RAGAnything FAQs

Question 1

How does RAGAnything manage data storage and retrieval?

Accepted Answer

Files are retrieved from MinIO object storage and automatically indexed into a PostgreSQL-backed knowledge graph. This graph leverages `pgvector` for vector embeddings and `Apache AGE` for graph capabilities, ensuring efficient and intelligent data organization and retrieval.

Question 2

Can I customize how RAGAnything queries my knowledge base?

Accepted Answer

Yes, RAGAnything offers multiple query modes, including 'naive', 'local', 'global', 'hybrid', 'mix', and 'bypass'. These modes allow users to fine-tune retrieval strategies, optimizing how relevant information is extracted from the knowledge graph for diverse use cases and improved query accuracy.

Question 3

What types of content can RAGAnything process?

Accepted Answer

RAGAnything supports a comprehensive range of formats including PDFs (with OCR), Microsoft Word (DOCX), PowerPoint (PPTX), Excel (XLSX), HTML, plain text (TXT, MD), Quarto Markdown, R Markdown, and various image formats (PNG, JPG, GIF, etc.) for multi-modal understanding.

Question 4

What is RAGAnything and what does it do?

Accepted Answer

RAGAnything is a powerful multi-modal RAG (Retrieval Augmented Generation) service that provides a REST API and MCP server. It enables users to index various documents and images into a PostgreSQL-backed knowledge graph, then perform advanced, intelligent queries against that knowledge base.

Question 5

What are the integration options for RAGAnything?

Accepted Answer

RAGAnything provides a flexible REST API for programmatic integration into any application. It also features an MCP (Multi-modal Conversational Platform) server, allowing seamless integration with AI agent frameworks and tools like Claude Desktop for enhanced AI workflows.

RAGAnything

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