mirror of
https://github.com/signerless/llm-checker.git
synced 2026-10-19 09:54:45 +00:00
Fixed remaining unprotected spawn('ollama') calls across multiple files:
- src/models/deterministic-selector.js: Added ENOENT error handling in runOllamaCommand and getModelDetails
- ml-model/js/cli.js: Protected getAvailableModels and runOllamaModel functions
- Added proper try-catch blocks around all spawn calls
- Added graceful fallbacks when Ollama executable is not found
- Enhanced error messages to guide users to install Ollama
This should completely resolve the Windows ENOENT crash when Ollama is not installed.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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| ml-model | ||
| scripts | ||
| src | ||
| .gitignore | ||
| .npmignore | ||
| ADVANCED_USAGE.md | ||
| CLAUDE_CODE_STYLE.md | ||
| debug-ollama.js | ||
| LICENSE | ||
| package.json | ||
| PROGRESS_IMPROVEMENTS.md | ||
| README.md | ||
| TECHNICAL_DOCS.md | ||
| USAGE_GUIDE.md | ||
LLM Checker - Intelligent Ollama Model Selector
Advanced CLI tool that analyzes your hardware and intelligently recommends the optimal Ollama LLM models for your system with automatic installation detection.
Designed specifically for Ollama - Integrates with 177+ models from the complete Ollama model library to find the best models for your hardware configuration.
✨ Key Features
🎯 Multiple Model Recommendations
--limitflag: Show multiple compatible models instead of just one- Ranked display: See top 3, 5, or 10 models with compatibility scores
- Smart alternatives: Get backup options with unique installation commands
- Hardware-aware filtering: Automatically excludes unreasonably large models
✅ Automatic Installation Detection
- Real-time detection: Automatically detects already installed Ollama models
- Smart Quick Start: Shows
ollama runfor installed models,ollama pullfor new ones - Status indicators: Clear "Already installed" vs "Available for installation" status
- No duplicate suggestions: Won't suggest installing models you already have
🧠 Intelligent Use Case Categories
- 7 specialized categories: coding, creative, reasoning, multimodal, embeddings, talking, general
- Typo tolerance: Handles common misspellings (e.g., "embedings" → "embeddings")
- Smart filtering: Each category shows models optimized for that specific use case
- Category-aware scoring: Different scoring weights for different use cases
📊 Real Model Data
- 177+ models with accurate size data from Ollama Hub
- Real file sizes: Uses actual model sizes instead of parameter estimates
- Pre-classified categories: All models categorized by capabilities
- Static database: Stable, reliable model information without dynamic updates
🚀 Advanced Algorithm
- Multi-objective ranking with hardware-size matching
- Hardware utilization scoring: Penalizes models that underutilize high-end hardware
- Smart size filtering: Filters out models too large for your system
- Cross-platform compatibility: macOS, Windows, Linux with GPU detection
🚀 Quick Start
Installation
npm install -g llm-checker
Prerequisites
- Node.js 16+
- Ollama installed and running (Download here)
Basic Usage
# Get the best model for your hardware
llm-checker check
# Show top 5 compatible models
llm-checker check --limit 5
# Get coding-specific models
llm-checker check --use-case coding --limit 3
# Find creative writing models
llm-checker check --use-case creative --limit 5
📋 Available Use Cases
| Use Case | Description | Example Models |
|---|---|---|
coding |
Programming and code generation | CodeLlama, DeepSeek Coder, CodeQwen |
creative |
Creative writing and content | Dolphin, Wizard, Uncensored models |
reasoning |
Logic and mathematical reasoning | DeepSeek-R1, Phi4-reasoning, Llama3.2-vision |
multimodal |
Image analysis and vision tasks | Llama3.2-vision, LlaVa |
embeddings |
Text vectorization and search | BGE, E5, embedding models |
talking |
General conversation and chat | Llama, Mistral, Qwen (excluding specialized) |
general |
Balanced, versatile models | Mixed selection prioritizing chat/reasoning |
🛠️ Command Reference
Main Commands
# Hardware analysis with model recommendations
llm-checker check [options]
# Get intelligent recommendations
llm-checker recommend [options]
# List available models
llm-checker list-models
# AI-powered model evaluation
llm-checker ai-check
# Ollama integration info
llm-checker ollama
Options
# Show multiple models
--limit <number> Number of models to show (default: 1)
# Use case filtering
--use-case <case> Specify use case (coding, creative, reasoning, etc.)
# Output control
--no-verbose Clean, minimal output
--include-cloud Include cloud-based models
# Filtering
--filter <type> Filter by model type
--ollama-only Only show Ollama-available models
📖 Examples
Basic Recommendations
# Single best model
llm-checker check
# Output: Shows #1 model with installation command
# Multiple options
llm-checker check --limit 5
# Output: Shows top 5 ranked models with scores
Use Case Specific
# Coding models
llm-checker check --use-case coding --limit 3
# Output: CodeLlama, DeepSeek Coder, CodeQwen with install commands
# Creative writing
llm-checker check --use-case creative --limit 5
# Output: Dolphin, Wizard, creative-optimized models
# Reasoning tasks
llm-checker check --use-case reasoning --limit 3
# Output: DeepSeek-R1, Phi4-reasoning, specialized reasoning models
Installation Detection
llm-checker check --limit 5 --use-case coding
Example output:
TOP 5 COMPATIBLE MODELS
#1 - CodeLlama 7B
Size: 3.8GB
Compatibility Score: 84.88/100
Status: Already installed in Ollama
#2 - Qwen 2.5 7B
Size: 5.2GB
Compatibility Score: 83.78/100
Status: Available for installation
QUICK START
1. Start using your installed model:
ollama run codellama:7b
Alternative options:
2. ollama pull qwen2.5:7b
3. ollama pull codeqwen
🔧 Advanced Features
Hardware Tier Detection
- Ultra High: 64+ GB RAM → 13B-70B models
- High: 24-64 GB RAM → 7B-30B models
- Medium: 8-16 GB RAM → 3B-13B models
- Low: 4-8 GB RAM → 1B-7B models
- Ultra Low: <4 GB RAM → <3B models
Smart Filtering
- Automatically excludes models >25GB for systems with <32GB RAM
- Penalizes tiny models on high-end hardware
- Prioritizes models in the "sweet spot" for your hardware tier
- Removes duplicate commands from alternatives
Cross-Platform Support
- macOS: Apple Silicon optimization with unified memory
- Windows: NVIDIA/AMD GPU detection with device ID mapping
- Linux: Full GPU compatibility with proper driver detection
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Development
git clone https://github.com/Pavelevich/llm-checker.git
cd llm-checker
npm install
# Run locally
node bin/enhanced_cli.js check --limit 5
📄 License
MIT License - see LICENSE file for details.
👨💻 Author
⭐ Support
If you find LLM Checker useful, please consider:
- Starring the repository ⭐
- Contributing improvements 🛠️
- Reporting issues 🐛
- Sharing with others 📢
Buy me a coffee: github.com/signerless/llm-checker