feat: replace manual web scraping with an agentic tool-selection engine

refactor: replace standard logging with a centralized loguru configuration and interception handler

feat: implement LLM fallback for quiz generation and enhance OAuth error handling

feat: implement lazy chunk caching for topic-based materials to reduce quiz and summary generation time

refactor: replace agent-based web search with parallelized retrieval using Wikipedia and DuckDuckGo

feat: introduce robust web-based prompt templates for quizzes and summaries.

refactor: update content limits for quiz and summary generation modules

refactor: changing to gemini model, modularize constants and schemas and update user daily generation limit

feat: implement profile caching and optimize database client initialization.

feat: configure LLM generation parameters and implement text truncation for summarization inputs

feat: enable AI-generated summaries for topic-based materials by integrating Wikipedia and Arxiv search providers.

refactor: add structured logging across summary and quiz generation modules

refactor: replace legacy login page with integrated Google OAuth landing page and dashboard redirect logic

refactor: improve markdown parsing, update summary export formatting, and refine UI loading states for material summaries

feat: Adding Parallel Processing and enhance main dashboard, summary and chat styles

feat: migrate UI to Next.js with extensive component library and integrate Hugging Face deployment workflow

refactor: restructure project into modular src architecture and implement database store layer