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---
title: MentorFlow
emoji: 🎓
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.9.0
app_file: app.py
pinned: false
license: mit
hardware: gpu-t4
---
# MentorFlow - Teacher-Student RL System
A meta-curriculum reinforcement learning system where an AI Teacher Agent learns to select optimal educational tasks to train an AI Student Agent.
## 🚀 Features
- **Three Training Strategies**: Compare Random, Progressive, and Teacher-guided curriculum
- **LM Student (DistilBERT)**: Real neural network learning with memory decay
- **GPU Support**: Fast training with CUDA acceleration
- **Interactive Comparison**: Visualize learning curves and performance metrics
## 📊 Usage
1. **Set Parameters**:
- Iterations: Number of training iterations (50-500)
- Seed: Random seed for reproducibility
- Device: Choose GPU (cuda) or CPU
2. **Run Comparison**:
- Click "Run Comparison" to start training
- Monitor progress in the output text
- View generated comparison plots
3. **Analyze Results**:
- Learning curves show how each strategy improves
- Difficult question performance shows final accuracy
- Curriculum diversity shows topic coverage
## ⚡ Performance
- **With GPU**: ~5-10 minutes for 500 iterations
- **With CPU**: ~15-30 minutes for 500 iterations
## 📁 Project Structure
```
MentorFlow/
├── app.py # Gradio web interface
├── teacher_agent_dev/ # Teacher agent system
│ ├── compare_strategies.py # Main comparison script
│ ├── teacher_agent.py # UCB bandit teacher
│ └── ...
├── student_agent_dev/ # LM Student system
│ ├── student_agent.py # DistilBERT student
│ └── ...
└── requirements_hf.txt # Dependencies
```
## 🔧 Technical Details
- **Teacher Agent**: UCB (Upper Confidence Bound) multi-armed bandit
- **Student Agent**: DistilBERT with online learning
- **Memory Decay**: Ebbinghaus forgetting curve
- **Task Generator**: Procedural generation with 15 topics × 7 difficulties
## 📖 More Information
See the main repository for detailed documentation and development guides.
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