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4 Commits

Author SHA1 Message Date
egg
b048f2d640 fix: disable chart recognition due to PaddlePaddle 3.0.0 API limitation 
PaddleOCR-VL chart recognition model requires `fused_rms_norm_ext` API
which is not available in PaddlePaddle 3.0.0 stable release.

Changes:
- Set use_chart_recognition=False in PP-StructureV3 initialization
- Remove unsupported show_log parameter from PaddleOCR 3.x API calls
- Document known limitation in openspec proposal
- Add limitation documentation to README
- Update tasks.md with documentation task for known issues

Impact:
- Layout analysis still detects/extracts charts as images ✓
- Tables, formulas, and text recognition work normally ✓
- Deep chart understanding (type detection, data extraction) disabled ✗
- Chart to structured data conversion disabled ✗

Workaround: Charts saved as image files for manual review

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-14 13:16:17 +08:00
egg
36944117f4 fix: update setup script to install PaddlePaddle GPU version from official source 
Changes to setup_dev_env.sh:
- Add support for CUDA 13.x (install CUDA 12.x compatible version)
- Use official PaddlePaddle source for GPU versions
- Install paddlepaddle-gpu==3.0.0b2 from official index
- CUDA 13.x: use cu123 package (backward compatible)
- CUDA 12.x: use cu123 package
- CUDA 11.7+: use cu118 package
- CUDA 11.2-11.6: use cu117 package

Changes to requirements.txt:
- Comment out paddlepaddle dependency
- Let setup script handle GPU/CPU version installation

This fixes the issue where pip installed CPU-only paddlepaddle 3.2.1
instead of GPU version, causing GPU acceleration to be unavailable.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-14 09:35:12 +08:00
egg
7536f43513 feat: implement GPU acceleration support for OCR processing 
實作 GPU 加速支援，自動偵測並啟用 CUDA GPU 加速 OCR 處理

主要變更：

1. 環境設置增強 (setup_dev_env.sh)
   - 新增 GPU 和 CUDA 版本偵測功能
   - 自動安裝對應的 PaddlePaddle GPU/CPU 版本
   - CUDA 11.2+ 安裝 GPU 版本，否則安裝 CPU 版本
   - 安裝後驗證 GPU 可用性並顯示設備資訊

2. 配置更新
   - .env.local: 加入 GPU 配置選項
     * FORCE_CPU_MODE: 強制 CPU 模式選項
     * GPU_MEMORY_FRACTION: GPU 記憶體使用比例
     * GPU_DEVICE_ID: GPU 裝置 ID
   - backend/app/core/config.py: 加入 GPU 配置欄位

3. OCR 服務 GPU 整合 (backend/app/services/ocr_service.py)
   - 新增 _detect_and_configure_gpu() 方法自動偵測 GPU
   - 新增 get_gpu_status() 方法回報 GPU 狀態和記憶體使用
   - 修改 get_ocr_engine() 支援 GPU 參數和錯誤降級
   - 修改 get_structure_engine() 支援 GPU 參數和錯誤降級
   - 自動 GPU/CPU 切換，GPU 失敗時自動降級到 CPU

4. 健康檢查與監控 (backend/app/main.py)
   - /health endpoint 加入 GPU 狀態資訊
   - 回報 GPU 可用性、裝置名稱、記憶體使用等資訊

5. 文檔更新 (README.md)
   - Features: 加入 GPU 加速功能說明
   - Prerequisites: 加入 GPU 硬體要求（可選）
   - Quick Start: 更新自動化設置說明包含 GPU 偵測
   - Configuration: 加入 GPU 配置選項和說明
   - Notes: 加入 GPU 支援注意事項

技術特性：
- 自動偵測 NVIDIA GPU 和 CUDA 版本
- 支援 CUDA 11.2-12.x
- GPU 初始化失敗時優雅降級到 CPU
- GPU 記憶體分配控制防止 OOM
- 即時 GPU 狀態監控和報告
- 完全向後相容 CPU-only 環境

預期效能：
- GPU 系統: 3-10x OCR 處理速度提升
- CPU 系統: 無影響，維持現有效能

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-14 07:42:13 +08:00
egg
d7e64737b7 feat: migrate to WSL Ubuntu native development environment 
從 Docker/macOS+Conda 部署遷移到 WSL2 Ubuntu 原生開發環境

主要變更：
- 移除所有 Docker 相關配置檔案 (Dockerfile, docker-compose.yml, .dockerignore 等)
- 移除 macOS/Conda 設置腳本 (SETUP.md, setup_conda.sh)
- 新增 WSL Ubuntu 自動化環境設置腳本 (setup_dev_env.sh)
- 新增後端/前端快速啟動腳本 (start_backend.sh, start_frontend.sh)
- 統一開發端口配置 (backend: 8000, frontend: 5173)
- 改進資料庫連接穩定性（連接池、超時設置、重試機制）
- 更新專案文檔以反映當前 WSL 開發環境

Technical improvements:
- Database connection pooling with health checks and auto-reconnection
- Retry logic for long-running OCR tasks to prevent DB timeouts
- Extended JWT token expiration to 24 hours
- Support for Office documents (pptx, docx) via LibreOffice headless
- Comprehensive system dependency installation in single script

Environment:
- OS: WSL2 Ubuntu 24.04
- Python: 3.12 (venv)
- Node.js: 24.x LTS (nvm)
- Backend Port: 8000
- Frontend Port: 5173

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-13 21:00:42 +08:00