GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #35
A Generative AI Engineer received the following business requirements for an internal chatbot. The internal chatbot needs to know what types of questions the user asks and route them to appropriate…
The correct answer is B. The chatbot should be implemented as a multi-step LLM workflow. First, identify the type of. The requirement is a single chatbot that routes different question types to appropriate data sources and models. Option B - a multi-step LLM workflow that first classifies the question type (e.g., historical failure rate lookup vs. troubleshooting guidance) and then routes to…
Question
A Generative AI Engineer received the following business requirements for an internal chatbot. The internal chatbot needs to know what types of questions the user asks and route them to appropriate models to answer the questions. For example, the user might ask about historical failure rates of a specific electrical part. Another user might ask about how to troubleshoot a piece of electrical equipment. Available data sources include a database of electrical equipment PDF manuals and also a table with information on when an electrical part experiences failure. Which workflow supports such a chatbot?
Options
- AParse the electrical equipment PDF manuals into a table of question and response pairs. That
- BThe chatbot should be implemented as a multi-step LLM workflow. First, identify the type of
- CThere should be two different chatbots handling different types of user queries.
- DThe table with electrical part failures should be converted into a text document first. That way, the
How the community answered
(28 responses)- A4% (1)
- B86% (24)
- C4% (1)
- D7% (2)
Explanation
The requirement is a single chatbot that routes different question types to appropriate data sources and models. Option B - a multi-step LLM workflow that first classifies the question type (e.g., historical failure rate lookup vs. troubleshooting guidance) and then routes to the appropriate data source and model - is the correct architecture. Option A loses the value of structured failure data by converting everything to Q&A pairs. Option C (two separate chatbots) doesn't meet the single-chatbot routing requirement. Option D converts the structured failure table to unstructured text, which sacrifices the precision and queryability of tabular data. A routing workflow preserves the strengths of each data source.
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