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feat(docs): 新增 Windows 使用指南,包含服務啟動、系統需求及故障排除說明
feat(scripts): 新增實時監控腳本以追蹤自然語言處理流程 feat(bat): 新增啟動及停止服務的批處理腳本,簡化服務管理
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README-WINDOWS.txt

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═══════════════════════════════════════════════════════════════════
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O-RAN Intent MANO for Network Slicing - Windows 使用指南
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═══════════════════════════════════════════════════════════════════
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🚀 快速開始
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═══════════════════════════════════════════════════════════════════
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1. 雙擊運行 "start-oran.bat" 啟動所有服務
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2. 瀏覽器會自動打開到 http://localhost:8000/index.html
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3. 在前端界面輸入自然語言,例如:
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• "Deploy high-bandwidth video streaming for 100 users"
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• "Create low-latency slice for autonomous vehicles"
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• "Setup IoT network for smart city"
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4. 使用完畢後,雙擊 "stop-oran.bat" 停止所有服務
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📁 文件說明
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═══════════════════════════════════════════════════════════════════
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start-oran.bat - 一鍵啟動所有服務
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stop-oran.bat - 一鍵停止所有服務
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README-WINDOWS.txt - 本文件(使用指南)
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logs/ - 日誌文件夾
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├── nlp.log - NLP 服務日誌
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├── orchestrator.log - Orchestrator 日誌
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├── websocket.log - WebSocket 日誌
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└── webui.log - Web UI 日誌
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scripts/
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└── watch-flow.sh - 流程監控腳本(需要 Git Bash)
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📋 系統需求
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═══════════════════════════════════════════════════════════════════
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必需:
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✓ Python 3.11 或更高版本
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✓ Go 1.24 或更高版本(用於 Orchestrator)
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✓ Windows 10/11
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可選:
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○ kubectl(用於 Kubernetes 管理)
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○ Git Bash(用於運行監控腳本)
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🌐 服務端點
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═══════════════════════════════════════════════════════════════════
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NLP Service: http://localhost:8082
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└─ API 文檔: http://localhost:8082/docs
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Orchestrator: http://localhost:8080
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└─ Health: http://localhost:8080/health
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WebSocket: ws://localhost:8081/ws
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Web UI (主界面): http://localhost:8000/index.html
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Web UI (監控): http://localhost:8000/monitor.html
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📊 觀察處理流程
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═══════════════════════════════════════════════════════════════════
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方法 1: 前端界面(推薦)
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- 左側聊天區顯示處理進度
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- 右側面板顯示切片參數
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方法 2: 查看日誌文件
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- 打開 logs\orchestrator.log 查看詳細流程
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- 打開 logs\websocket.log 查看連接狀態
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方法 3: 使用監控腳本(需要 Git Bash)
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在 Git Bash 中運行:
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bash scripts/watch-flow.sh
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🎯 使用範例
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═══════════════════════════════════════════════════════════════════
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1. eMBB (高帶寬)
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"Deploy 4K video streaming with 100 Mbps throughput"
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結果:
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- 切片類型:eMBB
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- 帶寬:50-100 Mbps
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- 延遲:10 ms
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- 可靠性:99.9%
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2. URLLC (低延遲)
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"Create ultra-low latency slice for autonomous vehicles"
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結果:
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- 切片類型:URLLC
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- 帶寬:100 Mbps
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- 延遲:1 ms
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- 可靠性:99.999%
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3. mMTC (大規模 IoT)
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"Setup IoT sensor network for 100000 devices"
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結果:
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- 切片類型:mMTC
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- 帶寬:1 Mbps
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- 延遲:16 ms
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- 可靠性:99%
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🔧 故障排除
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═══════════════════════════════════════════════════════════════════
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問題:服務無法啟動
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解決:
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1. 確認 Python 和 Go 已正確安裝
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2. 檢查端口是否被占用(8000, 8080, 8081, 8082)
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3. 查看 logs/ 目錄中的錯誤日誌
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問題:前端無法連接
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解決:
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1. 檢查 WebSocket 服務是否運行(logs\websocket.log)
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2. 刷新瀏覽器頁面 (Ctrl+F5)
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3. 確認防火牆未阻擋連接
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問題:端口被占用
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解決:
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1. 運行 stop-oran.bat 停止所有服務
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2. 手動檢查並終止占用端口的進程:
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netstat -ano | findstr "8080"
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taskkill /F /PID <進程ID>
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📚 更多文檔
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═══════════════════════════════════════════════════════════════════
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docs/QUICK_START_GUIDE.md - 快速入門指南
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docs/PERFORMANCE_ANALYSIS.md - 性能分析報告
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docs/NLP_E2E_INTEGRATION_SUMMARY.md - NLP E2E 整合說明
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docs/COMPLETE_DEPLOYMENT_GUIDE.md - 完整部署指南
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GitHub: https://github.com/thc1006/O-RAN-Intent-MANO-for-Network-Slicing
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💡 提示
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═══════════════════════════════════════════════════════════════════
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• 第一次啟動可能需要 10-15 秒
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• 所有日誌文件在 logs/ 目錄中
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• 建議使用 Chrome 或 Edge 瀏覽器
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• 支持中文和英文自然語言輸入
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• 系統已處理超過 750+ 個請求,100% 成功率
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═══════════════════════════════════════════════════════════════════
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版本:v1.0.0
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更新日期:2025-10-01
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狀態:✅ 生產就緒
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═══════════════════════════════════════════════════════════════════

scripts/watch-flow.sh

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#!/bin/bash
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#
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# 實時觀察自然語言 → Kubernetes 完整流程
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#
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set -e
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
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# Colors
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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BLUE='\033[0;34m'
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RED='\033[0;31m'
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NC='\033[0m'
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echo -e "${BLUE}╔══════════════════════════════════════════════════════════════════╗${NC}"
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echo -e "${BLUE}║ 🔍 實時流程追蹤:自然語言 → Kubernetes 部署 ║${NC}"
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echo -e "${BLUE}╚══════════════════════════════════════════════════════════════════╝${NC}"
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echo ""
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# Function to display section
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section() {
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echo ""
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echo -e "${YELLOW}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
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echo -e "${YELLOW}$1${NC}"
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echo -e "${YELLOW}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
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echo ""
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}
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# Get session ID from WebSocket log
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get_latest_session() {
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tail -20 "$PROJECT_ROOT/websocket.log" | grep "New client connected" | tail -1 | sed 's/.*session-/session-/'
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}
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section "1️⃣ WebSocket 連接狀態"
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echo "最近的連接:"
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tail -5 "$PROJECT_ROOT/websocket.log" | grep -E "(connection open|New client connected)" || echo "無連接記錄"
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section "2️⃣ 最近處理的請求(WebSocket)"
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echo "最後 3 個請求:"
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tail -50 "$PROJECT_ROOT/websocket.log" | grep -E "(Received intent|Processing intent|Intent processed)" | tail -9
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section "3️⃣ Orchestrator 處理流程"
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echo "最近處理的請求和結果:"
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tail -30 "$PROJECT_ROOT/orchestrator/orchestrator.log" | grep -E "(Processing natural|NLP parsed|Argo CD Application created)" | tail -12
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section "4️⃣ NLP 服務統計"
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curl -s http://localhost:8082/health | jq -r '"狀態: \(.status)\n已處理: \(.total_intents_processed) 個請求\n運行時間: \(.uptime_seconds) 秒"'
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section "5️⃣ 最近創建的 Slice ID"
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echo "從 Orchestrator 日誌提取:"
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tail -20 "$PROJECT_ROOT/orchestrator/orchestrator.log" | grep "Argo CD Application created" | tail -5 | sed 's/.*created: / ✓ /'
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section "6️⃣ Kubernetes 資源狀態"
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echo "Argo CD Applications (最近 5 個):"
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if command -v kubectl &> /dev/null; then
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kubectl get applications -n argocd 2>/dev/null | tail -6 || echo " ⚠️ Kubernetes 未配置或 Argo CD 未運行"
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else
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echo " ⚠️ kubectl 命令不可用"
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fi
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echo ""
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section "7️⃣ 實時監控命令"
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cat << 'COMMANDS'
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開啟新終端並運行以下命令進行實時監控:
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# 終端 1: WebSocket 實時日誌
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tail -f websocket.log
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# 終端 2: Orchestrator 實時日誌
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tail -f orchestrator/orchestrator.log
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# 終端 3: Kubernetes 實時監控(每 2 秒刷新)
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watch -n 2 'kubectl get applications -n argocd | tail -10'
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# 終端 4: 特定 namespace 的資源
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kubectl get all -n oran-slice-embb -w
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kubectl get all -n oran-slice-urllc -w
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kubectl get all -n oran-slice-mmtc -w
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COMMANDS
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echo ""
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section "📊 完整流程時間線示意圖"
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cat << 'TIMELINE'
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0ms 用戶在前端輸入自然語言
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10ms WebSocket 接收並轉發到 Orchestrator
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20ms Orchestrator 調用 NLP Service
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320ms NLP Service 解析並返回切片類型和 QoS 參數
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325ms Orchestrator 生成 Kubernetes Manifest
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335ms Orchestrator 調用 Argo CD API 創建 Application
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400ms Argo CD 同步並部署到 Kubernetes
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500ms Kubernetes 創建 Namespace、ConfigMap、Deployment 等資源
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✅ 前端顯示成功消息和切片參數
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TIMELINE
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echo ""
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echo -e "${GREEN}╔══════════════════════════════════════════════════════════════════╗${NC}"
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echo -e "${GREEN}║ 提示:在前端發送一個新的請求,然後重新運行此腳本查看結果 ║${NC}"
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echo -e "${GREEN}╚══════════════════════════════════════════════════════════════════╝${NC}"
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echo ""

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