# Session Handover Report - Email Sorter
**Date:** 2025-11-28
**Session ID:** eb549838-a153-48d1-ae5d-891e0e83108f

---

## What Was Done This Session

### 1. Classified 801 emails from brett-gmail using three methods:

| Method | Accuracy | Time | Output Location |
|--------|----------|------|-----------------|
| ML-Only | 54.9% | ~5 sec | `/home/bob/Documents/Email Manager/emails/brett-gm-md/` |
| ML+LLM | 93.3% | ~3.5 min | `/home/bob/Documents/Email Manager/emails/brett-gm-llm/` |
| Manual Agent | 99.8% | ~25 min | Same as ML-only + analysis files |

### 2. Created/Modified Files

**New Files:**
- `tools/generate_html_report.py` - HTML report generator
- `tools/brett_gmail_analyzer.py` - Custom dataset analyzer
- `data/brett_gmail_analysis.json` - Analysis output
- `docs/REPORT_FORMAT.md` - Report system documentation
- `docs/CLASSIFICATION_METHODS_COMPARISON.md` - Method comparison
- `docs/PROJECT_ROADMAP_2025.md` - Full roadmap and learnings
- `/home/bob/Documents/Email Manager/emails/brett-gm-md/BRETT_GMAIL_ANALYSIS_REPORT.md` - Analysis report
- `/home/bob/Documents/Email Manager/emails/brett-gm-md/report.html` - HTML report (ML-only)
- `/home/bob/Documents/Email Manager/emails/brett-gm-llm/report.html` - HTML report (ML+LLM)

**Modified Files:**
- `src/cli.py` - Added `--force-ml` flag, enriched results.json with email metadata
- `src/llm/openai_compat.py` - Removed API key requirement for local vLLM
- `config/default_config.yaml` - Changed LLM to openai provider on localhost:11433

### 3. Key Configuration Changes

```yaml
# config/default_config.yaml - LLM now uses vLLM endpoint
llm:
  provider: "openai"
  openai:
    base_url: "http://localhost:11433/v1"
    api_key: "not-needed"
    classification_model: "qwen3-coder-30b"
```

---

## Key Findings

1. **ML pipeline overkill for <5000 emails** - Agent analysis gives better accuracy in similar time
2. **Sender domain is strongest signal** - Top 5 senders = 47.5% of emails
3. **Categories should serve downstream routing** - Not human labels, but processing decisions
4. **Risk-based accuracy** - Personal emails need high accuracy, junk can tolerate errors
5. **This tool = triage** - Sorts into buckets for other specialized tools

---

## Project Scope (Agreed with User)

**Email Sorter IS:**
- Bulk classification/triage tool
- Router to downstream specialized tools
- Part of larger email processing ecosystem

**Email Sorter IS NOT:**
- Complete email management solution
- Spam filter (trust Gmail/Outlook)
- Final destination for emails

---

## Recommended Dataset Size Routing

| Size | Method |
|------|--------|
| <500 | Agent-only |
| 500-5000 | Agent pre-scan + ML |
| >5000 | ML pipeline |

---

## Background Processes

There are stale background bash processes (f8678e, 0a3549, 0d150e) from classification runs. These completed successfully and can be ignored.

---

## What Needs Doing Next

1. **Review docs/** - All learnings are in PROJECT_ROADMAP_2025.md
2. **Phase 1 development** - Dataset size routing, sender-first classification
3. **Agent pre-scan module** - 10-15 min discovery phase before ML

---

## User Preferences (from CLAUDE.md)

- NO emojis in commits
- NO "Generated with Claude" attribution
- Use tools (Read/Edit/Grep) not bash commands for file ops
- Virtual environment required for Python
- TTS available via `fss-speak` (single line messages only, no newlines)

---

## Quick Start for Next Agent

```bash
cd /MASTERFOLDER/Tools/email-sorter
source venv/bin/activate

# Read the roadmap
cat docs/PROJECT_ROADMAP_2025.md

# Run classification
python -m src.cli run --source local \
  --directory "/path/to/emails" \
  --output "/path/to/output" \
  --force-ml --llm-provider openai

# Generate HTML report
python tools/generate_html_report.py --input /path/to/results.json
```

---

*Session ended: 2025-11-28 ~03:30 AEDT*