What is a Retrieval Augmentation Pipeline?
A system that combines retrieval and generation processes to enhance AI model outputs with relevant knowledge.
More about Retrieval Augmentation Pipeline:
Retrieval Augmentation Pipeline integrates retrieval systems and generative models to produce knowledge-grounded outputs. The pipeline retrieves relevant information from sources like vector databases or knowledge graphs and passes it to a generative model to produce accurate and contextually rich responses.
This approach is widely used in frameworks like retrieval-augmented generation (RAG) and context-aware generation, ensuring responses are factual and relevant.
Frequently Asked Questions
How does a retrieval augmentation pipeline improve AI outputs?
It ensures responses are grounded in reliable information, reducing hallucinations and improving factual accuracy.
What components are commonly part of a retrieval augmentation pipeline?
Key components include retrieval models, embeddings, and generative AI models.
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