Search Results for "vector"
Sort By:
563 projects for "vector" with 1 filter applied:
-
Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
-
Cortex: Boost Developer Coding SkillsCortex is a simple portal that helps developers work smarter by linking all your tools, setting clear rules, and slashing repetitive tasks. It speeds up onboarding, updates old code, and fixes issues fast. Over 100 big companies use it to save time and get better results.
-
1
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. -
2
MyScaleDB
A @ClickHouse fork that supports high-performance vector search
MyScaleDB is an open-source SQL vector database designed for building large-scale AI and machine learning applications that require both analytical queries and semantic vector search. The system is built on top of the ClickHouse database engine and extends it with specialized indexing and search capabilities optimized for vector embeddings. This design allows developers to store structured data, unstructured text, and high-dimensional vector embeddings within a single database platform. ... -
3
Zvec
A lightweight, lightning-fast, in-process vector database
Zvec is an open-source, lightweight, in-process vector database designed to embed directly into applications and serve fast similarity search workloads without the overhead of a separate server process. Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. -
4
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. -
Jscrambler: Pioneering Client-Side Protection PlatformJscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.
-
5
RuVector
Self-Learning, Vector Graph Neural Network, and Database built in Rust
RuVector is part of the broader rUv ecosystem of AI engineering tools and focuses on enabling advanced vector-based processing and intelligent system development within agentic and AI-driven pipelines. The project fits into a larger vision of modular, composable AI infrastructure designed to support autonomous agents, data retrieval, and intelligent automation workflows. It emphasizes extensibility and interoperability with modern AI stacks, allowing developers to integrate vector operations into search, reasoning, or generative systems. ... -
6
HelixDB
Graph-vector database for building unified AI backends fast
...A central feature of the project is its custom query language, HelixQL, which is fully type-safe and compiled to ensure reliability and correctness in production environments. HelixDB includes built-in capabilities for embeddings, vector search, keyword search, and graph traversal, which are particularly useful for retrieval-augmented generation and agent-based systems. -
7
JTS Topology Suite
Java library for creating and manipulating vector geometry.
The JTS Topology Suite is a Java library for creating and manipulating vector geometry. It also provides a comprehensive set of geometry test cases, and the TestBuilder GUI application for working with and visualizing geometry and JTS functions. -
8
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, allowing systems to perform multi-turn reasoning, tool calling, and retrieval-based tasks within structured pipelines. ... -
9
LLPhant
A comprehensive PHP Generative AI Framework
...It provides developers with a set of abstractions for building AI-powered features such as chat systems, retrieval pipelines, and automated workflows while remaining simple enough to integrate into existing Symfony or Laravel projects. The framework focuses on usability by offering straightforward APIs for tasks like embeddings, question answering, and vector search, which are commonly required in real-world applications. It includes support for vector stores, enabling developers to build retrieval-augmented generation systems using structured or unstructured data. LLPhant also allows integration with external services and tools, making it possible to extend model capabilities beyond text generation into actionable workflows. -
Captain Compliance - Data Privacy and Compliance SoftwareCaptain Compliance handles your data privacy requirements so you can be privacy compliant. No more compliance stress, stop stressing over regulatory risks – just privacy protection managed by experts. Our user-friendly platform backed by privacy professionals simplifies the process of navigating regulations, giving your customers transparent choices, and building essential trust for your organization.
-
10
LangChain for .NET
C# implementation of LangChain
LangChain .NET is a C# implementation of the LangChain framework that enables developers to build LLM-powered applications using the .NET ecosystem. The project aims to replicate the core abstractions of LangChain, such as chains, agents, and vector stores, while adapting them to the conventions and strengths of C#. It emphasizes composability, allowing developers to build complex workflows by combining modular components that interact with language models and external data sources. The framework supports integration with multiple providers, including OpenAI and other compatible APIs, and includes tools for embeddings, document loading, and vector database interaction. ... -
11
GBrain
Garry's Opinionated OpenClaw/Hermes Agent Brain
GBrain is an open-source AI memory system designed to give autonomous agents persistent, structured, and scalable long-term memory across interactions and workflows. It operates by transforming large collections of markdown documents, personal notes, and external data into a searchable knowledge base backed by PostgreSQL and vector embeddings, enabling both semantic and keyword-based retrieval. The system is tightly integrated with agent frameworks such as OpenClaw and Hermes, allowing AI agents to read from and write to memory continuously, effectively evolving their understanding over time. GBrain introduces a hybrid retrieval model that combines embeddings with ranking strategies to improve relevance when querying large datasets. ... -
12
Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. ... -
13
OP Vault
Give ChatGPT long-term memory using the OP Stack
...It combines a backend written in Go with a React frontend, allowing users to upload files such as PDFs, text documents, and books to create a searchable repository of information. The system uses vector databases like Pinecone alongside OpenAI models to index and retrieve relevant content, enabling precise question-answering grounded in the uploaded materials. Users can query the system in natural language and receive answers that include references to specific files and sections, improving transparency and trust in the responses. ... -
14
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 of long documents. ... -
15
JOML
A Java math library for OpenGL rendering calculations
JOML is a high-performance, lightweight math library designed for 3D graphics applications in Java, particularly those using OpenGL, Vulkan, or LWJGL. It provides a complete suite of vector, matrix, quaternion, and geometry operations essential for real-time graphics and game development. Unlike other math libraries, JOML avoids object allocation during calculations, making it highly optimized for garbage-free performance. With precise control over mathematical operations and compatibility with low-level APIs, JOML is a go-to library for Java developers working on real-time 3D engines and simulations. -
16
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. -
17
RAG from Scratch
Demystify RAG by building it from scratch
...Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into language model prompts. Each example is written with detailed explanations so that developers can understand the internal mechanics of semantic search and context-aware language generation. The repository emphasizes learning through direct implementation, allowing users to see how each component of the RAG architecture functions independently. -
18
typst.ts
Run Typst in JavaScriptWorld
typst.ts is a project that brings the Typst typesetting system into the JavaScript ecosystem, enabling document compilation and rendering directly in browser and Node.js environments. It provides an implementation of Typst’s execution environment along with tools for compiling documents into various output formats, including vector graphics and web-friendly representations. The system is designed to support both client-side and server-side rendering workflows, allowing flexible deployment architectures for document generation. It includes multiple modules such as compilers, renderers, and exporters, which can be combined depending on the application’s needs. ... -
19
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 information before generating responses. JamAI Base exposes its functionality through a simple REST API and a spreadsheet-style interface that allows users to manage AI workflows visually. ... -
20
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 notebooks or the Code Editor, and export results to Cloud Storage, Drive, or asset collections. ... -
21
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 developers to build both local and cloud-based AI workflows. It is designed with developer experience in mind, offering strongly typed APIs, modular packages, and seamless integration into Flutter applications. ... -
22
Supermemory
Memory engine and app that is extremely fast, scalable
...It often incorporates clustering, semantic search, and summarization modules to reduce cognitive load and surface key ideas, which makes it useful for research, study, writing, and long-term project tracking. Users can interact with the system via conversational queries or traditional search interfaces, and the system leverages vector embeddings and memory scoring to prioritize the most relevant results. -
23
rag-search
RAG Search API
rag-search is a lightweight Retrieval-Augmented Generation API service designed to provide structured semantic search and answer generation through a simple FastAPI backend. The project integrates web search, vector embeddings, and reranking logic to retrieve relevant context before passing it to a language model for response generation. It is built to be easily deployable, requiring only environment configuration and dependency installation to run a functional RAG service. The system supports configurable filtering, scoring thresholds, and reranking options, allowing developers to fine-tune retrieval quality. ... -
24
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 and executed in parallel or sequential flows. It supports multimodal inputs and outputs, including text, images, audio, and documents, making it suitable for a wide range of AI applications. ... -
25
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, APIs, and tools. It supports multiple providers including OpenAI, Anthropic, Google, and local models, offering a unified interface for interacting with different backends. ...
