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# Uni-Mol Tools - Molecular Property Prediction CLI

name: "cli-anything-unimol-tools"
description: >-
Interactive CLI for Uni-Mol molecular property prediction training and inference workflows.

# Uni-Mol Tools - Molecular Property Prediction CLI#

Package: `cli-anything-unimol-tools`
Command: `python3 -m cli_anything.unimol_tools`

## Description#

Interactive CLI for training and inference of molecular property prediction models using Uni-Mol Tools. Supports 5 task types: binary classification, regression, multiclass, multilabel classification, and multilabel regression.

## Key Features#

- Project Management: Organize experiments with named projects
- 5 Task Types: Classification, regression, multiclass, multilabel variants
- Model Tracking: Automatic performance history and rankings
- Smart Storage: Analyze usage and clean up underperformers
- JSON API: Full automation support with `--json` flag

## Common Commands#

### 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:
https://github.com/545487677/CLI-Anything-unimol-tools/tree/main/unimol_tools/examples

Includes data for all 5 task types.

## Requirements#

- Python 3.8+
- PyTorch 1.12+
- Uni-Mol Tools backend
- 4GB+ RAM (8GB+ recommended for training)

## Installation#

    cd unimol_tools/agent-harness
    pip install -e .

## Documentation#

- SOP: UNIMOL_TOOLS.md
- Quick Start: docs/guides/02-QUICK-START.md
- Full Documentation: docs/README.md

## Testing#

    cd docs/test
    bash run_tests.sh --unit -v    # Unit tests (67 tests)
    bash run_tests.sh --full -v    # Full test suite

## Performance Tips#

- Start with 10 epochs for initial experiments
- Use smaller batch sizes if memory is limited
- Monitor storage with `storage analyze`
- Use `models rank` to identify best performers
- Clean up regularly with `cleanup auto`

## Troubleshooting#

- CUDA errors: Reduce batch size or use CPU mode
- CSV not recognized: Verify SMILES column exists
- Low accuracy: Try more epochs or adjust learning rate
- Storage full: Run `cleanup auto` to free space

## Related#

- Uni-Mol Tools: https://github.com/dptech-corp/Uni-Mol/tree/main/unimol_tools
- Uni-Mol Paper: https://arxiv.org/abs/2209.11126
- CLI-Anything: https://github.com/HKUDS/CLI-Anything