# ODS: Local AI Infrastructure

ODS is a turnkey local AI stack designed to bring powerful AI capabilities to your own hardware. It provides a complete solution for running large language models, voice processing, and workflow automation entirely on your own infrastructure.

## Core Components

### llama-server - High Performance Inference
llama-server (from llama.cpp) serves as the backbone of ODS, providing OpenAI-compatible API endpoints for language model inference. It supports GGUF models including Qwen 3, Llama 3, and Mistral, automatically selecting the best model for your hardware tier.

### Open WebUI - Chat Interface
A beautiful, responsive chat interface that works with any OpenAI-compatible backend. Features include conversation history, model selection, and user management.

### Voice Processing
- **Whisper** for speech-to-text transcription with high accuracy
- **Piper** for natural-sounding text-to-speech synthesis
- Combined, these enable fully local voice assistants

### Workflow Automation
n8n integration provides visual workflow automation. Pre-built workflows include:
- Document Q&A (RAG pipeline)
- Voice transcription
- Code assistance
- Scheduled summarization

### Vector Database
Qdrant provides efficient vector storage and similarity search for RAG (Retrieval Augmented Generation) applications.

## Hardware Tiers

ODS automatically detects your GPU and configures appropriate models:

1. **Minimal** (<20GB VRAM): 7B quantized models
2. **Entry** (20-27GB VRAM): 14B AWQ models
3. **Prosumer** (28-47GB VRAM): 32B AWQ models
4. **Pro** (48GB+ VRAM): 70B+ models

## Installation

```bash
git clone https://github.com/Light-Heart-Labs/ODS.git
cd ODS/ods
./install.sh
```

The installer handles everything: Docker setup, GPU configuration, model selection, and service startup.

## Philosophy

ODS embodies the principle that AI should be accessible, private, and owned by users. Your data stays on your hardware. Your models run locally. Your AI, your rules.

Built by The Collective — making local AI practical for everyone.
