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Chatbot Agent with Amazon Bedrock

This project is based on the demo presented during my talk at AWS Summit Jakarta 2024 (September 5, 2024).

The Architecture

Architecture Diagram

Prerequisites

  1. AWS Account: Ensure you have an active AWS account.

  2. AWS CLI Configuration: Set up your AWS CLI with the necessary credentials.

  3. Frontend Setup: Place your frontend web application with chatbot functionality inside the ./src/web/public directory.

  4. Model Access: Make sure you already request model access the model you are going to use in your Amazon Bedrock Console in AWS us-east-1 region. .

  5. Environment Variables: Configure the following in the .env file:

    AWS_REGION=us-east-1

# Get your Pinecone credentials from https://www.pinecone.io/
PINECONE_CONNECTION_STRING=<pinecone connection string>
PINECONE_API_KEY=<pinecone API key>

CRAWL_TARGET_URL=<your target URL, obtained after deploying your frontend stack or using your custom domain>

FROM_EMAIL=<sender email for notifications, must be configured in Amazon SES>
EMAIL_DOMAIN=<email domain identity, also configured in Amazon SES>

Deployment Steps

  1. Clone the Repository:

    git clone <repository-url>
cd <repository-directory>

  2. Install Dependencies:

    npm install && npm install --prefix src/crawler

  3. Deploy the Stacks:

    cdk deploy KnowledgeBaseStack CrawlerWebStack AgentStack QueryStack

    The deployment process will start as shown below: CDK Deployment

  4. Configure Frontend:

    • Once the deployment is complete, you will receive the chatbot API endpoint (highlighted in blue). Chatbot API Endpoint
    • Copy the endpoint URL and update your frontend configuration. Frontend Configuration

  5. Deploy Frontend:

    cdk deploy FrontendStack
    • After the deployment, you will receive a CloudFront URL to access your frontend. Frontend URL

Running the Application

  1. Prepare Knowledgebases:

    • Load documents into Amazon Bedrock from the S3 Bucket.
    • Alternatively, you can wait for EventBridge to trigger the Lambda function to crawl your web, or manually invoke the CrawlerWebStack Lambda function. Invoke Web Crawler Manually

  2. Interact with the Chatbot:

    • Allow Amazon Bedrock a few minutes to process your files.
    • Test the chatbot either through your frontend or via the Amazon Bedrock Management Console. Amazon Bedrock Agent Console