chore: project cleanup and prepare for dual-track processing refactor

- Removed all test files and directories
- Deleted outdated documentation (will be rewritten)
- Cleaned up temporary files, logs, and uploads
- Archived 5 completed OpenSpec proposals
- Created new dual-track-document-processing proposal with complete OpenSpec structure
  - Dual-track architecture: OCR track (PaddleOCR) + Direct track (PyMuPDF)
  - UnifiedDocument model for consistent output
  - Support for structure-preserving translation
- Updated .gitignore to prevent future test/temp files

This is a major cleanup preparing for the complete refactoring of the document processing pipeline.

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

Co-Authored-By: Claude <noreply@anthropic.com>

openspec/changes/archive/2025-11-18-add-gpu-acceleration-support/specs/ocr-processing/spec.md

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+# OCR Processing Specification
+
+## ADDED Requirements
+
+### Requirement: GPU Acceleration
+The system SHALL automatically detect and utilize GPU hardware for OCR processing when available, with graceful fallback to CPU mode when GPU is unavailable or disabled.
+
+#### Scenario: GPU available and enabled
+- **WHEN** PaddleOCR service initializes on system with compatible GPU
+- **THEN** the system detects GPU availability using CUDA runtime
+- **AND** initializes PaddleOCR with `use_gpu=True` parameter
+- **AND** sets appropriate GPU memory fraction to prevent OOM errors
+- **AND** logs GPU device information (name, memory, CUDA version)
+- **AND** processes OCR tasks using GPU acceleration
+
+#### Scenario: CPU fallback when GPU unavailable
+- **WHEN** PaddleOCR service initializes on system without GPU
+- **THEN** the system detects absence of GPU
+- **AND** initializes PaddleOCR with `use_gpu=False` parameter
+- **AND** logs CPU mode status
+- **AND** processes OCR tasks using CPU without errors
+
+#### Scenario: Force CPU mode override
+- **WHEN** FORCE_CPU_MODE environment variable is set to true
+- **THEN** the system ignores GPU availability
+- **AND** initializes PaddleOCR in CPU mode
+- **AND** logs that CPU mode is forced by configuration
+- **AND** processes OCR tasks using CPU
+
+#### Scenario: GPU out-of-memory error handling
+- **WHEN** GPU runs out of memory during OCR processing
+- **THEN** the system catches CUDA OOM exception
+- **AND** logs error with GPU memory information
+- **AND** attempts to process the task using CPU mode
+- **AND** continues batch processing without failure
+- **AND** records GPU failure in task metadata
+
+#### Scenario: Multiple GPU devices available
+- **WHEN** system has multiple CUDA devices
+- **THEN** the system detects all available GPUs
+- **AND** uses primary GPU (device 0) by default
+- **AND** allows GPU device selection via configuration
+- **AND** logs selected GPU device information
+
+### Requirement: GPU Performance Optimization
+The system SHALL optimize GPU memory usage and batch processing for efficient OCR performance.
+
+#### Scenario: Automatic batch size adjustment
+- **WHEN** GPU mode is enabled
+- **THEN** the system queries available GPU memory
+- **AND** calculates optimal batch size based on memory capacity
+- **AND** adjusts concurrent processing threads accordingly
+- **AND** monitors memory usage during processing
+- **AND** prevents memory allocation beyond safe threshold
+
+#### Scenario: GPU memory management
+- **WHEN** GPU memory fraction is configured
+- **THEN** the system allocates specified fraction of total GPU memory
+- **AND** reserves memory for PaddleOCR model
+- **AND** prevents other processes from causing OOM
+- **AND** releases memory after batch completion
+
+### Requirement: GPU Status Reporting
+The system SHALL provide GPU status information through health check API and logging.
+
+#### Scenario: Health check with GPU available
+- **WHEN** client requests `/health` endpoint on GPU-enabled system
+- **THEN** the system returns health status including:
+  - `gpu_available`: true
+  - `gpu_device_name`: detected GPU name
+  - `cuda_version`: CUDA runtime version
+  - `gpu_memory_total`: total GPU memory in MB
+  - `gpu_memory_used`: currently used GPU memory in MB
+  - `gpu_utilization`: current GPU utilization percentage
+
+#### Scenario: Health check without GPU
+- **WHEN** client requests `/health` endpoint on CPU-only system
+- **THEN** the system returns health status including:
+  - `gpu_available`: false
+  - `processing_mode`: "CPU"
+  - `reason`: explanation for CPU mode (e.g., "No GPU detected", "CPU mode forced")
+
+#### Scenario: Startup GPU status logging
+- **WHEN** OCR service starts
+- **THEN** the system logs GPU detection results
+- **AND** logs selected processing mode (GPU/CPU)
+- **AND** logs GPU device details if available
+- **AND** logs any GPU-related warnings or errors
+- **AND** continues startup successfully regardless of GPU status