Chapter 01

00 Tutorial How To

Notebookpy31013 cells

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

Clone this repository to your local machine.
Install the required dependencies by running the following command:

In [2]python · cell 3

python

%pip install -qU pip
%pip install -qr ../requirements.txt

Output

Note: you may need to restart the kernel to use updated packages.
Note: you may need to restart the kernel to use updated packages.

Restart the kernel after installing dependencies

In [ ]python · cell 5

python

# restart kernel
from IPython.core.display import HTML
HTML("<script>Jupyter.notebook.kernel.restart()</script>")

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.

In [ ]python · cell 8

python

import boto3
session = boto3.Session() # create a boto3 session to dynamically get and set the region name
AWS_REGION = session.region_name
print("AWS Region:", AWS_REGION)
MODEL_NAME = "anthropic.claude-3-haiku-20240307-v1:0"

%store MODEL_NAME
%store AWS_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.

In [ ]python · cell 10

python

from anthropic import AnthropicBedrock

client = AnthropicBedrock(aws_region=AWS_REGION)

def get_completion(prompt, system=''):
    message = client.messages.create(
        model=MODEL_NAME,
        max_tokens=2000,
        temperature=0.0,
        messages=[
          {"role": "user", "content": prompt}
        ],
        system=system
    )
    return message.content[0].text

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.

In [ ]python · cell 12

python

# Prompt
prompt = "Hello, Claude!"

# Get Claude's response
print(get_completion(prompt))

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.

Chapter 01

00 Tutorial How To

Notebookpy31013 cells

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

Clone this repository to your local machine.
Install the required dependencies by running the following command:

In [2]python · cell 3

python

%pip install -qU pip
%pip install -qr ../requirements.txt

Output

Note: you may need to restart the kernel to use updated packages.
Note: you may need to restart the kernel to use updated packages.

Restart the kernel after installing dependencies

In [ ]python · cell 5

python

# restart kernel
from IPython.core.display import HTML
HTML("<script>Jupyter.notebook.kernel.restart()</script>")

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.

In [ ]python · cell 8

python

import boto3
session = boto3.Session() # create a boto3 session to dynamically get and set the region name
AWS_REGION = session.region_name
print("AWS Region:", AWS_REGION)
MODEL_NAME = "anthropic.claude-3-haiku-20240307-v1:0"

%store MODEL_NAME
%store AWS_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.

In [ ]python · cell 10

python

from anthropic import AnthropicBedrock

client = AnthropicBedrock(aws_region=AWS_REGION)

def get_completion(prompt, system=''):
    message = client.messages.create(
        model=MODEL_NAME,
        max_tokens=2000,
        temperature=0.0,
        messages=[
          {"role": "user", "content": prompt}
        ],
        system=system
    )
    return message.content[0].text

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.

In [ ]python · cell 12

python

# Prompt
prompt = "Hello, Claude!"

# Get Claude's response
print(get_completion(prompt))

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.