Models & Architectures
Glossary
Retrieval-Augmented Generation
A technique that lets a model look up relevant documents and include them in its answer, improving accuracy and freshness.
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Retrieval-augmented generation (RAG) combines a retrieval system with a language model. When a question arrives, the system searches a knowledge base for relevant passages, then passes them to the model as context so the answer is grounded in real source material. RAG reduces hallucination, keeps answers current without retraining and is the standard way to build chatbots over private documents.
Related terms
Embedding
A numeric vector that represents the meaning of text, an image or another object so that similar items sit close togethe...
Vector Database
A database optimised for storing embeddings and finding the nearest vectors quickly.
Hallucination
When a model confidently states something that is false or unsupported by its sources.
Context Window
The maximum amount of text, measured in tokens, that a model can consider at once.
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