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AIEngineeringWeek2V1

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Zainab4626 commited on Apr 15

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@@ -6,7 +6,7 @@ End-to-end **Retrieval-Augmented Generation (RAG)** system built for **Applied A
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-## What this project demonstrates (recruiter-friendly)
 - **Production-shaped RAG**: not “call an LLM”—a full pipeline from documents → chunks → embeddings → retrieval → grounded answers.
 - **Grounding + safety posture**: answers are constrained to retrieved context with an explicit fallback when evidence is insufficient.

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+## What this project demonstrates
 - **Production-shaped RAG**: not “call an LLM”—a full pipeline from documents → chunks → embeddings → retrieval → grounded answers.
 - **Grounding + safety posture**: answers are constrained to retrieved context with an explicit fallback when evidence is insufficient.