QuestionQ91
Design ApplicationsA Generative AI Engineer has received the following business requirements for an internal chatbot. The internal chatbot must identify the types of questions users ask and route them to the appropriate models for answers. For example, a user might ask about the historical failure rates of a particular electrical part. Another user might ask how to troubleshoot a piece of electrical equipment.
Available data sources include a database of PDF manuals for electrical equipment and a table containing information about when an electrical part experiences failure.
Which workflow supports this chatbot?
- A Parse the electrical equipment PDF manuals into a table of question and response pairs. That way, the same chatbot can query tables easily to answer questions about both historical failure rates and equipment troubleshooting.
- B The chatbot should be implemented as a multi-step LLM workflow. First, identify the type of question asked, then route the question to the appropriate model. If it’s a historical failure rate question, send the query to a text-to-SQL model. If it’s a troubleshooting question, then send the query to another model that summarizes the equipment-specific document and generates the response.
- C There should be two different chatbots handling different types of user queries.
- D The table with electrical part failures should be converted into a text document first. That way, the same chatbot can use the same document retrieval process to generate answers regardless of question types.
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