https://github.com/ai-mindset/modelmeter
A lightweight, cross-platform utility that calculates the total storage footprint of locally installed large language models managed through Ollama
https://github.com/ai-mindset/modelmeter
deno go gola javascr llms local ollama on-prem on-premise python storage
Last synced: 3 months ago
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A lightweight, cross-platform utility that calculates the total storage footprint of locally installed large language models managed through Ollama
- Host: GitHub
- URL: https://github.com/ai-mindset/modelmeter
- Owner: ai-mindset
- License: mit
- Created: 2025-03-25T10:58:15.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-25T11:46:50.000Z (3 months ago)
- Last Synced: 2025-03-25T12:36:21.877Z (3 months ago)
- Topics: deno, go, gola, javascr, llms, local, ollama, on-prem, on-premise, python, storage
- Language: Python
- Homepage:
- Size: 8.79 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ModelMeter
[](https://opensource.org/licenses/MIT)
**ModelMeter** is a lightweight, cross-platform utility that calculates the total storage footprint of locally installed large language models managed through Ollama.
## 📋 Overview
Managing multiple large language models locally can quickly consume significant disk space. ModelMeter provides a simple command-line tool to instantly determine exactly how much storage your LLM collection is using, helping you manage system resources effectively.
## 🚀 Quick Start
```bash
# Python
./py/ollama_total.py
# Deno (JavaScript)
deno run --allow-run ./js/ollama_total.js
# Go
./go/ollama_total
# Example output
26.8 GB
```
## ✨ Features
- **Accurate Size Calculation:** Precisely measures total storage used by all installed Ollama models
- **Smart Unit Formatting:** Automatically selects the most appropriate unit (MB, GB, TB)
- **Multiple Language Implementations:** Choose from Python, Deno (JavaScript), or Go
- **Simple Integration:** Use as a standalone command or integrate into larger workflows
- **Minimal Dependencies:** Relies only on standard libraries in each language
## ❓ Why ModelMeter?
While you could manually add up model sizes from `ollama list` output, ModelMeter:
- Saves time with instant calculations
- Eliminates human error in size conversions and addition
- Provides consistent formatting across different model sizes
- Enables easy integration into monitoring scripts and dashboards
- Serves as a building block for more complex LLM resource management tools
## 💻 Installation
### System Requirements
- **Python:** Python 3.10+
- **JavaScript:** Deno 2.0+
- **Go:** Go 1.16+
- **All implementations:** Ollama must be installed and in your PATH
### Python Implementation
```bash
# Clone the repository
git clone https://github.com/ai-mindset/ModelMeter.git
cd ModelMeter/py
# Make the Python script executable
chmod +x ollama_total.py
# Optional: Add to your PATH
ln -s $(pwd)/ollama_total.py /usr/local/bin/ollama_total
```
### Deno Implementation
```bash
# Clone the repository
git clone https://github.com/ai-mindset/ModelMeter.git
cd ModelMeter/js
# Make the JavaScript file executable
chmod +x ollama_total.js
# Run with Deno
deno run --allow-run ollama_total.js
# Optional: Install as a command
deno install --allow-run --name ollama_total ollama_total.js
```
### Go Implementation
```bash
# Clone the repository
git clone https://github.com/ai-mindset/ModelMeter.git
cd ModelMeter/go
# Build the Go binary
go build -o ollama_total ollama_total.go
# Move to a directory in your PATH
sudo mv ollama_total /usr/local/bin/
```
## 💻 Usage
### Basic Command
```bash
ollama_total
```
### Integrating Into Scripts
#### Python
```python
from ollama_total import get_ollama_total
# Get the total storage used by Ollama models
total = get_ollama_total()
print(f"Your Ollama models are using {total}")
```
#### Deno (JavaScript)
```javascript
import { getOllamaTotal } from "./ollama_total.js";
// Get the total storage used by Ollama models
const total = await getOllamaTotal();
console.log(`Your Ollama models are using ${total}`);
```
#### Go
```go
package main
import (
"fmt"
"path/to/modelMeter"
)
func main() {
total, err := getOllamaTotal()
if err != nil {
fmt.Printf("Error: %s\n", err)
return
}
fmt.Printf("Your Ollama models are using %s\n", total)
}
```
## 🔍 Technical Details
### How It Works
ModelMeter executes the `ollama list` command, parses the output to extract size information, converts all sizes to bytes for accurate summation, and then converts the total back to the most appropriate unit.
### Size Conversion and Parsing
- Uses SI units: 1 MB = 10^6 bytes, 1 GB = 10^9 bytes, 1 TB = 10^12 bytes (matching Ollama's output)
- Regex pattern `(\d+(?:\.\d+)?) (MB|GB|TB)` extracts size values and units
- Results are formatted with one decimal place precision for readability
## ⚠️ Troubleshooting
| Issue | Solution |
|-------|----------|
| `Command not found: ollama` | Ensure Ollama is installed and in your PATH |
| No output displayed | Check if you have any models installed with `ollama list` |
| Permission denied | Run `chmod +x` on the script file |
| Incorrect total | Ensure no other process is installing/removing models during calculation |
| Deno security errors | Ensure you've provided the `--allow-run` flag when using Deno |
## 🔄 Alternatives
| Approach | Pros | Cons |
|----------|------|------|
| ModelMeter | Automatic calculation, multiple languages, formatting | Additional tool to install |
| Manual addition from `ollama list` | No installation needed | Time-consuming, error-prone |
| Shell one-liner[^1] | Quick for one-time use | Complex syntax, limited formatting |
| Disk usage tools (du) | System-wide analysis | Includes non-model files, less precise |
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## 📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
## 🙏 Acknowledgments
- [Ollama](https://github.com/ollama/ollama) - For making local LLM deployment accessible
---
[^1]: Example shell one-liner: `ollama list | awk 'NR>1 {size=$3; if($4=="GB") size*=1000; if($4=="TB") size*=1000000; sum+=size} END {printf "%.1f %s\n", sum>=1000000 ? sum/1000000 : sum>=1000 ? sum/1000 : sum, sum>=1000000 ? "TB" : sum>=1000 ? "GB" : "MB"}'`