Ai Chatbot

In the exciting journey of creating my AI chatbot, I harnessed the power of Python and PyTorch to lay the foundation. Leveraging the robust META LLAMA2 model, I obtained the necessary permissions and seamlessly integrated it into my Python notebook. The real magic happened when I harnessed the GPU to train the model, fine-tuning it to meet the specific needs of my application. Transitioning from the realm of notebooks to the user-friendly Streamlit framework, I crafted an end-to-end web application that not only showcases the capabilities of the AI chatbot but also provides a seamless and intuitive experience for the end user. To further enhance accessibility and integration, I extended the functionality by creating a Flask API, allowing effortless communication with the JavaScript backend. This holistic approach ensures a smooth and responsive user experience, showcasing the convergence of powerful technologies in the realm of AI and web development.