Databricks Generative AI Engineer Associate exam dumps

Databricks Generative AI Engineer Associate practice question 101 of 306

Databricks Certified Generative AI Engineer Associate. Free level, Databricks. Free question with the correct answer and a full explanation.

Databricks Generative AI Engineer Associate Question 101

Select 2

You are tasked with building a Generative AI application that integrates external data from multiple APIs, provides conversational capabilities, and requires document retrieval for prompt generation. Which of the following tools or approaches would be most appropriate to streamline the development of this application?

  1. A

    LangChain for managing the chain of prompts, data retrieval, and API integrations

  2. B

    Hugging Face Transformers for fine-tuning a pre-trained model to improve conversational accuracy

  3. C

    PyTorch for building and training a custom model from scratch

  4. D

    Vector databases (e.g., Pinecone, Weaviate) for efficient document retrieval and similarity search

  5. E

    OpenCV for processing and analyzing images within the application

Show answer and explanation

Correct answers: A, D

Explanation

The scenario involves building a Generative AI application with conversational capabilities, external API integrations, and document retrieval. LangChain is an excellent tool for managing workflows, such as chaining prompts and integrating APIs, while vector databases provide efficient document retrieval and similarity search. Together, these tools streamline the development of the required application. Other options, like fine-tuning a model or using OpenCV, are not directly relevant to the requirements described in the question.

  • A. Correct.

    LangChain is highly suitable for managing complex workflows in a Generative AI application, such as chaining prompts, retrieving data from APIs, and structuring interactions with external tools.

  • B. Incorrect.

    Fine-tuning a Hugging Face Transformers model can improve conversational accuracy, but it is not directly related to managing workflows or integrating external tools, which is the focus of the question.

  • C. Incorrect.

    Building a custom model from scratch using PyTorch is unnecessary for this scenario. Pre-trained models and existing frameworks (e.g., LangChain) are better suited for simplifying development.

  • D. Correct.

    Vector databases are essential for document retrieval and similarity search, which is a key part of the application's requirements. They work well with tools like LangChain to fetch relevant data efficiently.

  • E. Incorrect.

    OpenCV is a library for image processing and analysis. It is unrelated to the requirements of this Generative AI application, which focus on conversational capabilities, data retrieval, and APIs.

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