In recent years, the integration of deep learning and bionic algorithms has opened a new horizon for the development of high-end chatbots. This article explores the design and implementation of a chatbot that uses deep learning (specifically neural networks) and bionic algorithms (such as genetic algorithms and Ant colony optimization) to well enhance communication and interaction. Chatbot architecture integrates deep learning models to generate natural and intuitive messages for target users. At the same time, bionic algorithms are used to optimize the chatbot's responses and improve its adaptation to a dynamic conversation environment. For example, genetic algorithms facilitate the development of response strategies by selecting and displaying the most efficient communication patterns, while the development of ants helps find the shortest path and stay relevant in the discussion tree. The combination method outperforms legitimate and deep learning chatbots in terms of correct answers, user satisfaction, and adaptability. The integration of biomimetic algorithms not only improves the chatbot's functionality but also supports its ability to learn and evolve over time by optimally following natural selection and activation in biological systems. The results demonstrate the potential of combining deep learning with bionic algorithms to create stronger, smarter and more user-friendly chatbots. This article lays the groundwork for future research to further explore the use of bionic technology in artificial intelligence and natural language processing.