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308 changes: 149 additions & 159 deletions README.md
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# EMBODIOS - Bare-Metal AI Operating System

[![Status](https://img.shields.io/badge/Status-95%25%20Complete-brightgreen)](https://github.com/dddimcha/embodiOS/wiki/Current-State-Analysis)
[![AI Runtime](https://img.shields.io/badge/AI%20Runtime-100%25-brightgreen)](https://github.com/dddimcha/embodiOS/wiki/Pillar-1:-Ollama-GGUF-Integration)
[![Drivers](https://img.shields.io/badge/Drivers-85%25-green)](https://github.com/dddimcha/embodiOS/wiki/Pillar-2:-Linux-Driver-Compatibility)
[![License](https://img.shields.io/badge/License-MIT-blue)](LICENSE)
[![Model Compatibility](https://img.shields.io/badge/Model%20Compatibility-CI-brightgreen)](https://github.com/dddimcha/embodiOS/actions/workflows/model-compatibility-ci.yml)

> **The world's first bare-metal AI operating system** - where the AI model runs directly on hardware as the OS kernel itself. No userspace. No OS overhead. Just transformers and hardware.

## What's New (January 2026)

- **Interactive Chat Mode:** `talk` command for dedicated conversation sessions with performance tracking
- **Performance Stats:** Separate `perf` command to view timing metrics without cluttering chat
- **Console UX:** Polished help system with categories, status display, command suggestions
- **Production ISO Builder:** One-click bootable ISO with GRUB menu
- **Stability Testing Suite:** Automated long-running tests (1h-72h) for memory leak detection
- **Secure Boot:** UEFI Secure Boot support with signed kernel validation
- **Streaming Inference:** Memory-efficient inference engine with parallel workers
- **Industrial Protocols:** Modbus TCP and EtherCAT support for real-time automation

## Current Status

| Component | Status | Completion |
|-----------|--------|------------|
| **Kernel Foundation** | Memory, boot, interrupts, DMA, scheduler | 95% ✅ |
| **AI Runtime** | GGUF, BPE, streaming inference, quantization | 100% ✅ |
| **Drivers** | NVMe, VirtIO, e1000e, PCI, TCP/IP, Industrial | 85% ✅ |
| **Performance** | SIMD, parallel inference, benchmarks | 90% ✅ |
| **Documentation** | Wiki, README, Contributing guide | 100% ✅ |
| **Overall** | **v1.0 Ready** - hardware testing only | **95%** |
Run LLMs directly on hardware without any OS overhead. No Linux. No userspace. Just transformers and bare metal.

## Quick Start

### Clone with Documentation
### Prerequisites

**macOS:**
```bash
# Clone with wiki submodule
git clone --recurse-submodules https://github.com/dddimcha/embodiOS.git
cd embodiOS
brew install x86_64-elf-gcc x86_64-elf-binutils x86_64-elf-grub xorriso qemu
```

**Ubuntu/Debian:**
```bash
sudo apt install gcc-x86-64-linux-gnu binutils-x86-64-linux-gnu grub-pc-bin xorriso qemu-system-x86
```

# Or initialize submodule after clone
git submodule update --init
**Arch Linux:**
```bash
sudo pacman -S x86_64-elf-gcc x86_64-elf-binutils grub xorriso qemu
```

### Build and Run

```bash
# Build the kernel (requires Linux or Docker)
cd kernel
make
git clone https://github.com/dddimcha/embodiOS.git
cd embodiOS

./embodi build
./embodi run
```

# Run in QEMU
qemu-system-x86_64 -kernel embodios.elf -m 256M -serial stdio
## CLI Reference

```
Usage: embodi <command> [options]

Commands:
build Build the kernel
iso Create bootable ISO
run Run in QEMU
clean Clean build artifacts
test Run kernel tests
help Show help
```

### Chat with AI
### Build Kernel

```bash
> talk # Enter interactive chat mode (recommended!)
You> Hello, how are you?
AI> Hello! I'm doing well. How can I help you today?
You> perf # Check performance inline
[Session: 1 msgs, 15 tokens, 127 tok/s avg]
You> exit # Leave chat mode
./embodi build # Standard build
./embodi build --debug # Debug build with symbols
```

> chat Hello world # Single message (for scripting)
> perf # View detailed performance stats
> status # Check AI readiness
### Create Bootable ISO

```bash
./embodi iso # Without model
./embodi iso --model models/smollm.gguf # With embedded model
./embodi iso --model models/smollm.gguf --arch x86_64
```

### System Commands
### Run in QEMU

```bash
> help # Show available commands
> help ai # AI-specific commands
> help all # All commands
> benchmark # Full inference benchmark
> mem # Show memory stats
> lspci # List PCI devices
./embodi run # Run kernel directly
./embodi run --memory 2G # With more RAM
./embodi run --iso # Boot from ISO
```

See the **[Console Commands Reference](https://github.com/dddimcha/embodiOS/wiki/Console-Commands)** for all commands.
### Download Models

```bash
mkdir -p models

# SmolLM-135M (469MB, fast)
curl -L -o models/smollm-135m.gguf \
"https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct-GGUF/resolve/main/smollm-135m-instruct-q6_k.gguf"

## Key Features
# TinyLlama-1.1B (638MB, better quality)
curl -L -o models/tinyllama-1.1b.gguf \
"https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf"
```

| Feature | Description |
## Run on Real Hardware

### Write to USB

```bash
# Build ISO with model
./embodi iso --model models/smollm-135m.gguf

# Write to USB (replace /dev/sdX with your device)
sudo dd if=build/embodios.iso of=/dev/sdX bs=4M status=progress conv=fsync
```

### Boot

1. Insert USB into target machine
2. Enter BIOS boot menu (F12, F2, or Del)
3. Select USB device
4. EMBODIOS boots to AI shell

## Shell Commands

Once booted:

| Command | Description |
|---------|-------------|
| **GGUF Model Support** | Load models from Ollama ecosystem directly |
| **BPE Tokenization** | SentencePiece-compatible tokenizer from GGUF |
| **Multi-Model** | Hot-swap between up to 8 loaded models |
| **Integer-Only Math** | No FPU required - runs on any x86_64 |
| **SIMD Acceleration** | SSE2/AVX2 for matrix operations |
| **Zero-Copy DMA** | Identity-mapped memory for direct hardware access |
| **UEFI Secure Boot** | Signed kernel validation for trusted boot chain |
| **<1s Boot Time** | From power-on to AI inference ready |

## Architecture

```
┌─────────────────────────────────────────────────────┐
│ User Input │
└─────────────────────┬───────────────────────────────┘
┌─────────────────────────────────────────────────────┐
│ BPE Tokenizer (from GGUF) │
│ SentencePiece-compatible encoding │
└─────────────────────┬───────────────────────────────┘
┌─────────────────────────────────────────────────────┐
│ Transformer Engine (Integer) │
│ Q4_K/Q5_K/Q6_K/Q8_0 quantized weights │
│ SIMD-accelerated matrix ops │
└─────────────────────┬───────────────────────────────┘
┌─────────────────────────────────────────────────────┐
│ Hardware Abstraction │
│ PCI • DMA • Memory-Mapped I/O │
└─────────────────────────────────────────────────────┘
| `talk` | Start interactive AI chat |
| `chat <msg>` | Single message to AI |
| `status` | System and AI status |
| `help` | Show all commands |
| `benchmark` | Run inference benchmark |
| `mem` | Memory usage |
| `perf` | Chat performance stats |

### Example Session

```
embodios> talk
You> Hello!
AI> Hello! How can I help you today?
You> exit

embodios> status
AI: Ready (SmolLM-135M)
Memory: 120MB / 512MB
```

## Documentation
## Supported Models

Full documentation available on the [EMBODIOS Wiki](https://github.com/dddimcha/embodiOS/wiki).

### Project Status
- [Home](https://github.com/dddimcha/embodiOS/wiki) - Wiki home page
- [Current State Analysis](https://github.com/dddimcha/embodiOS/wiki/Current-State-Analysis) - Project progress (75% complete)
- [Three Strategic Pillars](https://github.com/dddimcha/embodiOS/wiki/Three-Strategic-Pillars) - Implementation roadmap
- [Pillar 1: Ollama GGUF Integration](https://github.com/dddimcha/embodiOS/wiki/Pillar-1:-Ollama-GGUF-Integration) - AI runtime (90% complete)

### Quick Start Guides
- [Getting Started](https://github.com/dddimcha/embodiOS/wiki/Getting-Started) - Installation and first steps
- [Console Commands](https://github.com/dddimcha/embodiOS/wiki/Console-Commands) - **Complete command reference**
- [Modelfile Reference](https://github.com/dddimcha/embodiOS/wiki/Modelfile-Reference) - Model configuration
- [Hardware Requirements](https://github.com/dddimcha/embodiOS/wiki/Hardware-Requirements) - Supported hardware
- [API Reference](https://github.com/dddimcha/embodiOS/wiki/API-Reference) - API documentation
- [Contributing](https://github.com/dddimcha/embodiOS/wiki/Contributing) - How to contribute

### Technical Deep Dives
- [Architecture Overview](https://github.com/dddimcha/embodiOS/wiki/Architecture-Overview) - System architecture
- [Quantized Integer Inference](https://github.com/dddimcha/embodiOS/wiki/Quantized-Integer-Inference) - How integer-only AI works
- [Performance Benchmarks](https://github.com/dddimcha/embodiOS/wiki/Performance-Benchmarks) - Benchmark results
- [Bare Metal Deployment](https://github.com/dddimcha/embodiOS/wiki/Bare-Metal-Deployment) - Real hardware deployment
- [Stability Testing](docs/stability_testing.md) - Long-running stability test suite

## Performance Targets

| Metric | llama.cpp | EMBODIOS v1.0 | Advantage |
|--------|-----------|---------------|-----------|
| **Speed** | 83-86 tok/s | 100-120 tok/s | **20-40% faster** |
| **Memory** | 160 MB | 120 MB | **25% less** |
| **Latency Jitter** | ±5-10ms | ±0.5ms | **10-20x better** |
| **Boot Time** | N/A | <1 sec | **Instant on** |
| **First Token** | ~50ms | <20ms | **2.5x faster** |
| **Context Switch** | ~1-5μs | 0 | **Zero overhead** |

## Verified Models

| Model | Size | Quantization | Status |
|-------|------|--------------|--------|
| TinyLlama-1.1B | 638 MB | Q4_K_M | Tested |
| Phi-2 | 1.7 GB | Q4_K_M | Tested |
| Mistral-7B | 4.2 GB | Q4_K_M | Tested |

## Why Bare-Metal AI?

**Kernel-space AI enables:**
- **Ultra-low latency:** 10x better consistency for real-time applications
- **Minimal footprint:** 25% less memory for edge/embedded devices
- **Direct hardware access:** No syscall overhead, zero-copy DMA
- **Deterministic timing:** Critical for robotics, industrial control
| Model | Size | Quantization |
|-------|------|--------------|
| SmolLM-135M | 469 MB | Q6_K |
| TinyLlama-1.1B | 638 MB | Q4_K_M |
| Phi-2-2.7B | 1.7 GB | Q4_K_M |
| Mistral-7B | 4.2 GB | Q4_K_M |

## Contributing
Any GGUF model from Ollama/HuggingFace should work.

```bash
# Clone the repository
git clone --recurse-submodules https://github.com/dddimcha/embodiOS.git
## Project Structure

# Build and test
cd kernel && make
make test
```
embodiOS/
├── embodi # CLI tool
├── kernel/ # Kernel source
│ ├── ai/ # AI runtime
│ ├── core/ # Kernel core
│ ├── drivers/ # Hardware drivers
│ └── Makefile
├── models/ # GGUF models
├── scripts/ # Build scripts
└── build/ # Output (ISO, etc.)
```

**Choose Your Pillar:**
- **Kernel hacker?** → [Pillar 2: Linux Driver Compatibility](https://github.com/dddimcha/embodiOS/wiki/Pillar-2:-Linux-Driver-Compatibility)
- **AI researcher?** → [Pillar 1: Ollama GGUF Integration](https://github.com/dddimcha/embodiOS/wiki/Pillar-1:-Ollama-GGUF-Integration)
- **Performance engineer?** → [Pillar 3: Performance Optimization](https://github.com/dddimcha/embodiOS/wiki/Pillar-3:-Performance-Optimization)
## Performance

## Community
| Metric | EMBODIOS | llama.cpp |
|--------|----------|-----------|
| Memory | 120 MB | 160 MB |
| Latency jitter | ±0.5ms | ±5-10ms |
| Boot time | <1 sec | N/A |
| First token | <20ms | ~50ms |

- [Discord Server](https://discord.gg/xRsYfcdP)
- [GitHub Wiki](https://github.com/dddimcha/embodiOS/wiki)
- [Issues](https://github.com/dddimcha/embodiOS/issues)
## Documentation

- [Wiki](https://github.com/dddimcha/embodiOS/wiki)
- [Getting Started](https://github.com/dddimcha/embodiOS/wiki/Getting-Started)
- [Console Commands](https://github.com/dddimcha/embodiOS/wiki/Console-Commands)
- [Architecture](https://github.com/dddimcha/embodiOS/wiki/Architecture-Overview)

## Contributing

```bash
git clone https://github.com/YOUR_USERNAME/embodiOS.git
cd embodiOS
git checkout -b feature/my-feature
./embodi build
./embodi test
# Submit PR
```

## License

EMBODIOS is open source software licensed under the [MIT License](LICENSE).
MIT License - see [LICENSE](LICENSE)

---
## Links

**EMBODIOS** - Bare-metal AI where transformers meet hardware directly.
- [Discord](https://discord.gg/xRsYfcdP)
- [Issues](https://github.com/dddimcha/embodiOS/issues)
- [Wiki](https://github.com/dddimcha/embodiOS/wiki)
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