让AI心理咨询的思考过程可被看见，辅助人类治疗师更好工作。
Psy-Copilot: Visual Chain of Thought for Counseling
- 用图结构可视化LLM在咨询中的推理步骤和关键洞察。
- 能检索相似对话、应对策略，并展示结果的可追溯路径。
- 适合心理治疗师与AI协作，提升咨询质量与透明度。
大型语言模型（LLMs）在心理咨询服务中日益普及，但其决策过程难以理解。为解决此问题，我们构建了Psy-COT——一种用于可视化LLM在咨询会话中思维过程的图结构。该图结合半结构化咨询对话与逐步标注，呈现治疗师的推理与洞察。我们还开发了Psy-Copilot，一个面向人类心理治疗师的对话式AI助手，可基于检索提供可追踪的心理信息，包括回复候选、相似会话、相关策略及结果的可视化路径。我们还搭建了一个交互式平台，界面可显示检索子图的相关部分。Psy-Copilot旨在促进人机协作而非替代治疗师，助力心理健康发展。代码与演示均已开源。
原文摘要 · Abstract (English)
Large language models (LLMs) are becoming increasingly popular in the field of psychological counseling. However, when human therapists work with LLMs in therapy sessions, it is hard to understand how the model gives the answers. To address this, we have constructed Psy-COT, a graph designed to visualize the thought processes of LLMs during therapy sessions. The Psy-COT graph presents semi-structured counseling conversations alongside step-by-step annotations that capture the reasoning and insights of therapists. Moreover, we have developed Psy-Copilot, which is a conversational AI assistant designed to assist human psychological therapists in their consultations. It can offer traceable psycho-information based on retrieval, including response candidates, similar dialogue sessions, related strategies, and visual traces of results. We have also built an interactive platform for AI-assisted counseling. It has an interface that displays the relevant parts of the retrieval sub-graph. The Psy-Copilot is designed not to replace psychotherapists but to foster collaboration between AI and human therapists, thereby promoting mental health development. Our code and demo are both open-sourced and available for use.
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