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.
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Posted May 8, 2026
AI Study Notes Agent
Project Overview
A cloud-native, multi-user AI application designed to transform how users interact with and synthesize study materials....