Aliyah

Work in progress

Being able to see to see my model train and interact with it in the terminal is important to me

Wrapper libary in /python

Keyboard Controls

q/ESC : Quit

p/SPACE: Pause/Resume training

s : Stop training

e : Toggle error log

↑/↓ : Scroll error log | Scroll training log

c : Clear error log

h : Show this help

tab/n : Show node information

click : Switch training and node panel

o : Output panel

Pre-Alpha Release

git clone https://github.com/lovechants/Aliyah.git 
cargo build
pip install -e . 
cargo run -- <script.py>

data folder is for example scripts only

Current TODO

• Fix mouse input cature bug when you exit (if clicked)
• Fix help render bug
• Fix prediction timer bug
• Fix logging crash
• Fix prediction screen text
• Make plotting more robust
• Make visualization better for networks
• Make classic machine learning visualizations (not just networks)
• Update examples (Make more robust examples with the new features and remove the original test examples)
  • MNIST neural net
  • MNIST VAE
  • Deep network
  • Shallow network
  • Transformer
  • Algorithmic Pipeline -> PSO -> PNN (no boltzmann) adapted from this paper
    • Either show each algorithm / model indepent of each other move to the next
    • Or show all of them at the same time running async?
• Test custom metrics
• Fix output match statements to be more robust
• Make framework hooks for visualizations
  • PyTorch
  • JAX
  • Keras
  • TF
  • TinyGrad
  • SciKit Learn
  • Custom
  • Default
• User Config
• Publish Packages for pip, uv, and cargo
• Add other GPU monitoring
  • Test Metal
  • Test NVIDIA
  • Test AMD
• Fix memory bug || check if its just local browser issues

Roadmap to 1.0 alpha

1. Core Infrastructure

• Install and set up ZMQ dependencies (Rust and Python)
• Create ZMQ context and socket management
• Implement basic message patterns
  • Command channel (REQ-REP)
  • Metrics channel (PUB-SUB)
  • Control flow channel

2. Python Monitor Library

• Update monitor class for ZMQ
  • Command handling
  • Metric sending
  • Control flow checks
• Context manager implementation
• Error handling and recovery
• Basic metric formatting
• Safe cleanup on exit

3. Rust UI Updates

• ZMQ socket integration
• Command sending system
• Metric receiving and parsing
• Update existing UI components for new data flow
• Error handling and connection management

4. Core Features for 0.1a

• Training control (pause/resume/stop)
• Basic metric display
  • Loss
  • Accuracy
  • Epoch progress
• Simple network visualization
• Resource monitoring
  • Basic GPU stats
  • Memory usage
  • CPU usage

5. Testing and Validation

• Basic integration tests
• Cross-platform testing
• Error recovery testing
• Example scripts

6. Documentation

• Usage guide
• Example implementations
• Installation instructions
• Clean up codebase (again)

Future Features (Post 1.0a)

• User configuration
• Layer-specific visualization
• Advanced GPU monitoring
• Custom metric tracking
• Interactive parameter adjustment
• Extended framework support
• Advanced network visualization
• Custom algorithm support