RAG Fusion FAQs

Question 1

What is RAG Fusion and its primary purpose?

Accepted Answer

RAG Fusion is a powerful Retrieval-Augmented Generation (RAG) server designed for dynamic support of various AI embedding providers, like OpenAI and DashScope, via the Model Context Protocol (MCP). Its primary purpose is to offer flexible, robust, and production-ready RAG capabilities.

Question 2

How does RAG Fusion handle different embedding providers?

Accepted Answer

RAG Fusion offers dynamic provider switching, allowing you to seamlessly switch between embedding providers (e.g., OpenAI, DashScope/Qwen) at runtime, without requiring code changes. It also supports multi-index configurations, so different document collections can use different providers.

Question 3

Is RAG Fusion suitable for production environments?

Accepted Answer

Yes, RAG Fusion is production-ready. It includes essential features like robust error handling with automatic fallback, rate limiting, comprehensive monitoring, and environment-based configuration for reliable deployment in scalable AI applications.

Question 4

Does RAG Fusion offer web search capabilities?

Accepted Answer

Yes, RAG Fusion integrates with leading web search APIs such as Perplexity and Exa. This integration allows your RAG system to perform enhanced searches and retrieve up-to-date information directly from the web.

Question 5

What is the Model Context Protocol (MCP) in RAG Fusion?

Accepted Answer

The Model Context Protocol (MCP) is the underlying framework that enables RAG Fusion's dynamic provider support. It standardizes how the server interacts with different embedding models, allowing for easy switching and integration without re-coding.

RAG Fusion

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