Databricks Generative AI Engineer Associate Question 21
Select 3You are designing a generative AI workflow in Databricks to summarize long documents into concise bullet points. The input is a text file, and the output should be a list of summarized points. Which chain components should you select to achieve the desired outcome?
- A
Text Loader for reading the input file
- B
Document Splitter for breaking the text into manageable chunks
- C
Text-to-Image Generator for converting summaries into images
- D
Summarization Chain for generating concise bullet points
- E
Memory Component for storing the summarized points persistently
Show answer and explanation
Correct answers: A, B, D
Explanation
To summarize long documents into concise bullet points, you need to first load the text file (Text Loader) and split the text into smaller chunks for easier processing (Document Splitter). The Summarization Chain is then used to generate the bullet points. Other components like Text-to-Image Generator and Memory Component are not relevant to this specific workflow.
- A. Correct.
Text Loader is required to read the input text file and load it into the workflow for further processing.
- B. Correct.
Document Splitter is essential for breaking down a long text into smaller chunks, making it manageable for the summarization task.
- C. Incorrect.
Text-to-Image Generator is not relevant for this task as it is used for converting text into visual images, which is not the goal here.
- D. Correct.
Summarization Chain is the core component responsible for transforming the input text into concise bullet points, aligning with the desired output.
- E. Incorrect.
Memory Component is unnecessary in this scenario since the task does not require persistent storage of the generated summaries.