GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #77
A company has a typical RAG-enabled, customer-facing chatbot on its website. Select the correct sequence of components a user's questions will go through before the final output is returned. Use the…
The correct answer is A. 1.embedding model, 2.vector search, 3.context-augmented prompt, 4.response-generating LLM. Option A describes the correct RAG pipeline sequence. First, the user's question is converted into a vector by an embedding model. Second, vector search finds the most semantically similar documents in the vector store. Third, those retrieved documents are injected into a…
Question
A company has a typical RAG-enabled, customer-facing chatbot on its website. Select the correct sequence of components a user's questions will go through before the final output is returned. Use the diagram above for reference.
Exhibit
Options
- A1.embedding model, 2.vector search, 3.context-augmented prompt, 4.response-generating LLM
- B1.context-augmented prompt, 2.vector search, 3.embedding model, 4.response-generating LLM
- C1.response-generating LLM, 2.vector search, 3.context-augmented prompt, 4.embedding model
- D1.response-generating LLM, 2.context-augmented prompt, 3.vector search, 4.embedding model
How the community answered
(34 responses)- A91% (31)
- B6% (2)
- C3% (1)
Explanation
Option A describes the correct RAG pipeline sequence. First, the user's question is converted into a vector by an embedding model. Second, vector search finds the most semantically similar documents in the vector store. Third, those retrieved documents are injected into a context-augmented prompt alongside the original question. Fourth, the response-generating LLM processes this enriched prompt and returns the final answer. All other options place these steps in logically incorrect orders.
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