# TODO

## Phase 0: Infrastructure (DONE)

- [x] Azure VMs created and configured (jt-ub, jt-win)
- [x] Ubuntu VM provisioned (Docker, Go, Python, rclone, zsh, dotfiles)
- [x] Directory structures on both VMs (William's layout)
- [x] Sample document generator (7 generators, Azure Claude content pools, CJK fonts)
- [x] Project restructure: Tracker/Setup.bat + Tracker/Code/{Sync,Tools,Tracker}
- [x] Windows rclone sync setup (Setup.bat, Win-Setup.ps1, sync.ps1, config.ini)
  - rclone auto-download + self-contained install in _LLM/Code/Sync/rclone/
  - Password-based SFTP auth (demo), config.ini for server details
  - .sync_ignore generated on setup (excludes_LLM/, dotfiles, temp/lock files)
  - 5-minute scheduled task (JingTian-Sync)
  - Pull-first-then-push: bidirectional files pulled with --update, excluded from push
  - Bidirectional file list in config.ini (e.g. Admin/Tracker.xlsx)
  - Daily log rotation in _LLM/Code/Sync/logs/
- [x] Ubuntu VM SSH password auth enabled (Azure cloud-init was blocking it)
- [x] Both sync directions tested and working
- [x] Old JingTian-Rclone repo archived on Gitea

## Phase 1: Services (Services-First Approach)

Rationale: De-risk unknowns (Docling OCR quality, Ollama CPU inference speed) before building orchestrator.

### 1a. Docker Compose + Docling (DONE)

- [x] Docker Compose base (Docling service)
- [x] Test Docling API with sample PDFs (curl)
- [x] Validate OCR quality on real PDFs + generated samples
- [x] Test OCR on images (PNG) — works with `force_ocr=true`

**Docling API Spec:**

- Image: `ds4sd/docling-serve:latest`
- Port: `5001`
- Endpoint: `POST /v1/convert/file`
- Form params: `files=@<path>;type=application/pdf`, `to_formats=md`, `do_ocr=true`
- Response: `{ "document": { "md_content": "..." }, "status": "success" }`
- OCR engine: `easyocr` (default), supports CJK

**OCR Options:**

- `do_ocr=true` — enabled by default, processes bitmap content
- `force_ocr=true` — use for images/scanned PDFs (replaces existing text with OCR)
- `ocr_engine` — `easyocr` (default), `tesseract`, `rapidocr`, `tesserocr`, `ocrmac`
- `ocr_lang` — language codes (engine-specific), e.g. `ch_sim` for Simplified Chinese

**Tested Formats:**

- PDF (Filing Receipt) — extracted text, tables, CJK content ✅
- PNG (Email screenshot) — extracted subject, dates, recipient ✅
- PNG with `ocr_lang=ch_tra` — Traditional Chinese extracted correctly (官藥坊) ✅

**Portable Chinese OCR:**

- Auto-downloads `ch_sim` (Simplified) and `ch_tra` (Traditional) models on first run
- Models persist in `docling_models` volume
- First run takes ~1-2 min extra for model download; subsequent runs instant
- Use `ocr_lang=ch_tra` for HK/Taiwan, `ocr_lang=ch_sim` for Mainland China

### 1b. Ollama (DONE)

- [x] Add Ollama to Docker Compose (Qwen3-1.7B, CPU mode)
- [x] Test structured extraction prompt (curl)
- [x] Measure inference time per document (~15-30s on 4 vCPU)
- [x] Validate extraction accuracy (deadline, doc type, etc.)

**Ollama API Spec:**

- Image: `ollama/ollama:0.9.3`
- Port: `11434`
- Model: `qwen3:1.7b` (~1.4 GB, auto-pulled on startup)
- Endpoint: `POST /api/generate`
- Body: `{"model":"qwen3:1.7b","prompt":"...","stream":false,"options":{"temperature":0}}`
- Response: `{ "response": "<json>" }` (strip `<think>...</think>` tags in post-processing)
- Note: Qwen3 includes reasoning by default; `/no_think` leaves empty tags, so strip instead

### 1c. Python Tools Service

- [ ] FastAPI + openpyxl service
- [ ] Endpoints: read tracker, write/update rows, get column schema
- [ ] Test with sample Tracker.xlsx

### 1d. Manual Integration Test

- [ ] Chain test: PDF → Docling → Ollama → Tools → Excel updated
- [ ] Document any issues / adjustments needed

## Phase 2: Go Orchestrator

- [ ] Init Go module in Tracker/
- [ ] Config loading (YAML)
- [ ] SQLite schema + migrations (documents, extractions, processing_log)
- [ ] Docling HTTP client
- [ ] Ollama HTTP client
- [ ] Tools service HTTP client
- [ ] File watcher (inotify on Ubuntu, 2-min stability check via SHA256 hash)
- [ ] State tracker integration (new/changed/skip logic)
- [ ] Pipeline orchestrator (read latest Tracker before writing, merge not overwrite)

## Phase 3: Integration + Testing

- [ ] End-to-end test (drop file on Windows → syncs to Ubuntu → pipeline → Tracker updates → syncs back)
- [ ] Smoke test with real PDFs + generated samples
- [ ] README documentation

## Future

- [ ] Key-based SFTP auth (replace password for production)
- [ ] Windows Go service (replace PowerShell scheduled task)
- [ ] File hash (SHA256) change detection on Windows side
- [ ] WhatsApp deadline notifications
- [ ] Processing retry logic
- [ ] Multi-client support
- [ ] Smarter bidirectional merge (cell-level, not file-level)