- server.py now auto-loads .env file directly (robust key loading)
- Strip whitespace from all env var values
- Add POST /api/photos/{id}/reset endpoint to delete + allow re-upload
- Frontend: Reset button on prev-photo-cards + duplicate banners
- Improved mini-map rendering with better popups and zoom control
- Machine info panel shows building/floor/room/address/model details
- Added resetAndReupload() for in-place re-processing after reset
- SQLite DB (photos.db) — persists all processed photo records
- Dedup by SHA256 hash — same file upload returns duplicate: true
- /api/photos — list previously processed photos
- /api/photos/{id} — get single record
- /api/photos/{id}/file — serve saved image
- /api/photos/{id}/reprocess — re-run OCR with different engine/model
- Google Gemini OCR engine (gemini-2.5-flash, free tier) alongside
OpenCode Go LLM and Tesseract
- Sticker mode — specialized LLM/Google prompt for green/orange/yellow
equipment stickers with 2D barcode + machine ID
- Manual machine ID entry — when GPS exists but OCR fails, show text
input for manual lookup
- Frontend: Previous Photos section, Re-run OCR per photo, duplicate
badges, engine dropdown, sticker toggle
- Add run_ocr_llm_batch() — sends N images in a single vision API call
with structured JSON prompt, up to 20 images per batch
- Add _resize_for_llm() — downscales images to 1600px max dimension
before sending to LLM, reducing per-image token cost
- Update bulk_process() to pre-read all files and batch-OCR in one call
- Graceful fallback: if batch JSON parsing fails, retries individually
- Frontend shows llm_batch engine badge
Without batch: N photos = N API calls (each with full prompt overhead)
With batch: N photos = ceil(N/20) API calls + image downscaling savings
Adds optional LLM-based OCR as an alternative to Tesseract for reading
machine IDs from photos.
Backend (server.py):
- New run_ocr_llm() function calls OpenCode Go API (mimo-v2-omni model)
- Auto-falls back to Tesseract if API key missing or call fails
- Endpoints /api/analyze and /api/bulk-process accept ?ocr_engine=llm
query param (default: tesseract) and ?ocr_model for model override
- Configurable via env vars: OPENCODE_GO_API_KEY, LLM_OCR_MODEL
- Requires User-Agent: Hermes-Agent/1.0 header for OpenCode Go API
Frontend (static/index.html):
- Toggle checkbox 'Use LLM OCR' in the UI
- OCR engine badge shown in results (llm vs tesseract + model name)
- getOcrParams() helper appends ?ocr_engine=llm to API calls
Infrastructure:
- .gitignore for uploads/ directory
Closes: #2
Root cause: FileReader.readAsDataURL() loads the entire file into memory
as a base64 string. With 50+ iPhone photos (3-12 MB each), this exceeds
iOS Safari's per-tab memory limit and freezes the tab.
Changes:
- Replace readAsDataURL with URL.createObjectURL(file) — zero-copy file
reference, no memory bloat (static/index.html)
- Reduce batch size from 4 to 2 — gentler on memory-constrained devices
- Add URL.revokeObjectURL() on reset — prevent blob URL leaks
- Add HEIC/HEIF support to server.py — iPhone format compatibility
Closes#1
shawn