Hyper

What is Hyper?

Hyper is an open-source developer toolkit designed to facilitate enhanced interactions with Large Language Models (LLMs) through Retrieval-Augmented Generation (RAG). It allows users to sync data from various sources to vector storage, enabling efficient querying and discovery of insights from real-time data derived from databases, APIs, and other integrations.

What are the main features of Hyper?

1. Data Synchronization: Connect and sync your data from multiple sources effortlessly.

2. RAG Queries: Execute sophisticated RAG queries that return accurate responses in milliseconds.

3. Multi-Model Support: Seamlessly switch between different LLMs, including GPT-4, Claude, and open-source models.

4. Access Control: Maintain strict access control and data privacy at a granular level.

5. High Performance: Benefit from optimized query processing through caching, indexing, and parallelization.

6. Open Source: Hyper is built on open-source technology, reinforcing a commitment to community contributions.

How to use Hyper?

To use Hyper, developers can easily connect their data sources by following a straightforward onboarding process. After integrating data with vector storage, users can implement RAG queries using minimal lines of code to achieve powerful insights.

What pricing options are available for Hyper?

Hyper is primarily open source, which means it is free to use for developers. However, for organizations that require additional features or support, custom plans may be available. Interested users should join the waitlist for more information regarding potential subscription models or enterprise solutions.

Helpful Tips for Using Hyper

• Explore Documentation: Familiarize yourself with the Hyper documentation to understand the capabilities and setup processes.

• Experiment with Queries: Take time to try different query types to see how they perform with various data sets.

• Join the Community: Engage with the Hyper community on GitHub to share experiences, ask questions, and contribute to the project.

Frequently Asked Questions

How does Hyper handle data privacy?

Hyper allows users to own their data pipeline at a granular level. You can manage what data is used in your queries while ensuring strict access control for security.

Can I integrate Hyper with popular data sources?

Yes, Hyper supports integration with widely used platforms such as Slack, Google Drive, Notion, and Airtable, making it flexible for various workflows.

What should I do if I encounter issues during setup?

If you experience difficulties during the setup or integration process, refer to the Hyper documentation for troubleshooting steps or seek assistance from the community on GitHub.

Is Hyper suitable for enterprise applications?

Absolutely, Hyper is designed to scale from individual developer tools to enterprise RAG implementations, allowing large organizations to make effective use of their data with LLMs.