Search Results for "vector database"

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...

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. ...

Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It...

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. ...