edgemodelr
Local Large Language Model Inference Engine
Enables R users to run large language models locally using 'GGUF' model files and the 'llama.cpp' inference engine. Provides a complete R interface for loading models, generating text completions, and streaming responses in real-time. Supports local inference without requiring cloud APIs or internet connectivity, ensuring complete data privacy and control. Based on the 'llama.cpp' project by Georgi Gerganov (2023) <https://github.com/ggml-org/llama.cpp>.
README
# edgemodelr Examples
This directory contains examples for using edgemodelr with modern small language models.
## 📁 Organization
### 🚀 Quick Start Examples
**For immediate solutions and learning:**
- `working_document_analysis.R` - Simple document analysis (works immediately)
- `manual_setup_example.R` - Troubleshooting model downloads
- `document_analysis_example.R` - Alternative analysis approach
### 🎯 Professional Examples
**For production applications:**
- `01_model_comparison.R` - Modern model selection and comparison
- `02_document_analysis.R` - Advanced document analysis system
- `03_content_generation.R` - Multi-format content generation
- `04_streaming_chat.R` - Interactive streaming conversations
- `05_model_benchmarking.R` - Systematic model evaluation
## 🏃 Quick Start
```r
# Option 1: Quick working solution
source(system.file("examples", "working_document_analysis.R", package = "edgemodelr"))
# Option 2: Professional system
source(system.file("examples", "02_document_analysis.R", package = "edgemodelr"))
analyzer <- DocumentAnalyzer()
results <- analyzer$analyze_documents(your_texts)
```
## 📚 Choose Your Path
- **Need it working NOW** → Start with `working_document_analysis.R`
- **Building production app** → Use `02_document_analysis.R`
- **Learning about models** → Check `01_model_comparison.R`
- **Having download issues** → Use `manual_setup_example.R`
## 🆚 Quick vs Professional Examples
| Aspect | Quick Examples | Professional Examples |
|--------|----------------|----------------------|
| **Goal** | Solve immediate problem | Production-ready systems |
| **Complexity** | Simple, direct | Comprehensive, feature-rich |
| **Error Handling** | Basic | Extensive |
| **Documentation** | Minimal | Complete |
## 📖 Additional Documentation
- `../../MODERN_MODELS.md` - Guide to 2024 small language models
- `../../EXAMPLES_GUIDE.md` - Complete navigation guide
---
All examples include error handling and work with the latest 2024 quantized models including Llama 3.2, Phi-3.5, Qwen2.5, and Gemma 2.Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | edgemodelr_0.2.0.tar.gz |
2.3 MiB |
0.2.0 |
rolling linux/noble R-4.5 | edgemodelr_0.2.0.tar.gz |
2.2 MiB |
0.2.0 |
rolling source/ R- | edgemodelr_0.2.0.tar.gz |
811.1 KiB |
0.2.0 |
latest linux/jammy R-4.5 | edgemodelr_0.2.0.tar.gz |
2.3 MiB |
0.2.0 |
latest linux/noble R-4.5 | edgemodelr_0.2.0.tar.gz |
2.2 MiB |
0.2.0 |
latest source/ R- | edgemodelr_0.2.0.tar.gz |
811.1 KiB |
0.2.0 |
2026-04-26 source/ R- | edgemodelr_0.2.0.tar.gz |
811.1 KiB |
0.2.0 |
2026-04-23 source/ R- | edgemodelr_0.2.0.tar.gz |
811.1 KiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | edgemodelr_0.2.0.zip |
1.9 MiB |