## Dataset Description
The **RealMedConv** dataset consists of anonymized, real-world dialogues between licensed pharmacists and users seeking over-the-counter (OTC) medication advice. Each conversation is goal-oriented: the pharmacist gathers sufficient symptom information to provide an online and appropriate recommendation. Dialogues are typically concise, spanning 3–5 turns, reflecting the efficient and expert-driven nature of professional medical consultations.
This dataset originates from real user-pharmacist interactions on an Alibaba Group service platform. To ensure strict compliance with data privacy and security standards, the raw logs have undergone rigorous processing—including de-identification, filtering, translation, and controlled perturbation—so that *no personally identifiable information (PII) or sensitive content remains*. The released version poses *no privacy leakage or security risks*.
Only a small subset is being open-sourced to support academic research, par…
