MemoMate

2025.01.08

MemoMate

A web application that streamlines note-taking and summarization powered by AI. Upload documents, create AI chatbots from your notes, and generate diagrams via natural language.

Features

Note Workspaces — Hierarchical tree-based file/folder organization
Document Upload — Support for PDF, DOCX, and Excalidraw formats
AI Chatbot Creation — RAG-based chatbots from uploaded notes
Diagram Generation — Natural language to Mermaid syntax (flowcharts, Gantt charts)
Whiteboard — Excalidraw-based collaborative drawing
Command Bar — kmenu-powered quick actions
Shareable Bot Links — Create bots from notes and share via unique URLs
Admin Dashboard — Site metrics, token usage, and user engagement

Technical Highlights

LangChain + LangGraph for RAG workflow orchestration
Faiss vector store for similarity search
OpenAI GPT-4o-mini for chat and diagram generation
Excalidraw integration for whiteboard functionality
Redux Toolkit for state management
AWS EC2 deployment with GitHub Actions CI/CD

Tech Stack

Layer	Technology
Frontend	React 18 + TypeScript + Redux
Backend	Bun + Express + MongoDB
AI/ML	LangChain, LangGraph, OpenAI
Vector Store	Faiss
Auth	JWT + bcrypt

Architecture

User uploads documents (PDF, DOCX)
         ↓
Document Parser (pdf-parse, mammoth)
         ↓
Text Splitter (RecursiveCharacterTextSplitter)
         ↓
Embedding Generator (OpenAI)
         ↓
Faiss Vector Store
         ↓
User chats → Retrieve relevant chunks → LLM generates response

notes ai react

Dynamic RAG

2025.01.02

Dynamic RAG

A sophisticated Retrieval-Augmented Generation system with multi-agent architecture for intelligent question-answering over custom knowledge bases.

Features

Multi-Agent Architecture — Specialized agents working together:
- QA Agent — Main agent for answering questions using the knowledge base
- Personal Agent — For personal/general questions not requiring RAG
- Validation Agent — Classifies queries as on-context, personal, bad, or unknown
- Prompt Agent — Generates diverse query perspectives for comprehensive retrieval
- Reranking Agent — Reorders retrieved chunks for better relevance
Hybrid Search — Combines FAISS vector similarity with keyword matching
Streaming Responses — Token-by-token streaming of LLM outputs
Multi-language Support — Uses multilingual embeddings via Cohere
Document Processing — PDF parsing with OCR support via Mistral

Technical Highlights

LangChain + LangGraph for orchestrating the RAG pipeline
FAISS vector store for similarity search
Cohere embeddings for multilingual support
SQLite for session persistence and analytics
Configurable agents via JSON configuration files

Tech Stack

Component	Technology
Web Framework	FastAPI + Uvicorn
AI Integration	Together AI, LangChain, LangGraph
Vector Store	FAISS
Embeddings	Cohere
Database	SQLite + SQLAlchemy 2.0

Architecture

ValidationAgent → classifies query type
       ↓
PromptAgent → generates specialized prompts
       ↓
QA Agent → retrieves chunks, reranks, generates answer
       ↓
StreamingResponse

ai rag fastapi