Summary
In this tutorial, you'll learn how to enhance your chatbot's performance and cost-effectiveness by implementing a guard system. By setting up agents with complexity ratings like easy, moderate, or complex, you can ensure accurate responses to user queries. Creating custom fields for response ratings and using conditions based on complexity levels, such as with OpenAI, allows for tailored and efficient interactions with users through the chatbot.
Building a Guard for Chatbot Efficiency
Learn how to build a guard for your chatbot to save money and improve efficiency by setting up agents, assigning complexity ratings, and ensuring accurate outputs.
Setting Up Agent "Judge Robert"
Navigate to agents, add a new agent named "Judge Robert," and assign a complexity rating based on the type of questions the bot will handle.
Configuring Complexity Ratings
Understand the complexity ratings (easy, moderate, complex) and how to assign them based on the nature of incoming questions to the chatbot.
Creating Custom Field and Response Ratings
Set up custom fields for response ratings in Judge Robert, ensuring accurate and tailored responses to user queries based on a predefined scale.
Adding Conditions and Actions
Create conditions based on response ratings and define corresponding actions using OpenAI to generate appropriate bot responses for different levels of complexity.
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