Research CommonsResearch Commons
docparser/Roadmap

Roadmap

Where docparser stands today and where it's headed.

docparser is beta (0.2.x), published on PyPI as rc-docparser. For the live state, follow the repository.

Solid today

  • Nine input formats — .docx, .xlsx, .pdf, .html, .pptx, .epub, .txt, .md, .csv — normalized into a shared Markdown + JSON block schema.
  • Pluggable PDF backends (builtin / pymupdf4llm / docling / marker), OCR, and table extraction.
  • Optional VLM captioning across OpenRouter, OpenAI, Gemini, a local server, or a fully-local transformers model, with hash-keyed caching.
  • A lean MIT core with opt-in extras, plus a docparser CLI.
  • CI runs lint + mypy + tests on Python 3.10–3.12; tagged releases publish to PyPI via Trusted Publishing (OIDC, no stored token).

Direction

  • Broader fidelity. Continued improvements to heading/structure detection and table handling across formats.
  • More captioning options. Expanding provider/model coverage and caption schema as VLMs evolve.
  • Corpus tooling. Richer corpus-level rollups for RAG and fine-tuning pipelines.

Contributing

git clone https://github.com/Research-Commons/docparser
cd docparser
python -m venv .venv && source .venv/bin/activate
pip install -e ".[all,dev]"
pytest -ra
ruff check src tests
mypy

Licensed under MIT.