Digital systems increasingly mediate emotional support, yet their interactions often remain culturally generic. Accordingly, we examine how a poetic tradition can be operationalized as a culturally grounded interactive medium and how generative AI can support such engagement. The resulting interaction design framework translates staged literature-based support and tradition-specific poetic aesthetics into guidance for digital system design. Poemithy instantiates the framework as a multimodal, LLM-enabled multi-agent system for guided reflection through classical Chinese poetry. A controlled between-subjects study with 50 participants compared text-only and multimodal versions. Both conditions showed medium-to-large within-session improvements in affect, anxiety, and emotion regulation, while between-condition tests detected no differences in these changes. Among secondary post-session user-experience measures, the clearest observed differences favored multimodality in perceived attunement, perceived task success, and engagement; usability and hedonic quality were descriptively higher, while workload did not differ detectably. Post-only cultural ratings were descriptively favorable in both conditions for cultural identification, poetry-engagement and dissemination intentions, and perceived cultural enrichment. Together, the findings suggest that culturally grounded content and structured guidance should anchor system design, while multimodal presentation may strengthen resonance and engagement. More broadly, the work shows how generative AI can mediate engagement with poetic heritage in culturally grounded emotional-support interactions.

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