Verified65% confidenceFactExact time
RAG treats an external document library as a dynamic knowledge source that can be retrieved in real time, constituting non-parametric knowledge that can be added, deleted, or modified at any time.
3
Sources
65%
Confidence
Long-term
Relevance
7/6/2026
First Seen
Sources
Building a RAG Q&A Workflow with Dify: A 4-Step Guide to Enterprise Knowledge Base Chatbots
bilibiliAI大模型大课堂6/30/2026
Related Claims
UnverifiedRAG technology allows models to retrieve external knowledge bases in real time without permanently uploading private data for training.83% similarUnverifiedThe knowledge source in RAG consists of human-readable, editable raw documents, and knowledge updates require only modifying the documents without retraining or rebuilding the embedding index.78% similarUnverifiedThe knowledge source of RAG (retrieval-augmented generation) usually relies on manually curated document chunks, whereas the knowledge source of LLM WIKI is the code repository itself.77% similarUnverifiedRAG通过持续更新的外部知识库缓解知识截止问题，且每个回答可附带来源文档提升可验证性77% similar
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