Databricks Generative AI Engineer Associate Question 22
Select 3You are designing a generative AI system using Databricks for a customer service chatbot. The chatbot should accept user queries as text input, retrieve relevant knowledge base documents, and generate a conversational response. Which chain components should you include to achieve the desired input and output?
- A
Text-to-Vector Embedding Module
- B
Knowledge Retrieval Component
- C
Prompt Template for Response Generation
- D
Speech-to-Text Conversion Module
- E
Response Ranking and Filtering Component
Show answer and explanation
Correct answers: A, B, C
Explanation
To design a chatbot with the specified functionality, the system must include components to process the text input (e.g., through embedding), retrieve relevant knowledge (via a retrieval component), and structure the model prompt to generate a response. Speech-to-text and response ranking are not essential for this specific use case.
- A. Correct.
Correct: Text-to-Vector Embedding is necessary to convert user queries into vector representations for similarity searches in the knowledge base.
- B. Correct.
Correct: The Knowledge Retrieval Component retrieves relevant documents or information from the knowledge base to be used in response generation.
- C. Correct.
Correct: A Prompt Template is required to structure the input for the language model to generate a conversation-like response based on the retrieved knowledge.
- D. Incorrect.
Incorrect: Speech-to-Text Conversion is not required here as the chatbot is expected to work with text input, not voice input.
- E. Incorrect.
Incorrect: Response Ranking and Filtering is useful for multi-response scenarios, but it is not a core requirement in this specific chatbot design.