3de3c8cb36
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251 lines
7.2 KiB
Bash
251 lines
7.2 KiB
Bash
#!/bin/bash
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# Install Swoper with all required models for Node-2
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# CORRECTED VERSION: Using q4/q5 quantization for large models
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# Models optimized for 64GB RAM with single-active LLM scheduler
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set -e
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echo "🚀 Installing Swoper with models for microDAO Node-2 (q4/q5 optimized)"
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echo "=================================================="
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# Colors
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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RED='\033[0;31m'
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NC='\033[0m' # No Color
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# Check if Swoper service exists
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SWAPPER_DIR=""
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if [ -d "services/swapper" ]; then
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SWAPPER_DIR="services/swapper"
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elif [ -d "/opt/microdao-daarion/services/swapper" ]; then
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SWAPPER_DIR="/opt/microdao-daarion/services/swapper"
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else
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echo -e "${RED}❌ Swoper service not found. Please check the path.${NC}"
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exit 1
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fi
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echo -e "${GREEN}✅ Found Swoper at: ${SWAPPER_DIR}${NC}"
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# Models configuration for Node-2 with q4/q5 quantization
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# Format: ollama_model_name:size_gb:quantization:priority
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declare -A MODELS=(
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# Large models - q4/q5 required
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["deepseek-r1"]="deepseek-r1:q4:40:high"
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["qwen-code-72b"]="qwen2.5-coder-72b-instruct:q4:40:high"
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["deepseek-math-33b"]="deepseek-math:33b:q4:20:high"
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# Medium models - q4 recommended
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["gemma-30b"]="gemma2:27b-it:q4:18:medium"
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["mistral-22b"]="mistral-nemo:22b:q4:13:medium"
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["starcoder2-34b"]="starcoder2:34b:q4:20:medium"
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["gpt-oss-20b"]="gpt-oss:20b:q4:12:low"
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# Small models - q4 for consistency
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["mistral-13b"]="mistral:13b-instruct:q4:7.5:medium"
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["falcon-40b"]="falcon:40b-instruct:q4:24:low"
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# Vision models - upgraded to better quality
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["qwen-vl-32b"]="qwen2-vl:32b-instruct:q4:20:high"
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# Alternative: qwen2-vl:7b-instruct:q4:8 (smaller, faster)
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)
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# Create models directory
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MODELS_DIR="$HOME/node2/swoper/models"
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mkdir -p "$MODELS_DIR"
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echo -e "\n${GREEN}📦 Installing models via Ollama...${NC}"
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# Check if Ollama is running
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if ! curl -s http://localhost:11434/api/tags > /dev/null 2>&1; then
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echo -e "${YELLOW}⚠️ Ollama is not running. Starting Ollama...${NC}"
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brew services start ollama || {
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echo -e "${RED}❌ Failed to start Ollama${NC}"
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exit 1
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}
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sleep 5
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fi
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# Install models
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INSTALLED=0
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FAILED=0
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echo -e "\n${YELLOW}📋 Model Installation Plan:${NC}"
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echo -e " 🔴 Large models (q4 required): DeepSeek-R1, Qwen Code 72B, DeepSeek Math 33B"
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echo -e " 🟡 Medium models (q4 recommended): Gemma 30B, Mistral 22B, StarCoder2-34B, GPT-OSS-20B"
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echo -e " 🟢 Small models (q4): Mistral 13B, Falcon-40B"
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echo -e " 👁️ Vision (upgraded): Qwen2-VL-32B q4 (better quality than 7B)"
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echo ""
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for model_key in "${!MODELS[@]}"; do
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model_info="${MODELS[$model_key]}"
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model_name=$(echo "$model_info" | cut -d: -f1)
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quantization=$(echo "$model_info" | cut -d: -f2)
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size_gb=$(echo "$model_info" | cut -d: -f3)
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priority=$(echo "$model_info" | cut -d: -f4)
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# Construct Ollama model name with quantization
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if [ "$quantization" = "q4" ]; then
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ollama_model="${model_name}:q4"
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elif [ "$quantization" = "q5" ]; then
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ollama_model="${model_name}:q5"
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else
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ollama_model="$model_name"
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fi
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echo -e "\n${GREEN}📥 Installing: ${model_name} ${quantization} (${size_gb} GB) [${priority} priority]${NC}"
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if ollama pull "$ollama_model" 2>&1 | tee /tmp/ollama_install.log; then
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echo -e "${GREEN} ✅ ${model_name} ${quantization} installed${NC}"
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INSTALLED=$((INSTALLED + 1))
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else
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echo -e "${RED} ❌ Failed to install ${model_name} ${quantization}${NC}"
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echo -e "${YELLOW} 💡 Trying without quantization suffix...${NC}"
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# Try without quantization suffix (Ollama might handle it automatically)
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if ollama pull "$model_name" 2>&1; then
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echo -e "${GREEN} ✅ ${model_name} installed (without explicit quantization)${NC}"
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INSTALLED=$((INSTALLED + 1))
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else
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FAILED=$((FAILED + 1))
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fi
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fi
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done
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echo -e "\n${GREEN}=================================================="
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echo "📊 Installation Summary"
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echo "==================================================${NC}"
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echo -e " ✅ Installed: ${INSTALLED} models"
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echo -e " ❌ Failed: ${FAILED} models"
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echo ""
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# Create Swoper configuration for Node-2
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echo -e "${GREEN}📝 Creating Swoper configuration for Node-2...${NC}"
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cat > "$HOME/node2/swoper/config_node2.yaml" << 'EOF'
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# Swoper Configuration for microDAO Node-2
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# Single-active LLM scheduler with q4/q5 optimized models
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swoper:
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mode: single-active
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max_concurrent_models: 1
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model_swap_timeout: 30
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gpu_enabled: true
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metal_acceleration: true # Apple Silicon Metal
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quantization: q4 # Default quantization for large models
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models:
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# Large models - q4 required
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deepseek-r1:
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path: ollama:deepseek-r1:q4
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type: llm
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size_gb: 40
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priority: high
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quantization: q4
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qwen-code-72b:
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path: ollama:qwen2.5-coder-72b-instruct:q4
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type: code
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size_gb: 40
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priority: high
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quantization: q4
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deepseek-math-33b:
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path: ollama:deepseek-math:33b:q4
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type: math
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size_gb: 20
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priority: high
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quantization: q4
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# Medium models - q4 recommended
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gemma-30b:
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path: ollama:gemma2:27b-it:q4
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type: llm
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size_gb: 18
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priority: medium
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quantization: q4
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mistral-22b:
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path: ollama:mistral-nemo:22b:q4
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type: llm
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size_gb: 13
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priority: medium
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quantization: q4
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starcoder2-34b:
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path: ollama:starcoder2:34b:q4
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type: code
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size_gb: 20
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priority: medium
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quantization: q4
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gpt-oss-20b:
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path: ollama:gpt-oss:20b:q4
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type: llm
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size_gb: 12
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priority: low
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quantization: q4
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# Small models - q4 for consistency
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mistral-13b:
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path: ollama:mistral:13b-instruct:q4
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type: llm
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size_gb: 7.5
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priority: medium
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quantization: q4
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falcon-40b:
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path: ollama:falcon:40b-instruct:q4
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type: llm
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size_gb: 24
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priority: low
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quantization: q4
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# Vision models - upgraded to better quality
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qwen-vl-32b:
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path: ollama:qwen2-vl:32b-instruct:q4
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type: vision
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size_gb: 20
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priority: high
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quantization: q4
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# Alternative: qwen2-vl:7b-instruct:q4 (8 GB, faster but lower quality)
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storage:
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models_dir: ~/node2/swoper/models
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cache_dir: ~/node2/swoper/cache
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swap_dir: ~/node2/swoper/swap
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ollama:
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url: http://localhost:11434
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timeout: 300
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EOF
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echo -e "${GREEN}✅ Configuration saved to: $HOME/node2/swoper/config_node2.yaml${NC}"
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# Calculate total size
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TOTAL_SIZE=$(python3 << 'PYEOF'
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models = [40, 40, 20, 18, 13, 20, 12, 7.5, 24, 20] # All q4 sizes
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total = sum(models)
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print(f"{total}")
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PYEOF
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)
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echo -e "\n${GREEN}📊 Total models size (q4): ~${TOTAL_SIZE} GB${NC}"
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echo -e "${GREEN} Available disk: 1.5 TB${NC}"
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echo -e "${GREEN} ✅ Models will fit comfortably${NC}"
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echo -e "\n${GREEN}=================================================="
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echo "✅ Swoper Installation Complete"
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echo "==================================================${NC}"
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echo ""
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echo "📁 Configuration: $HOME/node2/swoper/config_node2.yaml"
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echo "📦 Models directory: $HOME/node2/swoper/models"
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echo ""
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echo "⏭️ Next steps:"
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echo " 1. Review config_node2.yaml"
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echo " 2. Test Swoper with: curl http://localhost:8890/health"
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echo " 3. Update router-config.yml with Node-2 Swoper provider"
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echo ""
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