PsyChain: A Collaborative Chain-of-Agents Framework for Generating Personalized and Professional Counseling Dialogues

Existing psychological counseling datasets often suffer from monolithic client personas, insufficient therapeutic depth, and a lack of process controllability. To address these critical limitations, we propose PsyChain, a chain-ofagents framework that evolves static counseling corpora into high-fidelity dialogues through collaborative simulation which explicitly models client personality, stage progression, safety monitoring, and expert supervision. PsyChain involves a Client Profiler that extracts life scenarios and pairs them with psychological personality archetypes to synthesize diverse profiles. To simulate the complete counseling process, five specialized agents-Process Monitor, Client Speaker, Safety Monitor, Counselor Supervisor, and Counselor Speaker-collaborate and interact autonomously at each dialogue turn to ensure therapeutic professionalism and safety. We apply this to construct PsyChainD, a Chinese dataset of 10,456 dialogues featuring systematically diverse client profiles. Extensive evaluation across client side, counselor side and overall quality shows substantial improvements. The model trained on PsyChainD achieves 61-91% win rates against domainspecific baselines in pairwise evaluation and the highest average score in human evaluation, indicating potential for real-world counseling.