Tutorial How-To

This tutorial requires this initial notebook to be run first so that the requirements and environment variables are stored for all notebooks in the workshop

How to get started

1. Clone this repository to your local machine.

2. Install the required dependencies by running the following command:

3. Restart the kernel after installing dependencies

Usage Notes & Tips 💡

• This course uses Claude 3 Haiku with temperature 0. We will talk more about temperature later in the course. For now, it's enough to understand that these settings yield more deterministic results. All prompt engineering techniques in this course also apply to previous generation legacy Claude models such as Claude 2 and Claude Instant 1.2.

• You can use Shift + Enter to execute the cell and move to the next one.

• When you reach the bottom of a tutorial page, navigate to the next numbered file in the folder, or to the next numbered folder if you're finished with the content within that chapter file.

The Anthropic SDK & the Messages API

We will be using the Anthropic python SDK and the Messages API throughout this tutorial.

Below is an example of what running a prompt will look like in this tutorial.

First, we set and store the model name and region.

Then, we create get_completion, which is a helper function that sends a prompt to Claude and returns Claude's generated response. Run that cell now.

Now we will write out an example prompt for Claude and print Claude's output by running our get_completion helper function. Running the cell below will print out a response from Claude beneath it.

Feel free to play around with the prompt string to elicit different responses from Claude.

The MODEL_NAME and AWS_REGION variables defined earlier will be used throughout the tutorial. Just make sure to run the cells for each tutorial page from top to bottom.