AI-102 exam dumps

AI-102 practice question 446 of 493

Designing and Implementing a Microsoft Azure AI Solution. Professional level, Microsoft. Free question with the correct answer and a full explanation.

AI-102 Question 446

Select 3

You are designing a chatbot using Azure OpenAI Service that needs to generate natural language responses based on prompts submitted by users. The chatbot must ensure the responses are relevant, concise, and well-structured. Which of the following configurations should you prioritize to achieve this goal?

  1. A

    Set the temperature to a low value such as 0.2.

  2. B

    Use a maximum token limit to control response length.

  3. C

    Set the frequency penalty to a high value such as 2.0.

  4. D

    Provide detailed and context-specific instructions in the prompt.

  5. E

    Enable content filtering in the Azure OpenAI Service.

Show answer and explanation

Correct answers: A, B, D

Explanation

To generate natural language responses that are relevant, concise, and well-structured, it is critical to configure the Azure OpenAI Service appropriately. Setting a low temperature ensures deterministic responses, using a maximum token limit controls verbosity, and crafting detailed prompts provides clear task instructions. These configurations collectively help achieve the desired chatbot behavior.

  • A. Correct.

    Setting the temperature to a low value such as 0.2 ensures more deterministic and focused responses, which is ideal for generating concise and relevant answers.

  • B. Correct.

    Using a maximum token limit helps control the response length, preventing overly verbose replies.

  • C. Incorrect.

    Setting a high frequency penalty like 2.0 is not recommended as it excessively penalizes repeated words, potentially distorting the natural flow of language.

  • D. Correct.

    Providing detailed and context-specific instructions in the prompt ensures the AI understands the task and generates a well-structured response.

  • E. Incorrect.

    While enabling content filtering can help moderate inappropriate responses, it does not directly affect the relevance, conciseness, or structure of the language generated.

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