🤖 What Does the LLM Do in RAG?

You might wonder:

“If we already found the answer in the document, why do we need a language model?”

Let’s break it down with a real example 👇

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📦 You Ask a Question

Q: What are the benefits of TCP?

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🔍 Retriever Finds a Chunk

📄 Retrieved:
"TCP provides reliable, ordered delivery,
error checking, and congestion control."

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🤖 The LLM Thinks...

It takes that chunk and your question, and:

• Rephrases
• Summarizes
• Explains clearly

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💬 LLM Responds

A: TCP is more reliable than other protocols because it guarantees your data will arrive in order and without errors. This is especially useful for web browsing and email.

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🧠 Why Use an LLM at All?

Retriever 📚	LLM 🤖
Finds relevant info	Turns it into a helpful answer
Keyword matching	Language understanding
Memory	Reasoning

You need both to make RAG powerful.

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📚 Suggested Use

• Include in lab instructions
• Link in student guides
• Use in tutorials explaining RAG

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