When your AI agent fails to accurately respond to a question, it is often due to the lack of explicit information or the absence of relevant data in the datastore it accesses. To enhance the accuracy of your agent or to uncover knowledge gaps, integrating a Q&A datasource is recommended. This approach enables the agent to access explicit answers to specific questions. Consider a scenario where an agent is queried, “What’s nuclear fusion?” Without information on nuclear fusion in its datastore, the agent might respond, “I’m sorry, I don’t have the information you’re looking for”
ℹ️ In this example, the knowledge restriction option is enabled; otherwise, the language model would have used knowledge from its training dataset.
Xnapper-2024-01-31-21.28.21.png To rectify this, click the “improve” button (available only from the Inbox page). You will then be prompted to provide a correct answer for the question that stumped the agent. Xnapper-2024-01-31-21.30.02.png This process automatically generates a new Q&A datasource within the linked datastore, which you can later edit or delete from the Datastore page. Xnapper-2024-01-31-21.30.51.png Following this procedure ensures that the agent will correctly respond to similar questions in the future. Xnapper-2024-01-31-21.32.11.png This method is effective across various languages, offering a versatile solution to improve your AI agent’s performance 😎 Xnapper-2024-01-31-21.42.35.png