https://github.com/jtgsystems/universal-ollama-optimizer
Professional bash script for launching and managing Ollama AI models with parameter profile suggestions, system monitoring, and automated configuration. Not an automatic optimizer - provides suggested /set commands for manual application.
https://github.com/jtgsystems/universal-ollama-optimizer
ai ai-models automation bash launcher linux llm local-ai model-management model-optimizer ollama optimization shell terminal-ui tools
Last synced: about 1 month ago
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Professional bash script for launching and managing Ollama AI models with parameter profile suggestions, system monitoring, and automated configuration. Not an automatic optimizer - provides suggested /set commands for manual application.
- Host: GitHub
- URL: https://github.com/jtgsystems/universal-ollama-optimizer
- Owner: jtgsystems
- License: mit
- Created: 2025-09-16T05:15:54.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2026-02-09T17:43:48.000Z (4 months ago)
- Last Synced: 2026-02-09T21:12:45.375Z (4 months ago)
- Topics: ai, ai-models, automation, bash, launcher, linux, llm, local-ai, model-management, model-optimizer, ollama, optimization, shell, terminal-ui, tools
- Language: Shell
- Size: 719 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# Ollama Launcher & Manager
**Developed by [JTGSYSTEMS.COM](https://jtgsystems.com) | [JointTechnologyGroup.com](https://jointtechnologygroup.com)**
A professional bash script for launching and managing Ollama AI models with intelligent profile suggestions, system monitoring, and automated configuration.
[](https://opensource.org/licenses/MIT)
[](https://github.com/jtgsystems/universal-ollama-optimizer)
[](https://ollama.ai)
[](https://www.gnu.org/software/bash/)
## What This Actually Does
This is a **model launcher and management toolkit** for Ollama. It provides:
- **Interactive model selection** from 55+ pre-configured 2025 models
- **System validation** before launching (network, Ollama service, disk space, GPU/RAM checks)
- **Parameter profile suggestions** with recommended settings for different use cases
- **Automatic model downloading** with validation and retry logic
- **Clean terminal UI** with colors and progress indicators
### Important Note on "Optimization"
This script **does NOT automatically apply parameters** to models. Ollama's CLI doesn't support passing parameters like `temperature` or `top_p` at launch time. Instead, this tool:
1. **Suggests optimized profiles** based on your use case
2. **Shows you the recommended parameters** for that profile
3. **Provides copy-paste ready `/set` commands** to apply manually during your session
For automatic parameter application, you would need to use Ollama's HTTP API directly or create custom Modelfiles (which this script can help with).
## Latest Updates (September 2025)
**Added 5 Critical Missing Models Based on Community Research:**
- **GLM-4** - Ranks 3rd overall on hardcore benchmarks, beats Llama 3 8B
- **Magicoder** - OSS-Instruct trained coding specialist with 75K synthetic instruction data
- **Gemma3n** - Multimodal model optimized for everyday devices (phones, tablets, laptops)
- **Granite 3.3** - IBM's improved models with 128K context (2B and 8B variants)
- **Gemma3:270M** - Ultra-compact 270M model with 0.75% battery usage on mobile devices
**Enhanced Menu Organization:**
- Expanded model selection from 50+ to 55+ latest 2025 models
- Added new performance benchmarks and descriptions
- Updated all optimization profiles and system recommendations
## Features
- ** Universal Model Support** - Works with any Ollama model (llama3.2, mistral, gemma2, etc.)
- ** 6 Profile Suggestions** - Pre-configured parameter suggestions: Balanced, Technical, Creative, Code, Reasoning, Roleplay
- ** System Resource Monitoring** - Real-time GPU, RAM, and disk space monitoring
- ** Auto-Download & Validation** - Intelligent model downloading with space checking
- ** Professional Interface** - Clean, colorful terminal UI with progress indicators
- ** Configuration Management** - File-based config with runtime overrides
- ** Custom Parameters** - Full manual parameter control and Modelfile creation
- ** Error Logging** - Comprehensive logging to `~/.config/universal-ollama-optimizer/errors.log`
## Requirements
- **Linux** (Ubuntu 20.04+, other distros compatible)
- **Bash 5.0+** (pre-installed on most systems)
- **Ollama** ([Download here](https://ollama.ai/download))
- **8GB+ RAM** recommended
- **GPU** optional but recommended (NVIDIA with CUDA support)
## Quick Start
### One-Command Install & Run
```bash
# Download and run
curl -fsSL https://raw.githubusercontent.com/jtgsystems/universal-ollama-optimizer/main/universal-ollama-optimizer.sh -o universal-ollama-optimizer.sh
chmod +x universal-ollama-optimizer.sh
./universal-ollama-optimizer.sh
```
### Manual Installation
```bash
# Clone repository
git clone https://github.com/jtgsystems/universal-ollama-optimizer.git
cd universal-ollama-optimizer
# Make executable
chmod +x universal-ollama-optimizer.sh
# Run
./universal-ollama-optimizer.sh
```
## Usage
### Interactive Mode (Default)
```bash
./universal-ollama-optimizer.sh
```
1. **Select Model** - Choose from available models or enter new model name
2. **Choose Profile** - Select parameter suggestion profile (1-9)
3. **Launch Model** - Model starts with parameter instructions displayed
4. **Apply Parameters** - Use `/set` commands manually during the session
### Example Session
```
Enter model name: llama3.2:latest
Model Information:
• Model: llama3.2:latest
• Size: 4.7GB
• Parameters: 3.2B
System Status:
• GPU Memory: 16380 MB
• System RAM: 32GB
• Available Disk: 150GB
Parameter Profiles:
1) Balanced - General purpose (temp: 0.5)
2) Technical/Factual - Precise answers (temp: 0.2)
3) Creative Writing - Imaginative content (temp: 1.0)
4) Code Generation - Programming tasks (temp: 0.15)
5) Reasoning/Logic - Problem solving (temp: 0.3)
6) Roleplay/Chat - Conversational (temp: 0.8)
Select profile [1-6]: 1
Starting llama3.2:latest with Balanced profile suggestion...
To apply these parameters during your session, use:
/set parameter temperature 0.5
/set parameter top_p 0.85
/set parameter top_k 30
/set parameter repeat_penalty 1.08
```
## Configuration
### Config File Location
```
~/.config/universal-ollama-optimizer/config.conf
```
### Example Configuration
```ini
# Default profile (balanced, technical, creative, code, reasoning, roleplay)
DEFAULT_PROFILE="balanced"
# Auto-start Ollama service if not running
AUTO_START_OLLAMA=true
# System monitoring
SHOW_SYSTEM_INFO=true
SHOW_GPU_INFO=true
# Download settings
DOWNLOAD_TIMEOUT=1800
MIN_DISK_SPACE_GB=5
```
## Parameter Profiles (Suggestions)
| Profile | Temperature | Top-P | Top-K | Best For |
|---------|-------------|-------|-------|----------|
| **Balanced** | 0.5 | 0.85 | 30 | General use, Q&A |
| **Technical** | 0.2 | 0.8 | 20 | Documentation, facts |
| **Creative** | 1.0 | 0.95 | 50 | Stories, brainstorming |
| **Code** | 0.15 | 0.7 | 15 | Programming, debugging |
| **Reasoning** | 0.3 | 0.75 | 25 | Logic, analysis |
| **Roleplay** | 0.8 | 0.9 | 40 | Character chat |
## Advanced Features
### Custom Parameters
Choose option `7` for manual parameter configuration:
- Temperature (0.0-2.0)
- Top-P (0.0-1.0)
- Top-K (1-100)
- Context length
- Max tokens per response
- Repeat penalty
### Modelfile Creation
Choose option `8` to create and save custom model configurations:
```bash
# Creates permanent optimized model variants
# Example: llama3.2-coding, mistral-creative
```
### Runtime Commands
Once model is running, use these commands:
```bash
/set parameter temperature 0.7 # Adjust parameters
/set system "You are a coding assistant" # Change system prompt
/show parameters # View current settings
/save my-conversation # Save session
/load my-conversation # Load session
```
## Troubleshooting
### Common Issues
**Ollama Not Found**
```bash
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh
```
**Permission Denied**
```bash
# Make script executable
chmod +x universal-ollama-optimizer.sh
```
**Model Download Fails**
```bash
# Check internet connection and disk space
df -h
ping ollama.ai
```
**GPU Not Detected**
```bash
# Check NVIDIA drivers
nvidia-smi
```
## Project Structure
```
universal-ollama-optimizer/
├── universal-ollama-optimizer.sh # Main script
├── README.md # This file
├── LICENSE # MIT License
└── .github/
├── workflows/
│ └── test.yml # CI/CD tests
├── ISSUE_TEMPLATE/ # Issue templates
└── PULL_REQUEST_TEMPLATE.md # PR template
```
## Contributing
We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md).
### Development Setup
```bash
# Fork and clone
git clone https://github.com/jtgsystems/universal-ollama-optimizer.git
cd universal-ollama-optimizer
# Test the script
./universal-ollama-optimizer.sh
# Run with debug mode
bash -x universal-ollama-optimizer.sh
```
### Reporting Issues
- Use the [issue tracker](https://github.com/jtgsystems/universal-ollama-optimizer/issues)
- Include OS version, Ollama version, and error messages
- Provide steps to reproduce
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- **Jesus Christ** - Our Lord and Saviour, for all gifts and abilities
- **Ollama Team** - For creating an excellent local AI platform
- **Community Contributors** - For feedback and improvements
- **JTGSYSTEMS.COM** - For development and maintenance
## Support
- **Issues**: [GitHub Issues](https://github.com/jtgsystems/universal-ollama-optimizer/issues)
- **Discussions**: [GitHub Discussions](https://github.com/jtgsystems/universal-ollama-optimizer/discussions)
- **Website**: [JTGSYSTEMS.COM](https://jtgsystems.com)
---
## Recommended Ollama Models (September 2025)
*Based on latest community recommendations and performance benchmarks*
### ** Top-Tier Models (September 2025)**
#### ** Best Overall Performance**
- **`llama3.3:70b`** - Meta's flagship 2025 model, rivals GPT-4 performance locally
- **`glm4:latest`** - Ranks 3rd overall, beats Llama 3 8B in benchmarks
- **`llama3.1:8b`** - Community favorite, best balance of performance and efficiency
- **`llama3.1:70b`** - High-performance for complex reasoning and enterprise use
- **`deepseek-r1`** - Powerhouse for deep logical reasoning and analysis
#### ** Premier Coding Models**
- **`deepseek-coder:33b`** - #1 coding model, excels at complex programming tasks
- **`magicoder:latest`** - OSS-Instruct trained specialist, 75K synthetic data
- **`qwen3-coder:30b`** - Alibaba's latest 2025 coding model with major improvements
- **`codellama:34b`** - Meta's specialized coding model with excellent context understanding
- **`qwen2.5-coder:32b`** - Previous Alibaba model with solid code generation
#### ** Resource-Efficient Champions**
- **`granite3.3:8b`** - IBM's improved model with 128K context, rivals Llama 3.1
- **`mistral:7b-instruct`** - Community-recommended for beginners, excellent performance/resource ratio
- **`phi4:14b`** - Microsoft's 2025 state-of-the-art efficiency model
- **`granite3.3:2b`** - IBM's efficient enterprise model for edge deployment
- **`llama3.2:3b`** - Compact Llama for lightweight deployments
- **`gemma3:270m`** - Ultra-compact 270M model, 0.75% battery usage on mobile
- **`gemma2:9b`** - Google's efficient model, great for general tasks
#### ** Creative & Multimodal**
- **`gemma3n:latest`** - Multimodal optimized for everyday devices (phones, tablets)
- **`llava:latest`** - Leading vision model for image analysis and VQA
- **`qwen-vl`** - Advanced multimodal model for document and image processing
- **`gemma2:27b`** - Excellent for creative writing and content generation
### ** Performance Matrix (September 2025)**
| Use Case | Top Model | Alternative | RAM Required | Best Profile |
|----------|-----------|-------------|--------------|--------------|
| **General Chat** | `llama3.3:70b` | `glm4:latest` | 64GB / 9GB | Balanced |
| **Code Development** | `deepseek-coder:33b` | `magicoder:latest` | 32GB / 7GB | Code |
| **Reasoning Tasks** | `deepseek-r1` | `glm4:latest` | 16GB / 9GB | Reasoning |
| **Creative Writing** | `gemma2:27b` | `gemma3n:latest` | 32GB / 8GB | Creative |
| **Resource-Limited** | `granite3.3:2b` | `gemma3:270m` | 2GB / 300MB | Balanced |
| **Vision/Multimodal** | `llava:latest` | `gemma3n:latest` | 16GB / 8GB | Technical |
| **Enterprise/128K Context** | `granite3.3:8b` | `llama3.1:8b` | 8GB | Technical |
| **Edge/Mobile** | `gemma3:270m` | `granite3.3:2b` | 300MB / 2GB | Balanced |
### ** Quick Download Commands (September 2025)**
```bash
# Most recommended overall (2025 flagship)
ollama pull llama3.3:70b-instruct
# High-performance alternative (ranks 3rd overall)
ollama pull glm4:latest
# Specialized coding assistant with OSS-Instruct training
ollama pull magicoder:latest
# Premier coding powerhouse
ollama pull deepseek-coder:33b
# Enterprise model with 128K context
ollama pull granite3.3:8b
# Ultra-efficient for mobile/edge (270M parameters)
ollama pull gemma3:270m
# Multimodal for everyday devices
ollama pull gemma3n:latest
# Advanced reasoning powerhouse
ollama pull deepseek-r1
# Vision and image analysis
ollama pull llava:latest
# Best for beginners/limited hardware
ollama pull mistral:7b-instruct
```
### ** 2025 Community Insights**
- **Llama 3.3** has become the gold standard for local deployment
- **DeepSeek models** dominate coding and reasoning benchmarks
- **Mistral 7B** remains the go-to recommendation for newcomers
- **Vision models** like LLaVA are gaining massive adoption
- Over **1,700+ models** now available in Ollama ecosystem
*Note: Model availability and performance may vary. Check [ollama.com/library](https://ollama.com/library) for the latest models.*
---
**Repository**: `universal-ollama-optimizer` | **Developer**: JTGSYSTEMS.COM | **Technology**: Bash, Linux, Ollama, AI