Databricks Generative AI Engineer Associate Question 102
Select 2You are building a Generative AI application for summarizing customer support conversations. The application needs to integrate a Large Language Model (LLM) and retrieve conversation history stored in a database. Which of the following tool(s) would be most appropriate to use in this scenario?
- A
LangChain
- B
Hugging Face Transformers
- C
Pandas
- D
Pinecone
- E
TensorFlow
Show answer and explanation
Correct answers: A, D
Explanation
LangChain is particularly useful for building workflows that connect LLMs with external data sources, like conversation history stored in databases. Pinecone adds value by serving as a vector database for efficient retrieval of conversation embeddings, making these tools ideal for this scenario. While Hugging Face Transformers and TensorFlow are powerful frameworks, they are not designed for the specific needs of this Generative AI application. Similarly, Pandas is better suited for data manipulation than for application or workflow development.
- A. Correct.
LangChain is designed for building applications that integrate LLMs with external data sources, such as databases. It provides tools for chaining prompts and retrieving data, making it highly suitable for this scenario.
- B. Incorrect.
Hugging Face Transformers is a library for working with pre-trained models, but it does not inherently handle integration with databases or provide tools for prompt chaining, which are necessary for this use case.
- C. Incorrect.
Pandas is a data manipulation tool, but it is not designed for interacting with LLMs or building applications that integrate databases with LLMs.
- D. Correct.
Pinecone is a vector database designed to store and retrieve embeddings efficiently, making it a good choice for retrieving conversation history in a way that complements LLM-based summarization.
- E. Incorrect.
TensorFlow is a machine learning framework primarily used for training and deploying models, but it is not designed for integrating LLMs with databases or handling application workflows.