Show What is Retrieval-Augmented Generation?
Show What is Retrieval-Augmented Generation?
What is Retrieval-Augmented Generation?
RAG is a technique that enhances language models by providing them with relevant external information during generation. Instead of relying solely on training data, RAG systems can access and reason over up-to-date information from knowledge bases, documents, or databases.
The RAG Process
- Retrieval: Find relevant documents or information based on the user’s query
- Augmentation: Combine the retrieved information with the original query
- Generation: Use a language model to generate a response using both sources
Show Vector Embeddings & Semantic Search
Show Vector Embeddings & Semantic Search
Vector Embeddings & Semantic Search
Vector embeddings convert text into numerical representations that capture semantic meaning. This allows us to find similar content based on meaning rather than just keyword matching.
Traditional Search
Matches exact keywords and phrases. Limited understanding of context and
meaning.
Semantic Search
Understands meaning and context. Can find relevant content even with
different wording.