BobAi
a96ddba3c9
Complete rebrand to eliminate any Claude/Anthropic references: Directory Changes: - claude_rag/ → mini_rag/ (preserving git history) Content Changes: - Replaced 930+ Claude references across 40+ files - Updated all imports: from claude_rag → from mini_rag - Updated all file paths: .claude-rag → .mini-rag - Updated documentation and comments - Updated configuration files and examples Testing Changes: - All tests updated to use mini_rag imports - Integration tests verify new module structure This ensures complete independence from Claude/Anthropic branding while maintaining all functionality and git history.
62 lines
1.9 KiB
Markdown
62 lines
1.9 KiB
Markdown
# RAG System - Hybrid Mode Setup
|
|
|
|
This RAG system can operate in three modes:
|
|
|
|
## 🚀 **Mode 1: Ollama Only (Recommended - Lightweight)**
|
|
```bash
|
|
pip install -r requirements-light.txt
|
|
# Requires: ollama serve running with nomic-embed-text model
|
|
```
|
|
- **Size**: ~426MB total
|
|
- **Performance**: Fastest (leverages Ollama)
|
|
- **Network**: Uses local Ollama server
|
|
|
|
## 🔄 **Mode 2: Hybrid (Best of Both Worlds)**
|
|
```bash
|
|
pip install -r requirements-full.txt
|
|
# Works with OR without Ollama
|
|
```
|
|
- **Size**: ~3GB total (includes ML fallback)
|
|
- **Resilience**: Automatic fallback if Ollama unavailable
|
|
- **Performance**: Ollama speed when available, ML fallback when needed
|
|
|
|
## 🛡️ **Mode 3: ML Only (Maximum Compatibility)**
|
|
```bash
|
|
pip install -r requirements-full.txt
|
|
# Disable Ollama fallback in config
|
|
```
|
|
- **Size**: ~3GB total
|
|
- **Compatibility**: Works anywhere, no external dependencies
|
|
- **Use case**: Offline environments, embedded systems
|
|
|
|
## 🔧 **Configuration**
|
|
|
|
Edit `.mini-rag/config.json` in your project:
|
|
```json
|
|
{
|
|
"embedding": {
|
|
"provider": "hybrid", // "hybrid", "ollama", "fallback"
|
|
"model": "nomic-embed-text:latest",
|
|
"base_url": "http://localhost:11434",
|
|
"enable_fallback": true // Set to false to disable ML fallback
|
|
}
|
|
}
|
|
```
|
|
|
|
## 📊 **Status Check**
|
|
```python
|
|
from mini_rag.ollama_embeddings import OllamaEmbedder
|
|
|
|
embedder = OllamaEmbedder()
|
|
status = embedder.get_status()
|
|
print(f"Mode: {status['mode']}")
|
|
print(f"Ollama: {'✅' if status['ollama_available'] else '❌'}")
|
|
print(f"ML Fallback: {'✅' if status['fallback_available'] else '❌'}")
|
|
```
|
|
|
|
## 🎯 **Automatic Behavior**
|
|
1. **Try Ollama first** - fastest and most efficient
|
|
2. **Fall back to ML** - if Ollama unavailable and ML dependencies installed
|
|
3. **Use hash fallback** - deterministic embeddings as last resort
|
|
|
|
The system automatically detects what's available and uses the best option! |