Let’s take the example of "Service X" to explain how the OpenAI Assistant works.
Internal data: When setting up the assistant, you upload general information about "Service X" — documentation, knowledge base, specifications, and other materials. This data is used to answer common questions about the service and remains unchanged during interactions with users.
For example, the assistant can explain how to register for "Service X", help users understand its main features, or answer frequently asked questions if that information was loaded during setup.
External context: When a customer contacts support with an issue, the assistant not only uses the internal data but also analyzes the customer’s messages using activated
tools. This allows it to provide more accurate and relevant responses.
For instance, if a customer reports an authorization error, the assistant reviews the messages, notices a typo in the provided email address, and crafts a response by combining the internal data (preloaded instructions) with the external context (the specific customer message).
Key difference:- Internal data is the information uploaded in advance when setting up the assistant (documentation, knowledge base, specifications, and other materials).
- External data is the information the assistant receives during its operation, such as user questions in chat.
Using external data allows the assistant to tailor its responses to the specific situation, while internal data provides the foundational knowledge and overall context.