alizeeshan-07 / blog-generation-using-awsbedrock

Blog Generation using Bedrock

Overview

This script generates a blog post using the Bedrock AI model and saves it to an AWS S3 bucket.

Requirements

• Python 3.10+
• boto3 library (pip install boto3)

Setup

1. AWS Setup:

   • Ensure you have an AWS account set up.
   • Configure AWS credentials with appropriate permissions to access S3 and Bedrock services.

2. Python Environment:

   • Install the required dependencies using pip:

     pip install boto3
     

Usage

1. Lambda Configuration:

   • Create an AWS Lambda function with the following configuration:
     • Runtime: Python 3.11+
     • Handler: lambda_handler.lambda_handler
     • Trigger: HTTP API Gateway (or other HTTP trigger)

2. HTTP Request Format:

   • Send an HTTP POST request to the Lambda endpoint with the following JSON payload:

     {
       "blog_topic": "Your Blog Topic Here"
     }

3. Output:

   • The generated blog post will be saved as a text file in the specified S3 bucket (aws_bedrock_blog_app) under the blog_output directory.

Function Details

• blog_generate_using_bedrock(blogtopic:str) -> str:

  • Generates a blog post using the specified blogtopic with parameters configured for the Bedrock AI model.

• save_blog_details_s3(s3_key, s3_bucket, generate_blog):

  • Saves the generated blog content (generate_blog) to the specified S3 bucket (s3_bucket) with the key (s3_key).

• lambda_handler(event, context):

  • Entry point for AWS Lambda function.
  • Extracts blog_topic from the incoming HTTP POST request.
  • Calls blog_generate_using_bedrock to generate the blog post.
  • Saves the generated blog to S3 using save_blog_details_s3.

Notes

• Ensure proper AWS IAM permissions are set for the Lambda function to access S3 and Bedrock services.
• Monitor AWS CloudWatch logs for debugging and operational insights.