I developed a custom AI chatbot in Python that uses a vector database to store and retrieve knowledge. When a user submits a query, the system searches the vector database for the most relevant questions and context, and then passes this information to the Gemini API to generate a coherent and natural response. This project gave me hands-on experience with embeddings, semantic search, and integrating large language models with retrieval pipelines.