light-heart-labs--ods
52 行
2.0 KiB
Plaintext
52 行
2.0 KiB
Plaintext
# ODS: Local AI Infrastructure
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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.
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## Core Components
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### llama-server - High Performance Inference
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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.
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### Open WebUI - Chat Interface
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A beautiful, responsive chat interface that works with any OpenAI-compatible backend. Features include conversation history, model selection, and user management.
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### Voice Processing
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- **Whisper** for speech-to-text transcription with high accuracy
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- **Piper** for natural-sounding text-to-speech synthesis
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- Combined, these enable fully local voice assistants
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### Workflow Automation
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n8n integration provides visual workflow automation. Pre-built workflows include:
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- Document Q&A (RAG pipeline)
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- Voice transcription
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- Code assistance
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- Scheduled summarization
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### Vector Database
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Qdrant provides efficient vector storage and similarity search for RAG (Retrieval Augmented Generation) applications.
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## Hardware Tiers
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ODS automatically detects your GPU and configures appropriate models:
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1. **Minimal** (<20GB VRAM): 7B quantized models
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2. **Entry** (20-27GB VRAM): 14B AWQ models
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3. **Prosumer** (28-47GB VRAM): 32B AWQ models
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4. **Pro** (48GB+ VRAM): 70B+ models
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## Installation
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```bash
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git clone https://github.com/Light-Heart-Labs/ODS.git
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cd ODS/ods
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./install.sh
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```
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The installer handles everything: Docker setup, GPU configuration, model selection, and service startup.
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## Philosophy
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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.
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Built by The Collective — making local AI practical for everyone.
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