Design a Retrieval-Augmented Generation pipeline with chunking strategy, embedding models, vector search, and answer generation with source attribution.
## CONTEXT Retrieval-Augmented Generation has become the dominant architecture for building knowledge-grounded AI systems — reducing hallucination rates by 50-70% compared to pure generation while enabling AI systems to answer questions from proprietary knowledge bases without fine-tuning. However, 65% of RAG…
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