    Qodo Cover is an open source developer tool designed to automate the creation of unit tests using generative AI, helping teams improve code coverage with minimal manual effort. It operates as a command-line interface and can also be integrated into continuous integration workflows, making it adaptable to different development environments. It analyzes an existing codebase, identifies gaps in test coverage, and generates new tests that target uncovered or weakly tested areas. It follows an...
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  • 8
    NVIDIA cuOpt

    NVIDIA cuOpt

    GPU accelerated decision optimization

    NVIDIA cuOpt is a GPU-accelerated optimization engine designed to solve complex mathematical optimization problems at large scale. It supports a range of optimization models including linear programming (LP), mixed integer linear programming (MILP), quadratic programming (QP), and vehicle routing problems (VRP). Built primarily in C++, cuOpt leverages NVIDIA GPUs to deliver near real-time solutions for optimization tasks involving millions of variables and constraints. The platform provides...
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  • 9
    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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  • 10
    The Hundred-Page Machine Learning Book

    The Hundred-Page Machine Learning Book

    The Python code to reproduce illustrations from Machine Learning Book

    The Hundred-Page Machine Learning Book is the official companion repository for The Hundred-Page Machine Learning Book written by machine learning researcher Andriy Burkov. The repository contains Python code used to generate the figures, visualizations, and illustrative examples presented in the book. Its purpose is to help readers better understand the concepts explained in the text by allowing them to run and experiment with the underlying code themselves. The book itself provides a...
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  • 11
    Advanced NLP with spaCy

    Advanced NLP with spaCy

    Advanced NLP with spaCy: A free online course

    Advanced NLP with spaCy is an open-source educational repository that provides the materials for an interactive course on advanced natural language processing using the spaCy library. The course is designed to teach developers how to build real-world NLP systems by combining rule-based techniques with machine learning models. The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and...
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  • 12
    TypeChat

    TypeChat

    Library for building type-safe natural language interfaces with LLMs

    TypeChat is an open source library developed by Microsoft that simplifies the creation of natural language interfaces by using type definitions to structure interactions with large language models. Traditional natural language interfaces often relied on complex decision trees to interpret user intent and gather required inputs. With the rise of large language models, developers can interpret user requests more easily, but they still face challenges related to output reliability, safety, and...
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  • 13
    Databend

    Databend

    Cloud-native open source data warehouse for analytics and AI queries

    Databend is an open source cloud-native data warehouse designed for large-scale analytics and modern data workloads. Built in Rust, the system focuses on high performance, scalability, and efficient data processing for analytical queries. It is designed with a separation of compute and storage, allowing compute nodes to scale independently while storing data in object storage systems. This architecture enables cost-efficient storage and elastic scaling for workloads that involve large...
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  • 14
    LEANN

    LEANN

    Local RAG engine for private multimodal knowledge search on devices

    LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing...
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  • 15
    MLE-bench

    MLE-bench

    AI multi-agent framework for automating data-driven R&D workflows

    RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By...
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  • 16
    Memori

    Memori

    SQL-native memory layer enabling persistent context for AI agents

    Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard...
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  • 17
    Semantra

    Semantra

    Multi-tool for semantic search

    Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs...
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  • 18
    OpenVINO Notebooks

    OpenVINO Notebooks

    Jupyter notebook tutorials for OpenVINO

    openvino_notebooks is a collection of interactive Jupyter notebooks designed to demonstrate how to build, optimize, and deploy artificial intelligence applications using the OpenVINO toolkit. The repository provides practical tutorials that guide developers through various AI workflows including computer vision, natural language processing, and generative AI tasks. Each notebook demonstrates how to run pre-trained models, optimize inference performance, and deploy models across hardware such...
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  • 19
    machine learning tutorials

    machine learning tutorials

    machine learning tutorials (mainly in Python3)

    machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis....
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  • 20
    AiLearning-Theory-Applying

    AiLearning-Theory-Applying

    Quickly get started with AI theory and practical applications

    AiLearning-Theory-Applying is a comprehensive educational repository designed to help learners quickly understand artificial intelligence theory and apply it in practical machine learning and deep learning projects. The repository provides extensive tutorials covering mathematical foundations, machine learning algorithms, deep learning concepts, and modern large language model architectures. It includes well-commented notebooks, datasets, and implementation examples that allow learners to...
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  • 21
    seq2seq-couplet

    seq2seq-couplet

    Play couplet with seq2seq model

    seq2seq-couplet is a deep learning application that generates Chinese couplet responses using a sequence-to-sequence model built with TensorFlow. Its purpose is not general machine translation, but a specialized text generation task in which the model produces a matching second line for a given first line in the style of traditional couplets. The repository includes the code needed to train the model, configure file paths and hyperparameters, and evaluate progress through loss and BLEU score...
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  • 22
    Kaggle Solutions

    Kaggle Solutions

    Collection of Kaggle Solutions and Ideas

    Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques...
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  • 23
    FlexLLMGen

    FlexLLMGen

    Running large language models on a single GPU

    FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on...
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  • 24
    Machine learning algorithms

    Machine learning algorithms

    Minimal and clean examples of machine learning algorithms

    Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. The repository...
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  • 25
    Transfer Learning Repo

    Transfer Learning Repo

    Transfer learning / domain adaptation / domain generalization

    Transfer Learning Repo is an open-source repository that compiles resources, code implementations, and academic references related to transfer learning and its related research areas. The project functions as a large knowledge hub that organizes papers, tutorials, datasets, and software implementations across topics such as domain adaptation, domain generalization, multi-task learning, and few-shot learning. The repository includes surveys and theoretical explanations that help readers...
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