📋 Contract Compliance Checker

🔒 An AI-powered GDPR compliance verification system for legal contracts

🌟 Overview

The Contract Compliance Checker is an intelligent web application that automates the process of analyzing legal contracts for - 🕐 Runs daily at midnight (00:00)

• 📥 Scrapes latest templates from official sources
• 🔍 Compares new templates with existing ones using hash verification
• 📧 Sends email notifications when changes are detected
• 💬 Sends Slack notifications (if configured)
• ✅ Ensures compliance checks use current standards
• ⚠️ Reports any errors encountered during updatesompliance. It uses advanced AI models to detect document types, extract clauses, and compare them against regulatory standards.

✨ Features

• 📄 Automated Document Classification - Identifies 5 types of GDPR-related agreements
• 🔍 Intelligent Clause Extraction - Extracts and summarizes contract clauses using AI
• ⚖️ Compliance Analysis - Compares uploaded contracts against standard templates
• 🎯 Risk Assessment - Assigns risk scores (0-100) for compliance gaps
• 📊 Detailed Reporting - Provides missing clauses, risks, and recommendations
• 🔄 Auto-Update System - Scheduled scraping to keep templates up-to-date
• 🎨 User-Friendly Interface - Built with Streamlit for easy interaction

🗂️ Supported Document Types

The system can analyze the following contract types:

1. 📑 Data Processing Agreement (DPA)
2. 🤝 Joint Controller Agreement (JCA)
3. 🔗 Controller-to-Controller Agreement (C2C)
4. 🔄 Processor-to-Subprocessor Agreement (PSA)
5. 📜 Standard Contractual Clauses (SCC)

🏗️ Project Structure

project/
├── main.py                          # 🚀 Streamlit application entry point
├── agreement_comparision.py         # 🔍 Document classification & comparison
├── data_extraction.py               # 📝 Clause extraction with AI
├── scrapping.py                     # 🕷️ Template scraping & updates
├── pipeline.py                      # ⚙️ Automated processing pipeline
├── notification.py                  # 📧 Email notification module (SMTP)
├── slack_notification.py            # 💬 Slack notification module (Webhooks)
├── requirements.txt                 # 📦 Python dependencies
├── .env                             # 🔐 Environment variables (not in git)
├── .env.example                     # 📋 Template for environment variables
├── json/                            # 💾 Template standards
│   ├── DPA.json
│   ├── JCA.json
│   ├── CCA.json
│   ├── PSA.json
│   └── SCC.json
└── templates/                       # 📚 Reference documents
    ├── (DPA) appendix-gdpr-eea-uk-4-27-21.pdf
    ├── (JCA) model-joint-controllership-agreement.pdf
    ├── (C2C) 2-Controller-to-controller-data-privacy-addendum.pdf
    ├── (SCCs) Standard Contractual Clauses.pdf
    └── (PSA) Personal-Data-Sub-Processor-Agreement-2024-01-24.pdf

🚀 Getting Started

Prerequisites

• 🐍 Python 3.8 or higher
• 🔑 Google Gemini API key

Installation

1. Clone the repository

   git clone <repository-url>
   cd project

2. Create virtual environment

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Set up environment variables

   Create a .env file in the project root (copy from .env.example):

   # API Keys
   GEMINI_API_KEY=your_gemini_api_key_here
   GROQ_API_KEY=your_groq_api_key_here
   
   # Email Configuration (for notifications)
   SMTP_SENDER_EMAIL=your_email@gmail.com
   SMTP_PASSWORD=your_app_password_here
   SMTP_RECEIVER_EMAIL=receiver_email@gmail.com
   SMTP_SERVER=smtp.gmail.com
   SMTP_PORT=587
   
   # Slack Configuration (optional)
   SLACK_WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL

   Note for Gmail Users: Use an App Password, not your regular password. Enable 2-Step Verification first, then generate an app password from Google Account Security settings.

5. Prepare template standards (if not already present)

   Run the pipeline to generate JSON templates:

   python pipeline.py

🎯 Running the Application

Launch the Streamlit web application:

streamlit run main.py

The application will open in your default browser at http://localhost:8501

📖 Usage

1. Upload Contract 📤

   • Click "Browse files" or drag & drop a PDF contract
   • Supported format: PDF only

2. Automatic Analysis 🤖

   • The system detects the document type
   • Extracts all clauses automatically
   • Compares against GDPR standard templates

3. Review Results 📊

   • View missing or altered clauses
   • Check compliance risks
   • Review risk score and recommendations
   • Get actionable amendments

🛠️ Core Modules

main.py

• 🎨 Streamlit web interface
• 📤 File upload handling
• 🔄 Background scheduler for auto-updates
• 📊 Results visualization

agreement_comparision.py

• 🔍 Document type detection using AI
• ⚖️ Clause-by-clause comparison
• 🎯 Risk scoring and analysis
• 💡 Compliance recommendations

data_extraction.py

• 📄 PDF text extraction
• 🤖 AI-powered clause extraction
• 📝 Summarization (for large documents)
• 💾 JSON output generation

scrapping.py

• 🕷️ Automated template scraping from web sources
• 🔄 Scheduled updates (daily at 12:00 AM)
• 📥 Downloads latest standard agreements
• � Detects changes using file hash comparison
• 📧 Sends email notifications when templates are updated
• 🛡️ Error handling and reporting

pipeline.py

• ⚙️ Orchestrates the entire workflow
• 🏗️ Builds template library
• 🔄 Runs end-to-end comparison pipeline

notification.py

• 📧 Email notification system using SMTP
• 🔐 Secure credential management via environment variables
• ✅ Configurable sender, receiver, and message content
• 🛡️ Error handling and validation

slack_notification.py

• 💬 Slack notification system using webhooks
• 📊 Rich formatted messages with blocks
• 🎯 Compliance report formatting
• 🔄 Template update notifications
• 🔐 Secure webhook URL management

🧪 Example Workflows

Document Analysis Pipeline

# Run pipeline for a new document
from pipeline import run_pipeline

result = run_pipeline("your-contract.pdf")
print(result)

Email Notifications

# Send email notification
from notification import send_email

# Use defaults from .env
send_email()

# Send custom notification
send_email(
    subject="Compliance Report Ready",
    body="Your GDPR compliance analysis is complete. Risk Score: 45/100",
    receiver="team@company.com"
)

Test Notification Module

python notification.py

Test Slack Notification

python slack_notification.py

Test Scraping with Notifications

python test_scraping_notification.py

This will manually trigger the scraping process and send notifications if changes are detected.

🔐 Security & Privacy

• 🔒 Temporary files are automatically cleaned up
• 🗑️ Uploaded files are deleted after processing
• 🔑 API keys and credentials stored securely in .env file
• 🚫 No data is stored permanently on the server
• 🔐 .env file excluded from version control via .gitignore
• 🛡️ Gmail App Passwords used instead of regular passwords
• ✅ Environment variables for all sensitive configuration

🤖 Technology Stack

• Frontend: Streamlit
• AI Model: Google Gemini 2.5 Flash
• PDF Processing: PyPDF2, pypdf
• Data Validation: Pydantic
• Scheduling: schedule
• Environment: python-dotenv

📊 Risk Score Interpretation

• 0-25: ✅ Low Risk - Minor issues
• 26-50: ⚠️ Medium Risk - Attention needed
• 51-75: 🔶 High Risk - Significant gaps
• 76-100: 🔴 Critical Risk - Major compliance issues

🔄 Auto-Update System

The application includes a background scheduler that:

• 🕐 Runs daily at midnight (00:00)
• 📥 Scrapes latest templates from official sources
• � Compares new templates with existing ones using hash verification
• 📧 Sends email notifications when changes are detected
• ✅ Ensures compliance checks use current standards
• ⚠️ Reports any errors encountered during updates

What Gets Notified?

• ✅ New templates created
• ✅ Existing templates updated with new clauses
• ⚠️ Download or processing errors

Notifications are sent via:

• 📧 Email (SMTP)
• 💬 Slack (Webhooks - if configured)

Notification Example

When templates are updated, you'll receive an email like:

Subject: 🔄 GDPR Template Update Notification

📝 CHANGES DETECTED:
  • Data Processing Agreement: Template updated with new clauses
  • Standard Contractual Clauses: New template created

See SCRAPING_NOTIFICATION_GUIDE.md for detailed information.

🤝 Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

📝 License

This project is licensed under the MIT License.

👥 Support

For questions or support, please contact the development team.

🎯 Future Enhancements

• 🌍 Multi-language support
• 📧 Email notifications for compliance reports ✅
• 📈 Historical comparison tracking
• 🔗 Integration with document management systems
• 📱 Mobile-responsive interface
• 🎨 Custom template creation
• 📊 Advanced analytics dashboard
• 🔔 Webhook support for real-time notifications
• 📱 SMS notifications

📝 Recent Updates

October 2025 - Security & Notification Enhancements

📧 Scraping Notification System

• Automatic change detection for template updates
• Sends email notifications when GDPR templates are updated
• Uses MD5 hash comparison for accurate change detection
• Reports both successful updates and errors
• Fixed JSON file paths (json_files/ → json/)
• Added comprehensive logging and error handling

✅ Notification Module Refactored

• notification.py completely rewritten with security best practices
• Moved all hardcoded credentials to .env file
• Added reusable send_email() function with flexible parameters
• Implemented proper error handling and input validation
• Added comprehensive documentation

🔐 Security Improvements

• All sensitive credentials now in .env file:
  • Email credentials (SMTP sender, password, receiver)
  • API keys (Gemini, Groq)
  • Server configuration
• Created .env.example as a safe template for team members
• Verified .gitignore excludes .env from version control

🎯 Code Quality

• Eliminated security risks of hardcoded credentials
• Improved code maintainability and reusability
• Added detailed inline documentation
• Fixed typos and improved code structure
• Follows Python PEP 8 standards

📚 Documentation

• Updated README.md with notification module usage
• Added Gmail App Password setup instructions
• Included environment variable configuration guide
• Provided example workflows for email notifications

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