Cli Anything Unimol Tools

Project Management

# Create a new project
project create --name drug_discovery

# List all projects
project list

# Switch to a project
project switch --name drug_discovery

Training

# Train a classification model
train --data-path train.csv --target-col active --task-type classification --epochs 10

# Train a regression model
train --data-path train.csv --target-col affinity --task-type regression --epochs 10

Model Management

# List all trained models
models list

# Show model details and performance
models show --model-id <id>

# Rank models by performance
models rank

Storage & Cleanup

# Analyze storage usage
storage analyze

# Automatic cleanup of poor performers
cleanup auto

# Manual cleanup with criteria
cleanup manual --max-models 10 --min-score 0.7

Prediction

# Make predictions with a trained model
predict --model-id <id> --data-path test.csv

Data Format

CSV files must contain:

• SMILES column: Molecular structures in SMILES format
• Target column(s): Values to predict (name specified via --target-col)

Example:

SMILES,target
CCO,1
CCCO,0
CC(C)O,1

Task Types

1. classification: Binary classification (0/1)
2. regression: Continuous value prediction
3. multiclass: Multiple class classification
4. multilabel_classification: Multiple binary labels
5. multilabel_regression: Multiple continuous values

JSON Mode

Add --json flag to any command for machine-readable output:

python3 -m cli_anything.unimol_tools --json models list

Output format:

{
  "status": "success",
  "data": [...],
  "message": "..."
}

Interactive Mode

Launch without commands for interactive REPL:

python3 -m cli_anything.unimol_tools

Features:

• Tab completion
• Command history
• Contextual help
• Project state persistence

Test Data

Example datasets available at: