PHASE 9: Processing Pipeline & Queue Management (bulk_processor.py)
- BulkProcessor class for batch processing with checkpointing
- ProcessingCheckpoint: Save/resume state for resumable processing
- Handles batches with periodic checkpoints every N emails
- Tracks completed, queued_for_llm, and failed emails
- Progress callbacks for UI integration
PHASE 10: Calibration System (sampler.py, llm_analyzer.py)
- EmailSampler: Stratified and random sampling
- Stratifies by sender domain type for representativeness
- CalibrationAnalyzer: Use LLM to discover natural categories
- Batched analysis to control LLM load
- Maps discovered categories to universal schema
PHASE 11: Export & Reporting (exporter.py)
- ResultsExporter: Export to JSON, CSV, organized by category
- ReportGenerator: Generate human-readable text reports
- Category statistics and method breakdown
- Accuracy metrics and processing time tracking
PHASE 13: Enron Dataset Parser (enron_parser.py)
- Parses Enron maildir format into Email objects
- Handles multipart emails and attachments
- Date parsing with fallback for malformed dates
- Ready to train mock model on real data
PHASE 14: Main Orchestration (orchestration.py)
- EmailSorterOrchestrator: Coordinates entire pipeline
- 4-phase workflow: Calibration → Bulk → LLM → Export
- Lazy initialization of components
- Progress tracking and timing
- Full pipeline runner with resume support
Components Now Available:
✅ Sampling (stratified and random)
✅ Calibration (LLM-driven category discovery)
✅ Bulk processing (with checkpointing)
✅ LLM review (batched)
✅ Export (JSON, CSV, by category)
✅ Reporting (text summaries)
✅ Enron parsing (ready for training)
✅ Full orchestration (4 phases)
What's Left (Phases 15-16):
- E2E pipeline tests
- Integration test with Enron data
- Setup.py and wheel packaging
- Deployment documentation
Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
