RAG Vault FAQs

Question 1

What is the setup process for RAG Vault?

Accepted Answer

Setup is remarkably simple and zero-configuration. You can deploy RAG Vault with a single `npx` command, eliminating the need for complex installations involving Docker, Python, databases, or extensive dependency management.

Question 2

How does RAG Vault ensure highly relevant search results for technical content?

Accepted Answer

RAG Vault employs a unique hybrid search combining vector similarity (semantic understanding) with exact keyword matching. This ensures it finds both conceptually related content and specific code terms (like `useEffect`) often missed by pure semantic models.

Question 3

What types of documents can RAG Vault ingest?

Accepted Answer

RAG Vault supports a wide range of formats, including PDFs, Word documents (.docx), Markdown (.md), plain text (.txt), JSON, and HTML (via `ingest_data`). It intelligently parses and chunks these documents to optimize search relevance.

Question 4

Is my data truly private and secure with RAG Vault?

Accepted Answer

Yes, RAG Vault ensures complete privacy by keeping all documents and processing local to your machine. After the initial embedding model download, zero data is ever sent to the cloud, giving you full control.

Question 5

Can RAG Vault be used offline?

Accepted Answer

Absolutely. After the initial embedding model download (approx. 90MB), RAG Vault functions entirely offline. The model caches locally, enabling you to access and search your private documents without any further internet connection.

RAG Vault

RAG Vault

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