Abstract: Techniques for simulating emotional intelligence in language model-based conversational agents through situationally adaptive trait expression are described. A text representation of a recording of a verbal request of a user recorded by a device and a paralinguistic caption indicative of a paralinguistic sentiment of the recording are sent to a user sentiment classifier model, which generates an estimated actual sentiment of the user. A first set of instructions are selected based at least in part on the estimated actual sentiment of the user, and include at least one trait to emphasize in a response to the verbal request. A first prompt to generate the response to the verbal request is sent to a language model, the first prompt including the first set of instructions. The response to the verbal request is received from the language model, and the response is sent to a rendering component for output by the device.