Search Results for "vector linux os"
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Showing 579 open source projects for "vector linux os"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Memory OS
A 7-layer memory operating system for Hermes Agent
Memory OS is a local memory operating system for Hermes Agent. It is designed to help an AI agent retain project context, decisions, structured facts, reasoning patterns, and prior conversations across sessions. The system uses seven memory layers that combine flat files, SQLite, full-text search, structured facts, semantic recall, Qdrant vector storage, and a self-curating wiki pipeline. -
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ZeusDB Vector Database
Blazing-fast vector DB with similarity search and metadata filtering
ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch,... -
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DESERT OS Linux
Beautiful XFCE distribution
DESERT OS Linux is a fast, elegant Ubuntu-based Linux from Ukraine. It offers a refined XFCE experience optimized for both modern and legacy hardware. Key Features: - Lightweight: Fast performance with low resource usage. - Beautiful UI: Polished, modern look right out of the box. - Tiling Support: Integrated Cortile for easy window management -
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VikingDB MCP Server
A mcp server for vikingdb store and search
An MCP server that interfaces with VikingDB, a high-performance vector database developed by ByteDance, enabling efficient vector storage and search capabilities. -
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StarVector
StarVector is a foundation model for SVG generation
StarVector is a multimodal foundation model designed for generating Scalable Vector Graphics (SVG) from images or textual descriptions. The system treats vector graphics creation as a code generation problem, producing SVG code that can render detailed vector images. Its architecture combines computer vision techniques with language modeling capabilities so it can understand visual inputs and textual prompts simultaneously. The model converts raster images or text instructions into... -
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turbovec
A vector index built on TurboQuant, written in Rust with Python
turbovec is a Rust-based vector index with Python bindings for fast similarity search. It is built around TurboQuant, a quantization approach designed to reduce vector storage while preserving useful distance information. The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning.... -
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MCP Server Qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on... -
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UForm
Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion
UForm is a Multi-Modal Modal Inference package, designed to encode Multi-Lingual Texts, Images, and, soon, Audio, Video, and Documents, into a shared vector space! It comes with a set of homonymous pre-trained networks available on HuggingFace portal and extends the transfromers package to support Mid-fusion Models. Late-fusion models encode each modality independently, but into one shared vector space. Due to independent encoding late-fusion models are good at capturing coarse-grained... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Status - a Mobile Ethereum OS
A free (libre) open source, mobile OS for Ethereum
Status is a secure messaging app, crypto wallet, and Web3 browser built with state-of-the-art technology. Integrated into one powerful super app for private secure communication. Safely send, store and receive cryptocurrencies including ERC20 and ERC721 tokens with the Status crypto wallet. Only you hold the keys to your funds. Status' intuitive design protects you and your funds from attacks. Status uses an open-source, peer-to-peer protocol, and end-to-end encryption to protect your... -
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pgai
A suite of tools to develop RAG, semantic search, and other AI apps
pgai is a suite of PostgreSQL extensions developed by Timescale to empower developers in building AI applications directly within their databases. It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
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PageIndex
Document Index for Vectorless, Reasoning-based RAG
PageIndex is an innovative open-source framework that reimagines retrieval-augmented generation (RAG) by eliminating conventional vector similarity search and instead building hierarchical semantic indexes that mirror a document’s natural structure. Rather than chunking text and embedding it into a vector database, PageIndex constructs a tree-structured index — similar to a detailed, AI-enhanced table of contents — that a large language model can traverse to locate the most relevant sections... -
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Noto Emoji
Noto Emoji fonts
Noto Emoji (Stands for No Tofu) is an open-source (Open Font License 1.1) emoji library that provides standard Unicode emoji support and tools for working with them. -
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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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All-in-RAG
Big Model Application Development Practice 1
All-in-RAG is an open-source educational project designed to teach developers how to build applications using retrieval-augmented generation techniques. The repository provides a structured learning path that covers both theoretical foundations and practical implementation steps for RAG systems. It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. The... -
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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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OpenFreeMap
Free and open-source map hosting solution with custom styles
OpenFreeMap is a free and open-source map hosting platform that allows developers to display customizable maps in websites and applications without relying on commercial providers. It uses OpenStreetMap data and modern vector tile technologies to deliver high-quality maps with flexible styling options. The platform can be self-hosted or accessed through a public instance, offering full control or convenience depending on user needs. It removes common barriers such as API keys, usage limits,... -
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SeaGOAT
local-first semantic code search engine
...By combining vector search with tools like ripgrep, SeaGOAT provides a hybrid approach that supports both natural language queries and precise keyword matching in source files. It is built primarily in Python and is intended to work on common operating systems such as Linux, macOS, and Windows. -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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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. -
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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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Open Notebook
An Open Source implementation of Notebook LM with more flexibility
Open Notebook is an open-source, privacy-focused alternative to Google’s Notebook LM that gives users full control over their research and AI workflows. Designed to be self-hosted, it ensures complete data sovereignty by keeping your content local or within your own infrastructure. The platform supports 16+ AI providers—including OpenAI, Anthropic, Ollama, Google, and LM Studio—allowing flexible model choice and cost optimization. Open Notebook enables users to organize and analyze... -
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memsearch
A Markdown-first memory system, a standalone library for any AI agent
memsearch is a markdown-first memory system designed to provide long-term memory capabilities for AI agents through structured storage and semantic retrieval. It enables agents to store, organize, and retrieve information using embeddings and hybrid search techniques, ensuring that relevant context is always available. The system supports advanced features such as reranking and progressive disclosure, which help prioritize the most useful information for a given query. It integrates with... -
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I...