Large language models (LLMs) have the potential to be powerful instruments for psychotherapy. However, there is a shortage of practical tools to support their use in production. We develop a novel, iterative process of updating conversational context for tracking EIS (Emotional Intelligence Scale) instantaneously, and test Llama-70b. Through this, we show that (1) EIS varies more on psychotherapeutic (emotional support) conversations than control (emotionally unstimulating) conversations and (2) model responses can be systematically classified to identify consistent patterns. Thus, EIS is a valid indicator of empathetic model behavior. Rises in the EIS score correspond to prosocial behavior, and falls correspond to detached, unsocial behavior. These results suggest that psychometric questionnaires like EIS can provide a structured lens for observing empathetic stability of models and offer a foundation for future work on their role in psychotherapy.