Digital Marketing Generative AI Demo Apps

This project uses Streamlit to build example generative AI applications on AWS with Amazon Bedrock focused on digital marketing use cases.

• Product Metadata Generator: Use product images to generate product descriptions, feature lists, and meta tag code for Open Graph, schema.org, and more...
• Product Review Summarizer: List the most common positive and negative comments from a set of consumer product reviews and summarize the overall sentiment.
• Product Blog Writer: Generate a 750-1000 word blog post with a comma-separated list of related SEO keywords.
• Doument FAQ Generator: Use PDF documents to generate a list of expected customer questions and their answers.
• Product Assistant Chatbot: Have a text and image-based conversation with a Claude 3 chatbot.

Install

Follow these steps to install and run this project on AWS using the AWS Cloud9 cloud-based integrated development environment (IDE).

Cloud9 Setup

1. Create a new Cloud9 environment.

   • Name: gen-ai-demo
   • EC2 Instance: m5.large (recommended)
   • Platform: Ubuntu Server 22.04 LTS

2. Once created, open the new Cloud9 environment.

3. Toggle off AWS managed temporary credential in Cloud9 by going to Preferences > AWS Settings > Credentials

4. Configure the AWS CLI with your permanent AWS credentials. You will need an AWS Access Key ID and AWS Secret Access Key for the next step.

   • (Optional) Create an access key for an IAM user with AdministratorAccess if you don't already have one.

5. Configure your AWS credentials and region in the Cloud9 terminal using the AWS CLI.

aws configure

Application Setup

1. Use the integrated Terminal to clone this GitHub repository.

git clone https://github.com/robsable/amazon-bedrock-genai-streamlit
cd amazon-bedrock-genai-streamlit

2. Install Python requirements.

pip3 install -r setup/requirements.txt -U

3. Run the Streamlit app.

cd app
streamlit run Main_Menu.py

4. In Cloud9, go to the Preview menu and select Preview Running Application. A new tab in the Cloud9 IDE will open and load your running application.

Customize

Once the app is up and running, you can begin to customize for your own use cases.

1. Edit main entry page content for the app in app/Main_Menu.py.

2. Add your own Streamlit scripts to the app/pages directory.

3. Edit main menu items and layout in app/.streamlit/pages.toml.

Clean Up

1. Delete the Cloud9 environment you created.