3de3c8cb36
- matrix-gateway: POST /internal/matrix/presence/online endpoint - usePresenceHeartbeat hook with activity tracking - Auto away after 5 min inactivity - Offline on page close/visibility change - Integrated in MatrixChatRoom component
316 lines
10 KiB
Bash
Executable File
316 lines
10 KiB
Bash
Executable File
#!/bin/bash
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# Install Swoper with optimized models for Node-2
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# CORRECTED: Only quantize models that don't fit (>60 GB)
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# Smaller models can use full precision or q4 for speed
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set -e
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echo "🚀 Installing Swoper with optimized models for microDAO Node-2"
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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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BLUE='\033[0;34m'
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NC='\033[0m' # No Color
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# Check if Swoper service exists (optional - models can be installed via Ollama)
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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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echo -e "${GREEN}✅ Found Swoper at: ${SWAPPER_DIR}${NC}"
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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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echo -e "${GREEN}✅ Found Swoper at: ${SWAPPER_DIR}${NC}"
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else
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echo -e "${YELLOW}⚠️ Swoper service not found in project.${NC}"
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echo -e "${YELLOW} Models will be installed via Ollama.${NC}"
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echo -e "${YELLOW} Swoper configuration will be created for future use.${NC}"
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fi
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# Models configuration - OPTIMIZED
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# Format: model_key:ollama_name:quantization:size_gb:priority:reason
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declare -A MODELS=(
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# 🔴 OBLIGATORY q4/q5 (>60 GB, don't fit)
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["deepseek-r1"]="deepseek-r1:q4:40:high:OBLIGATORY_67GB_full"
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["qwen-code-72b"]="qwen2.5-coder-72b-instruct:q4:40:high:OBLIGATORY_144GB_full"
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["deepseek-math-33b"]="deepseek-math:33b:q4:20:high:OBLIGATORY_66GB_full"
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["starcoder2-34b"]="starcoder2:34b:q4:20:medium:OBLIGATORY_68GB_full"
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["qwen-vl-32b"]="qwen2-vl:32b-instruct:q4:20:high:OBLIGATORY_64GB_full_better_quality"
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# 🟡 RECOMMENDED q4 (40-60 GB, fits but q4 better for performance)
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["gemma-30b"]="gemma2:27b-it:q4:18:medium:RECOMMENDED_60GB_full"
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["mistral-22b"]="mistral-nemo:22b:q4:13:medium:RECOMMENDED_44GB_full"
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# 🟢 OPTIONAL q4 or full (<40 GB, can use full)
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["mistral-13b"]="mistral:13b-instruct:full:26:medium:OPTIONAL_can_use_full"
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["gpt-oss-20b"]="gpt-oss:20b:full:40:low:OPTIONAL_can_use_full"
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["qwen-vl-7b"]="qwen2-vl:7b-instruct:full:8:high:OPTIONAL_can_use_full"
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# Already quantized
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["falcon-40b"]="falcon:40b-instruct:q4:24:low:ALREADY_Q4"
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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${BLUE}📋 Model Installation Strategy:${NC}"
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echo -e "${RED} 🔴 OBLIGATORY q4/q5 (>60 GB):${NC} DeepSeek-R1, Qwen Code 72B, DeepSeek Math 33B, StarCoder2-34B, Qwen2-VL-32B"
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echo -e "${YELLOW} 🟡 RECOMMENDED q4 (40-60 GB):${NC} Gemma 30B, Mistral 22B"
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echo -e "${GREEN} 🟢 OPTIONAL full/q4 (<40 GB):${NC} Mistral 13B, GPT-OSS-20B, Qwen-VL-7B"
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echo ""
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for model_key in "${!MODELS[@]}"; do
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model_info="${MODELS[$model_key]}"
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IFS=':' read -r ollama_name quantization size_gb priority reason <<< "$model_info"
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# Construct Ollama model name
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# Note: Ollama quantization is usually automatic or specified differently
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# For now, try the model name as-is first
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if [ "$quantization" = "q4" ]; then
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# Try with :q4 suffix first, then without
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ollama_model_q4="${ollama_name}:q4"
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ollama_model="$ollama_name"
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quant_label="q4"
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elif [ "$quantization" = "q5" ]; then
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ollama_model_q5="${ollama_name}:q5"
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ollama_model="$ollama_name"
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quant_label="q5"
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else
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ollama_model="$ollama_name"
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quant_label="full"
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fi
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# Color based on priority
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if [[ "$reason" == OBLIGATORY* ]]; then
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color=$RED
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icon="🔴"
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elif [[ "$reason" == RECOMMENDED* ]]; then
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color=$YELLOW
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icon="🟡"
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else
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color=$GREEN
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icon="🟢"
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fi
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echo -e "\n${color}${icon} Installing: ${ollama_name} ${quant_label} (${size_gb} GB) [${priority} priority]${NC}"
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echo -e "${color} Reason: ${reason}${NC}"
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# Try to pull model
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if [ "$quantization" = "q4" ] && [ -n "$ollama_model_q4" ]; then
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# Try q4 version first
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if ollama pull "$ollama_model_q4" 2>&1 | tee /tmp/ollama_install.log; then
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echo -e "${GREEN} ✅ ${ollama_name} ${quant_label} installed${NC}"
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INSTALLED=$((INSTALLED + 1))
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continue
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fi
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fi
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# Try standard model name (Ollama may handle quantization automatically)
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if ollama pull "$ollama_model" 2>&1 | tee /tmp/ollama_install.log; then
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echo -e "${GREEN} ✅ ${ollama_name} ${quant_label} installed${NC}"
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INSTALLED=$((INSTALLED + 1))
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else
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echo -e "${YELLOW} ⚠️ Model not found, checking available models...${NC}"
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# Check if model exists in different format
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if ollama list 2>/dev/null | grep -qi "$ollama_name"; then
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echo -e "${GREEN} ✅ ${ollama_name} already installed${NC}"
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INSTALLED=$((INSTALLED + 1))
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else
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echo -e "${RED} ❌ Failed to install ${ollama_name}${NC}"
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echo -e "${YELLOW} 💡 Model may not be available in Ollama. Check: ollama list${NC}"
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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 optimized quantization
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# Only large models (>60 GB) use q4/q5, smaller can use full precision
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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_strategy: smart # Only quantize when needed
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models:
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# 🔴 OBLIGATORY q4/q5 (>60 GB, don't fit in 64 GB RAM)
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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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reason: "67 GB full doesn't fit, q4 (40 GB) fits in 64 GB RAM"
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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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reason: "144 GB full doesn't fit, q4 (40 GB) required"
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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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reason: "66 GB full doesn't fit, q4 (20 GB) required"
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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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reason: "68 GB full doesn't fit, q4 (20 GB) required"
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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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reason: "64 GB full doesn't fit, q4 (20 GB) for better quality than 7B"
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# 🟡 RECOMMENDED q4 (40-60 GB, fits but q4 better for performance)
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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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reason: "60 GB full fits but q4 (18 GB) better performance"
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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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reason: "44 GB full fits but q4 (13 GB) better performance"
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# 🟢 OPTIONAL full/q4 (<40 GB, can use full precision)
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mistral-13b:
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path: ollama:mistral:13b-instruct
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type: llm
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size_gb: 26
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priority: medium
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quantization: full
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reason: "26 GB fits, can use full precision or q4 for speed"
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gpt-oss-20b:
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path: ollama:gpt-oss:20b
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type: llm
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size_gb: 40
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priority: low
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quantization: full
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reason: "40 GB fits, can use full precision"
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qwen-vl-7b:
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path: ollama:qwen2-vl:7b-instruct
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type: vision
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size_gb: 8
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priority: high
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quantization: full
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reason: "8 GB fits, can use full precision (fast vision model)"
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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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reason: "Already quantized"
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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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# GPU/VRAM info
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hardware:
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ram_gb: 64
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gpu: "M4 Max 40-core"
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vram: "Shared with RAM (up to 64 GB)"
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metal_acceleration: true
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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=$(python3 << 'PYEOF'
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# Only count models that will be installed
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obligatory = [40, 40, 20, 20, 20] # q4 models that are required
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recommended = [18, 13] # q4 models recommended
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optional_full = [26, 40, 8] # full models
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optional_q4 = [24] # already q4
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total = sum(obligatory) + sum(recommended) + sum(optional_full) + sum(optional_q4)
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print(f"{total}")
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PYEOF
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)
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echo -e "\n${GREEN}📊 Total models size: ~${TOTAL_SIZE} GB${NC}"
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echo -e "${GREEN} Available disk: 1.5 TB${NC}"
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echo -e "${GREEN} Available RAM: 64 GB${NC}"
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echo -e "${GREEN} ✅ Models will fit comfortably${NC}"
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echo -e "\n${BLUE}💡 DeepSeek-R1 q4 (40 GB) Analysis:${NC}"
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echo -e " - 64 GB RAM достатньо для 40 GB моделі ✅"
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echo -e " - M4 Max Metal acceleration підтримується ✅"
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echo -e " - Може працювати, але займе більшу частину RAM"
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echo -e " - Рекомендація: q4 для DeepSeek-R1 (40 GB < 64 GB) ✅"
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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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