You build a chatbot that uses the Azure OpenAI GPT 3.5 model.
You need to improve the quality of the responses from the chatbot. The solution must minimize development effort.
What are two ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
To improve the quality of the responses from a chatbot with minimal development effort, two effective strategies are: providing grounding content and adding sample request/response pairs. Providing grounding content involves supplying the chatbot with relevant and domain-specific information such as documents and FAQs, which helps the model generate more contextually accurate responses. Adding sample request/response pairs allows the chatbot to learn from specific examples, improving its ability to understand and mimic desired conversational patterns. These methods enhance the chatbot's performance without the extensive resource demands of fine-tuning or retraining the entire model.
Here are two ways to improve the quality of the responses from the chatbot with minimal development effort: 1. Provide grounding content: This involves feeding the chatbot with relevant domain-specific information and data. This can include documents, articles, FAQs, or any other content related to the chatbot's purpose. By providing this context, the chatbot can better understand the user's intent and respond in a more relevant and informative way. 2. Add sample request/response pairs: This technique involves providing the chatbot with a set of pre-defined questions and their corresponding answers. This helps the chatbot learn the conversation patterns and phrasing related to its specific domain. By analyzing these examples, the chatbot can improve its ability to generate natural and consistent responses to user queries. Both options (A. Provide grounding content and C. Add sample request/response pairs) achieve the goal of improving response quality with minimal development effort, as they do not require extensive retraining or model building. Therefore, the two correct answers are: B. Provide grounding content. C. Add sample request/response pairs.
Remember that while fine-tuning (A) and custom models (E) can yield high-quality results, they often require significant development effort and computational resources. In contrast, grounding content and sample pairs offer pragmatic improvements with minimal overhead
Must be B & C
B and C for me too
GPT 4 Answered: B. Provide grounding content. C. Add sample request/response pairs.
I say this answer is B and C.
BC is correct answer.
B and C are right answer.
Selected Answer: BC
All 4 answers work, while Training a custom LLM is the highest effort, so that probably isn't it.