This section includes a list of notebooks that walk you through some simple concepts in Instructor. We start small and then work our way up to more complex and tricky implementations using the library.

Overview

Currently we have the following notebooks avaliable

Introduction - This is a quick walkthrough some of the benefits of Pydantic and how the Instructor Library integrates nicely with Pydantic with instructor.patch()
Tips - Quick demonstration of how to use enums, Pydantic models and structured prompting to get specific output formats

Installation

We utilise the Graphviz package in this tutorial series. If you don't have it on hand, you should download it. Mac users can do so by running brew install graphviz while Linux users can try sudo apt install graphviz ( modify to your system specific package manager). Here is a link to their official [documentation](Install Graphviz based on your operation system https://graphviz.org/download/)

If you're encountering an error like the following when trying to run graphviz after installing it, just restart the notebook and verify you've got graphviz installed by running dot -v in your shell.

Command '[PosixPath('dot'), '-Kdot', '-Tsvg']' died with <Signals.SIGKILL: 9>.

Here are the steps to start running the notebooks

Create a virtual environment

python3 -m venv .venv
source .venv .venv/bin/activate

Install the dependencies

pip3 install -r requirements.txt

Add the virtual environment to Jupyter notebook

python -m ipykernel install --user --name=instructor-env

Add OpenAI API Key into your shell by running the following command. This will be set for as long as the shell is open.

export OPENAI_API_KEY=<api key goes here>

Start Jupyter Notebook

jupyter notebook