AI Study Notes Agent

Project Overview A cloud-native, multi-user AI application designed to transform how users interact with and synthesize study materials. Built with a focus on end-to-end engineering and MLOps, this platform leverages advanced Retrieval-Augmented Generation (RAG) to deliver context-aware document analysis and automated study aids.

Core Technologies & Frameworks

Python, Streamlit

Google Gemini 2.5 Flash

LangChain, ChromaDB

Supabase (PostgreSQL)

gTTS (Google Text-to-Speech)

Key Features & Engineering Highlights

Intelligent Document Analysis: Engineered a robust RAG pipeline utilizing ChromaDB and LangChain to process documents and generate highly accurate, citation-backed insights.

1-Click Anki Flashcard Generator: Developed an automated pipeline that extracts key concepts from text and instantly formats them into Anki-ready flashcards for spaced-repetition learning.

Audio Podcast Conversion: Integrated gTTS to automatically convert study notes and summaries into audio formats, allowing users to consume educational content on the go.

Scalable Cloud Architecture: Designed a multi-user environment backed by Supabase PostgreSQL, utilizing UUIDs for secure, persistent data storage and user isolation.

LLM Output Formatting: Implemented strict prompt engineering and formatting harnesses to prevent LLM output drift, ensuring 100% reliable and seamless database insertions.