Organizations today want to build chatbots capable of handling a multitude of tasks, such as FAQs, troubleshooting, recommendations, and ideation. My previous article focused on a high-level view of designing and testing chatbots. Here, I will dive deeper into how strong intent routing and orchestration should figure into your chatbot design.
What Is a Multi-Use Chatbot?
A multi-use case chatbot supports several distinct tasks, each with different goals, performance needs, and response styles. For each use case, LLM parameters are fine-tuned around its goals. For example, a factual FAQ flow might use a low temperature for consistency, while a recommendation flow might use a higher one for creativity. Similarly, top p-values, frequency, presence, and max token penalties are also adjusted based on the use case.
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