Manage computational resources carefully

in backend/Generator/mcq.py
Improve Computational Resource Management
Overview
Our current implementation of the question generation script faces significant computational resource management challenges that need systematic optimization.
Problem Statement
The existing codebase struggles with efficient memory and computational resource utilization, particularly when processing large datasets or working with multiple machine learning models.
Detailed Challenges
1. Memory Consumption Bottlenecks

Multiple complex models loaded simultaneously
High memory usage during text processing
Potential script crashes with large input texts

2. Inefficient Model Management

Lack of smart model loading/unloading mechanisms
No dynamic resource allocation strategies
Potential performance degradation in resource-constrained environments

3. Processing Limitations

Limited support for incremental data processing
No built-in mechanism for handling large datasets
Risk of out-of-memory errors

Proposed Solutions
Resource Management Improvements

Implement batch processing techniques
Add dynamic memory allocation strategies
Create resource monitoring mechanisms
Develop fallback processing options

Model Optimization

Create intelligent model loading/unloading mechanism
Add support for lightweight model versions
Implement model caching strategies

Scalability Enhancements

Design adaptive processing workflow
Add configurable resource allocation parameters
Create system capability detection

Expected Outcomes

Improved script performance across different computational environments
Reduced memory consumption
Enhanced processing capabilities
More robust error handling

Contribution Guidelines
Interested contributors should focus on:

Modular design approaches
Memory-efficient processing techniques
Dynamic resource management strategies

Additional Context
This optimization is crucial for:

Handling varied input sizes
Supporting different computational setups
Improving overall script reliability

Priority
High Priority
Potential Impacts

Performance improvement
Broader compatibility
Enhanced user experience