CHAT BOT APPLICATION

This paper presents the design and implementation of an
intelligent chatbot using Python and Generative AI for an
automated question-and-answer system. The proposed system
integrates the Gemini API with a Streamlit-based interface to
deliver real-time, context-aware responses to user queries. By
leveraging large language models, the chatbot is capable of
generating human-like responses while maintaining
conversational history for improved interaction. The system
architecture ensures efficient communication between the user
interface, backend processing, and AI model. Experimental
results demonstrate that the chatbot provides accurate
responses with minimal latency, making it suitable for
applications in education, customer support, and virtual
assistance. The proposed solution highlights the potential of
Generative AI in developing scalable and interactive
conversational systems.