PyData Global 2025

From Handwritten Notes to Smart Knowledge: Build Local AI Agents with Python
2025-12-11 , Machine Learning & AI

Your notebooks are full of insights—but they’re scattered and hard to search.
In this live-coding session I’ll show how to turn handwritten notes into a searchable, connected knowledge base using local AI and minimal Python.

We start with AnythingLLM’s UI for quick wins, then move to Python agents that:
• classify note types,
• extract key ideas,
• build a personal knowledge graph.

The entire stack runs on your laptop with MLC-AI—no cloud, no data leaks.
You’ll leave with a reusable agent blueprint you can drop into any data-processing workflow tomorrow.


What you’ll learn
• When to stay in a UI vs. when Python is essential
• How to orchestrate agents with CrewAI and plug in custom logic
• Clean patterns for local LLM inference with MLC-AI
• A complete, copy-paste-ready pipeline for knowledge extraction & linking

Live demos

AnythingLLM quick-start (2 min)
Python agent orchestration classifying & linking 10+ handwritten notes (15 min)
Querying the resulting knowledge graph for recurring themes (3 min)
Take-home repo
GitHub repo + requirements.txt + Docker compose file so attendees can rerun everything on their own notes.

Prerequisites
Basic Python (functions, classes, pip install). No prior AI/ML knowledge required.


Prior Knowledge Expected:

No

Data Science Leader with extensive experience in AI and MLOps, currently serving as the CTO at Infinitii AI. He has a strong background in team leadership, product innovation, and building scalable data-driven solutions. Piotr is passionate about using AI to solve real-world problems, particularly in time-series analysis. He is an advocate for Agile methodologies and MLOps practices, and has spoken at conferences about these topics.