CSU Global Transcript Evaluator

An AI-powered system for evaluating transfer credits from academic transcripts for CSU Global.

Features

• Extract course data from transcripts using Google's Gemini AI
• Apply transfer credit rules based on CSU Global policies
• Generate detailed evaluation reports
• Interactive UI for reviewing and managing evaluations
• Role-based access control
• Comprehensive audit logging
• API rate limiting and security
• Performance optimization through caching

System Components

Core Modules

• confidence_scorer.py: Confidence scoring for data extraction
• evaluator.py: Transfer credit evaluation rules
• models.py: Data structures for students, courses, and institutions
• display.py: UI and report generation
• parsers.py: Data parsing and normalization
• processors.py: Transcript processing workflow
• gemini_client.py: Google Gemini AI integration

Security & Performance

• auth.py: Role-based access control system
• rules_engine.py: Business rules engine
• audit.py: Comprehensive audit logging
• rate_limit.py: API rate limiting
• cache.py: Performance optimization

Installation

1. Clone the repository:

git clone https://github.com/yourusername/csug_transcript_estimator.git
cd csug_transcript_estimator

2. Create a 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:

cp .env.example .env
# Edit .env with your configuration

Configuration

Environment Variables

• GEMINI_API_KEY: Google Gemini API key
• JWT_SECRET_KEY: Secret key for JWT tokens
• REDIS_URL: Redis connection URL
• DATABASE_URL: Database connection URL
• LOG_LEVEL: Logging level (DEBUG, INFO, etc.)

Role-Based Access

Three user roles are available:

• Enrollment: Basic view access
• TES: Transfer evaluation specialist with edit access
• Admin: Full system access

Usage

1. Start the application:

streamlit run src/app.py

2. Access the web interface at http://localhost:8501

3. Log in with your credentials

4. Upload transcripts for evaluation

API Documentation

Rate Limits

• Default: 100 requests per hour
• Authenticated: 1000 requests per hour
• Burst: 50 requests per minute

Endpoints

• POST /api/v1/evaluate: Submit transcript for evaluation
• GET /api/v1/results/{id}: Get evaluation results
• PUT /api/v1/review/{id}: Update evaluation
• GET /api/v1/reports: Generate reports

Security Features

1. Role-Based Access Control

   • Granular permissions system
   • JWT-based authentication
   • Session management

2. API Protection

   • Rate limiting
   • Request validation
   • CORS configuration

3. Audit Logging

   • User activity tracking
   • Data change history
   • Security event logging

4. Data Security

   • Encryption at rest
   • Secure credential storage
   • Input sanitization

Performance Optimization

1. Caching System

   • Redis-based caching
   • In-memory fallback
   • Configurable TTL

2. Rate Limiting

   • Token bucket algorithm
   • Distributed rate limiting
   • Custom limits per endpoint

Development

Testing

Run tests:

pytest

Generate coverage report:

pytest --cov=src tests/

Code Style

Format code:

black src/

Run linter:

flake8 src/

Type checking:

mypy src/

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.