Overview Structure Tech Stack Getting Started Usage AI_Part Sample Data Contributing License

Ecometrics Net Footprint Dashboard

Table of Contents

• Project Overview
• Repository Structure
• Tech Stack
• Getting Started
• Usage & API
• AI_Part Module
• Sample Data
• Contributing
• License

Sections

Project Overview

apna‑nfd ingests industrial metrics, uses a PyTorch model to predict carbon footprints, and delivers sustainability recommendations via an AI chatbot. It’s split into backend, frontend, and an AI_Part module for recommendation logic.

Repository Structure

├── AI_Part/                # Chatbot & recommendation engine  
├── backend/                # FastAPI service, PyTorch model, templates  
│   ├── app.py  
│   ├── asgi.py  
│   ├── model/carbon_model.pth  
│   ├── data/sample_input.csv  
│   ├── data/sample_output.csv  
│   ├── static/css/style.css  
│   └── templates/index.html  
├── frontend/               # React/TypeScript SPA  
│   ├── package.json  
│   ├── public/index.html  
│   └── src/  
├── sample_data.csv         # Combined sample data  
└── index.html              # ← this file  
      

Tech Stack

• Backend: FastAPI (ASGI) , Uvicorn, Pydantic
• Model: PyTorch .pth serialization
• Chatbot: Groq AI integration
• Frontend: React, TypeScript, Vite
• Containerization: Docker & Docker Compose
• Docs: Swagger UI & ReDoc (OpenAPI)

Getting Started

Backend

cd backend
pip install -r requirements.txt
uvicorn asgi:asgi_app --reload --host 0.0.0.0 --port 8000
      

Frontend

cd frontend
npm install
npm run dev    # http://localhost:3000
      

Docker & Docker Compose

# docker-compose.yml
version: '3.8'
services:
  backend:
    build: ./backend
    ports: ["8000:8000"]
  frontend:
    build: ./frontend
    ports: ["3000:3000"]
launch all

docker-compose up --build

Usage & API

API Endpoints

Route	Method	Description
/	GET	Dashboard HTML
/predict	POST	Industrial metrics → carbon prediction
/chat	POST	AI sustainability advice

Interactive Docs

Swagger UI: /docs
ReDoc: /redoc

AI_Part Module

AI_Part/
├── chatbot.py       # Message handling
├── recommendations/ # Prompt templates & logic
└── utils.py
      

Run CLI tests: python AI_Part/chatbot.py

Sample Data

• backend/data/sample_input.csv
• backend/data/sample_output.csv
• sample_data.csv

Contributing

1. Fork & create branch (feature/xyz)
2. Commit with Conventional Commits
3. Open a Pull Request against main

License

MIT License. See LICENSE for details.