Project Brief: Serverless AI-Enhanced ESG Platform (MVP) Role: Full Stack Developer (Python/AWS Serverless) Goal: Build a multi-tenant ESG Data Platform using AWS Serverless architecture. Framework: Streamlit (Frontend), AWS Lambda (Backend), DynamoDB/InfluxDB (Database). 1. Project Overview We are building a SaaS platform for companies to upload ESG data (Environmental, Social, Governance) in CSV format. The system must parse these files, store the data, and visualize it. It also requires an AI reporting feature and IoT data ingestion. Architecture Status: The architecture is already designed. You are required to implement the code based on the provided blueprint. 2. Core Features to Build A. Frontend (Streamlit on AWS App Runner) Login Page: Simple authentication (integrate with AWS Cognito). Dashboard: Scope 1 & 2 Charts: Bar charts showing Monthly CO2e. Social & Gov: Tables displaying the uploaded data. IoT Widget: Real-time graph fetching data from InfluxDB. Upload Portal: Drag-and-drop interface for Environmental.csv, Social.csv, and Governance.csv. B. Backend (AWS Lambda & Python) Trigger: When a CSV is uploaded to S3, a Lambda function triggers. Parser Logic: Read CSV. Extract specific cells (e.g., "Electricity Consumption" rows). Apply Emission Factors (e.g., kWh * 0.774 = kgCO2e). Store structured result in DynamoDB. AI Agent: A function that takes the summarized data and sends a prompt to Amazon Bedrock (Claude 3.5) to generate a "Sustainability Commentary." C. Database Schema DynamoDB Table: ESG_Data Partition Key: TenantID (String) Sort Key: Date_Metric (String, e.g., 2024-01_Electricity) Attributes: Value, Unit, Category (Env/Soc/Gov). InfluxDB Cloud: Bucket: iot_sensor_data Tags: TenantID, SensorLocation. 3. Deliverables Source Code: GitHub repository with app.py (Frontend) and lambda_handlers (Backend). Deployment Script: Serverless Framework (serverless.yml) or AWS SAM template to deploy the stack. Documentation: A generic "How to Run" guide. 4. Constraints Language: Python 3.9+ ONLY. Security: No hardcoded keys. Use AWS IAM Roles. Budget: USD1000 Timeline: 4-6 weeks Note to Developer: The parsing logic for the specific NOS-F templates is provided in the attachment backend_logic.py. Please use this logic to ensure data accu