EcoStep: Your Friendly Carbon Footprint Whisperer

🚀 Tool Overview

Welcome to EcoStep, the AI-powered detective that sniffs out your carbon footprint from receipts! Ever wondered how much your shopping habits contribute to the planet's well-being (or destruction)? EcoStep analyzes your receipts, calculates carbon emissions, and gives you tailored suggestions to save the environment—without making you feel like a guilty penguin.

Think of it as a fusion of Sherlock Holmes and Captain Planet—but in Python! 🕵️‍♂️🌍

✨ Features

🔎 Receipt Analysis: Extracts, reads, and dissects receipts with the precision of a caffeine-fueled AI.
🧠 Smart OCR: Uses PaddleOCR and image processing to decipher even the messiest receipts.
📊 Category Classification: Groups items into Personal, Flight Travel, Electricity, and Vehicle for meaningful insights.
🤖 AI-Powered Chatbot: Powered by IBM WatsonX, it answers your eco-queries like a know-it-all environmentalist.
📂 Data Storage: Saves your receipt data in SQLite for future comparisons and trend analysis.
📈 Graphical Reports: Generates beautiful pie and bar charts because numbers are boring without colors!
🌱 Personalized Recommendations: Helps you reduce your carbon footprint without forcing you to live off sunlight.

🌍 Access the Project

You can access the project on GitHub:
EcoStep on GitHub

⚙️ Installation Instructions

Prerequisites

Python 3.8+ (because older Python versions belong in a museum 🏛️)
Pip (if you don’t have it, what have you been doing with your life?)

Steps to Install

Clone the repo like a pro hacker:

git clone https://github.com/Tech-Avinya-07/EcoStep.git
cd EcoStep

Install the required dependencies:
```
pip install -r requirements.txt
```
Update WatsonX credentials in these files:
- chatbot_main.py
- receipt_processing.py
- report_generator.py
  (Replace add your api key here with your actual key. No key, no AI magic! 🪄)
Run the app and watch the magic happen!

🎯 Usage Examples

1️⃣ Chat with CarbonBuddy

Run the chatbot interface and start asking eco-friendly questions!

streamlit run streamlit_chatbot.py

💬 Example: "How much CO₂e did my last grocery trip generate?"

2️⃣ Process Receipts Like a Boss

Want to upload your receipts and see how much they’re harming the planet?

streamlit run streamlit_ocr.py

📸 Upload your receipt → Watch as EcoStep does its AI wizardry → Get your carbon footprint insights!

3️⃣ Generate a Fancy Report

Turn raw data into an official-looking environmental report (great for showing off at parties 🥳).

python report_generator.py

📄 Your report will be saved as report_carbon_footprint_user.docx.

📡 API Documentation

1️⃣ WatsonX Integration

IBM WatsonX is the AI brain behind this eco-venture. It helps:

Analyze receipt text and classify purchases.
Provide chatbot responses with an environmental focus.
Generate personalized sustainability recommendations.

2️⃣ Key Modules & Functions

Module	Purpose
`chatbot_main.py`	Handles WatsonX AI queries and responses.
`database.py`	Manages SQLite storage of receipt data.
`databasetowordconverter.py`	Converts database entries into Word documents.
`image_preprocessing.py`	Enhances images for OCR processing.
`ocr_main.py`	Runs the full receipt-to-data pipeline.
`ocr_processing.py`	Extracts text from images using PaddleOCR.
`pdf_processing.py`	Converts PDFs into processable images.
`receipt_processing.py`	Analyzes receipts, calculates carbon footprints.
`report_generator.py`	Creates reports with charts and sustainability advice.
`streamlit_chatbot.py`	Streamlit-based chatbot interface.
`streamlit_ocr.py`	Streamlit-based OCR and receipt processing.

📚 References

IBM WatsonX Documentation
PaddleOCR GitHub
LangChain
OpenCV Documentation
The Environment—because, well, we owe it one! 🌍💚

🎉 Final Words

EcoStep is your friendly AI-powered eco-accountant, keeping track of your carbon sins while helping you atone for them. Whether you’re a sustainability nerd or just want to brag about your green lifestyle, EcoStep has your back!

Now go forth and reduce that footprint! 🦶💚

EcoStep: Your Friendly Carbon Footprint Whisperer

🚀 Tool Overview

Think of it as a fusion of Sherlock Holmes and Captain Planet—but in Python! 🕵️‍♂️🌍

✨ Features

🔎 Receipt Analysis: Extracts, reads, and dissects receipts with the precision of a caffeine-fueled AI.
🧠 Smart OCR: Uses PaddleOCR and image processing to decipher even the messiest receipts.
📊 Category Classification: Groups items into Personal, Flight Travel, Electricity, and Vehicle for meaningful insights.
🤖 AI-Powered Chatbot: Powered by IBM WatsonX, it answers your eco-queries like a know-it-all environmentalist.
📂 Data Storage: Saves your receipt data in SQLite for future comparisons and trend analysis.
📈 Graphical Reports: Generates beautiful pie and bar charts because numbers are boring without colors!
🌱 Personalized Recommendations: Helps you reduce your carbon footprint without forcing you to live off sunlight.

🌍 Access the Project

You can access the project on GitHub:
EcoStep on GitHub

⚙️ Installation Instructions

Prerequisites

Python 3.8+ (because older Python versions belong in a museum 🏛️)
Pip (if you don’t have it, what have you been doing with your life?)

Steps to Install

Clone the repo like a pro hacker:

git clone https://github.com/Tech-Avinya-07/EcoStep.git
cd EcoStep

Install the required dependencies:
```
pip install -r requirements.txt
```
Update WatsonX credentials in these files:
- chatbot_main.py
- receipt_processing.py
- report_generator.py
  (Replace add your api key here with your actual key. No key, no AI magic! 🪄)
Run the app and watch the magic happen!

🎯 Usage Examples

1️⃣ Chat with CarbonBuddy

Run the chatbot interface and start asking eco-friendly questions!

streamlit run streamlit_chatbot.py

💬 Example: "How much CO₂e did my last grocery trip generate?"

2️⃣ Process Receipts Like a Boss

Want to upload your receipts and see how much they’re harming the planet?

streamlit run streamlit_ocr.py

📸 Upload your receipt → Watch as EcoStep does its AI wizardry → Get your carbon footprint insights!

3️⃣ Generate a Fancy Report

Turn raw data into an official-looking environmental report (great for showing off at parties 🥳).

python report_generator.py

📄 Your report will be saved as report_carbon_footprint_user.docx.

📡 API Documentation

1️⃣ WatsonX Integration

IBM WatsonX is the AI brain behind this eco-venture. It helps:

Analyze receipt text and classify purchases.
Provide chatbot responses with an environmental focus.
Generate personalized sustainability recommendations.

2️⃣ Key Modules & Functions

Module	Purpose
`chatbot_main.py`	Handles WatsonX AI queries and responses.
`database.py`	Manages SQLite storage of receipt data.
`databasetowordconverter.py`	Converts database entries into Word documents.
`image_preprocessing.py`	Enhances images for OCR processing.
`ocr_main.py`	Runs the full receipt-to-data pipeline.
`ocr_processing.py`	Extracts text from images using PaddleOCR.
`pdf_processing.py`	Converts PDFs into processable images.
`receipt_processing.py`	Analyzes receipts, calculates carbon footprints.
`report_generator.py`	Creates reports with charts and sustainability advice.
`streamlit_chatbot.py`	Streamlit-based chatbot interface.
`streamlit_ocr.py`	Streamlit-based OCR and receipt processing.

📚 References

IBM WatsonX Documentation
PaddleOCR GitHub
LangChain
OpenCV Documentation
The Environment—because, well, we owe it one! 🌍💚

🎉 Final Words

Now go forth and reduce that footprint! 🦶💚

EcoStep: Your Friendly Carbon Footprint Whisperer

Table of contents

EcoStep: Your Friendly Carbon Footprint Whisperer

🚀 Tool Overview

✨ Features

🌍 Access the Project

⚙️ Installation Instructions

Prerequisites

Steps to Install

🎯 Usage Examples

1️⃣ Chat with CarbonBuddy

2️⃣ Process Receipts Like a Boss

3️⃣ Generate a Fancy Report

📡 API Documentation

1️⃣ WatsonX Integration

2️⃣ Key Modules & Functions

📚 References

🎉 Final Words

Table of contents

EcoStep: Your Friendly Carbon Footprint Whisperer

🚀 Tool Overview

✨ Features

🌍 Access the Project

⚙️ Installation Instructions

Prerequisites

Steps to Install

🎯 Usage Examples

1️⃣ Chat with CarbonBuddy

2️⃣ Process Receipts Like a Boss

3️⃣ Generate a Fancy Report

📡 API Documentation

1️⃣ WatsonX Integration

2️⃣ Key Modules & Functions

📚 References

🎉 Final Words