Personal AI Knowledge Assistant

A RAG (Retrieval-Augmented Generation) powered assistant that lets you chat with your own documents. Upload PDFs, text files, or markdown notes and get AI answers with exact source citations. A excellent local file reader using RAG framework.

Features

• Upload PDF, TXT, and Markdown documents
• Vector search using ChromaDB + sentence transformers
• Conversational chat with full context memory
• Source citations with relevance scores on every answer
• Drag and drop file upload
• Document management — add and remove from knowledge base

Tech Stack

• Backend: Python, Flask, SQLAlchemy
• Vector DB: ChromaDB with all-MiniLM-L6-v2 embeddings
• AI: Groq (Llama 3.3 70B)
• Frontend: Vanilla HTML/CSS/JS

Setup

1. Clone the repo
2. python -m venv venv then activate
3. pip install -r requirements.txt
4. Create .env:
5. python app.py
6. Open http://localhost:5002

How it works

1. Documents are chunked into 500-word segments with 50-word overlap
2. Each chunk is embedded using sentence-transformers (all-MiniLM-L6-v2)
3. Embeddings stored in ChromaDB vector database
4. On each question, top 5 most relevant chunks are retrieved by cosine similarity
5. Retrieved chunks + question sent to Groq LLM for synthesized answer with citations