Acess AWS services + Simple Bedrock Tutorial

This repo demonstrates how to get started with AWS services and how to make a basic call to Bedrock in Python

1) AWS Management Console

Before jumping into the code, we first need to make a new user. AWS typically has a root user that gives out permissions, with other users that run specifc services. Because the hackathon is so short, we're only going to create 1 user and give that one all the permissions you need

1a) Creating the User

• Navigate to the home page of the AWS console account you were given
• In the search bar, type IAM (Identity and Access Management) and click on that service, it has a red icon
• Click on Users under the IAM Resources window
• You should see your root user, which will have a bunch of Access denied text over it. Ignore that and click the orange Create user button in the top right
• Give it a name, whatever you think is best
  • You do NOT need to give it access to the AWS console, as the root user can already do that
• In the permission options, click the Attach policies directly box
  • If you create more users, you can copy permissions, but do NOT copy from the root
• There are many permission policies, but I would recommend searching the service you want to use, then FullAccess after it
  • Ex: bedrockFullAccess, click the full access permission
  • You can add policies later if you find out you missed one
  • I would recommend Bedrock, SageMaker, EC2, and S3 Full Access to start
• The next page will have a summary of your account, feel free to screenshot this if you need to

1b) Creating an Access Key

This will allow us to use AWS services in our code

• When you create the user, a green banner should appear at the top. Click View user or click on the User's name in the Users box
• This page is where you can add permissions later if necessary, but we need to create an Access Key. In the Summary box, there should be a Create access key link on the right side
• It will ask you for a use case, select the Local code option. Ignore the suggestion it gives you and check the conformation box
  • It techincally doesn't matter what you put here, it's just for identifing the key later
• The description is optional, so leave it blank and click Create access key
• This gives you an access key and a secret. Copy both of these in a place you won't lose them
  • THE SECRET CAN NEVER BE VIEWED AGAIN ONCE YOU CLOSE THIS SCREEN
  • If you lose it, just create another key
• NOTE: These are extremely sensitive keys! Do NOT push these codes to GitHub and share them with your team via Slack DM, Discord, etc.

1c) Enabling AWS Bedrock Models

• In the search bar, type Bedrock and click on that service, it has a green icon
• Feel free to click through the different models, determining what would be best for your use case
• Once you have your selection(s), click the orange Request model access button on the main page of one of the models
• Click the orange Modify model access button
• Check the models you want to enable for your account. There is no limit on this and you can select any models that say Avaliable to request
• Click Next at the bottom once you have made your selections
• Review the selections and hit Submit
• You can test he models you pick by going to the Playground tab on the left side to test parameters such as temperature, topP, etc.

2) Setting up your Python environment

First, we need to create a virtual environment for Python, which essentially installs your packages to 1 project instead of globally

2a) Installing the required packages

• Create a virtual environment by running the following in the terminal directory of your project
  • Windows: py -m venv venv
  • Mac/Linux: python3 -m venv venv
• Then, you need to actually use the environment, so type the following
  • Windows: venv\Scripts\activate.bat or venv\Scripts\Activate.ps1
  • Mac/Linux: source ./venv/bin/activate
• Your terminal should have (venv) at the beginning of it now! Also set your VSCode interpreter to the venv path in the bottom right
• I have made a requirements.txt to install all of the packages you will need, so run the following to install them
  • Windows: pip install -r requirements.txt
  • Mac/Linux: pip3 install -r requirements.txt

2b) Putting the AWS credentials in the right place

• In order to not push your keys to GitHub, we need to put them in a .env file
• Open that file and replace YOUR_ACCESS_KEY and YOUR_SECRET_KEY with the ones you copied earlier
• Go to the .gitignore file and uncomment (remove the #) from line 4 that says .env
  • A gitignore files tells git to not push certain files and keep them local to computer
• Now you are ready to call AWS services!

3) Using the Python files

There are 2 files I have made for you: bedrock.py and converse.py. Both call Amazon Bedrock, using the model you enabled and specify, to generate a response to a given prompt.

• Change model_id to the model you selected on the AWS console
• Change user_message to the prompt you want to use
• Change the inferenceConfig if you want to specifiy temperature, topP, etc.
• Run the file you changed with the following
  • Windows: py bedrock.py or py converse.py
  • Mac/Linux: python3 bedrock.py or python3 converse.py
• You should see the response in the console!
  • bedrock.py may take a long time depending on the prompt, as it waits for the entire response to complete
  • converse.py acts more like ChatGPT, where it generates the response in real-time!