u/Careless_Painter_607

I've been studying distributed systems from PDFs and notes, and I kept losing track of what I actually understood vs. what I just skimmed. And I know that when you work with documents inside of organization, it could be some issues with using cloud AI tools.

So I built deepowl — a CLI tool that reads your documents, extracts concepts, builds a knowledge graph, and then quizzes you on them through a Socratic loop.

How it works:

1. deepowl ingest ./docs/ — chunks your files, generates embeddings locally
2. deepowl build — LLM extracts concepts and relations, builds a graph
3. deepowl start — teaches you concept by concept, asks questions, scores answers, tracks confidence per concept across sessions

The teaching loop:

• Explains the concept using RAG over your own docs
• Asks one focused question
• Evaluates your answer (0–100 score)
• Moves to prerequisites first if you're weak on fundamentals

Runs fully local with Ollama. Also works with OpenAI, Anthropic, Groq if you prefer.

Stack: Python, ChromaDB, NetworkX, SQLite, Typer, Rich.

GitHub: github.com/alibekashirali/deepowl

Would love feedback — especially on the curriculum ordering and spaced repetition (not fully implemented yet).