RAGmind — Personal AI Assistant

The Problem

Professionals drown in documents — PDFs, notes, code, research, internal wikis. When they need an answer, they spend 20-30 minutes digging through files. ChatGPT can't help because it doesn't know their private data. And cloud-based solutions mean sending confidential documents to third-party servers — a dealbreaker for lawyers, doctors, and security-conscious teams.

The Approach

1. 1

   Built a full RAG (Retrieval-Augmented Generation) pipeline — documents are chunked, embedded with sentence-transformers, and stored in ChromaDB for instant cosine similarity search

2. 2

   Added support for 6 LLM providers (Groq, Claude, ChatGPT, Gemini, DeepSeek, Mistral) so users choose their preferred model — including free options

3. 3

   Designed a knowledge persistence layer — notes, URLs, and uploads survive database clears because they're saved as files, not just vectors

4. 4

   Implemented security from the ground up — bcrypt password hashing, Fernet-encrypted API keys at rest, session-based auth with httpOnly cookies, rate-limited login, and file upload validation

5. 5

   Added media generation capabilities — AI image generation (FLUX.1, DALL-E 3, Stability AI) and video generation (Kling, Replicate, Luma AI) with background processing and status tracking

6. 6

   Built a complete user experience — multiple profiles, conversation history, voice input/output, dark/light themes, mobile responsive design, analytics dashboard with token cost tracking

Tech Stack

"RAGmind turns your scattered documents into an AI that actually knows your work. Ask it anything about your files, your notes, your research — it answers in seconds with source citations, using whatever LLM provider you prefer. No cloud, no subscriptions, completely private."