Vector Search

RAG

Retrieval-Augmented Generation (RAG) is a technique that combines a language model with an external retrieval system: relevant documents or passages are fetche…

Embeddings

Embeddings are dense numerical vector representations of data — such as words, sentences, images, or documents — learned so that semantically similar items are…

Vector Search

Vector search is a retrieval method that finds items by comparing the numerical similarity of their vector embeddings rather than matching exact keywords.

Semantic Search

Semantic search is an information retrieval approach that ranks results by contextual meaning and user intent rather than by exact keyword matches.

Embedding Model

An embedding model converts text, images, or other data into dense numerical vectors that capture semantic meaning, so that items with similar meaning end up c…

Reranker Model

A reranker model takes a shortlist of candidate results — usually produced by a fast initial retrieval step such as embedding-based vector search — and re-scor…

Embedding

An embedding is a numeric vector representation of data — such as text, images, or audio — designed so that items with similar meaning or content are positione…

Knowledge Graph

A knowledge graph is a structured representation of information as a network of entities and the relationships between them, typically stored as nodes and labe…

AnythingLLM

AnythingLLM is an open-source, full-stack application that turns any set of documents into a chat-with-your-data assistant using retrieval-augmented generation…

PrivateGPT

PrivateGPT is an open-source project that lets users ask questions about their own documents using large language models running entirely on local hardware, wi…

Langflow

Langflow is an open-source, low-code visual IDE for building LLM applications and agent workflows by connecting components on a drag-and-drop canvas, built clo…