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Safe & Maintainable AI Apps in Python

SciPy 2026 tutorial · 4 hours · Carson Sievert (Posit)

Pre-configured workspace

A computing environment with all of the dependencies needed to run exercises has been made available here.

TODO: shortlink / QR code for workshop environment

Install

If you want to locally run the tutorial exercises, follow the following instructions to get set up.

  1. Clone the repo
git clone https://github.com/cpsievert/scipy26-tutorial.git
cd scipy26-tutorial
  1. Install uv globally
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

If you can't use uv for some reason, Just do what you'd normally do to install the requirements.txt

  1. Setup a virtual environment
uv venv
source .venv/bin/activate
  1. Install dependencies
uv pip install -r requirements.txt

LLM access

Exercises depend on access to an LLM. Here are a few different ways to get access:

  1. Sign up for a free trial at https://posit.ai/. No credit card required. You can use the free trial for the entire workshop.

  2. Bring your own API key. If you have your own API key, like OPENAI_API_KEY, ANTHROPIC_API_KEY, etc. that will work just fine.

  3. Run a local model on your laptop via LM Studio or Ollama. No key required, fully private, but slower and requires a beefy laptop. See the LM Studio docs for setup instructions.

For more choices and details, see https://posit-dev.github.io/chatlas/get-started/models.html

Exercises

Can be found in the exercises/ directory

Solutions

Can be found in the solutions/ directory

Resources

Learn more about the tutorial topics at these locations.

https://posit-dev.github.io/chatlas/ https://posit-dev.github.io/shinychat/py/ https://shiny.posit.co/py/docs/genai-chatbots.html https://posit-dev.github.io/querychat/py/index.html

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