Databricks Generative AI Engineer Associate Question 24
Select 3You are designing a conversational AI application using a pre-trained language model. The application must take user prompts as input, generate a step-by-step reasoning process, and finally provide a concise answer. Which chain components should you select to achieve this?
- A
PromptTemplate for structuring the input prompts
- B
LLMChain to connect the language model with the prompt
- C
VectorStore for storing and retrieving embeddings
- D
OutputParser for extracting specific data from the language model's output
- E
Memory to store conversation history for multi-turn dialogues
- F
ToolChain for integrating external APIs or tools
Show answer and explanation
Correct answers: A, B, D
Explanation
To achieve the desired input-output behavior for the conversational AI application, the PromptTemplate is used to structure input prompts, the LLMChain facilitates communication between the model and the prompts, and the OutputParser processes the model's output to extract reasoning and the final answer. Components like VectorStore, Memory, or ToolChain are not relevant in this specific context.
- A. Correct.
PromptTemplate is necessary to define the structure and format of the input prompts that will be sent to the model.
- B. Correct.
LLMChain is essential to link the language model with the input prompt and handle the flow of data between them.
- C. Incorrect.
VectorStore is not required in this scenario as there is no mention of embedding storage or retrieval in the problem statement.
- D. Correct.
OutputParser is important for processing the language model's output and ensuring the reasoning steps and final answer are extracted correctly.
- E. Incorrect.
Memory is not required because there is no mention of multi-turn dialogue or the need to store conversation history.
- F. Incorrect.
ToolChain is not relevant as the scenario does not involve integrating external APIs or tools.