A Very Brief Overview of Python’s “Lang” AI Tools and Two Low-Code GUI AI Tools: Flowise and n8n

AI is the theme of the moment - and even as a pythonista you might not know where to begin, or you may have started as you had time - and wished to go further. This talk is a guide about where some have gone, and where you might want to go with AI in python. But it is not the last stop. This talk is designed to be a stating guide to move from hobbyist level AI learning to more production-ready coding.

Often where you begin is with some of the low-code GUI tools - for instance Flowise [ flowiseai.com] - where with a api key and some clicks you can quickly build a chatbot - and then you leant to add complexity - maybe you pull out some embeddable code -or start to have more than one agent talk to each other, or with some walk-throughs you build a knowledge-base of documents for your bot ( a RAG - Retrieval Augmented Generation ) and now it knows - all your recipes.

Later you want to give your bot some "hands" or rather tools and later you connect to N8N [n8n.io] - which is a flexible workflow automation. You've made your bot reach out into the world to do something (aka made it "Agentic").

But then you want more control - and stability - so you look to do what you previously did in low-code- directly in python, with a view to production.

This is when you look to the "Lang" flavor tools: Langchain, Langflow, Langraph, and Langsmith.

Given the time, this will be a very quick tour of these concepts with both images and code shown - so it won't be a line-by line build along. A repo and suggested resources will be provided at the end.