Emotional Intelligence in Chatbots: A Study on Enhancing User Experience with Llama3 and Ollama

The field of emotional support chatbots has become a significant part of the tools designed to enhance mental well-being through human-like conversations. This paper introduces an innovative approach that prioritizes empathy and context continuity. The proposed solution, named "SOLARA" utilizes the Llama3.2:3b model within the Ollama framework. By incorporating sentiment analysis powered by fuzzy logic, SOLARA delivers context-aware, personalized, and empathetic responses. The Llama3.2:3b model enhances SOLARA’s ability to understand complex language and retain memory more effectively. With Ollama enabling offline functionality, SOLARA ensures user privacy and reliability. Compared to existing solutions, this approach demonstrates improvements in emotional accuracy, response quality, and conversational coherence. The solution highlights the potential of NLP in addressing emotional concerns while balancing performance and user privacy, paving the way for further exploration in this field.