International Research Journal of Education and Technology

With the growing demand for intelligent customer support solutions, chatbots have become essential for enhancing user engagement and providing instant support. Traditional chatbot systems often lack contextual understanding and adaptability, which limits their ability to handle complex, multi-turn conversations. This study aims to develop a more advanced chatbot leveraging deep learning to address these limitations. The primary goal of this project is to build an adaptive chatbot using the GPT-4 model, capable of delivering natural language responses with high contextual accuracy and domain-specific knowledge. The chatbot is fine-tuned on a curated dataset to ensure specialized responses. Key methods include deploying the chatbot on cloud infrastructure (AWS, Google Cloud, or Azure) for scalability, utilizing Docker and Kubernetes for efficient orchestration, and implementing RESTful APIs for cross-platform integration. This project seeks to create an advanced chatbot system that overcomes the limitations of traditional models by combining the powerful language processing capabilities of GPT-4 with a robust cloud deployment strategy, adaptive learning, and stringent data privacy measures. The resulting chatbot will be capable of handling complex, multi-turn conversations with high contextual understanding, making it suitable for a wide range  of  applications,  including  customer  support, e-commerce, and interactive learning environments. By addressing the current gaps in chatbot technology, this project has the potential to set a new standard in AI-driven conversational agents, providing users with a more intuitive, responsive, and secure interaction experience. The chatbot demonstrates significant improvements in contextual understanding, achieving high BLEU and ROUGE scores that validate its accuracy. Initial user testing indicates effective multi turn dialogue handling and adaptive learning capabilities. These findings suggest the chatbot's potential for broader applications in customer support, with continuous learning from user interactions to enhance future performance. The project highlights the importance of secure deployment and regulatory compliance for data privacy.

Keywords: Chatbot, GPT-4, Deep Learning, Natural Language Processing