Search Results for "linux performance booster" - Page 87
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Showing 6284 open source projects for "linux performance booster"
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
OpenMemory is a self-hosted memory engine designed to provide long-term, persistent storage for AI and LLM-powered applications. It enables developers to give otherwise stateless models a structured memory layer that can store, retrieve, and manage contextual information over time. OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. It supports multiple embedding... -
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HelixDB
Graph-vector database for building unified AI backends fast
HelixDB is an open source database designed to unify multiple data storage paradigms into a single platform tailored for AI-driven applications. It combines graph and vector data models, allowing developers to manage relationships and embeddings within the same system without relying on separate services. HelixDB is built from scratch in Rust and uses LMDB as its storage engine, enabling high performance and low-latency query execution. HelixDB also supports additional data formats such as... -
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David UI
Free Tailwind CSS UI component library for modern web interfaces
David AI is a free and open source library of customizable, production-ready UI components designed to work with Tailwind CSS. It focuses on helping developers build modern and visually consistent user interfaces faster by providing ready-made components that can be integrated directly into web applications. These components are designed to be flexible and easy to customize, allowing developers to adapt them to the design needs of their projects while maintaining a clean and efficient... -
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Medusa Next.js Starter Template
A performant frontend ecommerce starter template with Next.js
Next.js Starter Medusa is an open-source starter template designed to help developers quickly build modern eCommerce storefronts using the Medusa headless commerce engine and the Next.js framework. The project provides a complete frontend architecture that connects to a Medusa backend, which handles core commerce logic such as products, carts, customers, and orders. By combining Medusa’s modular commerce APIs with the capabilities of Next.js, the template enables developers to build fast,... -
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DreamerV3
Mastering Diverse Domains through World Models
DreamerV3 is an open-source implementation of a reinforcement learning algorithm that uses world models to train intelligent agents capable of learning complex behaviors across many environments. The system works by building an internal model of the environment and then using that model to simulate possible future outcomes of actions, allowing the agent to learn from imagined experiences rather than only from real interactions. This approach enables the algorithm to efficiently learn... -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on... -
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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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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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videodl
Lightweight Python tool for downloading videos from many platforms
Videodl is a lightweight video downloader implemented entirely in Python that allows users to retrieve videos from a wide range of online media platforms. It focuses on providing a fast and simple way to parse video pages and download media files, often prioritizing high-definition versions without watermarks when available. It supports numerous video platforms across both Chinese and international streaming ecosystems, enabling users to fetch content from many popular services through a... -
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Made With ML
Learn how to develop, deploy and iterate on production-grade ML
Made-With-ML is an open-source educational repository and course designed to teach developers how to build production-grade machine learning systems using modern MLOps practices. The project focuses on bridging the gap between experimental machine learning notebooks and real-world software systems that can be deployed, monitored, and maintained at scale. It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets,... -
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xLSTM
Neural Network architecture based on ideas of the original LSTM
xLSTM is an open-source machine learning architecture that reimagines the classic Long Short-Term Memory (LSTM) network for modern large-scale language modeling and sequence processing tasks. The project introduces a new recurrent neural network design that incorporates exponential gating mechanisms and enhanced memory structures to overcome limitations of traditional LSTM models. By introducing innovations such as matrix-based memory and improved normalization techniques, xLSTM improves the... -
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Torch Pruning
DepGraph: Towards Any Structural Pruning
Torch-Pruning is an open-source toolkit designed to optimize deep neural networks by performing structural pruning directly within PyTorch models. The library focuses on reducing the size and computational cost of neural networks by removing redundant parameters and channels while maintaining model performance. It introduces a graph-based algorithm called DepGraph that automatically identifies dependencies between layers, allowing parameters to be pruned safely across complex architectures.... -
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Chat with LLMs Everywhere
Run PyTorch LLMs locally on servers, desktop and mobile
TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a... -
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Huatuo-Llama-Med-Chinese
Instruction-tuning LLM with Chinese Medical Knowledge
Huatuo-Llama-Med-Chinese is an open-source project that develops medical-domain large language models by instruction-tuning existing models using Chinese medical knowledge. The project builds specialized models by fine-tuning architectures such as LLaMA, Alpaca-Chinese, and Bloom with curated medical datasets. These datasets are constructed from medical knowledge graphs, academic literature, and question-answer pairs designed to teach models how to respond accurately to healthcare-related... -
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Intel LLM Library for PyTorch
Accelerate local LLM inference and finetuning
Intel LLM Library for PyTorch is an open-source acceleration library developed to optimize large language model inference and fine-tuning on Intel hardware platforms. Built as an extension of the PyTorch ecosystem, the library enables developers to run modern transformer models efficiently on Intel CPUs, GPUs, and specialized AI accelerators. The framework provides hardware-aware optimizations and low-precision computation techniques that significantly improve the performance of large... -
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Nano-vLLM
A lightweight vLLM implementation built from scratch
Nano-vLLM is a lightweight implementation of the vLLM inference engine designed to run large language models efficiently while maintaining a minimal and readable codebase. The project recreates the core functionality of vLLM in a simplified architecture written in approximately a thousand lines of Python, making it easier for developers and researchers to understand how modern LLM inference systems work. Despite its compact design, nano-vllm incorporates advanced optimization techniques such... -
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MemFree
Hybrid AI Search Engine & AI Page Generator
memfree is an open source hybrid AI search engine and page generation platform designed to help users retrieve information from both personal knowledge bases and the public web through a unified interface. The project combines retrieval-augmented search with AI summarization to deliver concise answers instead of forcing users to manually sift through multiple sources. It supports multiple AI models and search providers, enabling flexible configuration depending on cost, performance, or... -
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also... -
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LiteBox
A security-focused library OS supporting kernel execution
LiteBox is a security-focused “library OS” sandboxing project that aims to shrink the interface between an application and its host environment to reduce attack surface. Instead of relying solely on broad OS-level permissions, it focuses on isolating workloads by tightly controlling the boundary where code interacts with host services and system resources. The design emphasizes interoperability across different integration layers, describing a separation between “North” shims (how apps or... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling... -
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Faved
Free open-source bookmark manager with customisable nested tags
Faved is a free, open-source, self-hosted bookmark manager focused on simplicity, speed, and local control of your saved links and references. It provides a clean web-based interface where users can store, organize, and search bookmarks without relying on third-party cloud services. Instead of just listing URLs, Faved supports customizable nested tags, helping users categorize their bookmarks in hierarchical structures that reflect personal workflows or project needs. All data is stored... -
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Glean
A self-hosted RSS reader and personal knowledge management tool
Glean is a self-hosted RSS reader and personal knowledge management platform designed to help information-heavy users efficiently aggregate, browse, and organize content from feeds. It centralizes RSS/Atom subscriptions, offering clean reading views, tagging, and organization features such as folders and bookmarks, while giving users full control over their data by deploying on their own infrastructure. Glean also includes real-time background synchronization, enabling feeds to update at... -
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zpdf
Zero-copy PDF text extraction library written in Zig
zpdf is a high-performance PDF text extraction library written in Zig that focuses on speed, low overhead, and modern parsing techniques. It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. It implements multiple PDF... -
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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...
