This project offers a sample front-end application built with Streamlit to showcase RAG using Amazon Bedrock, LangChain and Amazon Kendra. You can deploy this CDK project in your AWS account. Alternatively, you can run the Streamlit application on your local machine. See sections below for instructions.
Make sure you have access to the Bedrock models before using this application. You can request access to the Bedrock models through the console:
The AWS identity you assume from your notebook environment (which is the Studio/notebook Execution Role from SageMaker, or could be a role or IAM User for self-managed notebooks), must have sufficient AWS IAM permissions to call the Amazon Bedrock service.
To grant Bedrock access to your identity, you can:
Open the AWS IAM Console Find your Role (if using SageMaker or otherwise assuming an IAM Role), or else User Select Add Permissions > Create Inline Policy to attach new inline permissions, open the JSON editor and paste in the below example policy:
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "BedrockFullAccess",
"Effect": "Allow",
"Action": ["bedrock:*"],
"Resource": "*"
}
]
}
If you are running the application from your local machine, make sure you have the following tools installed:
- AWS CLI
- Node.js
- IDE for your programming language
- AWS CDK Toolkit (v2.0 or later)
- Git, JQ, etc
- Docker
We recommend you use an AWS Cloud9 development enviroment for this project. See this Cloud9 setup guide.
Clone the repository and enter the project directory:
git clone https://github.com/Hantzley/amazon-bedrock-kendra-rag-demo.git
cd amazon-bedrock-kendra-rag-demo
Create a virtualenv on MacOS or Linux:
python3 -m venv .venv
After the init process completes and the virtualenv is created, you can use the following step to activate your virtualenv.
source .venv/bin/activate
Once the virtualenv is activated, you can install the required dependencies.
pip install -r requirements.txt
If your account is not yet boostrapped for CDK, execute the following command:
cdk bootstrap
At this point you can now list the stacks in the project.
cdk ls
You should see the following output:
GenAiRagVpcStack
GenAiRagKendraStack
GenAiRagWebStack
Deploy the application as a container on Elastic Container Services in our AWS account:
cdk deploy GenAiRagKendraStack GenAiRagWebStack
The GenAiRagKendraStack
and GenAiRagWebStack
depends on GenAiRagVpcStack
. CDK will resolve that dependency and automatically deploy GenAiRagVpcStack
first.
Copy the WebApplicationServiceURL
from the output and paste it on your browser.
Alternatively, you can execute the Streamlit application on your local machine:
cd web-app
streamlit run Home.py --server.maxUploadSize 50
The application should open in your browser.
Enjoy!
To avoid unnecessary cost, you can destroy the resources used in the project:
cdk deploy --all