feat: add GPU acceleration support OpenSpec proposal
新增 GPU 加速支援的 OpenSpec 變更提案 主要內容: - 在環境建置腳本中加入 GPU 偵測功能 - 自動安裝對應 CUDA 版本的 PaddlePaddle GPU 套件 - 在 OCR 處理程式中加入 GPU 可用性偵測 - 自動啟用 GPU 加速(可用時)或使用 CPU(不可用時) - 支援強制 CPU 模式選項 - 加入 GPU 狀態報告到健康檢查 API 變更範圍: - 新增 capability: environment-setup (環境設置) - 修改 capability: ocr-processing (加入 GPU 支援) 實作任務包含: 1. 環境設置腳本增強 (GPU 偵測、CUDA 安裝) 2. 配置更新 (GPU 相關環境變數) 3. OCR 服務 GPU 整合 (自動偵測、記憶體管理) 4. 健康檢查與監控 (GPU 狀態報告) 5. 文檔更新 6. 測試與效能評估 7. 錯誤處理與邊界情況 預期效果: - GPU 系統: 3-10x OCR 處理速度提升 - CPU 系統: 無影響,向後相容 - 自動硬體偵測與優化配置 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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openspec/changes/add-gpu-acceleration-support/tasks.md
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openspec/changes/add-gpu-acceleration-support/tasks.md
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# Implementation Tasks
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## 1. Environment Setup Enhancement
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- [ ] 1.1 Add GPU detection function in `setup_dev_env.sh`
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- Detect NVIDIA GPU using `nvidia-smi` or `lspci`
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- Detect CUDA version if GPU is available
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- Output GPU detection results to user
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- [ ] 1.2 Add conditional CUDA package installation
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- Install `paddlepaddle-gpu` with matching CUDA version when GPU detected
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- Install `paddlepaddle` (CPU-only) when no GPU detected
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- Handle different CUDA versions (11.2, 11.6, 11.7, 12.0, etc.)
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- [ ] 1.3 Add GPU verification step after installation
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- Test PaddlePaddle GPU availability
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- Report GPU status and CUDA version to user
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- Provide fallback instructions if GPU setup fails
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## 2. Configuration Updates
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- [ ] 2.1 Add GPU configuration to `.env.local`
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- Add `FORCE_CPU_MODE` option (default: false)
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- Add `CUDA_VERSION` for manual override
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- Add `GPU_MEMORY_FRACTION` for memory allocation control
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- [ ] 2.2 Update backend configuration
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- Add GPU settings to `backend/app/core/config.py`
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- Load GPU-related environment variables
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- Add validation for GPU configuration values
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## 3. OCR Service GPU Integration
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- [ ] 3.1 Add GPU detection in OCR service initialization
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- Create GPU availability check function
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- Detect available GPU devices
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- Log GPU status (available/unavailable, device name, memory)
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- [ ] 3.2 Implement automatic GPU/CPU mode selection
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- Enable GPU mode in PaddleOCR when GPU is available
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- Fall back to CPU mode when GPU is unavailable or forced
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- Set appropriate `use_gpu` parameter for PaddleOCR initialization
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- [ ] 3.3 Add GPU memory management
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- Set GPU memory fraction to prevent OOM errors
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- Adjust batch size based on GPU memory availability
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- Handle GPU memory allocation failures gracefully
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- [ ] 3.4 Update `backend/app/services/ocr_service.py`
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- Modify PaddleOCR initialization with GPU parameters
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- Add GPU status logging
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- Add error handling for GPU-related issues
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## 4. Health Check and Monitoring
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- [ ] 4.1 Add GPU status to health check endpoint
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- Report GPU availability (true/false)
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- Report GPU device name and compute capability
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- Report CUDA version
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- Report current GPU memory usage
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- [ ] 4.2 Update `backend/app/api/v1/endpoints/health.py`
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- Add GPU status fields to health check response
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- Handle cases where GPU detection fails
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## 5. Documentation Updates
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- [ ] 5.1 Update README.md
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- Add GPU requirements section
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- Document GPU detection and setup process
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- Add troubleshooting for GPU issues
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- [ ] 5.2 Update openspec/project.md
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- Add GPU hardware recommendations
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- Document CUDA version compatibility
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- Add GPU-specific configuration options
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- [ ] 5.3 Create GPU setup guide
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- Document NVIDIA driver installation for WSL
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- Document CUDA toolkit installation
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- Provide GPU verification steps
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## 6. Testing
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- [ ] 6.1 Test GPU detection on GPU-enabled system
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- Verify correct CUDA version detection
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- Verify correct PaddlePaddle GPU installation
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- Verify OCR processing uses GPU
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- [ ] 6.2 Test CPU fallback on non-GPU system
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- Verify CPU-only installation
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- Verify OCR processing works without GPU
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- Verify no errors or warnings about missing GPU
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- [ ] 6.3 Test FORCE_CPU_MODE override
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- Verify GPU is ignored when FORCE_CPU_MODE=true
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- Verify CPU processing works on GPU-enabled system
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- [ ] 6.4 Performance benchmarking
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- Measure OCR processing time with GPU
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- Measure OCR processing time with CPU
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- Document performance improvements
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## 7. Error Handling and Edge Cases
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- [ ] 7.1 Handle GPU out-of-memory errors
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- Catch CUDA OOM exceptions
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- Automatically fall back to CPU mode
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- Log warning message to user
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- [ ] 7.2 Handle CUDA version mismatch
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- Detect PaddlePaddle/CUDA compatibility issues
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- Provide clear error messages
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- Suggest correct CUDA version installation
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- [ ] 7.3 Handle missing NVIDIA drivers
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- Detect when GPU hardware exists but drivers are missing
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- Provide installation instructions
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- Fall back to CPU mode gracefully
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