Introduction
Welcome to the Hyper documentation.
Hyper is a developer platform designed to improve data ingestion and interaction capabilities for large language models (LLMs). It integrates multiple data sources, such as Google Drive, Zendesk, and Redis, into a unified interface, supporting complex Retrieval-Augmented Generation (RAG) queries and sophisticated access control.
The platform streamlines the processes of data ingestion, querying, and access management, allowing developers building LLM applications to focus on building features.
Hyper also supports the ingestion of various data types, including documents, images, and websites. By configuring Hyper with a model and vector store, developers can leverage RAG techniques such as information retrieval, question & answer, and semantic search for improved data querying.
Features
Hyper offers a suite of powerful features designed to facilitate the integration and querying of diverse data sources. Here's a quick overview of the Hyper toolkit: