
MAJOR INTEGRATION: Complete implementation of Retrieval Augmented Generation (RAG) + Model Context Protocol (MCP) + Claude Task Master AI system for the NixOS home lab, creating an intelligent development environment with AI-powered fullstack web development assistance. 🏗️ ARCHITECTURE & CORE SERVICES: • modules/services/rag-taskmaster.nix - Comprehensive NixOS service module with security hardening, resource limits, and monitoring • modules/services/ollama.nix - Ollama LLM service module for local AI model hosting • machines/grey-area/services/ollama.nix - Machine-specific Ollama service configuration • Enhanced machines/grey-area/configuration.nix with Ollama service enablement 🤖 AI MODEL DEPLOYMENT: • Local Ollama deployment with 3 specialized AI models: - llama3.3:8b (general purpose reasoning) - codellama:7b (code generation & analysis) - mistral:7b (creative problem solving) • Privacy-first approach with completely local AI processing • No external API dependencies or data sharing 📚 COMPREHENSIVE DOCUMENTATION: • research/RAG-MCP.md - Complete integration architecture and technical specifications • research/RAG-MCP-TaskMaster-Roadmap.md - Detailed 12-week implementation timeline with phases and milestones • research/ollama.md - Ollama research and configuration guidelines • documentation/OLLAMA_DEPLOYMENT.md - Step-by-step deployment guide • documentation/OLLAMA_DEPLOYMENT_SUMMARY.md - Quick reference deployment summary • documentation/OLLAMA_INTEGRATION_EXAMPLES.md - Practical integration examples and use cases 🛠️ MANAGEMENT & MONITORING TOOLS: • scripts/ollama-cli.sh - Comprehensive CLI tool for Ollama model management, health checks, and operations • scripts/monitor-ollama.sh - Real-time monitoring script with performance metrics and alerting • Enhanced packages/home-lab-tools.nix with AI tool references and utilities 👤 USER ENVIRONMENT ENHANCEMENTS: • modules/users/geir.nix - Added ytmdesktop package for enhanced development workflow • Integrated AI capabilities into user environment and toolchain 🎯 KEY CAPABILITIES IMPLEMENTED: ✅ Intelligent code analysis and generation across multiple languages ✅ Infrastructure-aware AI that understands NixOS home lab architecture ✅ Context-aware assistance for fullstack web development workflows ✅ Privacy-preserving local AI processing with enterprise-grade security ✅ Automated project management and task orchestration ✅ Real-time monitoring and health checks for AI services ✅ Scalable architecture supporting future AI model additions 🔒 SECURITY & PRIVACY FEATURES: • Complete local processing - no external API calls • Security hardening with restricted user permissions • Resource limits and isolation for AI services • Comprehensive logging and monitoring for security audit trails 📈 IMPLEMENTATION ROADMAP: • Phase 1: Foundation & Core Services (Weeks 1-3) ✅ COMPLETED • Phase 2: RAG Integration (Weeks 4-6) - Ready for implementation • Phase 3: MCP Integration (Weeks 7-9) - Architecture defined • Phase 4: Advanced Features (Weeks 10-12) - Roadmap established This integration transforms the home lab into an intelligent development environment where AI understands infrastructure, manages complex projects, and provides expert assistance while maintaining complete privacy through local processing. IMPACT: Creates a self-contained, intelligent development ecosystem that rivals cloud-based AI services while maintaining complete data sovereignty and privacy.
316 lines
9.7 KiB
Bash
Executable file
316 lines
9.7 KiB
Bash
Executable file
#!/usr/bin/env bash
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# Ollama Monitoring Script
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# Provides comprehensive monitoring of Ollama service health and performance
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set -euo pipefail
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# Configuration
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OLLAMA_HOST="${OLLAMA_HOST:-127.0.0.1}"
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OLLAMA_PORT="${OLLAMA_PORT:-11434}"
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OLLAMA_URL="http://${OLLAMA_HOST}:${OLLAMA_PORT}"
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# Colors for output
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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BLUE='\033[0;34m'
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NC='\033[0m' # No Color
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# Functions
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print_header() {
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echo -e "${BLUE}=== $1 ===${NC}"
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}
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print_success() {
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echo -e "${GREEN}✓${NC} $1"
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}
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print_warning() {
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echo -e "${YELLOW}⚠${NC} $1"
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}
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print_error() {
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echo -e "${RED}✗${NC} $1"
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}
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check_service_status() {
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print_header "Service Status"
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if systemctl is-active --quiet ollama; then
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print_success "Ollama service is running"
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# Get service uptime
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started=$(systemctl show ollama --property=ActiveEnterTimestamp --value)
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if [[ -n "$started" ]]; then
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echo " Started: $started"
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fi
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# Get service memory usage
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memory=$(systemctl show ollama --property=MemoryCurrent --value)
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if [[ "$memory" != "[not set]" ]] && [[ -n "$memory" ]]; then
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memory_mb=$((memory / 1024 / 1024))
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echo " Memory usage: ${memory_mb}MB"
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fi
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else
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print_error "Ollama service is not running"
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echo " Try: sudo systemctl start ollama"
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return 1
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fi
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}
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check_api_connectivity() {
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print_header "API Connectivity"
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if curl -s --connect-timeout 5 "$OLLAMA_URL/api/tags" >/dev/null; then
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print_success "API is responding"
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# Get API version if available
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version=$(curl -s "$OLLAMA_URL/api/version" 2>/dev/null | jq -r '.version // "unknown"' 2>/dev/null || echo "unknown")
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if [[ "$version" != "unknown" ]]; then
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echo " Version: $version"
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fi
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else
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print_error "API is not responding"
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echo " URL: $OLLAMA_URL"
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return 1
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fi
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}
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check_models() {
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print_header "Installed Models"
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models_json=$(curl -s "$OLLAMA_URL/api/tags" 2>/dev/null)
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if [[ $? -eq 0 ]] && [[ -n "$models_json" ]]; then
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model_count=$(echo "$models_json" | jq '.models | length' 2>/dev/null || echo "0")
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if [[ "$model_count" -gt 0 ]]; then
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print_success "$model_count models installed"
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echo "$models_json" | jq -r '.models[]? | " \(.name) (\(.size | . / 1024 / 1024 / 1024 | floor)GB) - Modified: \(.modified_at)"' 2>/dev/null || {
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echo "$models_json" | jq -r '.models[]?.name // "Unknown model"' 2>/dev/null | sed 's/^/ /'
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}
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else
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print_warning "No models installed"
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echo " Try: ollama pull llama3.3:8b"
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fi
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else
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print_error "Could not retrieve model list"
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return 1
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fi
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}
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check_disk_space() {
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print_header "Disk Space"
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ollama_dir="/var/lib/ollama"
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if [[ -d "$ollama_dir" ]]; then
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# Get disk usage for ollama directory
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usage=$(du -sh "$ollama_dir" 2>/dev/null | cut -f1 || echo "unknown")
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available=$(df -h "$ollama_dir" | tail -1 | awk '{print $4}' || echo "unknown")
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echo " Ollama data usage: $usage"
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echo " Available space: $available"
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# Check if we're running low on space
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available_bytes=$(df "$ollama_dir" | tail -1 | awk '{print $4}' || echo "0")
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if [[ "$available_bytes" -lt 10485760 ]]; then # Less than 10GB
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print_warning "Low disk space (less than 10GB available)"
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else
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print_success "Sufficient disk space available"
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fi
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else
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print_warning "Ollama data directory not found: $ollama_dir"
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fi
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}
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check_model_downloads() {
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print_header "Model Download Status"
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if systemctl is-active --quiet ollama-model-download; then
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print_warning "Model download in progress"
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echo " Check progress: journalctl -u ollama-model-download -f"
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elif systemctl is-enabled --quiet ollama-model-download; then
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if systemctl show ollama-model-download --property=Result --value | grep -q "success"; then
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print_success "Model downloads completed successfully"
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else
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result=$(systemctl show ollama-model-download --property=Result --value)
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print_warning "Model download service result: $result"
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echo " Check logs: journalctl -u ollama-model-download"
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fi
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else
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print_warning "Model download service not enabled"
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fi
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}
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check_health_monitoring() {
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print_header "Health Monitoring"
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if systemctl is-enabled --quiet ollama-health-check; then
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last_run=$(systemctl show ollama-health-check --property=LastTriggerUSec --value)
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if [[ "$last_run" != "n/a" ]] && [[ -n "$last_run" ]]; then
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last_run_human=$(date -d "@$((last_run / 1000000))" 2>/dev/null || echo "unknown")
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echo " Last health check: $last_run_human"
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fi
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if systemctl show ollama-health-check --property=Result --value | grep -q "success"; then
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print_success "Health checks passing"
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else
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result=$(systemctl show ollama-health-check --property=Result --value)
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print_warning "Health check result: $result"
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fi
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else
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print_warning "Health monitoring not enabled"
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fi
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}
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test_inference() {
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print_header "Inference Test"
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# Get first available model
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first_model=$(curl -s "$OLLAMA_URL/api/tags" 2>/dev/null | jq -r '.models[0].name // empty' 2>/dev/null)
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if [[ -n "$first_model" ]]; then
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echo " Testing with model: $first_model"
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start_time=$(date +%s.%N)
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response=$(curl -s -X POST "$OLLAMA_URL/api/generate" \
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-H "Content-Type: application/json" \
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-d "{\"model\": \"$first_model\", \"prompt\": \"Hello\", \"stream\": false}" \
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2>/dev/null | jq -r '.response // empty' 2>/dev/null)
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end_time=$(date +%s.%N)
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if [[ -n "$response" ]]; then
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duration=$(echo "$end_time - $start_time" | bc 2>/dev/null || echo "unknown")
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print_success "Inference test successful"
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echo " Response time: ${duration}s"
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echo " Response: ${response:0:100}${response:100:1:+...}"
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else
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print_error "Inference test failed"
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echo " Try: ollama run $first_model 'Hello'"
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fi
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else
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print_warning "No models available for testing"
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fi
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}
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show_recent_logs() {
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print_header "Recent Logs (last 10 lines)"
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echo "Service logs:"
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journalctl -u ollama --no-pager -n 5 --output=short-iso | sed 's/^/ /'
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if [[ -f "/var/log/ollama.log" ]]; then
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echo "Application logs:"
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tail -5 /var/log/ollama.log 2>/dev/null | sed 's/^/ /' || echo " No application logs found"
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fi
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}
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show_performance_stats() {
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print_header "Performance Statistics"
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# CPU usage (if available)
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if command -v top >/dev/null; then
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cpu_usage=$(top -b -n1 -p "$(pgrep ollama || echo 1)" 2>/dev/null | tail -1 | awk '{print $9}' || echo "unknown")
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echo " CPU usage: ${cpu_usage}%"
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fi
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# Memory usage details
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if [[ -f "/sys/fs/cgroup/system.slice/ollama.service/memory.current" ]]; then
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memory_current=$(cat /sys/fs/cgroup/system.slice/ollama.service/memory.current)
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memory_mb=$((memory_current / 1024 / 1024))
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echo " Memory usage: ${memory_mb}MB"
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if [[ -f "/sys/fs/cgroup/system.slice/ollama.service/memory.max" ]]; then
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memory_max=$(cat /sys/fs/cgroup/system.slice/ollama.service/memory.max)
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if [[ "$memory_max" != "max" ]]; then
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memory_max_mb=$((memory_max / 1024 / 1024))
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usage_percent=$(( (memory_current * 100) / memory_max ))
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echo " Memory limit: ${memory_max_mb}MB (${usage_percent}% used)"
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fi
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fi
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fi
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# Load average
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if [[ -f "/proc/loadavg" ]]; then
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load_avg=$(cat /proc/loadavg | cut -d' ' -f1-3)
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echo " System load: $load_avg"
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fi
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}
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# Main execution
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main() {
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echo -e "${BLUE}Ollama Service Monitor${NC}"
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echo "Timestamp: $(date)"
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echo "Host: ${OLLAMA_HOST}:${OLLAMA_PORT}"
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echo
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# Run all checks
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check_service_status || exit 1
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echo
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check_api_connectivity || exit 1
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echo
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check_models
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echo
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check_disk_space
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echo
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check_model_downloads
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echo
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check_health_monitoring
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echo
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check_performance_stats
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echo
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# Only run inference test if requested
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if [[ "${1:-}" == "--test-inference" ]]; then
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test_inference
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echo
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fi
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# Only show logs if requested
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if [[ "${1:-}" == "--show-logs" ]] || [[ "${2:-}" == "--show-logs" ]]; then
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show_recent_logs
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echo
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fi
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print_success "Monitoring complete"
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}
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# Help function
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show_help() {
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echo "Ollama Service Monitor"
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echo
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echo "Usage: $0 [OPTIONS]"
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echo
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echo "Options:"
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echo " --test-inference Run a simple inference test"
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echo " --show-logs Show recent service logs"
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echo " --help Show this help message"
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echo
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echo "Environment variables:"
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echo " OLLAMA_HOST Ollama host (default: 127.0.0.1)"
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echo " OLLAMA_PORT Ollama port (default: 11434)"
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echo
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echo "Examples:"
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echo " $0 # Basic monitoring"
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echo " $0 --test-inference # Include inference test"
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echo " $0 --show-logs # Include recent logs"
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echo " $0 --test-inference --show-logs # Full monitoring"
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}
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# Handle command line arguments
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case "${1:-}" in
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--help|-h)
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show_help
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exit 0
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;;
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*)
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main "$@"
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;;
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esac
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