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Details of the RAG Chatbot, including UI and backend logic.
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Based on SOC occupation classification
Documentation for the FastAPI backend, endpoints, and dependency injection.
Overview of the project's tech stack, directory structure, and architectural patterns.
Guide to using Better Auth for client and server-side authentication.
Validates and analyzes Docusaurus MDX chapters for structure, pedagogical quality, and component usage.
Interaction with NeonDB Postgres using Drizzle ORM.
Knowledge of the Vercel deployment pipeline, hybrid build scripts, and environment configuration.
| name | Chatbot Implementation |
| description | Details of the RAG Chatbot, including UI and backend logic. |
A specialized RAG (Retrieval Augmented Generation) chatbot that helps users learn from the textbook content.
app/api/chat/route.tsquery and history.We use Qdrant for storing embeddings of the textbook.
textbook_chunks (or similar).text, source, chunk_id.textbook/src/components/Chatbot/index.tsx.styles.module.css (Premium animations, shadow effects).--ifm variables).