Developer Code Documentation

This document outlines the developer guidelines and code structure for the Marketing Question Answering Recommendation Engine, which operates on AWS SageMaker Studio with integrations to AWS Comprehend for entity recognition and Bedrock Claude V2 for answer generation. Data storage and management are handled using AWS S3 buckets.

System Overview Our engine is designed to provide precise answers to marketing-related questions using machine learning and NLP (Natural Language Processing). The core components include:

  • AWS Comprehend: For training models to label entities within the user questions.
  • Bedrock Claude V2: An advanced model used for generating accurate answers.
  • AWS S3: For secure storage of input data, processed data, and models.

Environment Setup

  1. AWS SageMaker Studio
    • Ensure you have access to AWS SageMaker Studio.
    • Configure your SageMaker instance with the required permissions to access Comprehend, Bedrock API, and S3.
  2. AWS S3 Bucket Configuration
    • Create S3 buckets for input data, output data, and model storage.
    • Set up the necessary IAM policies to allow read/write operations from SageMaker.

Code Structure

  1. Data Preprocessing
    • Python scripts for data cleaning and formatting.
    • Includes functions to validate and prepare data for model training and inference.
  2. Model Training with AWS Comprehend
    • Code for initiating and managing the training process.
    • Includes methods for selecting labels, monitoring training progress, and evaluating model performance.
  3. Answer Generation with Bedrock Claude V2
    • Integration code for Bedrock Claude V2 API.
    • Functions to send processed questions to the Bedrock API and receive generated answers.
  4. Data Storage and Retrieval with AWS S3
    • Functions to upload input data to S3 and download results.
    • Includes error handling for storage operations.

Sample Code Snippets

Data Upload to S3

import boto3 def upload_to_s3(bucket_name, file_name, object_name=None): if object_name is None: object_name = file_name s3_client = boto3.client('s3') response = s3_client.upload_file(file_name, bucket_name, object_name) return response

Entity Labeling with AWS Comprehend

import boto3

comprehend_client = boto3.client(service_name='comprehend', region_name='region')

def train_entity_recognizer(data_access_role_arn, input_data_s3_uri, entity_list):
    create_response = comprehend_client.create_entity_recognizer(
        DataAccessRoleArn=data_access_role_arn,
        InputDataConfig={
            'EntityTypes': entity_list,
            'S3Uri': input_data_s3_uri
        },
        RecognizerName='MarketingEntityRecognizer',
        LanguageCode='en'
    )
    return create_response

Answer Generation with Bedrock Claude V2

import requests

def generate_answer(question):
    bedrock_endpoint = 'https://api.bedrock.ai/claude-v2/generate-answer'
    payload = {'question': question}
    response = requests.post(bedrock_endpoint, json=payload)
    return response.json()

Testing and Deployment

  • Provide unit tests for each component of the system.
  • Include integration tests to ensure that the components work together as expected.
  • Outline the deployment process, including any CI/CD pipelines used.

Security and Compliance

  • Ensure that all data handling complies with GDPR, CCPA, or any other relevant data protection regulations.
  • Implement logging and monitoring to detect and respond to security events.

Support and Maintenance

  • Include contact information for developers to reach out for support.
  • Document the process for reporting issues and the expected response times.

Version Control

  • Use Git for version control, and document the branch strategy.
  • Include a changelog to track the updates and fixes made over time.

This documentation serves as a starting point and should be expanded and updated as the project evolves. It is crucial to maintain clear and up-to-date documentation to support the development and maintenance of the recommendation engine.