Beyond a Single AI Assistant: Creating a Team Chat App Using Spring Boot and LangChain4j

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Nowadays, wherever we look, AI chat solutions are everywhere. From customer support bots handling inquiries to personal assistants scheduling meetings, AI-powered conversations have become an integral part of digital interactions. Developers experiment with different models, fine-tuning prompts, integrating memory, or giving assistants unique personalities to enhance user experience. However, most of these solutions follow the same fundamental pattern: a single AI assistant engaging with a human user.


If I ask anyone whether a conversation with ChatGPT feels realistic, they’ll likely say yes without hesitation, perhaps adding that it sometimes confidently states incorrect information or struggles with counting the “r”s in “strawberry.” Yet the most obvious imperfection, its unwavering willingness to answer every question instantly and politely, rarely raises any eyebrows. A chat interaction between two people is never this effortless and seamless. Many factors influence when and how someone responds. They might be busy with other tasks, waiting for you to clarify your question, or unsure of their own answer. Their response could also depend on their level of interest in the topic, their relationship with you, or even external distractions pulling their attention away.

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