Search Results for "vector linux" - Page 5
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Showing 954 open source projects for "vector linux"
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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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Intel Extension for PyTorch
A Python package for extending the official PyTorch
Intel® Extension for PyTorch* extends PyTorch* with up-to-date features optimizations for an extra performance boost on Intel hardware. Optimizations take advantage of Intel® Advanced Vector Extensions 512 (Intel® AVX-512) Vector Neural Network Instructions (VNNI) and Intel® Advanced Matrix Extensions (Intel® AMX) on Intel CPUs as well as Intel Xe Matrix Extensions (XMX) AI engines on Intel discrete GPUs. Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel... -
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QuadGK.jl
adaptive 1d numerical Gauss–Kronrod integration in Julia
This package provides support for one-dimensional numerical integration in Julia using adaptive Gauss-Kronrod quadrature. The code was originally part of Base Julia. It supports the integration of arbitrary numeric types, including arbitrary-precision (BigFloat), and even the integration of arbitrary normed vector spaces. The package provides three basic functions: quadgk, gauss, and kronrod. quadgk performs the integration, gauss computes Gaussian quadrature points and weights for... -
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Vedana
Open source multi-agent RAG over a knowledge graph
Vedana is an open-source multi-agent RAG system built around a typed knowledge graph. It is designed for questions that require structure, completeness, and traceability instead of simple text similarity. The system lets agents navigate data step by step through Cypher queries, vector search, document lookup, and source verification. Its architecture combines a knowledge graph, pgvector-based embeddings, incremental ETL, and a backoffice interface for chat, metrics, prompt tuning, and data... -
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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ParadeDB
ParadeDB is a modern Elasticsearch alternative built on Postgres
ParadeDB is an open-source search and analytics engine built on top of PostgreSQL. It serves as a modern alternative to Elasticsearch, offering real-time search capabilities for update-heavy workloads. By leveraging PostgreSQL's robustness, ParadeDB provides a scalable and efficient solution for full-text search and analytics. -
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React Native RAG
Private, local RAGs. Supercharge LLMs with your own knowledge base
React Native RAG is a local retrieval-augmented generation library for React Native applications. It lets mobile apps enhance language models with the user’s own knowledge base while keeping retrieval local. The library is modular, so developers can choose pieces such as LLM, embeddings, vector store, and text splitter components. It is also extensible, allowing teams to implement their own interfaces when they need custom model or storage behavior. React Native RAG supports multiple... -
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Claude Context
Code search MCP for Claude Code
Claude Context is a tool designed to enhance the contextual understanding of large language models by managing and injecting relevant information into prompts. It focuses on improving response quality by ensuring that models have access to the most relevant data when generating outputs. The system integrates with vector databases and retrieval systems, enabling efficient storage and retrieval of contextual information. It supports workflows such as retrieval-augmented generation, where... -
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LangChain.dart
Build LLM-powered Dart/Flutter applications
LangChain.dart is a Dart and Flutter implementation of the LangChain framework, designed to enable developers to build LLM-powered applications for mobile, web, and cross-platform environments. It provides a structured way to integrate language models into applications by offering abstractions for chains, agents, embeddings, and vector stores. The framework supports multiple providers and includes packages for integrating with services such as OpenAI, Google AI, and Firebase, allowing... -
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NeMo Retriever Library
Document content and metadata extraction microservice
NeMo Retriever Library is a scalable microservice framework designed for extracting, structuring, and enriching content from documents to support downstream generative AI applications. It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient... -
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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Reor Project
Private & local AI personal knowledge management app
Reor is an AI-powered desktop note-taking app: it automatically links related notes, answers questions on your notes, provides semantic search and can generate AI flashcards. Everything is stored locally and you can edit your notes with an Obsidian-like markdown editor. The hypothesis of the project is that AI tools for thought should run models locally by default. Reor stands on the shoulders of the giants Ollama, Transformers.js & LanceDB to enable both LLMs and embedding models to run locally. -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
Rivet is an open source visual AI programming environment designed to help developers build complex AI agents using a node-based interface and prompt chaining workflows. It provides a desktop application that allows users to visually construct and debug AI logic as interconnected graphs, making it easier to manage sophisticated interactions between language models and external tools. Rivet also includes a TypeScript library that enables these visual graphs to be executed and integrated... -
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SymEngine.jl
Julia wrappers of SymEngine
Julia Wrappers for SymEngine, a fast symbolic manipulation library, written in C++. -
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Jlama
Jlama is a modern LLM inference engine for Java
Jlama is a modern inference engine written entirely in Java that enables developers to run large language models locally within Java applications. Unlike frameworks that require external APIs or remote services, Jlama performs inference directly on a machine using pre-trained models. This allows organizations to integrate generative AI features into their systems while maintaining full control over data privacy and infrastructure. The engine supports a wide range of open-source model... -
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Self-hosted AI Package
Run all your local AI together in one package
Self-hosted AI Package is an open-source Docker Compose-based starter kit that makes it easy to bootstrap a full local AI and low-code development environment with commonly used open tools, empowering developers to run LLMs and AI workflows entirely on their infrastructure. The stack typically includes Ollama for running local large language models, n8n as a low-code workflow automation platform, Supabase for database and vector storage, Open WebUI for interacting with models, Flowise for... -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in... -
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OpenAI .NET
The official .NET library for the OpenAI API
OpenAI .NET is the official client library for calling the OpenAI REST API from C# and other .NET languages, with first-class support for modern .NET patterns. It provides strongly typed clients across API areas (chat, audio, images, embeddings, moderations, batches, files, models, vector stores, responses, realtime, assistants) and works with .NET Standard 2.0 while the examples use .NET 8. You install it via NuGet and authenticate with an API key, ideally through environment variables or... -
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AnythingLLM
The all-in-one Desktop & Docker AI application with full RAG and AI
A full-stack application that enables you to turn any document, resource, or piece of content into a context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions. AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no... -
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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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LLM Tornado
The .NET library to build AI agents with 30+ built-in connectors
LLM Tornado is a provider-agnostic .NET SDK designed to build, orchestrate, and deploy AI agents and workflows with a strong focus on flexibility and integration. It provides a unified interface that connects to more than 30 AI providers and vector databases, allowing developers to switch between models and services without rewriting application logic. The framework introduces a powerful orchestration system based on graph-like structures, where agents, tasks, and transitions can be defined... -
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LangChainGo
LangChain for Go, the easiest way to write LLM-based programs in Go
LangChainGo is a Go-based implementation of the LangChain framework, designed to help developers build applications powered by large language models using the Go programming language. It provides a modular architecture that allows developers to combine components such as language models, chains, agents, memory systems, and vector stores into flexible workflows. The framework emphasizes composability, making it easy to create complex pipelines that integrate LLMs with external data sources,... -
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Pathway AI Pipelines
Ready-to-run cloud templates for RAG
Pathway AI Pipelines is a collection of ready-to-deploy AI pipeline templates designed to help developers rapidly build production-grade retrieval-augmented generation and enterprise search applications. The project provides end-to-end examples that connect live data sources to LLM workflows, enabling applications to stay synchronized with continuously changing information. It supports numerous connectors including local files, Google Drive, SharePoint, Kafka, PostgreSQL, and real-time APIs,... -
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AI PDF Chatbot LangChain
AI PDF chatbot agent built with LangChain & LangGraph
AI PDF Chatbot LangChain is a full-stack template for building conversational agents that can ingest and answer questions about PDF documents. The project demonstrates how to combine LangChain and LangGraph with a vector database to enable retrieval-augmented question answering over user-provided files. It includes both frontend and backend components, making it suitable as a production starting point rather than just a minimal demo. The system parses uploaded PDFs into document chunks,... -
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SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
SimpleMem is a lightweight memory-augmented model framework that helps developers build AI applications that retain long-term context and recall relevant information without overloading model context windows. It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory... -
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Discord.SortedSet
Elixir SortedSet backed by a Rust-based NIF
SortedSet NIF is a performant and reliable sorted set data structure for Elixir, implemented in Rust using the Rustler crate to take advantage of native performance while maintaining seamless integration with the BEAM ecosystem. It provides ordering and uniqueness guarantees, with all terms stored according to Elixir’s built-in sorting rules. Internally, it uses a vector of vectors layout rather than a single vector to minimize costly reallocations, allowing efficient bucket pointer copying... -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so...
