Search Results for "vector linux" - Page 4
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Showing 954 open source projects for "vector linux"
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ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD). While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms (such as finite-differencing) in both speed and accuracy. Functions like f which map a vector to a scalar are the best case... -
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Elastiknn
Elasticsearch plugin for nearest neighbor search
Elasticsearch plugin for nearest neighbor search. Store vectors and run similarity searches using exact and approximate algorithms. Methods like word2vec and convolutional neural nets can convert many data modalities (text, images, users, items, etc.) into numerical vectors, such that pairwise distance computations on the vectors correspond to semantic similarity of the original data. Elasticsearch is a ubiquitous search solution, but its support for vectors is limited. This plugin fills the... -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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QuivrHQ
Opiniated RAG for integrating GenAI in your apps
Quivr is an open-source platform that leverages Retrieval-Augmented Generation (RAG) to integrate Generative AI into applications. It serves as a "second brain," enabling users to build powerful AI-driven assistants that can process and retrieve information efficiently. Quivr supports various large language models and vector stores, providing flexibility and customization for developers. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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GeoInterface.jl
A Julia Protocol for Geospatial Data
This Package describe a set of traits based on the Simple Features standard (SF) for geospatial vector data, including the SQL/MM extension with support for circular geometry. Using these traits, it should be easy to parse, serialize and use different geometries in the Julia ecosystem, without knowing the specifics of each individual package. In that regard it is similar to Tables.jl, but for geometries instead of tables. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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Vector Pascal is a language targeted at SIMD multi-core instruction-sets such as the AVX and SSE2 or x86-64-v3. It has a SIMD compiler which supports parallel vector operations, loop unrolling, common sub expression removal etc. It is implemented in Java.
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
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SmythOS
Cloud-native runtime for agentic AI
SmythOS SRE (Smyth Runtime Environment) is an open-source runtime and development platform designed for building and operating production-grade AI agents. It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. Developers can use the runtime to create, deploy, and orchestrate intelligent agents across local machines,... -
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DBreeze Database
C# .NET NOSQL ( key value store embedded ) ACID database
DBreeze Database is a professional, open-source, multi-paradigm (embedded Key-Value store, objects, NoSql, text search, multi-parameter search, embedding vector database, vector similarity search/clustering, etc.), multi-threaded, transactional and ACID-compliant data management system for .NET5> / .NET Framework 3.5> / Xamarin MONO Android iOS / .NET Core 1.0> / .NET Standard 1.6> / Universal Windows Platform / .NET Portable / UNITY / CoreRT. -
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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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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. Example scripts demonstrate how to train... -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
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Local Deep Research
95% on SimpleQA (e.g. Qwen3.6-27B on a 3090)
Local Deep Research is an open-source AI-powered research assistant designed to perform deep, iterative investigations by combining large language models with multi-source search capabilities. It runs locally, giving users full control over their data, privacy, and infrastructure while supporting both local and cloud-based LLMs. The system breaks down complex queries into smaller steps, performs parallel searches across web and academic sources, and generates structured, citation-backed... -
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XiangShan
Open-source high-performance RISC-V processor
XiangShan is an open-source, high-performance RISC-V processor project that implements out-of-order superscalar cores using Chisel for hardware construction. The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and... -
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SAG
SQL-Driven RAG Engine
SAG is an open-source SQL-driven retrieval-augmented generation engine that dynamically constructs knowledge graphs during query processing. Instead of relying on a static knowledge graph prepared in advance, the system automatically builds relational structures between entities while processing user queries. Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. These vectors allow the system to identify... -
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DeepMatch
A deep matching model library for recommendations & advertising
DeepMatch is an open-source deep matching library built for recommendation and advertising systems. It helps developers train models that learn vector representations for users and items. These representations can be exported and used in approximate nearest neighbor search for large-scale retrieval. The library supports familiar Keras workflows through model.fit() and model.predict(). Its model collection includes FM, DSSM, YouTubeDNN, NCF, SDM, MIND, and ComiRec. It is designed to make... -
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JamAI Base
The collaborative spreadsheet for AI
JamAI Base is an open-source backend platform designed to simplify the development of retrieval-augmented generation systems and AI-driven applications. The platform integrates both a relational database and a vector database into a single embedded architecture, allowing developers to store structured data alongside semantic embeddings. It includes built-in orchestration for large language models, vector search, and reranking pipelines so that AI applications can retrieve relevant... -
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Friction
Powerful and versatile motion graphics application
Friction is a lightweight 2D animation and motion graphics tool designed to provide a modern and efficient workflow for creating vector-based animations. It focuses on simplicity while offering essential features such as keyframe animation, timeline editing, and curve-based motion control. The application is built to be fast and responsive, enabling real-time feedback during animation editing. It supports exporting animations to various formats, making it suitable for use in games, web... -
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WeKnora
LLM framework for document understanding and semantic retrieval
WeKnora is an open source framework developed for deep document understanding and semantic information retrieval using large language models. It focuses on analyzing complex and heterogeneous documents by combining multiple processing stages such as multimodal document parsing, vector indexing, and intelligent retrieval. It follows the Retrieval-Augmented Generation (RAG) paradigm, where relevant document segments are retrieved and used by language models to generate accurate, context-aware... -
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Memvid
Video-based AI memory library. Store millions of text chunks in MP4
Memvid encodes text chunks as QR codes within MP4 frames to build a portable “video memory” for AI systems. This innovative approach uses standard video containers and offers millisecond-level semantic search across large corpora with dramatically less storage than vector DBs. It's self-contained—no DB needed—and supports features like PDF indexing, chat integration, and cloud dashboards. -
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Turso Database
Turso is an in-process SQL database, compatible with SQLite
...Turso includes support for concurrent writes through MVCC, change data capture, and faster schema management. It offers bindings and integrations across languages such as Rust, JavaScript, Go, Python, Java, .NET, and WebAssembly. The database also includes vector support, asynchronous Linux I/O with io_uring, and a built-in MCP server that lets AI assistants inspect and modify databases through structured tools. -
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city-roads
Visualization of all roads within any city
city-roads is a data visualization and mapping project that renders street networks of cities as vector paths, offering an interactive, zoomable experience that highlights how cities are stitched together by their road infrastructure. It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. The visual style often abstracts away labels and... -
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Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for... -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data...
