Chatbot Logic Overview A specialized RAG (Retrieval Augmented Generation) chatbot that helps users learn from the textbook content. Backend - Route : - Logic : 1. Receives and . 2. Embeds query using Gemini or OpenAI embedding model. 3. Searches Qdrant (vector DB) for relevant textbook chunks. 4. Constructs context from matches. 5. Generates response using Gemini Flash/Pro. Vector Search (Qdrant) We use Qdrant for storing embeddings of the textbook. - Collection: (or similar). - Fields: , , . UI Component - Location : . - Features : - Floating chat window. - Size controls (Small, Medium, Larg…