The document twin of meetus. Turns locally-downloaded files (Drive exports, PDFs, images, ...) into a shareable textified product (content.md) plus structured meta.json, mirroring the meetus output/<run>/ contract.

Extraction is deterministic and offline — no cloud AI touches the raw source. The textified output is what feeds permitted services (Gemini web, NotebookLM) and the local search index; the raw source stays on disk.

Quick start

# one document
python process_doc.py notes.docx                 # → docs-output/<YYYYMMDD-NNN-notes>/
python process_doc.py report.pdf --render        # also render page 1 → thumb.jpg
python process_doc.py scan.png --ocr             # OCR the image into content.md

# a whole downloaded folder (mirrors the input tree)
make docs IN="/mnt/win/drive"                    # → docs-output/...
make docs IN="..." DOC_EXTRA="--render --ocr"
make docs-dry IN="..."                           # list what would run

Output contract

docs-output/<YYYYMMDD-NNN-stem>/
  content.md      textified document — the shareable product
  meta.json       source info, sha256, dates, author, title, pages/sheets/slides, word_count, warnings
  thumb.jpg       optional single preview (image / rendered page / video frame)
  manifest.json   run config + outputs inventory + source pointer (path, not a copy)

Supported types

Family	Extensions	Notes
text	md, txt, yaml/yml, json	passthrough; json/yaml add a structure summary
tabular	csv	markdown table + row/col metadata (stdlib)
office	docx, pptx, xlsx	text + core properties (author, dates, title)
pdf	pdf	text per page + info dict; `--render` for page-1 thumb
web	html/htm	visible text + title/meta tags
image	jpg/jpeg, png	EXIF (incl. capture date) + thumbnail; `--ocr` for text
media	mp4	ffprobe metadata + thumbnail; delegates transcription to meetus

Each extractor is isolated: a missing optional dependency or a corrupt file is recorded as a warning in meta.json, never aborting a batch (same resilience as ctrl/batch.sh).

Dependencies

Core text/tabular use only the stdlib. Everything else is a uv group in the repo's pyproject.toml:

uv sync --group doocus                 # Pillow, PyYAML, python-docx, python-pptx,
                                       # openpyxl, pypdf, beautifulsoup4, lxml
uv sync --group doocus --group ocr     # + pytesseract (needs system `tesseract`)

mp4 uses system ffmpeg/ffprobe (shared with meetus). PDF page rendering (--render) additionally needs the pdf-render group (pdf2image) + system poppler.

Browser UI

ui/doocus-app/ (sibling of ui/meetus-app/, shares ui/framework/) browses the extracted docs with per-type viewers, a metadata panel, and a package builder that zips the original file + content.md + meta.json per doc for a chosen target (Gemini web / NotebookLM):

cd ui/doocus-app && npm install
DOOCUS_OUTPUT=/path/to/docs-output npm run dev