RAG Data Ingestion and Retrieval Pipeline Explained

Building a RAG system without both pipelines is the most common mistake in AI development.

1️⃣ Data Ingestion Pipeline: Load your files, chunk the content, embed each chunk into a vector, and store it in a vector DB.

2️⃣ Data Retrieval & Generation Pipeline: Convert the user query into a vector, run semantic search, fetch top-k results, and send the full context to the LLM for a response.

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