Building an Interactive Python and SQL Learning Companion chatbot using CodeLlama2-7B LLM

During the Christmas holidays, I dedicated my time to working on a project that is part of my university course.

The project involves building an interactive Python and SQL Learning Companion chatbot using CodeLlama2-7B LLM and Qdrant Vector DB. The primary objective of this project is to demonstrate my learning experience in the Python and SQL course to my professor.

To achieve this, I utilized various tools and tech stacks such as FastAPI for web application development and SQLite for storing user data. With these tools, I was able to create a custom knowledge base that would enable the chatbot to provide personalized responses to users’ queries.

Overall, this project has been an exciting and challenging experience for me. It has allowed me to apply the skills and knowledge I have gained in my Python and SQL course while also exploring new technologies such as CodeLlama2-7B LLM and Qdrant Vector DB.

The tools and tech stack I harnessed for this project selected to bring this chatbot to life listed bellow:

• CodeLlama2-7B LLM served as the core intelligence, empowering the chatbot’s conversational prowess.
• Qdrant Vector DB acted as the guardian of accumulated wisdom, facilitating quick and precise retrieval of information.
• FastAPI formed the backbone of the web application, enabling seamless interaction between users and the chatbot.
• The reliability and simplicity of SQLite were tapped into for efficiently storing and managing user data, ensuring privacy and security at its core.

I am confident that this project will not only impress my professor but also serve as a valuable resource for my classmates who are looking to learn Python and SQL.